Medical Illness and Schizophrenia, Second Edition

Medical Illness and

Schizophrenia Second Edition

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Medical Illness and

Schizophrenia Second Edition

Edited by

Jonathan M. Meyer, M.D. Henry A. Nasrallah, M.D.

Washington, DC London, England

Note: The authors have worked to ensure that all information in this book is accurate at the time of publication and consistent with general psychiatric and medical standards, and that information concerning drug dosages, schedules, and routes of administration is accurate at the time of publication and consistent with standards set by the U.S. Food and Drug Administration and the general medical community. As medical research and practice continue to advance, however, therapeutic standards may change. Moreover, specific situations may require a specific therapeutic response not included in this book. For these reasons and because human and mechanical errors sometimes occur, we recommend that readers follow the advice of physicians directly involved in their care or the care of a member of their family. Books published by American Psychiatric Publishing, Inc., represent the views and opinions of the individual authors and do not necessarily represent the policies and opinions of APPI or the American Psychiatric Association. If you would like to buy between 25 and 99 copies of this or any other APPI title, you are eligible for a 20% discount; please contact APPI Customer Service at [email protected] or 800-368-5777. If you wish to buy 100 or more copies of the same title, please e-mail us at [email protected] for a price quote. Copyright © 2009 American Psychiatric Publishing, Inc. ALL RIGHTS RESERVED Manufactured in the United States of America on acid-free paper 13 12 11 10 09 5 4 3 2 1 Second Edition Typeset in Adobe’s Book Antiqua and Albertus American Psychiatric Publishing, Inc. 1000 Wilson Boulevard Arlington, VA 22209-3901 www.appi.org Library of Congress Cataloging-in-Publication Data Medical illness and schizophrenia / edited by Jonathan M. Meyer, Henry A. Nasrallah. — 2nd ed. p. ; cm. Includes bibliographical references and index. ISBN 978-1-58562-346-4 (alk. paper) 1. Schizophrenics—Diseases. 2. Schizophrenics—Medical care. 3. Mentally ill—Diseases. 4. Mentally ill—Medical care. I. Meyer, Jonathan M., 1962– II. Nasrallah, Henry A. {DNLM: 1. Schizophrenia—complications. 2. Schizophrenia—epidemiology. 3. Comorbidity. 4. Patient Care. WM 203 M489 2009] RC514.M425 2009 616.89—dc22 2009005567 British Library Cataloguing in Publication Data A CIP record is available from the British Library.

Contents Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .ix Disclosure of Interests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv

Part I Public Health Issues for Schizophrenia Patients

Chapter 1 Improving Physical Health Care for Patients With Serious Mental Illness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 David Folsom, M.D., M.P.H.

Chapter 2 Excessive Mortality and Morbidity Associated With Schizophrenia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17 Daniel E. Casey, M.D. Thomas E. Hansen, M.D.

Chapter 3 Medical Outcomes From the CATIE Schizophrenia Study . . . . . . . . . . . . . . . . . . . . . 37 Henry A. Nasrallah, M.D.

Part II Metabolic Disease, Heart Disease, and Related Conditions

Chapter 4 Obesity and Schizophrenia . . . . . . . . . . . . . . . . . . . . . . . . . .61 Tony Cohn, M.B.Ch.B., M.Sc., F.R.C.P.C.

Chapter 5 Glucose Intolerance and Diabetes in Patients With Schizophrenia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .91 David C. Henderson, M.D. Kathleen Miley, B.S.

Chapter 6 Effects of Antipsychotics on Serum Lipids . . . . . . . . . . . . . 117 Jonathan M. Meyer, M.D.

Chapter 7 The Spectrum of Cardiovascular Disease in Patients With Schizophrenia . . . . . . . . . . . . . . . . . . . . . . . .169 Jimmi Nielsen, M.D. Egon Toft, M.D., F.E.S.C.

Chapter 8 Behavioral Treatments for Weight Management of Patients With Schizophrenia. . . . . . . . . . . . . . . . . . . . . . . . 203 Rohan Ganguli, M.D., F.R.C.P.C. Tony Cohn, M.B.Ch.B., M.Sc., F.R.C.P.C. Guy Faulkner, B.Ed., M.Sc., Ph.D.

Chapter 9 Nicotine and Tobacco Use in Patients With Schizophrenia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Andrea H. Weinberger, Ph.D. Tony P. George, M.D., F.R.C.P.C.

Part III Special Topics and Populations

Chapter 10 HIV and Hepatitis C in Patients With Schizophrenia . . . . . 247 Milton L. Wainberg, M.D. Francine Cournos, M.D. Karen McKinnon, M.A. Alan Berkman, M.D. Mark Drew Crosland Guimarães, M.D., D.Sc., M.P.H.

Chapter 11 Substance Abuse and Schizophrenia . . . . . . . . . . . . . . . . . 275 Peter F. Buckley, M.D. Jonathan M. Meyer, M.D.

Chapter 12 Sexual Dysfunction and Schizophrenia . . . . . . . . . . . . . . . . 303 Heidi J. Wehring, Pharm.D., B.C.P.P. Deanna L. Kelly, Pharm.D., B.C.P.P.

Chapter 13 Managing the Health Outcomes of Schizophrenia Treatment in Children and Adolescents . . . 343 Christoph U. Correll, M.D.

Chapter 14 Medical Health in Aging Persons With Schizophrenia . . . . 377 Samantha Brenner, M.P.H. Carl I. Cohen, M.D.

Chapter 15 Managing Health Outcomes of Women With Schizophrenia During Pregnancy and Breastfeeding . . . . . . .415 Adele C. Viguera, M.D., M.P.H. Mackenzie Varkula, D.O. Katherine Donovan, B.A. Ross J. Baldessarini, M.D.

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435

Contributors Ross J. Baldessarini, M.D. Professor of Psychiatry, Harvard Medical School and Massachusetts General Hospital, Boston, Massachusetts; Director, International Consortium for Psychotic Disorders Research, McLean Hospital, Belmont, Massachusetts Alan Berkman, M.D. Associate Professor of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York Samantha Brenner, M.P.H. Medical Student, Department of Psychiatry, State University of New York Health Science Center at Brooklyn, Brooklyn, New York Peter F. Buckley, M.D. Professor and Chairman, Department of Psychiatry, Medical College of Georgia, Augusta, Georgia Daniel E. Casey, M.D. Professor of Psychiatry and Neurology, Oregon Health and Science University, Portland, Oregon Carl I. Cohen, M.D. Professor and Director, Division of Geriatric Psychiatry, Department of Geriatric Psychiatry, State University of New York Health Science Center at Brooklyn, Brooklyn, New York Tony Cohn, M.B.Ch.B., M.Sc., F.R.C.P.C. Director, Mental Health and Metabolism Clinic, Centre for Addiction and Mental Health; Assistant Professor, Departments of Psychiatry and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada

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Christoph U. Correll, M.D. Assistant Professor of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine; Medical Director, Director, Adverse Events Assessment and Prevention Unit, The Zucker Hillside Hospital North Shore, Long Island Jewish Health System, Glen Oaks, New York Francine Cournos, M.D. Professor of Clinical Psychiatry, Columbia College of Physicians and Surgeons; Director, Washington Heights Community Service, New York State Psychiatric Institute, New York, New York Mark Drew Crosland Guimarães, M.D., D.Sc., M.P.H. Professor of Epidemiology, Department of Preventive and Social Medicine, Faculty of Medicine, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil Katherine Donovan, B.A. Clinical Research Coordinator, Massachusetts General Hospital Center for Women’s Health, Boston, Massachusetts Guy Faulkner, B.Ed., M.Sc., Ph.D. Professor, Faculty of Physical Education and Health, University of Toronto, Toronto, Ontario, Canada David Folsom, M.D., M.P.H. Assistant Professor of Psychiatry, University of California, San Diego, La Jolla, California Rohan Ganguli, M.D., F.R.C.P.C. Professor of Psychiatry and Executive Vice-President of Clinical Programs, Centre for Addiction and Mental Health, Toronto, Ontario, Canada Tony P. George, M.D., F.R.C.P.C. Head, Addiction Psychiatry Program, Department of Psychiatry, University of Toronto, and Schizophrenia Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada Thomas E. Hansen, M.D. Associate Professor of Psychiatry, Oregon Health and Science University; Staff Psychiatrist, Portland Oregon State Hospital, Portland, Oregon

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David C. Henderson, M.D. Director, Schizophrenia, Diabetes, and Weight Reduction Research Program, Massachusetts General Hospital; Associate Professor of Psychiatry, Harvard Medical School, Boston, Massachusetts Deanna L. Kelly, Pharm.D., B.C.P.P. Associate Professor of Psychiatry and Acting Director, Treatment Research Program, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland Karen McKinnon, M.A. Research Scientist, New York State Psychiatric Institute; Project Director, Columbia University HIV Mental Health Training Project, Columbia University College of Physicians and Surgeons, New York, New York Jonathan M. Meyer, M.D. Assistant Professor of Psychiatry, University of California, San Diego; Staff Psychiatrist, San Diego VA Medical Center, La Jolla, California Kathleen Miley, B.S. Research Assistant, Massachusetts General Hospital, Boston, Massachusetts Henry A. Nasrallah, M.D. Professor of Psychiatry, Neurology and Neuroscience, University of Cincinnati College of Medicine, Cincinnati, Ohio Jimmi Nielsen, M.D. Research Psychiatrist, Unit for Psychiatric Research, Aarhus University Hospital and Aalborg Psychiatric Hospital, Aalborg, Denmark Egon Toft, M.D., F.E.S.C. Professor, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark Mackenzie Varkula, D.O. Resident Physician, Department of Psychiatry and Psychology, Cleveland Clinic Foundation, Cleveland, Ohio Adele C. Viguera, M.D., M.P.H. Associate Professor of Psychiatry, Department of Psychiatry and Psychology, Cleveland Clinic Foundation, Cleveland, Ohio

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Milton L. Wainberg, M.D. Associate Clinical Professor of Psychiatry, Columbia University College of Physicians and Surgeons; Director of Medical Education, Columbia University HIV Mental Health Training Project, New York, New York Heidi J. Wehring, Pharm.D., B.C.P.P. Fellow, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland Andrea H. Weinberger, Ph.D. Assistant Professor, Program for Research in Smokers with Mental Illness, Division of Substance Abuse, Department of Psychiatry, Yale University School of Medicine, The Connecticut Mental Health Center, New Haven, Connecticut

Disclosure of Interests The following contributors to this book have indicated a financial interest in or other affiliation with a commercial supporter, a manufacturer of a commercial product, a provider of a commercial service, a nongovernmental organization, and/or a government agency, as listed below: Daniel E. Casey, M.D.—Consultant: Abbott Laboratories, Bristol-Myers Squibb, Dainippon Sumitomo Pharma, Janssen Pharmaceutica, NuPathe, Pfizer, Solvay Pharmaceuticals, and Wyeth Pharmaceuticals; Speaker’s bureau: Abbott Laboratories, Bristol-Myers Squibb, Janssen, and Pfizer. Tony Cohn, M.B.Ch.B., M.Sc., F.R.C.P.C.—Research grant funding: Pfizer Canada; Speaker’s fees: Pfizer Canada. Christoph U. Correll, M.D.—Grant support: Einstein Institute for Medical Research, National Institute of Mental Health (NIMH), and Stanley Foundation; Consultant: AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Janssen, Otsuka, Pfizer, Supernus, and Vanda; Speaker's bureau: AstraZeneca, Bristol-Myers Squibb, and Otsuka. Rohan Ganguli, M.D., F.R.C.P.C.—Consultant: Janssen; Speaker’s honoraria: Bristol-Myers Squibb. Tony P. George, M.D., F.R.C.P.C.—Grant support: Donaghue Medical Research Foundation, National Alliance for Research on Schizophrenia and Depression (NARSAD), National Institute on Drug Abuse (NIDA), Sanofi-Aventis, and Sepracor; Advisory board/consultant: Eli Lilly, Evotec, and Pfizer. David C. Henderson, M.D.—Research grants: NIMH, Solvay, and Takeda; Honoraria: Bristol-Myers Squibb, Covance, Janssen, Pfizer, Primedia, Reed Medical Education, and Solvay Pharmaceuticals. Deanna L. Kelly, Pharm.D., B.C.P.P.—Advisory board: Bristol-Myers Squibb and Solvay. Jonathan M. Meyer, M.D.—Research support: Bristol-Myers Squibb, NIMH, and Pfizer; Speaking/advising fees: AstraZeneca, Bristol-Myers Squibb, Organon, Pfizer, Vanda Pharmaceuticals, and Wyeth. Henry A. Nasrallah, M.D.—Research support: AstraZeneca, Forest Pharmaceuticals, GlaxoSmithKline, Janssen, NIMH, Pfizer, Roche, and Sanofi; Consultant: AstraZeneca, Cephalon, Janssen, Pfizer, and Vanda; Speaker’s bureau: Abbott, AstraZeneca, Janssen, Pfizer, Solvay, and Vanda.

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Adele C. Viguera, M.D., M.P.H.—Grant/research support: AstraZeneca (Claffin Award), Berlex Laboratories, Eli Lilly, Epilepsy Foundation*, Forest, GlaxoSmithKline, Beecham Pharmaceuticals, Harvard Medical School's Scholars in Medicine Fellowship, Janssen, NARSAD, NIMH, Pfizer, Sepracor, Stanley Medical Research Institute, and Wyeth-Ayerst; Speaker's bureau/honoraria: AstraZeneca*, Eli Lilly, Forest*, GlaxoSmithKline, Novartis Pharmaceuticals, Wyeth-Ayerst; Advisory board: GlaxoSmithKline*, Novartis, and Wyeth-Ayerst*. *Funding in the last 12 months. Andrea H. Weinberger, Ph.D.—Grant support: NARSAD and Sepracor. The following authors affirmed that they have no competing interests: Alan Berkman, M.D. Samantha Brenner, M.P.H. Carl I. Cohen, M.D. Francine Cournos, M.D. Mark Drew Crosland Guimarães, M.D., D.Sc., M.P.H. Guy Faulkner, B.Ed., M.Sc., Ph.D. David Folsom, M.D., M.PH. Thomas E. Hansen, M.D. Karen McKinnon, M.A. Jimmi Nielsen, M.D. Egon Toft, M.D., F.E.S.C. Milton L. Wainberg, M.D. Heidi J. Wehring, Pharm.D., B.C.P.P.

American Psychiatric Publishing, Inc. (APPI)—Subsequent to peer review and acceptance for publication of this volume, APPI entered into an agreement for Dainippon Sumitomo Pharma America, Inc., to underwrite and distribute a separate printing of Medical Illness and Schizophrenia, 2nd Edition.

Preface Since the publication of the first edition of this volume in 2003, there has been a dramatic increase in the literature on optimizing medical outcomes for patients with schizophrenia. Sitting before me is the August 2008 issue of Psychiatric Services, which includes no less than eight research articles devoted to medical issues of relevance to those who care for individuals with severe mental illness. Despite the growing awareness of the unique medical needs in this patient population, natural causes of death remain the primary source of excess mortality, with recent data indicating a widening mortality gap between patients with schizophrenia and the general population (Saha et al. 2007). The recognition that antipsychotic treatment can be associated with deleterious metabolic and other health effects emphasizes the need to address medical aspects of schizophrenia treatment, yet the mental health community as a whole still has a great deal to accomplish toward achieving parity in physical health monitoring and treatment between the severely mentally ill and the rest of society. Barriers remain, but they are not insurmountable. We have expanded this second edition with the aim of providing a comprehensive resource for those who wish to be informed about the various medical issues that impinge on schizophrenia treatment. Our intent is to create a practical manual that can serve as a reference for the medical management of patients with severe mental illness across the age spectrum, with a focus on those areas of significant importance to schizophrenia patients, such as cardiometabolic disorders and their relationship to antipsychotic therapy, smoking, substance use, and infection with human immunodeficiency virus (HIV) and hepatitis C. We have also added a section on the important but neglected topic of sexual function in patients with schizophrenia and have devoted an entire chapter to the behavioral management of weight gain and obesity. The intent, as always, is to stimulate those who work in mental health settings to take a broader view of schizophrenia care, recognizing that this is a systemic disease with multiple manifestations that go beyond the obvious psychiatric symptoms. Jonathan M. Meyer, M.D. xv

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Reference Saha S, Chant D, McGrath J: A systematic review of mortality in schizophrenia: is the differential mortality gap worsening over time? Arch Gen Psychiatry 64:1123–1131, 2007

PART I Public Health Issues for Schizophrenia Patients

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CHAPTER 1 Improving Physical Health Care for Patients With Serious Mental Illness David Folsom, M.D., M.P.H.

Much has been written about the need to integrate mental health care into the primary care setting. Psychiatrists and other mental health care providers have often criticized primary care physicians for underrecognizing and undertreating depression, substance abuse, and other common mental health conditions (Wells et al. 2000). Meanwhile, the challenge of providing quality medical care to patients with serious mental illnesses represents a similar challenge for psychiatrists. Atypical antipsychotic medications are the mainstay of contemporary pharmacological treatment for psychotic disorders (Harrington et al. 2000; IMS Health 2002; Jin et al. 2004). However, in the past decade, concern and awareness have been growing that these medications may cause or exacerbate medical conditions including weight gain and obesity (Daumit et al. 2003; Lieberman et al. 2005), elevated blood sugar and diabetes (Henderson et al. 2005; Leslie and Rosenheck 2004; Lieberman et al. 2005), and cerebrovascular events (Schneider et al. 2005). The U.S. Food and Drug Administration currently mandates that the package inserts for all six atypical antipsychotics—aripiprazole (Abilify 3

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2008), clozapine (Clozaril 2008), olanzapine (Zyprexa 2008), quetiapine (Seroquel 2008), risperidone (Risperdal 2008), and ziprasidone (Geodon 2008)—include black-box warnings regarding the increased risk of mortality in elderly patients with dementia and a warning about the risk of hyperglycemia and diabetes. These warnings and the emerging data on the medical side effects of antipsychotics have raised psychiatrists’ concern and awareness about comorbid medical conditions in their patients and have led to guidelines for the medical monitoring of patients taking these medications (American Diabetes Association et al. 2004; Marder et al. 2002). However, evidence that predates the atypical antipsychotics suggested that patients with severe mental illness (SMI) are at higher risk for several medical conditions and often receive inferior medical care, both of which likely contribute to their elevated mortality. In this chapter, I briefly review the data on the prevalence of comorbid medical conditions and the lack of quality medical care for patients with SMI, examine prior studies that attempt to improve the health status of these patients, and consider policies that might improve the integration of medical and mental health care for patients with SMI.

Medical Comorbidity and Access to Quality Medical Care for Patients With Serious Mental Illness Patients with schizophrenia and other serious mental illnesses constitute a particularly vulnerable group, for whom access to quality medical care is problematic (Druss et al. 2001a; Harvey et al. 2005). Druss et al. (2001a) reported that following myocardial infarction, patients with schizophrenia had a 30% greater 1-year mortality than patients who were not mentally ill. Approximately half of this increased mortality was due to a lack of quality medical treatment after the myocardial infarction. Folsom et al. (2002) found that in homeless patients with mental illness, those with schizophrenia were less likely to receive primary and preventive care than were patients with major depression. Furthermore, investigators have reported elevated cardiovascular risk (McCreadie 2003), as well as inferior medical care and elevated mortality in persons with schizophrenia compared with the general population (Koran et al. 1989; Phelan et al. 2001). For example, the rates of reported hypertension were 40% lower in persons with schizophrenia than in the general population, but the rates of admission for end-stage complications of hypertension, including cardiomyopathy and pulmonary

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edema, were 1.8 and 1.5 times greater, respectively, in the patients with schizophrenia (Munk-Jørgensen et al. 2000). These findings suggest that patients with schizophrenia were less likely to receive treatment in the early phase of a disease and instead were receiving care later, when the disease became more severe and required hospitalization. Some encouraging data have also been published regarding health care for patients with schizophrenia. An investigation of patients treated in community-based settings found that, compared with the general population, a greater percentage of patients with schizophrenia had received primary care treatment in the prior year (Dickerson et al. 2003). At the same time, the growing concerns about the risk of diabetes, myocardial infarction, and stroke in patients taking atypical antipsychotics have increased the awareness of the importance of diagnosis and treatment of comorbid medical conditions in patients with schizophrenia (Folsom and Okereke 2005; Jin et al. 2004).

Models for Improving Medical Care for Patients With Serious Mental Illness Although the literature on interventions and service delivery models to improve the health outcomes of patients with SMI is not as extensive as that of treating depression in primary care, four basic approaches have been examined: 1) health care skills training for patients, 2) training of psychiatrists to directly provide primary care, 3) facilitated referral to primary care, and 4) co-location or integration of primary care with mental health care (Druss 2007).

Health Care Skills Training for Patients Several interventions that have been developed and tested focus on providing education and skills training for patients with chronic mental illnesses who also have a comorbid medical condition. Two skills training interventions specifically related to health care outcomes are particularly noteworthy. One intervention has been described by McKibbin et al. (2006), who enrolled 60 patients over age 40 with schizophrenia and comorbid diabetes into their diabetes awareness and rehabilitation training (DART) program. These authors tested whether patients who received an intervention based on social cognitive theory and incorporating standard diabetes self-management approaches experienced greater reductions in weight and hemoglobin A1c than did a comparison group that received only diabetes education. The intervention

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lasted 24 weeks, with patients randomly assigned to one of the two groups. At the end of the study, patients in the DART intervention lost an average of 2.3 kg, compared with a 2.7-kg weight gain in the comparison group; however, there were no significant differences in hemoglobin A1c between the two groups. The second skills training intervention is exemplified by Wu et al.’s (2008) study, which included patients who had experienced at least a 10% weight gain from atypical antipsychotics. A 2 ×2 factorial design was used to compare the effects of a lifestyle intervention, metformin (a diabetes medication that inhibits hepatic glucose production), both interventions, and placebo. This study, conducted in China, enrolled 128 patients and examined changes in weight after 12 weeks of treatment. Over the 12-week period, patients in the placebo group gained an average of 3.1 kg, whereas those receiving the lifestyle intervention lost 1.4 kg, those taking metformin lost 3.2 kg, and those in the combined lifestyle-metformin group lost 4.7 kg. Similar results were reported by Weber and Wyne (2006), who also tested a cognitive-behavioral intervention for overweight patients taking an atypical antipsychotic. The mean body mass index of patients enrolled in this study was 33, and at the end of the investigation, the mean weight loss for those in the intervention group was 2.4 kg, compared with 0.6 kg for those in the comparison group. These results demonstrate that lifestyle interventions modified for patients with schizophrenia and other serious mental illnesses can result in improved health outcomes. However, aside from weight gain and a single report on patients with diabetes, data are lacking on the effects of patient education interventions on other health outcomes for patients with SMI. Ongoing studies funded by the National Institute of Mental Health (NIMH) are examining health care outcomes, and in the coming years, information from these studies should help provide data on improving the health of patients with SMI and other health problems.

Training of Psychiatrists to Provide Primary Care A second approach to improving the health of patients with SMI is to have some aspects of primary health care provided by psychiatrists. McIntyre and Romano’s (1977) article “Is There a Stethoscope in the House (and Is It Used)?” highlighted the lack of practicing psychiatrists’ comfort with conducting physical examinations of their patients. Shore (1996) proposed that psychiatrists need to be able to provide

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basic primary care to their patients with SMI, arguing that psychiatrists are frequently the only physicians these patients see. Golomb et al. (2000) assembled a consensus panel of Veterans Affairs (VA) psychiatrists, internists, hospital administrators, and nurses to identify health conditions that would be appropriately treated by a psychiatrist who has primary care training and on-site supervision by an internist. All panel members agreed that a psychiatrist with primary care training could provide care for 17 of 38 preventive screening and counseling interventions but could perform only 10 of 157 evaluations of medical conditions and provide treatment for only 14 of 125 medical conditions. Examples of common medical conditions that the consensus panel thought primary care psychiatrists could treat included cough, headache, and nasal congestion. Examples of common conditions that the panel did not think that primary care psychiatrists could treat included chest pain and ear infection. A few psychiatry residencies have begun to train their residents to provide primary care to patients with serious mental illness. These programs include the University of California San Diego and the Oregon Health and Science University in Portland. In a series of reports, Dobscha and colleagues at the Portland VA describe the outcomes of providing this type of training in an integrated psychiatry primary medical care (PPMC) program (Dobscha and Ganzini 2001; Dobscha et al. 2005; Snyder et al. 2008). In one of these studies (Dobscha et al. 2005), nine graduates of the PPMC program and 34 other residency graduates were asked how comfortable they were with general medical conditions and how frequently they screened for or provided treatment for medical conditions. Responses indicated that, overall, the residents who worked in the PPMC program were more comfortable with general medical conditions than were their fellow residents who did not work in this program. However, few of the PPMC-trained residents provided direct medical care to their patients after graduation. In summary, despite some recommendations that training psychiatrists should provide a limited range of primary care to their patients with a serious mental illness, this model has been adopted in only a few residency training programs. In addition, although the data from these programs are limited, the psychiatrists whose training included providing primary care for some of their patients appeared to be more comfortable with the medical problems of their patients than were psychiatrists without such training, but the primary care–trained psychiatrists did not provide much direct medical care after leaving the training program.

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Facilitated Referral to Primary Care The third model for improving the health care of patients with SMI is to improve the ability of mental health centers to refer their patients to primary care providers and medical clinics. This can be done either by providing training, time, and resources to all of the mental health clinicians in a particular clinic or by having a specific care manager provide this linkage and care coordination. Some empirical evidence supports this model, and findings indicate that patients who receive specific help with accessing primary care treatment receive more primary and preventive health care than patients who do not receive such help. In a small pilot study, Bartels et al. (2004) compared the primary care received by 24 older patients with a serious mental illness who worked with a nurse care manager whose job was to help patients access primary and preventive health care. Using a chart review, the researchers found that, prior to the intervention, 17% of patients did not have a designated primary care provider and 29% had not received any preventive health care in the past year, whereas after working with the nurse case manager, all the patients had a designated primary care provider and had completed a preventive health care visit. In a larger study of 470 patients with a substance abuse disorder entering a detoxification program, Samet et al. (2003) randomly assigned half to a one-time comprehensive assessment plus working with a social worker to arrange for follow-up primary medical care at a clinic, and the other half of the patients received usual care. The patients in the clinic intervention group were more likely to have successfully seen a primary care physician at least once in the 12 months after completing the detoxification program than were patients who received usual care (69% vs. 53%). Currently, at least two ongoing NIMH-funded studies are examining whether this model would result in improved health outcomes for patients with serious mental illness (S. Bartels, personal communication, July 2008; Druss 2007).

Co-Location or Integration of Mental Health Treatment and Primary Care The fourth approach to improving the health care of patients with SMI is to co-locate primary care and mental health care within the same clinic, ideally in an integrated manner that has psychiatrists and primary care providers working together to care for patients with SMI and chronic medical conditions. These clinics would be staffed by a combination of psychiatry and primary care physicians, or by physicians du-

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ally trained in psychiatry and a primary care specialty (family medicine or internal medicine). Druss et al. (2001b) compared patient outcomes in a clinic that provided integrated medical and psychiatric care with those of a clinic providing a usual care model. In this VA-based study, 59 patients were randomly assigned to receive care in an integrated care clinic based in a VA mental health clinic that was also staffed by a full-time nurse practitioner, a part-time family physician, and a nurse case manager. The comparison group included 61 veterans who received their care in a typical VA outpatient medical clinic. Approximately three-fourths of the patients had a serious mental illness, with posttraumatic stress disorder, substance use disorders, and schizophrenia being the most common diagnoses. In addition, more than half of the patients had a previously unknown medical diagnosis. Compared to the patients receiving usual care, those in the integrated care clinic were more likely to use primary care services and less likely to use the emergency room. In addition, patients in the integrated clinic were more likely to receive preventive health care, including screening for colon cancer and diabetes, immunizations, and health education. Patients in the integrated clinic also rated their satisfaction with care more highly than did those in the comparison group, and demonstrated a small but significant improvement in their physical health-related quality of life. In an interesting qualitative assessment of this integrated clinic, Miller et al. (2003) used focus groups to identify three aspects of integrated care that were particularly important to people with a serious mental illness. First, patients reported that they had previously faced difficulty obtaining medical care in more traditional settings. For example, patients reported that in the past they had been turned away from medical clinics, were not treated with respect, or had their medical concerns dismissed. Second, the integrated clinic had greater flexibility and availability of resources, including a nurse case manager and a smaller patient panel size for the primary care providers. Finally, both patients and clinic staff noted that the communication between the patients’ psychiatrist and primary care provider was greater than what they had previously experienced, and primary care and mental health clinicians reported that they benefited from regular contact with each other. Another option for integrated care, training physicians in both psychiatry and a primary care specialty, has been less well studied. To date, two studies have been published describing the type of practice setting for dually trained physicians. A survey of physicians trained in both family medicine and psychiatry found that most (60%) practice both family medicine and psychiatry (McCahill and Palinkas 1997). In con-

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trast, psychiatrists also trained in internal medicine reported that only 15% practiced any type of medicine and 75% identified themselves as psychiatrists (Stiebel and Schwartz 2001). However, neither of these reports examined the patient outcomes of care provided by these dually trained physicians compared with usual care. Also, both of these studies are based on data that are more than a decade old, and more training programs are available now than when these data were published. Dual training programs in the United States are limited. Only seven training programs are offered in family medicine and psychiatry and 11 in internal medicine and psychiatry, and most of these programs take only two residents per year. In 2007, a total of 11 graduating medical students matched into family medicine and psychiatry residencies and 22 matched into internal medicine and psychiatry residencies (National Resident Matching Program 2008).Therefore, although this model of training physicians in both psychiatry and a primary care specialty offers the possibility of truly integrated medical and psychiatric care for patients with serious mental illness, the capacity of the current training programs is not large enough to provide this kind of care on a large scale. In summary, two models have been proposed for providing integrated medical and psychiatric care to people with serious mental illness: 1) co-locating primary care physicians in mental health clinics and 2) staffing these clinics with physicians trained in both psychiatry and a primary care specialty. Druss (2007) suggested that these types of clinics may be best suited for VA system and staff model health maintenance organizations, which use shared funding streams and medical records.

Challenges to Providing Medical Care for Patients With Serious Mental Illness Patient Level Researchers have offered several explanations as to why people with schizophrenia receive less health care than the general population. People with schizophrenia may have problems explaining their medical symptoms to primary care physicians. Physicians may be uncomfortable treating persons with schizophrenia (Lawrie et al. 1996), possibly reflecting a stigmatization of people with schizophrenia. Similarly, psychiatrists may not feel comfortable providing primary and preventive health care for their patients (McIntyre and Romano 1977). Fang and

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Rizzo (2007) used data from a national survey of physicians to examine whether psychiatrists had less access to medical services for their patients than did other medical specialists. This study compared psychiatrists’ reports of their ability to obtain medically necessary medical care for their patients with those of other specialist physicians. The study found that psychiatrists rated their ability to obtain most types of medical care “dramatically” lower than did other specialists, in part because many patients did not have insurance and those who did had barriers from their health plan.

Policy Level According to Horvitz-Lennon et al. (2006), challenges to integrating primary health care into specialty mental health treatment exist on three levels: clinical, organizational, and financial. Clinical challenges include the lack of training in physical health care by mental health clinicians. It is important to note that although most psychiatrists do not feel comfortable providing primary medical care, the knowledge of and comfort with medical problems is even lower among other mental health care providers, who rarely have formal medical training. Financial challenges include the high rates of uninsurance among persons with serious mental illness and the fact that financing for public mental health programs is typically separate from that of other public health programs. For example, in the San Diego County public mental health system, approximately 50% of patients with a serious mental illness are uninsured (Folsom et al. 2005). Furthermore, the application process for and financial restrictions of the public mental health system are separate and different from those of the safety-net health care program, resulting in a large number of patients receiving mental health treatment who do not have coverage for medical care.

Conclusion The growing recognition that people with schizophrenia and other serious mental illnesses have elevated rates of many medical conditions and often do not receive adequate medical care challenges psychiatrists and the mental health field to come up with practical approaches to improving their care. The four potential approaches examined in this chapter—health care skills training for patients, training psychiatrists to provide limited primary care, facilitated referral to primary care, and integration of primary care into mental health clinics—are all supported by some data. However, none of these approaches currently is

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widespread, and no single approach is likely to provide a solution. In an ideal world, psychiatrists would help ensure that their patients receive high-quality physical health care; staff at mental health clinics would help patients who need health care; mental health clinics would offer onsite primary care; and the financial barriers to providing integrated physical and mental health care would be removed.

Key Clinical Points ◗

Patients with schizophrenia and other serious mental illnesses receive less primary and preventive care than needed.

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Guidelines alone are unlikely to result in improved health care for patients with serious mental illness.

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Prior studies have examined four ways of improving health care for people with serious mental illness: health care skills training for patients, training psychiatrists to provide limited primary care, facilitated referral to primary care, and providing onsite primary care in mental health clinics.

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Integrating primary care into mental health clinics may require significant changes in how mental health care is funded and delivered.

References Abilify (package insert). Princeton, NJ, Bristol-Myers Squibb, 2008 American Diabetes Association, American Psychiatric Association, American Association of Clinical Endocrinologists, et al: Consensus Development Conference on Antipsychotic Drugs and Obesity and Diabetes. Diabetes Care 27:596–601, 2004 Bartels SJ, Forester B, Mueser KT, et al: Enhanced skills training and health care management for older persons with severe mental illness. Community Ment Health J 40:75–90, 2004 Clozaril (package insert). East Hanover, NJ, Novartis Pharmaceuticals Corp., 2008 Daumit GL, Crum RM, Guallar E, et al: Outpatient prescriptions for atypical antipsychotics for African Americans, Hispanics, and whites in the United States. Arch Gen Psychiatry 60:121–128, 2003 Dickerson FB, McNary SW, Brown CH, et al: Somatic healthcare utilization among adults with serious mental illness who are receiving community psychiatric services. Med Care 41:560–570, 2003

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Dobscha SK, Ganzini L: A program for teaching psychiatric residents to provide integrated psychiatric and primary medical care. Psychiatr Serv 52:1651– 1653, 2001 Dobscha SK, Snyder KM, Corson K, et al: Psychiatry resident graduate comfort with general medical issues: impact of an integrated psychiatry-primary medical care training track. Acad Psychiatry 29:448–451, 2005 Druss BG: Improving medical care for persons with serious mental illness: challenges and solutions. J Clin Psychiatry 68:40–44, 2007 Druss BG, Bradford WB, Rosenheck RA, et al: Quality of medical care and excess mortality in older patients with mental disorders. Arch Gen Psychiatry 58:565–572, 2001a Druss BG, Rohrbaugh RM, Levinson CM, et al: Integrated medical care for patients with serious psychiatric illness. Arch Gen Psychiatry 58:861–868, 2001b Fang H, Rizzo JA: Do psychiatrists have less access to medical services for their patients? J Ment Health Policy Econ 10:63–71, 2007 Folsom DP, Okereke OI: Medical comorbidity in geriatric psychiatry. Am J Geriatr Psychiatry 13:1, 2005 Folsom D, McCahill M, Bartels S, et al: Medical comorbidity and receipt of medical care by older homeless people with schizophrenia or depression. Psychiatr Serv 53:1456–1460, 2002 Folsom DP, Hawthorne W, Lindamer L, et al: Prevalence and risk factors for homelessness and utilization of mental health services among 10,340 patients with serious mental illness in a large public mental health system. Am J Psychiatry 162:370–376, 2005 Geodon (package insert). New York, NY, Pfizer, Inc., 2008 Golomb BA, Pyne JM, Wright B, et al: The role of psychiatrists in primary care of patients with severe mental illness. Psychiatr Serv 51:766–773, 2000 Harrington C, Gregorian R, Gemmen E, et al; for The Lewin Group: Access and utilization of new antidepressant and antipsychotic medications. January 2000. Available at: http://aspe.hhs.gov/search/health/reports/Psychmedaccess/ index.htm#TOC. Accessed October 8, 2008. Harvey SB, Newton A, Moye GA: Physical health monitoring in schizophrenia: the use of an invitational letter in a primary care setting. Primary Care and Community Psychiatry 10:71–74, 2005 Henderson DC, Cagliero E, Copeland PM, et al: Glucose metabolism in patients with schizophrenia treated with atypical antipsychotic agents: a frequently sampled intravenous glucose tolerance test and minimal model analysis. Arch Gen Psychiatry 62:19–28, 2005 Horvitz-Lennon M, Kilbourne AM, Pincus HA: From silos to bridges: meeting the general health care needs of adults with severe mental illnesses. Health Aff (Millwood) 25:659–669, 2006 IMS Health: Atypical antipsychotics—generating evidence to inform policy and practice. 2002. Available at: http://research.imshealth.com/research/ research_schizophrenia.htm. Accessed May 15, 2006.

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Jin H, Meyer JM, Jeste DV: Atypical antipsychotics and glucose dysregulation: a systematic review. Schizophr Res 71:195–212, 2004 Koran LM, Sox HC, Marton KI, et al: Medical evaluation of psychiatric patients: results in a state mental health system. Arch Gen Psychiatry 46:733–740, 1989 Lawrie SM, Parsons C, Patrick J, et al: A controlled trial of general practitioners’ attitudes to patients with schizophrenia. Health Bull 54:201–203, 1996 Leslie DL, Rosenheck RA: Incidence of newly diagnosed diabetes attributable to atypical antipsychotic medications. Am J Psychiatry 161:1709–1711, 2004 Lieberman JA, Stroup TS, McEvoy JP, et al: Effectiveness of antipsychotic drugs in patients with chronic schizophrenia. N Engl J Med 353:1209–1223, 2005 Marder SR, Essock SM, Miller AL, et al: The Mount Sinai Conference on the Pharmacotherapy of Schizophrenia. Schizophr Bull 28:5–16, 2002 McCahill ME, Palinkas LA: Physicians who are certified in family practice and psychiatry: who are they and how do they use their combined skills? J Am Board Fam Pract 10:111–115, 1997 McCreadie RG; Scottish Schizophrenia Lifestyle Group: Diet, smoking and cardiovascular risk in people with schizophrenia: descriptive study. Br J Psychiatry 183:534–539, 2003 McIntyre JS, Romano J: Is there a stethoscope in the house (and is it used)? Arch Gen Psychiatry 34:1147–1151, 1977 McKibbin CL, Patterson TL, Norman G, et al: A lifestyle intervention for older schizophrenia patients with diabetes mellitus: a randomized controlled trial. Schizophr Res 86:36–44, 2006 Miller CL, Druss BG, Rohrbaugh RM: Using qualitative methods to distill the active ingredients of a multifaceted intervention. Psychiatr Serv 54:568– 571, 2003 Munk-Jørgensen P, Mors O, Mortensen PB, et al: The schizophrenic patient in the somatic hospital. Acta Psychiatr Scand Suppl 407:96–99, 2000 National Resident Matching Program. Available at: http://www.nrmp.org/ data/resultsanddata2007.pdf. Accessed August 12, 2008. Phelan M, Stradins L, Morrison S: Physical health of people with severe mental illnesses. BMJ 322:443–444, 2001 Risperdal (package insert). Titusville, NJ, Janssen Pharmaceutica, Inc., 2008 Samet JH, Larson MJ, Horton NJ, et al: Linking alcohol- and drug-dependent adults to primary medical care: a randomized controlled trial of a multidisciplinary health intervention in a detoxification unit. Addiction 98:509– 516, 2003 Schneider LS, Dagerman KS, Insel P: Risk of death with atypical antipsychotic drug treatment for dementia: meta-analysis of randomized placebocontrolled trials. JAMA 294:1934–1943, 2005 Seroquel (package insert). Wilmington, DE, AstraZeneca Pharmaceuticals, LP, 2008 Shore JH: Psychiatry at a crossroad: our role in primary care. Am J Psychiatry 153:1398–1403, 1996

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Snyder K, Dobscha SK, Ganzini L, et al: Clinical outcomes of integrated psychiatric and general medical care. Community Ment Health J 44:147–154, 2008 Stiebel V, Schwartz CE: Physicians at the medicine/psychiatric interface: what do internist/psychiatrists do? Psychosomatics 42:377–381, 2001 Weber M, Wyne K: A cognitive/behavioral group intervention for weight loss in patients treated with atypical antipsychotics. Schizophr Res 83:95–101, 2006 Wells KB, Sherbourne C, Schoenbaum M, et al: Impacts of disseminating quality improvement programs for depression in managed primary care: a randomized controlled trial. JAMA 283:3204, 2000 Wu RR, Zhao JP, Jin H, et al: Lifestyle intervention and metformin for treatment of antipsychotic-induced weight gain: a randomized controlled trial. JAMA 299:185–193, 2008 Zyprexa (package insert). Indianapolis, IN, Eli Lilly, Inc., 2008

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CHAPTER 2 Excessive Mortality and Morbidity Associated With Schizophrenia Daniel E. Casey, M.D. Thomas E. Hansen, M.D.

Psychiatric conditions have long been recognized to be associated with premature mortality. In his review, Brown (1997) noted that “lunatics” (perhaps 25% having schizophrenia) in a study from 1841 experienced mortality at three to 14 times the rate seen in the general population. According to Brown, Eugen Bleuler reported that mortality in patients with schizophrenia was 1.4 times the expected rate, caused by accidents, suicide, refusing food, infectious disease, and other diseases from poor sanitation. Brown stated that although Emil Kraepelin considered mortality to be only slightly increased in dementia praecox, he reported that suicide, negativism, diet, and poor cooperation with medical care contributed to increased mortality. Studies from the first half of the twentieth century found mortality rates in psychiatric patients to be two and four times higher than in age- and gender-matched populations (Brown 1997). Hazards of institutional care (such as tuberculosis and gastrointestinal disease) added to risks associated with the underlying psychiatric illness. Unnatural causes (suicide and accidental 17

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death) became an increasingly important cause of premature death with the shift from inpatient to outpatient care for patients with schizophrenia (Black et al. 1985). More recently, cardiovascular disease and diabetes may be increasing in importance as causes of death and morbidity in these patients (Jeste et al. 1996). This chapter updates our earlier review (Casey and Hansen 2003) of mortality and morbidity associated with schizophrenia. Data clearly demonstrate that the life span for patients with schizophrenia is shortened. Many conditions leading to premature death are evident during patients’ lifetimes and account for the majority of the excess morbidity seen in patients with schizophrenia. Both patient behaviors and societal aspects of care for schizophrenia can contribute to this increase in morbidity.

Life Span and Mortality in Patients With Schizophrenia Mortality Rates Reports on mortality rates commonly use record linkage methodology: databases of all deaths in a region are linked with population registers of psychiatric patients (community or hospital derived) so that the number of deaths in a group of patients with a specific diagnosis can be determined. This observed number is contrasted to the number expected based on life expectancy data for people of the same age and gender applied to the time period studied. The ratio of observed to expected cases is the standardized mortality ratio (SMR), sometimes reported as the ratio multiplied by 100. The 95% confidence interval (CI) values indicate statistical significance, with lower CI values above 1.0 (or 100, when the SMR is multiplied by 100) supporting significance for elevated SMR, and upper CI values below 1.0 (or 100) supporting significance for decreased SMR (Harris and Barraclough 1998). In this chapter, for ease of comparison, we report SMR and CI data without multiplying by 100, even if so reported in cited references. Reviews of mortality rates consistently find increased death rates in patients with schizophrenia. This consistency is remarkable when one considers variation in methods across individual studies and reviews. For instance, individual studies from earlier periods may be overly influenced by inclusion of hospitalized patients (lower risk of suicide, higher risk of diseases related to institutionalization), whereas later studies are likely to include outpatients (greater risk of suicide) and to be more precise in diagnosis.

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Three reviews that summarized results from studies conducted between 1942 and 1996 found the mortality rate in patients with schizophrenia to be between 1.5 and 2 times the expected rate. Allebeck (1989) reviewed nine studies published between 1942 and 1985 in which patients had been followed at least 5 years and found mortality about twice the expected rate. He noted difficulty in ascertaining whether rates had changed because diagnostic and study criteria had varied over time. Brown (1997) examined studies published between 1986 and 1996 with schizophrenia patient populations of at least 100 individuals recruited after 1952 that included observed and expected death rates and that had follow-up periods of at least 2 years, with losses to followup of less than 15%. He found an aggregate SMR of 1.51 (95% CI 1.48– 1.54). The SMR for suicide was elevated (8.38, 95% CI 7.84–8.94), as were the SMR for accidents (2.16, 95% CI 1.96–2.36) and the SMR for natural causes of death (1.1, 95% CI 1.05–1.15). Brown interpreted data about specific natural causes of death conservatively, stating that patients with schizophrenia die from the same diseases as the rest of the population. He noted that peptic ulcer (perhaps related to alcohol use) and pneumonia (probably associated with elderly institutionalized patients) caused deaths at higher than expected rates. Harris and Barraclough (1998) reviewed mortality rates in cohorts of patients with various mental disorders between 1966 and 1995 (20 studies, nine countries, almost 36,000 patients) and found a death risk in patients with schizophrenia that was 1.6 times expected. The death risk from unnatural causes (suicide and violence) was 4.3 times that expected, whereas death from natural causes was 1.4 times that expected, but natural causes accounted for 68% of the excess in expected deaths. In our earlier review (Casey and Hansen 2003), we described three studies published in 2000–2001, with data on patients studied between 1973 and 1995, in which mortality rates were reported to be somewhat higher than in the earlier reviews (significantly increased relative risk or SMR of 2.4–3.8, depending on patient gender). A meta-analysis by Saha et al. (2007) confirms that SMRs for schizophrenia are increasing; the analysis reviewed 37 articles published between 1980 and 2006 from 25 countries and found the overall SMR to be 2.58. When studies were grouped by midpoint of the follow-up period, SMR increased from 1.84 in the 1970s, to 2.98 in the 1980s, and to 3.2 in the 1990s. A study not included in the meta-analysis from rural China (Ran et al. 2007) followed 510 patients with schizophrenia for the 10-year period of 1994–2004 and further demonstrated higher mortality in more recent studies (overall SMR of 4.0, 95% CI 2.4–5.8).

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Life expectancy and survival curve data offer further confirmation of increased mortality associated with schizophrenia. In our earlier review (Casey and Hansen 2003), we noted that in three studies based on 5- to 10-year follow-up of patients, authors projected decreased life expectancy of 8–16 years in general and of 3–4 years for patients ages 60 years and older. Three more recent studies also utilize survival data. Patients with first admissions for psychosis in Suffolk County, New York, between 1989 and 1995 were evaluated for survival rates at 5 and 10 years using survival curves; survival rates were 96.9% at 5 years and 94.5% at 10 years for the 235 patients with schizophrenia or schizoaffective disorder, with 60% of deaths resulting from unnatural causes (Craig et al. 2006). In a 10-year (1981–1991) mortality study of 255 patients with schizophrenia from Uppsala, Sweden, 23% of patients died compared with 11% of the 1,275 controls (P=0.003) (Fors et al. 2007). Patients with schizophrenia (n =319) seen at the Mayo Clinic from 1950–1980 were followed up to 2005 (mean 23.5 years); 44% died during this time, a rate higher (P <0.001) than for a comparable U.S. population (the specific rate was not reported, but appears to be 34% from the survival curve comparison) (Capasso et al. 2008). Thus, data from the last 50 years demonstrate that the increase in mortality seen for patients with schizophrenia in earlier time periods persists. Furthermore, the disparity in death rates between patients with schizophrenia and the general population appears to be widening.

Suicide and Other Unnatural Causes of Mortality Reviews consistently find that patients with schizophrenia die from suicide at increased rates compared with the general population (Allebeck 1989; Harris and Barraclough 1998), although underreporting is a possibility because suicides can be incorrectly reported as resulting from accidents or undetermined causes (Allebeck 1989). In this section, we focus on suicide as an unnatural cause of death given the lower mortality rates from accidents. For instance, one review reported SMRs of 8.38 for suicide and 2.16 for accidents (Brown 1997). In a Danish register study of patients admitted between 1973 and 1993 who died by 1993, Hiroeh et al. (2001) reported for males an SMR of 10.7 for suicide compared with 2.1 for accidents, and for females an SMR of 10.8 for suicide compared with 2.9 for accidents. In our earlier review (Casey and Hansen 2003), we summarized data from multiple studies; SMR values generally ranged from 12 to 20, except SMR of 1.32 in one study (Mortensen and Juel 1990) that included mostly elderly institutionalized patients from 1957 to 1986. Several recent stud-

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ies have found suicide SMRs in the higher range. The rate of suicide in the general population and in patients with schizophrenia in Denmark declined between 1981 and 1997, but the incidence ratio remained 20 times higher for patients with schizophrenia (Nordentoft et al. 2004). Even correcting for social and demographic differences, the rate remained high at 12.26. A French 10-year follow-up study starting in 1993 (Limosin et al. 2007) found the suicide SMR for males to be 15.8 (95% CI 13.7–18.2) and for females to be 17.7 (95% CI 13.6–23.1). In both of these studies, suicide rates were highest within the first year of follow-up. The suicide mortality data support several observations. The increase in risk from suicide for patients with schizophrenia was much lower many years ago when patients were commonly kept in hospitals for long time periods. The risk is greatest early in the course of illness and close to the hospital discharge, so that mortality rates vary between studies depending in part on study inclusion criteria. Finally, the risk of suicide appears to be increasing, perhaps related to greater reliance on less intensive treatment emphasizing outpatient care. A national psychological autopsy study from Finland provides important details about the nature of suicide by patients with schizophrenia (Heila et al. 1997). All suicides occurring during a 1-year period during 1987 and 1988 were identified. Providers and next of kin were interviewed, and adequacy of medication was examined. This sample had a somewhat older age of suicide (mean 40 years old) than hospitaltreated or initially treated patient groups. The mean illness duration was 15.5 years, and 75% of patients had active symptoms. About 9% had current suicide-command hallucinations. Twenty-five (27%) were hospitalized at the time of suicide, and 29 (32%) had been discharged within 3 months. A depressive syndrome had been present during either a residual or an active phase of psychosis in 61 patients (66%), with depressive symptoms at the time of suicide in 59 (64%). Drug overdose was the most common single cause of death (34 patients, 37%), although various violent means were used in 37 cases (40%). Of 34 drug overdoses, 27 (79%) were with neuroleptic medication and 25 (74%) specifically involved low-potency neuroleptics. The authors suspected that with the shift toward outpatient management, the availability of drugs to use in overdoses has increased. Additional data on risk factors and adequacy of treatment were reviewed for the 88 patients who were in treatment at the time of suicide (Heila et al. 1999). Data on compliance and treatment responsiveness were available for about 72 patients. For the entire group of patients who committed suicide (either with active psychotic symptoms or during a residual phase of illness), only 34 (47%) appeared to be compliant and to be receiving an adequate dosage

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of antipsychotic medication. Data were similar when the patients in active phase of illness were examined separately. Only 26 (46%) of the 57 patients experiencing active symptoms at the time of suicide were receiving an adequate dosage (defined as 700 mg daily in chlorpromazine equivalents) and were compliant in taking medication. These two studies suggest the importance of effective medication management and provision of appropriate intensity of treatment (if not inpatient, then close outpatient observation) in this era of managed care. The French study cited above also notes the importance of substance abuse (Limosin et al. 2007). Estimates of the lifetime risk of suicide, defined as the proportion of all deaths to which suicide contributes, provide an additional perspective on the importance of suicide in schizophrenia-associated mortality. Data from a large meta-analysis (Harris and Barraclough 1998) were analyzed by plotting the percentage of patients who had died against the percentage of patients who had died by suicide. The curve that best modeled the data was extrapolated to the point at which all members of the cohort would be deceased; the percentage of deaths by suicide was estimated to be 4% of all deaths, which is lower than the frequently cited value of 10% lifetime risk for suicide in patients with schizophrenia (Inskip et al. 1998). This finding was confirmed in a more recent meta-analysis (Palmer et al. 2005). Using both proportionate mortality and case fatality statistics from 61 studies to maximize accuracy in estimating suicide risk, the authors concluded that 4.9% of patients with schizophrenia will commit suicide, usually near the onset of illness. An emphasis on suicide rates may be misleading in terms of absolute risk, because suicide is rare and natural causes of death are far more common in the general population. Roughly two-thirds of excess deaths in patients with schizophrenia are by causes other than suicide, illustrating that although many patients with schizophrenia die from suicide, far more die from other causes. For example, suicide accounted for only 38% of the excess mortality in one review (Harris and Barraclough 1998) and 35% of excess mortality in another (Brown 1997). In a Southampton, England, cohort treated in 1981–1982 with 13 years of follow-up, suicide and other unnatural causes accounted for 33% of the deaths (Brown et al. 2000). Another way to understand this issue is to note that although the relative risk for suicide in patients with schizophrenia compared with the general population is higher than the relative risk for natural causes of death, the absolute risk for natural causes of death is far higher than for suicide in patients with schizophrenia. Thus, excess mortality in schizophrenia derives primarily from natural causes rather than from suicide. (See Table 2–1.)

Excessive Mortality and Morbidity

TABLE 2–1. • • • • •

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Evidence for increased mortality associated with schizophrenia

Increased overall mortality rates in patients with schizophrenia: 1.5–4 times expected Decrease in longevity from survival curves: 8–16 years Increased mortality rates for suicide: 12 to more than 20 times expected Lifetime death from suicide: about 5% Increased standardized mortality ratio from natural causes: at least 2 times expected (varies by disorder)

Natural Causes of Death in Patients With Schizophrenia An autopsy study from the time when phenothiazine medications were new, roughly 50 years ago, provided a view of death by natural causes (Hussar 1966). Autopsy data from 1,275 chronically hospitalized patients with schizophrenia who died at age 40 or older found that heart disease and cancer were the most common causes of death (similar to findings in the general population age 40+ years of that time). Pneumonia was somewhat overrepresented as a cause of death. Undetermined causes and aspiration of food were in the top eight causes of death in the patients with schizophrenia but not in the general population. The authors speculated that phenothiazines could be responsible, although they noted that other investigators at the time found no association between the new medications and death rates. More recent studies quantify increased mortality for various natural causes in patients with schizophrenia. Harris and Barraclough (1998) reviewed mortality rates in cohorts of patients with various mental disorders between 1966 and 1995. Cohorts of patients with schizophrenia had an SMR of 1.37 for natural causes, with significant increases in expected deaths from a variety of medical conditions (infectious, endocrine, circulatory, respiratory, digestive, and genitourinary disorders). In our previous review (Casey and Hansen 2003), we discussed several subsequent studies that reported somewhat higher values for diseasespecific SMR (1.9–2.3). Reviewing individual studies for increased risk of specific disorders presents challenges. Many studies report categories of diseases from the International Classification of Diseases (ICD) rather than specific disorders, not all studies report on the same categories of illness, and some illnesses could fall into more than one category. Also, findings vary between studies, perhaps because the SMR is greatly influenced by a

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small number of observed cases when the expected rate is low. Still, examining individual studies may be helpful in understanding risks for more recent periods, because reviews are likely to include older studies that reflect risks that are no longer as common (e.g., institutionalization and infectious diseases). Two recent Danish register studies of patients with schizophrenia covering overlapping time periods between 1973 and 2001 found significant increases in SMR (with some variation by gender) on the order of 1.44–2.98 for cardiovascular disease, cancer, respiratory diseases, endocrine conditions, gastrointestinal and genitourinary diseases, nervous system illnesses, and infectious diseases (Hiroeh et al. 2008; Laursen et al. 2007). (See Table 2–2.) Cancer, cardiovascular disease, and diabetes warrant additional discussion. The failure to demonstrate increased risk of cancer in patients with schizophrenia when all causes of cancer are aggregated has led to much speculation, including the possibility that having schizophrenia may convey protection from cancer. Consistent and increasing findings of both numbers of deaths from, and risk for, disorders such as cardiovascular disease and diabetes are of current interest. Cancer incidence and mortality rates reported for patients with schizophrenia range from decreased to increased, varying by type of cancer, gender, and country, as well as across studies. In a U.S. population report (Cohen et al. 2002) using a mortality follow-back database that sampled 1% of all deaths from 1986, cancer was the cause of 25 of the 130 deaths in patients with schizophrenia. The unadjusted odds ratio indicated a decreased risk for cancer (0.62, 95% CI 0.4–0.96). Overall, the patients with schizophrenia died at a younger age (55.6 vs. 63.7 years, P< 0.001); adjusting for age and other factors yielded an odds ratio of 0.59 (95% CI 0.38–0.93). A Danish register study (Dalton et al. 2005) of patients admitted with schizophrenia between 1969 and 1995 and followed through 1995 found no difference in overall cancer risk, but differences were seen based on gender and location of cancer. Men had decreased risks of prostate, rectal, and nonmelanoma skin cancer, and a nonsignificant decrease in lung cancer, whereas women had an increased risk of breast cancer. Other authors have noted offsets in mortality risk by location. A decreased rate of lung cancer in males was noted to offset an increased rate of breast cancer in females (Mortensen and Juel 1990) and digestive cancers (Newman and Bland 1991). In the latter study, the SMR for digestive disorders was 1.7 (P<0.05) and for lung cancer was 0.7 (NS). Limited access to cigarettes for institutionalized patients has been raised as a possible explanation for reduced rates of lung cancer (Harris and Barraclough 1998).

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TABLE 2–2. Conditions associated with increased mortality from schizophrenia • • • • • • • •

Cardiovascular disease Diabetes Respiratory disorders Gastrointestinal diseases Central nervous system disorders Genitourinary diseases Infectious diseases Cancer (controversial; breast cancer may be increased and lung cancer decreased)

Two incidence studies on cancer in patients with schizophrenia illustrate varying results between geographic locations for different types of cancer. The authors of the World Health Organization’s three-cohort study (Gulbinat et al. 1992) concluded that patients with schizophrenia do not demonstrate any consistent increase or decrease in risk for cancer. In contrast, the authors of a records linkage study using the Finnish cancer and psychiatric illness registries found a modest but significantly elevated standardized incidence ratio (SIR) for cancer (1.17, 95% CI 1.09–1.25) in patients with schizophrenia (Lichtermann et al. 2001), with the incidence of lung cancer twice as high in patients with schizophrenia (SIR 2.17, 95% CI 1.78–2.60). They also noted that the incidence of gallbladder cancer was elevated (SIR 2.07, 95% CI 1.03–3.70) and wondered about the role of obesity and poor diet in patients with schizophrenia, given that these are risk factors for gallstones, and hence possibly for gallbladder cancer. An investigation of possible lower rates of lung cancer death in patients with schizophrenia (Masterson and O’Shea 1984) led to speculation that phenothiazine medication might have antitumor activity. However, an alternative explanation may be that patients with schizophrenia die from other causes, such as cardiovascular disease, before they reach the expected age of death from lung cancer. Arguing against the hypothesis that phenothiazines have antitumor activity, the authors found that breast cancer caused proportionately more deaths in the patients with schizophrenia (8.3% vs. 3.4% in the general population, P<0.04). The authors also speculated that being nulliparous and having elevated prolactin, both associated with schizophrenia illness and treatment, while practicing inadequate breast care (insufficient self-examinations and incomplete reporting of lumps) could have caused the increase in breast cancer.

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Whether patients with schizophrenia have an increased risk of breast cancer remains unresolved. Two reports using similar Danish register data analysis methods and time periods came to different conclusions about breast cancer risk (Dalton et al. 2003, 2005). As part of a larger study of all types of cancer in men and women, female patients (N= 9,743) admitted for schizophrenia between 1969 and 1993 had a breast cancer SIR of 1.2 (95% CI 1.05–1.38) (Dalton et al. 2005). In another study of women who developed breast cancer between 1970 and 1997, patients with schizophrenia were identified (N=7,541) and found to have decreased risk (relative risk 0.97, 95% CI 0.76–1.20). When controlled for fertility issues, the relative risk fell to 0.90 (95% CI 0.71–1.12). The authors noted that this finding is not surprising because women with schizophrenia are more likely to be nulliparous, a risk factor for breast cancer. They also speculated that alcohol use, another risk factor for breast cancer (not controlled for in their study), may contribute to the apparent increase in risk for breast cancer reported in other studies (Dalton et al. 2003). Researchers who study disease-related mortality rates often report on endocrine and metabolic conditions without specifically mentioning diabetes, although one might expect it to be the most common endocrine condition. For instance, in a British study of patients followed from 1981 to 1994 (Brown et al. 2000), the SMR for all endocrine disorders was elevated at 11.66 (95% CI 3.79–27.21) and the diabetes SMR was 9.96 (95% CI 2.05–29.11), indicating that most of the endocrine mortality was accounted for by diabetes. Two recent studies found lower but significant elevations in mortality from all endocrine disorders. In a Danish register study of patients between 1973 and 1993 (Hiroeh et al. 2008), the endocrine SMR was 1.99 (95% CI 1.37–2.91) for females and 2.29 (95% CI 1.58–3.32) for males. In another Danish study (Laursen et al. 2007) covering 1973–2001, the rate was higher for males (SMR 3.56, 95% CI 2.68–4.73) and lower for females (SMR 1.69, 95% CI 1.14–2.5). Given the accepted increased risk of diabetes associated with some atypical antipsychotic medications (American Diabetes Association et al. 2004), one should expect increasing mortality from diabetes in the future. However, some of the increase may instead appear as increased cardiovascular mortality. Cardiovascular disease causes a large number of deaths in both the general population and patients with schizophrenia. In the review by Harris and Barraclough (1998), circulatory diseases caused 2,313 deaths out of the 5,591 deaths from natural causes, leading to an SMR in males of 1.1 (95% CI 1.04–1.16) and in females of 1.02 (NS, 95% CI 0.96–1.08). Although the increase in risk is relatively small, the number of excess

Excessive Mortality and Morbidity

27

deaths is substantial (230 more than expected compared with a total of excess deaths from natural causes of 1,250). Subsequent studies found higher cardiovascular mortality rates. In one study (Brown et al. 2000), circulatory disease had an SMR of 2.49 (95% CI 1.64–3.63); more specifically, cardiovascular disease had an SMR of 1.87 (95% CI 1.02–2.98). The Danish register studies noted comparable rates of 1.6–2.1. In their study involving patients from 1973 to 1993, Hiroeh et al. (2008) found the circulatory disorder SMR in females to be 1.61 (95% CI 1.47–1.76) and in males to be 1.91 (95% CI 1.75–2.08), whereas Laursen et al. (2007), in their 1973–2001 study, found the cardiovascular disease SMR in females to be 1.72 (95% CI 1.53–1.93) and in males to be 2.07 (95% CI 1.85–2.32). With rising mortality rates related to natural causes, especially diabetes and cardiovascular disease, increased attention to morbidity and health behaviors in patients with schizophrenia is warranted. In this chapter, we touch on these topics only briefly because they are covered in detail in subsequent chapters of this volume (Chapter 4, “Obesity and Schizophrenia”; Chapter 5, “Glucose Intolerance and Diabetes in Patients With Schizophrenia”; Chapter 7, “The Spectrum of Cardiovascular Disease in Patients With Schizophrenia”; and Chapter 9, “Nicotine and Tobacco Use in Patients With Schizophrenia”).

Morbidity in Schizophrenia Medical Conditions The increased rate of mortality from natural causes associated with schizophrenia should be reflected in higher rates of morbidity. In our chapter (Casey and Hansen 2003) in the previous edition of this book, we discussed reviews and studies that found medical conditions in 35%–70% of patients with schizophrenia. The disorders included diabetes, hyponatremia, thyroid disorder, urinary tract infection, bladder dysfunction, hypertension, liver disease, seizures, and visual problems, among others. Results from the interview survey study of patients with schizophrenia from the Patient Outcomes Research Team program (Dixon et al. 1999) illustrate increased medical morbidity. Of 719 patients, 469 (65%) reported having at least one lifetime medical condition, 256 (36%) had more than one condition, and 343 (48%) said the medical condition was active. The authors did not have a comparison control group but noted that the rates for diabetes, hypertension, and cardiac diseases were all higher than rates reported for these conditions in the National Health

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Medical Illness and Schizophrenia

Interview Survey. Not surprisingly, the number of medical comorbidities correlated significantly with patient self-rating of physical health. Jeste et al. (1996) reviewed reports on medical comorbidity in schizophrenia; for unclear reasons, rheumatoid arthritis seems to occur only rarely in patients with schizophrenia, whereas rates of cardiovascular disease and diabetes mellitus appear to be increased. The authors reported that studies vary in finding increased rates of other specific illnesses and that the impression of decreased risk of cancer does not appear to be valid. In the first of two morbidity studies of middle-aged to elderly patients, the authors compared patients with schizophrenia with a group of patients with depression and another group with Alzheimer’s disease; lower rates of physical illnesses were found in the patients with schizophrenia. In the second study, 45 patients with schizophrenia were compared with 38 normal control subjects; patients in both groups were older than age 45 years. Indications of morbidity were comparable, but the control group was about 10 years older than the patients with schizophrenia, suggesting that the schizophrenia group’s rate of morbidity was comparable to that of an older population. The authors noted that patients with schizophrenia endorsed more medical concerns when questioned in a structured manner. The expected increase in morbidity in patients with schizophrenia was also seen in a case-control study of hospitalizations in Stockholm, Sweden (Dalmau et al. 1997). The authors gathered data regarding treatment of somatic conditions in 775 schizophrenia patients and 775 case-matched control subjects regardless of whether the treatment occurred in a psychiatric or a general medical ward. The schizophrenia group had 523 (67%) admissions compared with 373 (48%) for the control group over the 15-year study period (McNemar test, P=0.000). An increased odds ratio was found for almost all medical disorders occurring in patients with schizophrenia, with the exception of genitourinary, musculoskeletal, and sensory organ diseases. Tumors (combined malignant and benign) were found twice as often in patients with schizophrenia. In summary, data demonstrate increased morbidity from medical conditions in patients with schizophrenia. Although almost all disorders can occur at higher than expected rates, cardiovascular disease and diabetes are particular concerns.

Substance Abuse Patients with schizophrenia have increased rates of all types of substance abuse (Dixon 1999), as is covered in detail in Chapter 11,

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“Substance Abuse and Schizophrenia.” The adverse psychiatric effects (Dixon 1999) combined with medical problems caused by substance abuse lead to the expectation of increased morbidity and mortality in patients with schizophrenia who abuse drugs or alcohol. Not surprisingly, Dalmau et al. (1997) found that inclusion of schizophrenia patients with substance abuse in their study cohort increased the number of somatic conditions that occurred more frequently in schizophrenia patients than in a nonpsychiatric control population. Also, results from a study of diabetes mortality in patients with co-occurring psychotic and substance use disorders suggested that diabetes may be increased in this group and be associated with a high mortality rate (Jackson et al. 2007).

Health Maintenance in Patients With Schizophrenia Treatment Concerns Treatment during the first half of the twentieth century undoubtedly contributed to morbidity and mortality in schizophrenia. Physical interventions such as leucotomy, insulin coma therapy, and cardiazolinduced convulsive therapy all carried substantial risk (Brown 1997). In the past 50 years, morbidity and mortality concerns related to treatment have shifted to medications, with recent attention focused on extrapyramidal side effects, cardiac conduction, and metabolic side effects (American Diabetes Association et al. 2004; Fontaine et al. 2001). In a 10-year follow-up study of mortality and medication use in patients with schizophrenia, Waddington et al. (1998) found that antipsychotic polypharmacy and absence of cotreatment with anticholinergic medication significantly increased mortality. No clear explanation related to other factors that might covary with polypharmacy seemed plausible, leaving the authors to wonder whether concurrent use of multiple antipsychotic medications causes some adverse biological consequence, or whether unrecognized subclinical drug-induced parkinsonism could contribute to mortality. A 1978–1980 Finnish study also found that increased mortality correlated with the number of prescribed typical antipsychotic medications (Joukamaa et al. 2006). Certainly, extrapyramidal side effects, including tardive dyskinesia, cause substantial morbidity in patients with schizophrenia (Casey 1993; Hansen et al. 1997). For further reading on the contribution of atypical antipsychotic medications to various metabolic problems, please see other chapters in this

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Medical Illness and Schizophrenia

volume: Chapter 4, “Obesity and Schizophrenia”; Chapter 5, “Glucose Intolerance and Diabetes in Patients With Schizophrenia”; Chapter 7, “The Spectrum of Cardiovascular Disease in Patients With Schizophrenia”; and Chapter 9, “Nicotine and Tobacco Use in Patients With Schizophrenia.”

Patient Health Habits and Related Concerns Behaviors such as abuse of drugs and alcohol, smoking, lack of exercise, and dietary indiscretion appear to contribute to mortality in the general population, and thus are likely to do so in patients with schizophrenia (Brown et al. 1999). Brown et al. (2000) noted that the SMR related to natural causes of death was significantly elevated in smokers (3.6, 95% CI 2.7–4.71) but not in nonsmokers (1.78, 95% CI 0.85–3.28). The authors reviewed apparently avoidable natural causes of death in these patients; causes included failure to recognize medical disease by the patient or care provider (3–8 cases), missed diagnoses (3 cases), poor treatment compliance (unable to quantify), treatment refusal (2 cases), and inadequate social support (1 case). Brown et al. (1999) directly investigated lifestyle concerns in 102 patients with schizophrenia. Patients with schizophrenia ate a diet significantly higher in fat and lower in fiber (significant for males, trend for females) than the reference population. Roughly one-third of the patients with schizophrenia reported doing no exercise, and no patient reported doing strenuous exercise (comparison rates not provided). In their sample, female patients demonstrated a trend toward obesity (P= 0.09). The rate of smoking was higher in patients with schizophrenia than in the comparison sample (68% vs. 28% in males, 57% vs. 25% in females); alcohol consumption was decreased in males and unexceptional in females. A study of 22 outpatients with schizophrenia conducted in 1992– 1993 found similar results (Holmberg and Kane 1999): patients with schizophrenia were less likely to practice health-promoting behaviors than were nonpsychiatric populations. In a study of smoking in Irish inpatients with schizophrenia (Masterson and O’Shea 1984), the rate of smoking was higher than for the general population (males 84% vs. 41%, females 82% vs. 36%), as were daily consumption of cigarettes, preference for medium- to high-tar cigarettes (59% vs. 1%), and duration of smoking (longer than 16 years, 80% vs. 56%). The sum of the evidence indicates clearly that patients with schizophrenia engage in behaviors that can be expected to increase morbidity and mortality.

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Access to Health Care One can easily imagine that decreased access to either medical or psychiatric care could exacerbate morbidity and contribute to increased mortality in patients with schizophrenia, and a number of reports suggest that access to medical care may be limited for patients with schizophrenia. Multiple factors could contribute to decreased access, including limitations in the communication of symptoms by patients, poor cooperation by psychotic patients, stigma toward patients with schizophrenia, and insufficient attention to medical problems by mental health providers (Druss and Rosenheck 1997; Goldman 1999). Dixon et al. (1999) found that less than 70% of the patients with medical problems were receiving treatment for their medical conditions in a study of 719 patients with schizophrenia from the Patient Outcomes Research Team project. Masterson and O’Shea (1984) speculated that inadequate breast examinations and incomplete reporting of breast lumps could have contributed to the increased rate of death from breast cancer in their study. The diagnosis of schizophrenia was significantly negatively associated with timeliness, access, and intensity of postdischarge medical care in a study of U.S. veterans (Druss and Rosenheck 1997). Finally, two related studies have demonstrated disparity in care for patients with schizophrenia following myocardial infarction. Patients with schizophrenia were less likely to have cardiac catheterization, more likely to die in the year after discharge, and less likely to receive interventions that represent quality of care following acute myocardial infarction (i.e., reperfusion therapy, or at discharge, aspirin, beta-blockers, and angiotensinconverting enzyme inhibitors) (Druss et al. 2000, 2001). Among the homeless, having a diagnosis of schizophrenia may be associated with better care and reduced mortality compared with the general homeless population. The age-adjusted mortality rate for a New York City homeless sample (follow-up period 1987–1994) was about four times that in a comparable reference group (Barrow et al. 1999). Having a mental illness had a significant protective effect, possibly explained by provision of relatively greater services and better housing for homeless people who were mentally ill than for other homeless people. Likewise, having schizophrenia appeared to convey protection from mortality in a Boston homeless population (Hwang et al. 1998). The benefit of additional care most likely creates only an impression of protection, however, considering that the comparison groups are highly ill and impoverished. For example, mortality was studied in homeless individuals who had been referred to a clinic in Sydney, Australia, between 1988 and 1991 (Babidge et al. 2001). The

Medical Illness and Schizophrenia

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SMR for the nonschizophrenia group was 4.41 (95% CI 2.02–6.19) compared with 2.52 (95% CI 1.8–3.43) for the schizophrenia group. Thus, although the SMR was much lower in the schizophrenia group, it still represented a mortality rate more than twice that expected in the general population.

Conclusion The literature conclusively establishes that patients with schizophrenia die at higher rates and earlier than other people. The causes of this excess mortality have varied over time, reflecting issues related to changes in the care of patients with schizophrenia and the unhealthy lifestyles that result from a combination of their illness and the type of care available. At this time, interventions must address risks from suicide and from medical illnesses. Effective medications with side-effect profiles that promote adherence to treatment plans must be provided. Avoiding adverse metabolic side effects, or at least monitoring and attempting to correct them as they occur, is also critical in reversing the trend toward higher mortality in patients with schizophrenia. Finally, the mental health system must work to ensure that adequate social services, medical treatment, and psychiatric care are provided despite society’s drive to reduce health care costs.

Key Clinical Points ◗

Schizophrenia carries increased mortality, as demonstrated by increased mortality rates and shortened life span.

◗

Differences in mortality rates between patients with schizophrenia and the general population are increasing.

◗

Suicide rates are very high for patients with schizophrenia, especially early in the course of illness.

◗

Increased rates of death from natural causes account for many of the excess deaths seen in patients with schizophrenia, although the increases in mortality rates associated with natural causes are not as great as those associated with suicide.

◗

The natural causes of death for patients with schizophrenia are similar to those that occur in the general population, with cardiovascular disease and diabetes being notably problematic.

Excessive Mortality and Morbidity

33

References Allebeck P: Schizophrenia: a life-shortening disease. Schizophr Bull 15:81–89, 1989 American Diabetes Association, American Psychiatric Association, American Association of Clinical Endocrinologists, et al: Consensus Development Conference on Antipsychotic Drugs and Obesity in Diabetes. Diabetes Care 27:596–601, 2004 Babidge NC, Buhrich N, Butler T: Mortality among homeless people with schizophrenia in Sydney, Australia: a 10-year follow-up. Acta Psychiatr Scand 103:105–110, 2001 Barrow SM, Herman DB, Cordova P, et al: Mortality among homeless shelter residents in New York City. Am J Public Health 89:529–534, 1999 Black DW, Warrack G, Winokur G: The Iowa record-linkage study, I: suicides and accidental deaths among psychiatric patients. Arch Gen Psychiatry 42:71–75, 1985 Brown S: Excess mortality of schizophrenia: a meta-analysis. Br J Psychiatry 171:502–508, 1997 Brown S, Birtwistle J, Roe L, et al: The unhealthy lifestyle of people with schizophrenia. Psychol Med 29:697–701, 1999 Brown S, Inskip H, Barraclough B: Causes of the excess mortality of schizophrenia. Br J Psychiatry 177:212–217, 2000 Capasso RM, Lineberry TW, Bostwick JM, et al: Mortality in schizophrenia and schizoaffective disorder: an Olmsted County, Minnesota cohort: 1950– 2005. Schizophr Res 98:287–294, 2008 Casey DE: Neuroleptic-induced acute extrapyramidal syndromes and tardive dyskinesia. Psychiatr Clin North Am 16:589–610, 1993 Casey DE, Hansen TE: Excessive morbidity and mortality in schizophrenia, in Medical Illness and Schizophrenia. Edited by Meyer JM, Nasrallah HA. Washington, DC, American Psychiatric Publishing, 2003, pp 13–34 Cohen ME, Dembling B, Schorling JB: The association between schizophrenia and cancer: a population-based mortality study. Schizophr Res 57:139–146, 2002 Craig TJ, Ye Q, Bromet EJ: Mortality among first-admission patients with psychosis. Compr Psychiatry 47:246–251, 2006 Dalmau A, Bergman B, Brismar B: Somatic morbidity in schizophrenia: a case control study. Public Health 111:393–397, 1997 Dalton SO, Laursen TM, Mellemkjaer L, et al: Schizophrenia and the risk for breast cancer. Schizophr Res 62:89–92, 2003 Dalton SO, Mellemkjaer L, Thomassen L, et al: Risk for cancer in a cohort of patients hospitalized for schizophrenia in Denmark, 1969–1993. Schizophr Res 75:315–324, 2005 Dixon L: Dual diagnosis of substance abuse in schizophrenia: prevalence and impact on outcomes. Schizophr Res 35(suppl):S93–S100, 1999 Dixon L, Postrado L, Delahanty J, et al: The association of medical comorbidity in schizophrenia with poor physical and mental health. J Nerv Ment Dis 187:496–502, 1999

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Druss BG, Rosenheck RA: Use of medical services by veterans with mental disorders. Psychosomatics 38:451–458, 1997 Druss BG, Bradford DW, Rosenheck RA, et al: Mental disorders and use of cardiovascular procedures after myocardial infarction. JAMA 283:506–511, 2000 Druss BG, Bradford WD, Rosenheck RA, et al: Quality of medical care and excess mortality in older patients with mental disorders. Arch Gen Psychiatry 58:565–572, 2001 Fontaine KR, Heo M, Harrigan EP, et al: Estimating the consequences of antipsychotic induced weight gain on health and mortality rate. Psychiatry Res 101:277–288, 2001 Fors BM, Isacson D, Bingefors K, et al: Mortality among persons with schizophrenia in Sweden: an epidemiological study. Nord J Psychiatry 61:252– 259, 2007 Goldman LS: Medical illness in patients with schizophrenia. J Clin Psychiatry 60 (suppl 21):10–15, 1999 Gulbinat W, Dupont A, Jablensky A, et al: Cancer incidence of schizophrenic patients: results of record linkage studies in three countries. Br J Psychiatry Suppl 75–83, 1992 Hansen TE, Casey DE, Hoffman WF: Neuroleptic intolerance. Schizophr Bull 23:567–582, 1997 Harris EC, Barraclough B: Excess mortality of mental disorder. Br J Psychiatry 173:11–53, 1998 Heila H, Isometsa ET, Henriksson MM, et al: Suicide and schizophrenia: a nationwide psychological autopsy study on age- and sex-specific clinical characteristics of 92 suicide victims with schizophrenia. Am J Psychiatry 154:1235–1242, 1997 Heila H, Isometsa ET, Henriksson MM, et al: Suicide victims with schizophrenia in different treatment phases and adequacy of antipsychotic medication. J Clin Psychiatry 60:200–208, 1999 Hiroeh U, Appleby L, Mortensen PB, et al: Death by homicide, suicide, and other unnatural causes in people with mental illness: a population-based study. Lancet 358:2110–2112, 2001 Hiroeh U, Kapur N, Webb R, et al: Deaths from natural causes in people with mental illness: a cohort study. J Psychosom Res 64:275–283, 2008 Holmberg SK, Kane C: Health and self-care practices of persons with schizophrenia. Psychiatr Serv 50:827–829, 1999 Hussar AE: Leading causes of death in institutionalized chronic schizophrenic patients: a study of 1,275 autopsy protocols. J Nerv Ment Dis 142:45–57, 1966 Hwang SW, Lebow JM, Bierer MF, et al: Risk factors for death in homeless adults in Boston. Arch Intern Med 158:1454–1460, 1998 Inskip HM, Harris EC, Barraclough B: Lifetime risk of suicide for affective disorder, alcoholism and schizophrenia. Br J Psychiatry 172:35–37, 1998

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Jackson CT, Covell NH, Drake RE, et al: Relationship between diabetes and mortality among persons with co-occurring psychotic and substance use disorders. Psychiatr Serv 58:270–272, 2007 Jeste DV, Gladsjo JA, Lindamer LA, et al: Medical comorbidity in schizophrenia. Schizophr Bull 22:413–430, 1996 Joukamaa M, Heliövaara M, Knekt P, et al: Schizophrenia, neuroleptic medication and mortality. Br J Psychiatry 188:122–127, 2006 Laursen TM, Munk-Olsen, T, Nordentoft M, et al: Increased mortality among patients admitted with major psychiatric disorders: a register-based study comparing mortality in unipolar depressive disorder, bipolar affective disorder, schizoaffective disorder, and schizophrenia. J Clin Psychiatry 68:899–907, 2007 Lichtermann D, Ekelund J, Pukkala E, et al: Incidence of cancer among persons with schizophrenia and their relatives. Arch Gen Psychiatry 58:573–578, 2001 Limosin F, Loze J-Y, Philippe A: Ten-year prospective follow-up study of the mortality by suicide in schizophrenic patients. Schizophr Res 94:23–28, 2007 Masterson E, O’Shea B: Smoking and malignancy in schizophrenia. Br J Psychiatry 145:429–432, 1984 Mortensen PB, Juel K: Mortality and causes of death in schizophrenic patients in Denmark. Acta Psychiatr Scand 81:372–377, 1990 Newman SC, Bland RC: Mortality in a cohort of patients with schizophrenia: a record linkage study. Can J Psychiatry 36:239–245, 1991 Nordentoft M, Laursen TM, Agerbo E, et al: Change in suicide rates for patients with schizophrenia in Denmark, 1981–97: nested case-control study. BMJ 329:261, 2004 Palmer BA, Pankratz VS, Bostwick JM: The lifetime risk of suicide in schizophrenia: a reexamination. Arch Gen Psychiatry 62:247–253, 2005 Ran MS, Chen E, Conwell Y, et al: Mortality in people with schizophrenia in rural China: 10-year cohort study. Br J Psychiatry 190:237–242, 2007 Saha S, Chant D, McGrath J: A systematic review of mortality in schizophrenia: is the differential mortality gap worsening over time? Arch Gen Psychiatry 64:1123–1131, 2007 Waddington JL, Youssef HA, Kinsella A: Mortality in schizophrenia: antipsychotic polypharmacy and absence of adjunctive anticholinergics over the course of a 10-year prospective study. Br J Psychiatry 173:325–329, 1998

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CHAPTER 3 Medical Outcomes From the CATIE Schizophrenia Study Henry A. Nasrallah, M.D.

When the Clinical Antipsychotic Trials for Intervention Effectiveness (CATIE) schizophrenia study was designed and submitted to the National Institute of Mental Health (NIMH) for funding in 1999, the main purpose of the study was to establish whether second-generation antipsychotics (SGAs) were more effective than first-generation antipsychotics (FGAs). Specifically, effectiveness was defined as discontinuation due to any of four reasons: lack of efficacy, lack of tolerability, emergence of safety problems (i.e., potential medical health threat), and patient decision (i.e., nonadherence and dropping out of the study). Measures related to physical health were considered a secondary outcome of this large study. By the time the initial findings of the CATIE trial were published in 2005 (Lieberman et al. 2005), the predominant focus in the field of schizophrenia pharmacotherapy had shifted from claims over relative efficacy of various SGAs to the medical complications of the SGA class, specifically metabolic disorders such as obesity, diabetes, hyperlipidemia, and hypertension (Nasrallah et al. 2006; Newcomer 2005). Fortunately, the CATIE study included several laboratory measures of metabolic function, including all five metabolic syndrome criteria: 37

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waist circumference, fasting triglycerides, fasting high-density lipoprotein, blood pressure, and fasting serum glucose (Grundy et al. 2004). A total of 1,460 persons with schizophrenia consented to participate in the CATIE study, and several analyses of metabolic parameters at CATIE baseline and again after administration of the SGA and FGA medications used in phases 1 and 2 have been published and are discussed in this review. Interestingly, although the effectiveness results of CATIE (i.e., the differential discontinuation of the four SGA agents and one FGA agent during phase 1) were subjected to intense critiques due to methodological issues, the metabolic data were widely accepted and were regarded as objectively valid and uninfluenced by design stipulations (Kasper and Winkler 2006; Meyer 2007). In addition to analyzing the CATIE metabolic data (with pre hoc hypotheses based on the totality of the literature and evidence that emerged while CATIE was being conducted 1999–2004), the researchers involved in the CATIE study also accumulated data on other healthrelated issues such as substance abuse and neurological movement disorders, both of which are discussed in this overview of the medical findings of the CATIE study.

The Buildup to the CATIE Awareness of the adverse metabolic effects from certain SGAs accelerated during the 5 years that it took to conduct the CATIE study (Nasrallah 2003; Newcomer et al. 2004). A key review by Allison et al. (1999) raised awareness of the seriousness of weight gain secondary to antipsychotic treatment, whether from FGAs or SGAs. Allison et al.’s literature review of comparative weight gain across old and new antipsychotics was a turning point in that it reframed the discussion about weight gain and its serious metabolic consequences as an important threat to the health of patients receiving antipsychotics. Awareness of the serious (and occasionally fatal) metabolic effects posed by some SGAs essentially replaced concerns over tardive dyskinesia, which had reigned supreme as the greatest health issue related to FGA exposure. Interestingly, Allison et al.’s review also implied that weight gain was a major problem with certain low-potency FGA agents (thioridazine and chlorpromazine), a fact that was often overlooked due to the preoccupation with tardive dyskinesia and the increasing use of highpotency FGAs in the years prior to widespread SGA use. Allison et al.’s analysis influenced the CATIE study design to the extent that on the basis of Allison et al.’s data, a weight-neutral SGA, ziprasidone, was planned as a treatment arm more than 2 years before final U.S. Food

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39

and Drug Administration (FDA) approval in 2001. Because of its benign metabolic profile, ziprasidone was included not only as one of the SGA options in phase 1 but also as a key element of the tolerability pathway in phase 2 of the CATIE study (Stroup et al. 2006). Aripiprazole, another metabolically benign SGA, came too late to be included in phase 1 or 2 but was included in phase 3, the open-label phase of CATIE in which investigators could choose any approved antipsychotic for subjects who had dropped out of phase 2 (Stroup et al., in press). Although weight gain secondary to clozapine was widely recognized in the 1990s, prior to the CATIE study (Umbricht et al. 1994), it was regarded as the unavoidable cost for treating refractory schizophrenia patients for whom there were no options; however, after several first-line SGA drugs were introduced (risperidone in 1993, olanzapine in 1996, quetiapine in 1997), the incidence of weight gain and diabetes increased markedly due to the drugs’ widespread use. By the turn of the millennium, while patients were being actively recruited for the CATIE study, metabolic disorders related to SGA use moved into the spotlight for both clinicians and researchers. From 2002 through 2004, the FDA MedWatch data from cases of diabetes and diabetic ketoacidosis (including deaths) were published in a series of papers (Koller and Doraiswamy 2002; Koller et al. 2003, 2004). The European Union and Japan subsequently added a diabetes warning to olanzapine’s product label in 2002, and in August 2003, the FDA imposed a class warning for diabetes on all SGA drugs, despite the absence of data implicating ziprasidone and aripiprazole. Three months after the FDA class warning, the American Diabetes Association, along with the American Psychiatric Association, American Association of Clinical Endocrinologists, and North American Association for the Study of Obesity, held a meeting in Philadelphia on November 19, 2003. The purpose of this joint conference was to generate a consensus statement (American Diabetes Association et al. 2004) on the association between SGA exposure and weight gain, lipid changes, and diabetes (predominantly level 2, 3, and 4 evidence) after reviewing the pre-CATIE world literature. The consensus statement, which was published jointly in the February 2004 issues of Diabetes Care and the Journal of Clinical Psychiatry, concluded that the members of the SGA class were associated with differential risks of weight gain, diabetes, and hyperlipidemia. Clozapine and olanzapine were found to have the highest risk, risperidone and quetiapine to have intermediate risk, and aripiprazole and ziprasidone to have the lowest risk. As will be discussed in the next section, the prospective, randomized, double-blind CATIE trial generated level 1 evidence about metabolic complications

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Medical Illness and Schizophrenia

of SGAs that professionals were waiting for, and confirmed the conclusions of the consensus statement regarding obesity and diabetes. Moreover, the CATIE data refined the knowledge of the relative metabolic effects of quetiapine and indicated that risperidone might be somewhat less of a metabolic offender than quetiapine, particularly with regard to effects on serum triglyceride levels (Meyer et al. 2008a, 2008b).

CATIE Baseline Data on Medical Illness in Schizophrenia Demographics Several health-related findings were reported in the CATIE schizophrenia sample, which comprised 1,460 outpatients from 57 public, academic, and private settings around the United States. The sample was 75% male, with a mean age of 41 years and a mean duration of illness of over 14 years. About 60% of the sample was white, 35% black, and 5% other races. Twelve percent of the sample was of Hispanic or Latino ethnicity. The mean educational level was 12.2 years, about 60% had never married, and 85% were unemployed. CATIE employed a broad enrollment strategy in an attempt to replicate the patient population seen in real-world clinical settings, as opposed to the type of patient often recruited for pharmaceutical trials, which excluded patients with medical comorbidities or substance use. As a result, the data provide a representative, cross-sectional view of the health of chronic schizophrenia patients in the United States.

Diabetes and Metabolic Syndrome At CATIE study baseline, 11% of enrolled subjects had diabetes type 1 or 2, 14% had hyperlipidemia, and 20% had hypertension. Table 3–1 shows the mean number of metabolic syndrome criteria met at CATIE study baseline in subjects with fasting blood samples available, along with overall metabolic syndrome prevalence (McEvoy et al. 2005). Metabolic syndrome prevalence in the CATIE sample, in both males and females, was twice the rate seen in a sample from the general population that was matched for age, gender, race, and ethnicity (using the National Health and Nutrition Examination Survey [NHANES] III study population as the source for comparator matching) (Figure 3–1). These were the first detailed data documenting an unusually high prevalence of metabolic syndrome in the schizophrenia outpatient population in the United States during the period when subjects were being recruited into the CATIE study.

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41

Cardiovascular Risk A comparison of 10-year cardiac risk estimates in the CATIE schizophrenia sample compared to matched controls from the NHANES III was also conducted using the baseline CATIE data (Goff et al. 2005). This analysis showed that the 10-year coronary heart disease (CHD) risk (using the Framingham CHD risk algorithm) was significantly elevated in the CATIE sample versus the matched general population (P= 0.0001) in males (9.4% vs. 7.0%) and females (6.3% vs. 4.2%). The patients with schizophrenia also had significantly higher rates of smoking (68% vs. 35%), diabetes (13% vs. 3%), and hypertension (27% vs. 17%), and lower HDL cholesterol (43.7 vs. 49.3 mg/dL) compared to the NHANES III control group. Goff et al. concluded that the CATIE data showing greater 10-year CHD risk are consistent with the published studies of increased cardiac mortality in schizophrenia.

Lack of Medical Treatment

Percentage of patients with metabolic syndrome

In light of the high prevalence of metabolic syndrome in the CATIE schizophrenia sample, one would expect that the subjects with metabolic disorders such as diabetes, hyperlipidemia, and hypertension would be receiving the appropriate standard medical treatments for

60

CATIE (N = 689) 50 40

*

NHANES (N = 689)

*

30 20 10 0

Males

Females

FIGURE 3–1. Prevalence of metabolic syndrome in CATIE schizophrenia study participants at baseline versus the general adult population (National Health and Nutrition Examination Survey [NHANES] III data). *P= 0.0001 CATIE versus NHANES.

42

TABLE 3–1.

Metabolic syndrome and criteria prevalences among CATIE fasting subjects Subject cohort

Syndrome/criteria Mean age (years) 2

Criteria met

0 1 2 3 4 5 Mean number of criteria met

MS prevalence, AHA criteria Criteria met

0 1 2

Black male

Hispanic male

White female

Black female

Hispanic female

39.8±11.2

38.5±11.6

38.0 ±12.3

44.2 ±10.7

44.0± 9.8

44.5±10.2

28.9±6.3

27.7±5.8

29.0 ±6.6

32.5 ±8.2

33.8± 8.1

31.7±6.5

40.9% (n=342)

22.7% (n=141)

31.8% (n=66)

56.5% (n=92)

43.1% (n=72)

73.3% (n=15)

(n =343) 12.2% 23.9% 23.0% 24.2% 14.3% 2.3% 2.11± 1.32

(n =141) 23.4% 31.9% 22.0% 10.6% 9.2% 2.8% 1.59± 1.35

(n =67) 13.4% 19.4% 35.8% 14.9% 13.4% 3.0% 2.05± 1.31

(n =93) 8.6% 12.6% 22.6% 26.9% 24.7% 4.3% 2.59±1.34

(n= 73) 5.5% 23.3% 28.8% 27.4% 12.3% 2.7% 2.26 ±1.19

(n= 15) 6.7% 6.7% 13.3% 46.7% 20.0% 6.7% 2.87 ±1.25

44.4% (n=342)

23.4% (n=141)

40.9% (n=66)

58.1% (n=93)

47.2% (n=72)

73.3% (n=15)

(n =343) 12.0% 21.0% 22.7%

(n =141) 22.7% 31.2% 22.7%

(n =67) 13.4% 16.4% 29.9%

(n =93) 8.6% 11.8% 21.5%

(n= 73) 5.5% 20.6% 27.4%

(n= 15) 6.7% 6.7% 13.3%

Medical Illness and Schizophrenia

Mean BMI (kg/m ) MS prevalence, ATPIII criteria

White male

TABLE 3–1.

Metabolic syndrome and criteria prevalences among CATIE fasting subjects (continued) Subject cohort

Syndrome/criteria

Mean number of criteria met

Black male

Hispanic male

White female

Black female

Hispanic female

22.3% 16.9% 4.1% 2.25± 1.38

11.4% 9.2% 2.8% 1.62± 1.35

20.9% 14.9% 4.5% 2.21± 1.38

26.9% 25.8% 5.4% 2.66±1.36

28.8% 13.7% 4.1% 2.37 ±1.23

40.0% 26.7% 6.7% 2.93 ±1.28

Criteria prevalence: all subjects Waist circumference 41.2% (n= 663) Blood pressure 46.9% (n= 674) HDL 54.3% (n= 671)

28.5% (n= 351) 55.3% (n= 358) 35.6% (n= 357)

37.8% (n =127) 38.8% (n =129) 55.0% (n =129)

70.8% (n =195) 38.4% (n =198) 69.1% (n =194)

76.5% (n =153) 48.1% (n =154) 52.6% (n =154)

77.0% (n= 40) 47.5% (n= 40) 64.1% (n= 39)

Criteria prevalence: fasting subjects Waist circumference 39.0% (n= 341) Blood pressure 45.9% (n= 342) Triglycerides 58.3% (n= 343) HDL 55.1% (n= 343) Glucose≥ 100 26.5% (n= 343) Glucose≥ 110 13.4% (n =343)

26.2% (n= 141) 57.1% (n= 141) 31.9% (n= 141) 34.8% (n= 141) 17.7% (n= 141) 14.9% (n= 141)

38.5% (n =65) 40.9% (n =66) 61.2% (n =67) 53.7% (n =66) 28.4% (n =67) 11.9% (n =67)

76.1% (n =92) 41.9% (n =93) 53.8% (n =93) 72.0% (n =93) 22.6% (n =93) 16.1% (n =93)

74.7% (n= 71) 50.0% (n= 72) 28.8% (n= 73) 52.1% (n= 73) 34.3% (n= 73) 23.3% (n= 73)

86.7% (n= 15) 60.0% (n= 15) 46.7% (n= 15) 66.7% (n= 15) 33.3% (n= 15) 26.7% (n= 15)

43

Note. AHA=American Heart Association; ATPIII= National Cholesterol Education Program Adult Treatment Panel III; BMI= body mass index; HDL=high-density lipoprotein; MS =metabolic syndrome.

Medical Outcomes From the CATIE Study

3 4 5

White male

44

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these serious medical disorders. However, Nasrallah et al. (2006) found that a high proportion of subjects were not receiving treatment for their serious medical diseases at the time of their enrollment into the CATIE trial. This serious lack of care means that persons with schizophrenia face a double jeopardy for early cardiovascular mortality: high rate of metabolic disorders and diminished quality of medical treatment. This combination of high medical risk and poor medical care may be one of the reasons that persons with schizophrenia lose an average of more than 25 potential years of life, according to research from several U.S. states (Colton and Manderscheid 2006; B.J. Miller et al. 2006). Metabolic disorders are also highly associated with depression; when CATIE subjects with metabolic syndrome were compared to CATIE subjects without metabolic syndrome, the only significant difference found was a higher rate of depression and somatic concern among the group with metabolic syndrome (Meyer et al. 2005).

Other Medical Risk Factors Of the CATIE subjects, 37% met criteria for substance abuse or dependence, 23% met criteria specifically for substance use, and 40% were abstinent (Swartz et al. 2008). Given the health risks of oral and intravenous substance use, abuse, and dependence, this is an additional medical risk factor for individuals with schizophrenia, a fact discussed at length in Chapter 11, “Substance Abuse and Schizophrenia.” Another medical risk factor in the CATIE sample was tardive dyskinesia, a serious form of neurotoxicity. Of the 1,460 subjects, 231 (15.8%) had tardive dyskinesia at the time of enrollment in CATIE (D.D. Miller et al. 2005). Of interest are the findings that the tardive dyskinesia subgroup had 1.5 times higher prevalence of substance abuse and 4.5 times higher odds of more severe psychopathology compared to those without tardive dyskinesia.

CATIE Phase 1 Medical Findings Several metabolic parameters were differentially influenced by the five antipsychotic agents—perphenazine (an FGA), risperidone, quetiapine, olanzapine, and ziprasidone (added after 40% of the sample had been recruited)—selected for phase 1 of the CATIE trial (Lieberman et al. 2005). Figure 3–2 shows the mean monthly weight change, with the olanzapine group showing over fourfold greater weight gain compared with the other antipsychotics during phase 1, and subjects randomized

Medical Outcomes From the CATIE Study

45

to ziprasidone showing a mean decrease in weight. Figure 3–3 shows the percentage of subjects who gained a significant amount of weight (> 7%) with each of the five antipsychotics. Again, the olanzapine cohort had the greatest problems with weight gain, with 30% gaining more than 7% of their baseline weight, and ziprasidone was the least offending medication, causing weight gain in only 6% of subjects. No statistically significant between-group changes in mean fasting glucose levels occurred across the various antipsychotics, although olanzapine had the highest numeric increase and ziprasidone the lowest. However, results indicated significant between-drug differences for change in glycosylated hemoglobin, a long-term measure of glycemic control that reflects values over the prior 2 months. As seen in Figure 3–4, the greatest increase in glycosylated hemoglobin was in the olanzapine group, and the ziprasidone group had an overall decrease. Similar divergences were seen with cholesterol and triglycerides (Figures 3–5 and 3–6) and are discussed in detail in Chapter 6, “Effects of Antipsychotics on Serum Lipids” (see Tables 6–2 and 6–3). Each patient’s corrected QT interval on the electrocardiogram (QTc) was measured every 3 months while participating in the CATIE study. Figure 3–7 shows that the QTc was minimally increased in all antipsychotic groups during CATIE phase 1. These negligible increases suggest that, contrary to the perception at the launch of the CATIE study, antipsychotic-related QTc changes are not a major medical threat to persons receiving atypical antipsychotics. The effects of antipsychotics on QTc are discussed at length in Chapter 7, “The Spectrum of Cardiovascular Disease in Patients With Schizophrenia,” but data from CATIE phase 1 revealed that in routine clinical practice, there are not worrisome QT changes with any SGA, including ziprasidone, which had been a source of concern. The past several years of clinical experience with millions of patients confirms the CATIE data in that unlike metabolic complications (e.g., metabolic syndrome and diabetes), which have increased markedly in populations receiving SGAs, morbidity or mortality from QTc changes is relatively minuscule. The development of cataracts was a concern only for patients taking quetiapine, based on preclinical findings from animal models. In phase 1, no difference was found among the antipsychotics, with quetiapine in particular showing minimal risk for cataracts, confirming that cataract development is a phenomenon encountered for the preclinical species studied (beagle dogs) but not humans.

46

2.5

2.0

Ziprasidone

Risperidone

Quetiapine

Olanzapine

Perphenazine

Clozapine

Medical Illness and Schizophrenia

Mean change from baseline (lbs)

1.5

1.0 0.5

0 –0.5

–1.0 –1.5

–2.0

Phase 1

Phase 2T

Phase 2E

FIGURE 3–2. Monthly weight gain (pounds/month) by subjects during CATIE phase 1, phase 2 tolerability arm (2T), and phase 2 efficacy arm (2E).

35

Ziprasidone

Risperidone

Quetiapine

Olanzapine

Perphenazine

Clozapine

30

Medical Outcomes From the CATIE Study

Percentage

25

20

15

10

5

0 Phase 1

Phase 2 E

Percentage of subjects with weight gain >7% in CATIE phase 1, phase 2 tolerability arm (2T), and phase 2 efficacy 47

FIGURE 3–3. arm (2E).

Phase 2 T

Medical Illness and Schizophrenia

48

50

Ziprasidone

Risperidone

Olanzapine

Perphenazine

Quetiapine

Mean change from baseline (%)

40

30

20

10

0

–10

–20

FIGURE 3–4.

Phase 1 changes in glycosylated hemoglobin.

Change in Metabolic Syndrome Status With Treatment Detailed analysis of changes in metabolic syndrome criteria in CATIE phase 1 were published in 2008 (Meyer et al. 2008a) and showed that after 3 months of exposure, the prevalence of metabolic syndrome increased in the olanzapine group from 34.8% to 43.9%, but decreased in the ziprasidone group from 37.7% to 29.9% (olanzapine vs. ziprasidone P=0.001) (Table 3–2). Subjects in the olanzapine and quetiapine groups also had an average waist circumference increase of 1.8 cm, compared with a 1-cm increase in the risperidone group and no change in the ziprasidone group, whereas subjects in the perphenazine group experienced a loss of 1 cm. The greatest increase in triglycerides occurred with olanzapine (+21.5 mg/dL). Although these findings are consistent with metabolic studies published before release of the CATIE results, they indicated greater effects of quetiapine on adiposity than previously indicated by the American Diabetes Association et al. (2004) consensus paper.

Nonfasting Triglyceride Levels Although the metabolic syndrome criterion for triglycerides is a fasting level of 150 mg/dL or greater, recent studies indicate that nonfasting

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49

TABLE 3–2. Proportion of subjects at baseline and 3 months meeting the criteria for metabolic syndrome in phase 1 of the CATIE schizophrenia trial—all classifiable subjects Metabolic syndrome Agent

n

Olanzapine 164 Perphenazine 129 Quetiapine 143 Risperidone 147 Ziprasidone 77 Overall treatment difference

Baseline

3 months

34.8% 37.2% 37.8% 30.6% 37.7%

43.9%a 38.0% 37.1% 30.6% 29.9%a 0.015

a

Change from baseline to 3 months in proportion of subjects meeting criteria for metabolic syndrome is greater for olanzapine than for ziprasidone (P=0.001) among all classifiable subjects. triglyceride levels may have a stronger association with cardiovascular risk than do fasting triglycerides. An analysis of the phase 1 CATIE data after 3 months of exposure (Meyer et al. 2008b) showed that the highest mean and median increases were in subjects randomly assigned to quetiapine (mean +54.7 mg/dL, median +26 mg/dL) and olanzapine (mean +54.7 mg/dL, median +26.5 mg/dL), whereas ziprasidone was neutral (mean +0.0 mg/dL, median +8 mg/dL) and decreases were seen in both risperidone (mean −18.4 mg/dL, median −6.5 mg/dL) and perphenazine (mean −1.3 mg/dL, median −22 mg/dL). Pairwise comparison indicated a significant between-group difference for perphenazine versus olanzapine and a trend for perphenazine versus quetiapine.

Inflammatory Markers Several biomarkers of cardiometabolic risk were collected in phase 1 of the CATIE trial and are still being analyzed at the time of writing of this chapter. However, data for one important inflammatory marker, C-reactive protein (CRP) have been analyzed (J.M. Meyer et al., in preparation) to examine the comparative effects of various antipsychotics after 3 months of exposure. Olanzapine and quetiapine had the greatest numerical increases, and significant treatment differences were observed between olanzapine versus perphenazine (P< 0.001) and risperidone (P = 0.001) in subjects with lower baseline cardiovascular risk (defined as CRP <1 mg/L). After 12 months of exposure, the difference

50

80

Ziprasidone

Risperidone

Quetiapine

Olanzapine

Perphenazine

Clozapine

Medical Illness and Schizophrenia

Change from baseline (mg/dL)

60

40

20

0

–20

–40 Ph ase 1

FIGURE 3–5.

Ph ase 2 T

Ph ase 2 E

Changes in serum triglycerides across CATIE phase 1, phase 2 tolerability arm (2T), and phase 2 efficacy arm (2E).

20

Ziprasidone

Risperidone

Quetiapine

Olanzapine

Perphenazine

Clozapine

Medical Outcomes From the CATIE Study

Change from baseline (mg/dL)

15

10

5

0

–5

–10

–15 Ph ase 1

FIGURE 3–6.

Ph ase 2T

Ph ase 2E

Changes in total cholesterol across CATIE phase 1, phase 2 tolerability arm (2T), and phase 2 efficacy arm (2E). 51

52

8

Ziprasidone

Risperidone

Olanzapine

Perphenazine

Quetiapine

4

Medical Illness and Schizophrenia

Mean change from baseline (msec)

6

2

0

–2

–4

–6 Phase 1

FIGURE 3–7.

Phase 2T

Mean changes in QT interval in CATIE phase 1 and phase 2 tolerability arm (2T).

Medical Outcomes From the CATIE Study

53

between olanzapine and perphenazine groups remained significant, and a significant difference (P= 0.003) was observed between olanzapine and ziprasidone. These data confirm that agents associated with greater cardiometabolic risk are associated with adverse changes in other measures that correlate with deleterious cardiovascular outcomes.

Phase 2 Findings Subjects who discontinued their antipsychotics in phase 1 of the CATIE study due to lack of efficacy were randomized either to clozapine or to one of three atypical antipsychotics: olanzapine, quetiapine, or risperidone. Those who discontinued due to tolerability or safety reasons (or who refused participation in the efficacy arm) were randomized to either ziprasidone or to one of the three atypical antipsychotics. In both arms of phase 2, the tolerability arm and the efficacy arm, all subjects were randomly assigned to receive agents that they did not take in phase 1. Metabolic parameters (weight, waist circumference, glucose, triglycerides, and cholesterol) were measured as in phase 1. (See Figures 3–5 and 3–6.) Figure 3–2 shows the mean weight gain per month in both pathways of phase 2 compared to phase 1, and Figure 3–3 shows the percentage of subjects with weight gain >7% for both phase 2 pathways. Figure 3–8 also shows the weight changes in phase 2 in subjects who had a significant amount of weight gain (> 7%) in phase 1. Only those randomized to ziprasidone lost much of the weight they had gained from the phase 1 antipsychotic. Differences did emerge between the phase 1 results and those seen in the phase 2 efficacy and tolerability pathways, but a consistent pattern remains: olanzapine is associated with the greatest deleterious changes in metabolic parameters, whereas ziprasidone is associated with the most benign changes.

Phase 3 Findings The open-label phase 3 included subjects who had discontinued phases 1 and 2. They were given a wide range of FGAs and/or SGAs. Aripiprazole, the only atypical antipsychotic that was not included in the first two phases of the CATIE because the drug was launched too late, was used in some patients in phase 3. The only surprising data regarding the metabolic changes in phase 3 were that glucose levels increased by 13 mg/dL in patients taking aripiprazole, which was a larger increase than with any other antipsychotic in this phase (Stroup et al., in press). This finding was unexpected, because aripiprazole has demonstrated a benign metabolic profile in FDA trials and in previous published studies. All other metabolic findings were consistent with phase 1 and phase 2 profiles.

54

4

Ziprasidone

Risperidone

Quetiapine

Olanzapine

0 –2 –4 –6 –8 –10 –12

FIGURE 3–8.

Phase 2 tolerability arm weight change in CATIE subjects with weight gain >7% in phase 1.

Medical Illness and Schizophrenia

Mean change from baseline (lbs)

2

Medical Outcomes From the CATIE Study

55

Conclusion The 5-year, double-blind, NIMH-sponsored effectiveness study known as the CATIE schizophrenia trial provided highly informative data about the comparative metabolic profiles of various antipsychotics and revealed the high risk for metabolic syndrome and CHD in a large sample (N= 1,460) of patients with chronic schizophrenia in the United States. These metabolic findings are likely to influence clinical practice research studies, prevention initiatives, and public policy in the foreseeable future. Although the primary measure outcome of the CATIE schizophrenia trial was effectiveness (i.e., all-cause discontinuation), a valuable body of metabolic data was obtained from the study sample, one that points to significant health problems seen in patients with schizophrenia.

Key Clinical Points ◗

The prevalence of metabolic syndrome in the CATIE schizophrenia subjects at the time of enrollment was 43%, about twice the prevalence in the general population.

◗

Olanzapine was associated with a fourfold higher monthly weight gain in phase 1 compared to the other antipsychotics.

◗

Fasting blood glucose, cholesterol, and triglyceride levels were most elevated with olanzapine and were not changed or declined with ziprasidone.

◗

Quetiapine resulted in higher lipid increases than risperidone, which had no deleterious effect on lipids.

◗

The overall metabolic profile of second-generation antipsychotics in phase 2 (both the efficacy and tolerability pathways) were the same as seen in phase 1 for olanzapine (highest increases) and ziprasidone (lowest increases or actual decreases), but were somewhat variable for quetiapine and risperidone.

◗

Subjects with >7% body weight increase in phase 1 lost weight only if they were assigned to ziprasidone in phase 2.

◗

QTc was minimally affected by all second-generation antipsychotics used in the CATIE study.

◗

Levels of the inflammatory marker C-reactive protein were increased with olanzapine or quetiapine but not with other antipsychotics.

Medical Illness and Schizophrenia

56 ◗

Aripiprazole was associated with the highest mean increase in fasting glucose among first-generation or second-generation antipsychotics in phase 3, the opposite of what was expected.

References Allison DB, Mentore JL, Heo M, et al: Antipsychotic-induced weight gain: a comprehensive research synthesis. Am J Psychiatry 156:1686–1696, 1999 American Diabetes Association, American Psychiatric Association, American Association of Clinical Endocrinologists, et al: Consensus Development Conference on Antipsychotic Drugs and Obesity and Diabetes. Diabetes Care 27:596–601, 2004 Colton CW, Manderscheid RW: Congruencies in increased mortality rates, years of potential life lost, and causes of death among public mental health clients in eight states. Prev Chronic Dis 3:1–14, 2006 Goff DC, Sullivan L, McEvoy JP, et al: A comparison of ten-year cardiac risk estimates in schizophrenia patients from the CATIE study and matched controls. Schizophr Res 80:45–53, 2005 Grundy SM, Brewer B, Cleeman JI, et al: Definition of metabolic syndrome: report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation 109:433–438, 2004 Kasper S, Winkler D: Addressing the limitations of the CATIE study. World J Biol Psychiatry 7:126–127, 2006 Koller EA, Doraiswamy PM: Olanzapine-associated diabetes mellitus. Pharmacotherapy 22:841–852, 2002 Koller EA, Cross JT, Doraiswamy PM, et al: Risperidone-associated diabetes mellitus: a pharmacovigilance study. Pharmacotherapy 23:735–744, 2003 Koller EA, Weber J, Doraiswamy PM, et al: A survey of reports of quetiapineassociated hyperglycemia and diabetes mellitus. J Clin Psychiatry 65:857– 863, 2004 Lieberman JA, Stroup TS, McEvoy JP, et al: Effectiveness of antipsychotic drugs in patients with chronic schizophrenia. N Engl J Med 353:1209–1223, 2005 McEvoy JP, Meyer JM, Goff DC, et al: Prevalence of the metabolic syndrome in patients with schizophrenia: baseline results from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial and comparison with national estimates from NHANES III. Schizophr Res 80:19–32, 2005 Meyer JM: Strategies for the long-term treatment of schizophrenia: real-world lessons from the CATIE trial. J Clin Psychiatry 68 (suppl 1):28–33, 2007

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Meyer JM, Nasrallah HA, McEvoy JP, et al: The Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial: clinical comparison of subgroups with and without the metabolic syndrome. Schizophr Res 80:9–18, 2005 Meyer JM, Davis VG, Goff DC, et al: Change in metabolic syndrome parameters with antipsychotic treatment in the CATIE schizophrenia trial: prospective data from phase 1. Schizophr Res 101:273–286, 2008a Meyer JM, Davis VG, McEvoy JP, et al: Impact of antipsychotic treatment on nonfasting triglycerides in the CATIE schizophrenia trial. Schizophr Res 103:104–109, 2008b Miller BJ, Paschall CB, Svendsen DP: Mortality and medical comorbidity among patients with serious mental illness. Psychiatr Serv 57:1482–1487, 2006 Miller DD, McEvoy JP, Davis SM, et al: Clinical correlates of tardive dyskinesia in schizophrenia: baseline data from the CATIE schizophrenia trial. Schizophr Res 80:33–43, 2005 Nasrallah H: A review of the effect of atypical antipsychotics on weight. Psychopharmacology 28:83–96, 2003 Nasrallah HA, Meyer JM, Goff DC, et al: Low rates of treatment for hypertension, dyslipidemia, and diabetes in schizophrenia: data from the CATIE schizophrenia trial sample at baseline. Schizophr Res 86:15–22, 2006 Newcomer JW: Second-generation (atypical) antipsychotics and metabolic effects: a comprehensive literature review. CNS Drugs 19 (suppl 1):1–93, 2005 Newcomer JW, Nasrallah HA, Loebel AD: The Atypical Antipsychotic Therapy and Metabolic Issues National Survey: practice patterns and knowledge of psychiatrists. J Clin Psychopharmacol 5 (suppl 1):S1–S6, 2004 Stroup TS, Lieberman JA, McEvoy JP, et al: Effectiveness of olanzapine, quetiapine, risperidone, and ziprasidone in patients with chronic schizophrenia following discontinuation of a previous atypical antipsychotic. Am J Psychiatry 163:611–622, 2006 Stroup TS, Lieberman JA, McEvoy JP, et al: Results of phase 3 of the CATIE schizophrenia trial. Schizophr Res (in press) Swartz MS, Wagner HR, Swanson JW, et al: The effectiveness of antipsychotic medications in patients who use or avoid illicit substances: results from the CATIE study. Schizophr Res 100:39–52, 2008 Umbricht DS, Pollack S, Kane JM: Clozapine and weight gain. J Clin Psychiatry 55 (suppl B):157–160, 1994

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PART II Metabolic Disease, Heart Disease, and Related Conditions

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CHAPTER 4 Obesity and Schizophrenia Tony Cohn, M.B.Ch.B., M.Sc., F.R.C.P.C.

Obesity is a common and burgeoning health problem that has an impact on both life expectancy and quality of life. Epidemic proportions of individuals are overweight and obese worldwide (James et al. 2001; Ogden et al. 2007). The prevalence of obesity is even greater among individuals with schizophrenia, who are known to have increased morbidity and mortality from obesity-related diseases (McEvoy et al. 2005; Osby et al. 2000), as well as poor access to primary and preventive health care (Druss et al. 2001; Meyer 2007). Individuals with schizophrenia may be predisposed to obesity because of biological and lifestyle factors but also require long-term treatment with antipsychotic medications that can promote weight gain (Green et al. 2000; Newcomer 2005). With the growth in prescription of second-generation antipsychotic (SGA) medications over the past 10 years, antipsychoticassociated weight gain has emerged as an iatrogenic issue of major public health concern. The problem is compounded further by the fact that commonly coprescribed psychiatric medications, antidepressants, and mood stabilizers also contribute to weight gain (Aronne and Segal 2003; Fava 2000). In addition, patients with schizophrenia are challenged by cognitive and functional deficits that need to be considered in clinical evaluation and in the delivery of obesity interventions. Although obesity medicine is now being recognized as a subspecialty in its own right, 61

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its application for individuals with serious mental illness, such as schizophrenia, is in its infancy. The onus for management is falling to mental health professionals. Clinicians of today who treat patients with schizophrenia are challenged to become knowledgeable in the assessment, prevention, and treatment of obesity and its complications. In this chapter, I review the clinical definition of obesity and its medical consequences; the epidemiology and determinants of obesity in the general population and in individuals with schizophrenia; and the assessment, monitoring, and management of obesity for patients with schizophrenia within a mental health context.

Definition and Measurement Obesity is considered a disease by the World Health Organization (2004), which defines obesity as a condition of excess body fat to the extent that health is impaired. However, measuring body fat accurately is difficult and requires highly specialized procedures (Pi-Sunyer 2000). For clinical purposes, obesity is usually defined by the body mass index (BMI), a measure of weight that takes height into account. In addition to BMI, a measure of the distribution of body fat is important, because the central accumulation of fat within the abdominal region (central, visceral, or abdominal adiposity) is a major factor that influences the effect of increasing weight on health. Central adipose tissue is now seen as an endocrine organ that releases substances (adipokines) that have systemic effects. Adipokines include leptin, tumor necrosis factor-alpha, adiponectin, C-reactive protein, interleukin-6, and plasminogen activator inhibitor type 1. Central adiposity is most accurately measured by computer-assisted tomography or magnetic resonance imaging, which enable a distinction to be made between subcutaneous and intra-abdominal fat. However, for practical purposes, the simple waist circumference is the common clinical proxy for central adiposity (Lemieux et al. 1996). Waist-to-hip ratio has also been used for this purpose, but this measure is less favored because racial and ethnic differences in hip size complicate interpretation (Ogden et al. 2007). Both BMI and waist circumference are independently correlated with health outcomes, but waist circumference has been shown to be an even better predictor of obesity-related disease. BMI and waist circumference measures have limitations. Although body fat is a continuous variable with an incremental health risk, BMI and waist circumference are often used as categorical variables with cutoff values that reflect risk. Also, these measures do not adequately take

Obesity

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into account individual, gender, and racial or ethnic differences in body type and body composition. BMI is calculated by dividing weight (measured in kilograms) by height (measured in meters) squared (i.e., BMI=kg/m2). Consensus exists among international health agencies, including the National Heart, Lung, and Blood Institute and the World Heath Organization, regarding BMI cutoffs. A BMI of 25–29.9 kg/m2 is considered overweight, and a BMI of ≥30 kg/m 2 is deemed obese. Obesity is further classified as class 1 (BMI 30–34.9 kg/m2), class 2 (BMI 35–39.9 kg/m2), and class 3 or severe obesity (BMI ≥40 kg/m2). BMI is a less accurate correlate for body fat when used for muscular individuals, who may have a high BMI and normal or low body fat, and for very short individuals (Pi-Sunyer 2000). In addition, because of differences in body composition, for a given BMI, women tend to have a higher percentage of body fat than men, and older individuals have a higher percentage of body fat than younger individuals (Ogden et al. 2007). Waist circumference is measured in the standing position with a simple tape measure placed around the waist. The waist is defined as midway between the top of the pelvis and the lowest rib. Measurement is taken after a modest expiration. For individuals with a pendulous abdomen, the waist circumference can be measured using the maximum girth, with the patient lying on his or her side on an examination table. Cutoff points are 88 cm for women and 102 cm for men. Racial or ethnic differences in body habitus can also influence the interpretation of waist circumference; therefore, the International Diabetes Federation has defined ethnic-specific cutoffs for waist circumference for the metabolic syndrome (Alberti et al. 2006). Metabolic syndrome, also known as syndrome X and insulin-resistance syndrome, is a clustering of risk markers reflecting a state of insulin resistance and compensatory hyperinsulinemia that has wide-ranging medical consequences. According to the revised Adult Treatment Panel III/American Heart Association definition, three out of the five following component criteria are required to diagnose metabolic syndrome (Grundy et al. 2005): 1. Abdominal obesity (waist circumference) ≥88 cm in women and ≥ 102 cm in men 2. Blood pressure ≥130/85 mmHg or antihypertensive treatment 3. Fasting glucose ≥5.6 mmol/L (100 mg/dL) or antidiabetic treatment 4. Fasting triglycerides ≥1.8 mmol/L (150 mg/dL) or treatment 5. Fasting high-density lipoprotein (HDL) <1.03 mmol/L (40 mg/dL) in men and <1.29 mmol/L (50 mg/dL) in women

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By the International Diabetes Federation definition of metabolic syndrome (Alberti et al. 2006), abdominal obesity is a necessary criterion, and two additional criteria (as listed above) are required for the diagnosis. Waist circumference cutoffs vary by racial or ethnic group as follows: • Europids or Middle Eastern: men >94 cm; women >80 cm • South Asian, Chinese: men > 90 cm; women >80 cm • Japanese: men >85 cm; women > 90 cm

Health Consequences of Obesity Central adiposity is specifically associated with the development of insulin resistance and, consequently, type 2 diabetes, hyperlipidemia (especially raised triglycerides and low HDL), coronary heart disease, hypertension, and polycystic ovarian disease. With obesity in general, rates of gallbladder disease; respiratory disease, including obstructive sleep apnea; certain cancers (colorectal, prostate, endometrial, gallbladder, cervical, ovarian, and breast); gout; and arthritis are also increased (Pi-Sunyer 1993). Obesity reduces life expectancy. In examining deaths attributable to being overweight and obese, investigators found that more than 80% of these deaths occurred in individuals with BMIs of at least 30 kg/m2 (Allison et al. 1999b). Years of life are lost primarily because of coronary heart disease (Dorn et al. 1997). Shortened life span has been specifically noted in patients with serious mental illness, such as schizophrenia (Osby et al. 2000), with a recent report indicating as much as 25–30 years of potential life lost (Colton and Manderscheid 2006). Obesity also has a negative impact on the quality of life, and this has also been explored in samples of schizophrenia patients. Based on results from the Psychological Well-Being Index, Allison et al. (2003) reported that weight gain with antipsychotic treatment was related to poorer quality of life as well as reduced well-being and vitality. Strassnig et al. (2003a) found that the physical component score of the Medical Outcomes Study 36-Item Short-Form Health Status Survey, a measure of quality of life that assesses both physical and mental health, was inversely correlated with the physical component score of patients with schizophrenia, suggesting that the burden from obesity is primarily experienced as a physical problem, a finding that was confirmed by Faulkner et al. (2007a) who found that, in addition, waist circumference was a better predictor of reduced quality of life than BMI. Those with

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obesity describe also being stigmatized. In the general population it has been demonstrated that this phenomenon also occurs with health services, causing obese individuals to avoid visiting health care providers (Drury and Louis 2002). Patients with schizophrenia face the additional stigma of having a mental illness. The economic burden of obesity is immense (Thompson and Wolf 2001). Direct health care costs are estimated to account for 5.5%–7.0% of national health expenditure in the United States and 2.0%–3.5% in other countries. When considering comorbidities, the three largest contributors to cost are hypertension, type 2 diabetes, and coronary artery disease. The cost of lost productivity due to obesity is almost as great as the direct medical costs. In the treatment of patients with schizophrenia, lipid lowering, antihypertensive, and antidiabetic medications are now commonly coprescribed with antipsychotic medications, adding considerable costs to health care budgets.

Epidemiology of Obesity In the general population, rates of overweight and obesity are rising at an alarming rate, with no plateau in sight. In the United States, almost two-thirds of adults (66%) were overweight or obese in 2004; 32% were obese and 5% had class 3 obesity (Wang and Beydoun 2007). The prevalence of obesity has more than doubled since 1980 (Ogden et al. 2007). In Canada in 2004, 65% of the adult population was overweight or obese, but the overall rate of obesity (23%) was lower than in the United States (Tjepkema 2006). Using linear regression, Wang and Beydoun (2007) predicted that 75% of the U.S. adult population will be overweight or obese and 41% will be obese by 2015. Studies have demonstrated that the distribution of obesity varies by gender, racial and ethnic group, and socioeconomic status, with minority and low-socioeconomic-status groups having higher prevalence. In 2004, more men than women were overweight and obese, but women had higher rates of obesity, especially in non-Hispanic black and Mexican American communities, where rates of obesity in women were as high as 49% and 38%, respectively (Wang and Beydoun 2007). Weight appears to vary more by socioeconomic status, race and ethnicity, and nationality for women than for men, and some authors have suggested that weight may be associated more closely with social and cultural roles for women than for men (Ogden et al. 2007). In patients with schizophrenia, rates of obesity are even higher than in the general population and are estimated to fall between 40% and

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60% (Catapano and Castle 2004). The average BMI in recent schizophrenia trials has often approximated or been in the obese range, as illustrated in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study, where the recruitment strategy was designed to be broadly representative of patients with schizophrenia. In the sample of patients (n =1,460) recruited between January 2001 and December 2004 (Lieberman et al. 2005), the mean BMI at baseline was 29.7 kg/m2 (men 28.5 kg/m 2; women 33.0 kg/m2) (McEvoy et al. 2005). In a Canadian study of 240 adult patients with schizophrenia recruited in 2003 and 2004 and treated with antipsychotic medication, Cohn et al. (2004b) found that the mean BMI was 28.7 kg/m2 (men 28.0 kg/m 2; women 30.1 kg/m2) and the rate of obesity was 31% in men and 43% in women. In the same study, the rate of metabolic syndrome was two times higher in patients with schizophrenia than in age- and gender-matched general population controls. Similarly, baseline CATIE data revealed that men and women with schizophrenia were 138% and 251% more likely, respectively, to have metabolic syndrome than a National Health and Nutrition Examination Survey matched sample (McEvoy et al. 2005). To compare rates of obesity in schizophrenia patients with the general population prior to the widespread use of atypical antipsychotics, Allison et al. (1999a) investigated BMI in patients with and without schizophrenia using data from the mental health supplement of the 1989 National Health Interview Schedule. Men with schizophrenia had a BMI similar to that of men without schizophrenia (26.14 vs. 25.63), but women with schizophrenia had a higher BMI than women without schizophrenia (27.36 vs. 24.50, P< 0.001). A consistent finding in these various studies has been that women with schizophrenia have a differentially higher rate of obesity and metabolic syndrome relative to the general population than do men with schizophrenia. Although this finding is similar to what has been found in various minority and lowincome groups, the reasons have yet to be fully explored.

Determinants and Mechanisms of Obesity General and Evolutionary Factors Weight maintenance is governed by a formula that is deceptively simple: energy input must equal energy output. Energy input is essentially food consumed, whereas energy output comprises a number of elements of which physical activity is the main modifiable factor and accounts for about 30% of energy output. Other energy output factors include basal metabolism (60% of energy output), diet-induced thermo-

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genesis (10% of energy output), and adaptive thermogenesis or alteration in metabolism related to environmental, psychological, or other influences, such as habitual body movement (Groff and Gropper 1999). (Subtle akathisia, which was a common side effect with classic antipsychotics, probably accounted for significant energy expenditure.) Energy balance is tightly controlled but tilted toward weight gain because of physiological adaptations that defend against weight loss, so that a very small positive energy balance of 100 calories a day (the equivalent of one slice of bread) results in a gain of 4.5 kg in 1 year. Evolutionary concepts best explain the evolving epidemic of obesity in developed and developing countries (Ogden et al. 2007; Pi-Sunyer 2003). The human body has evolved to survive the threat of famine from a time when food was scarce and a great deal of effort and energy was required to procure food. In contrast, many people now have an abundant supply of cheap, easily obtainable, and palatable food, and at the same time less requirement and opportunity for exercise. What was an advantage in times of food scarcity becomes a liability when the food supply is abundant or when there is change from a traditional diet to a more westernized diet. When food is scarce and weight is lost, the body has a powerful biological drive to regain weight: basal metabolic rate drops, and hunger signals increase. In contrast, when excessive weight is gained, biological signals are muted; there is no great increase in basal metabolism, and individuals tend to become less rather than more active. The thrifty phenotype hypothesis, as proposed by Hales and Barker (2001), is an extension of this view: With poor intrauterine nutritional conditions, the child efficiently conserves energy and is prepared for survival in an environment where food resources will be scarce. Then, when exposed to an environment of food excess, such an individual who is efficient at conserving energy would be predisposed to obesity. This hypothesis has gained considerable favor in explaining susceptibility to metabolic disturbance, particularly type 2 diabetes. The thrifty phenotype hypothesis also suggests a mechanism whereby patients with schizophrenia may be predisposed to obesity and associated metabolic disturbance. Epidemiological research has shown an association between intrauterine and childhood undernutrition and the lifetime risk of schizophrenia. For example, there was a doubling of the rate of schizophrenia following both the Dutch winter famine (1945) and the Chinese famine (1959–1961) (Hoek et al. 1998; St Clair et al. 2005). In addition, studies have demonstrated a relationship between schizophrenia and small size at birth, thinness in childhood, and short stature (Gunnell et al. 2003; Wahlbeck et al. 2001).

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Genetics and Neurophysiology Estimates of the heritability of obesity range from 30% to 70% (Martínez-Hernández et al. 2007). Different sets of monozygotic twins that are overfed differ in the degree to which excess calories are stored as fat, but within each set of twins the susceptibility to gain weight in a given environment is similar. Although a number of rare syndromes associated with obesity have been found to be caused by discrete genetic defects or chromosomal abnormalities (e.g., Prader-Willi syndrome), the more common forms of obesity likely involve more complex interactions between the environment and a multitude of polymorphisms located in genes and candidate regions throughout the genome. Genetic investigation has focused on genes that encode and regulate food intake, energy expenditure, and adipogenesis. Food intake is regulated by peptides such as leptin and neuropeptide Y that bind with receptors in the hypothalamus, as well as by a range of peptides synthesized along the gastrointestinal tract, such as ghrelin and cholecystokinin (Schwartz et al. 2000). Research on energy expenditure has focused on the sympathetic nervous system, in particular the β-adrenergic receptor gene family, and on uncoupling proteins at the mitochondrial level (Martínez-Hernández et al. 2007). In adipogenesis, peroxisome proliferator–activated receptor-γ (PPAR-γ) has become a focus of investigation (Marti et al. 2002).

Lifestyle Habitual diet and level of physical activity are important factors that contribute to energy balance and the development of obesity. Dietary intake has been studied in schizophrenia samples, but results have been conflicting. In a cohort of 102 middle-aged patients with schizophrenia living in the community, English researchers reported that patients had a diet higher in fat and lower in fiber than the general population (Brown et al. 1999). Using a 24-hour diet recall in 146 outpatients with schizophrenia living in Pittsburgh, Strassnig et al. (2003b) reported that patients consumed more food than matched control subjects, but the macronutrient composition (percentage of calories from fat, protein, and carbohydrate) was similar in both groups. In contrast, Henderson et al. (2006) used 4-day food diaries—a more rigorous sampling strategy—to evaluate the diet of 88 patients with schizophrenia attending a community mental health clinic in Boston and made comparisons with general population controls matched by age, gender, and ethnicity. The patients consumed significantly fewer calories and less carbohydrate, protein, total fat, and saturated fat than the general population controls.

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Habitual diet is notoriously difficult to measure and is prone to various degrees of underreporting (O’Neil 2001), which may help explain these discrepant findings. Patients with schizophrenia are often financially disadvantaged, and diet can vary based on the local availability of low-cost foods. Patients are often housed in group homes and boarding houses, where food, if it is provided, is cost-based and tends to be high in starch and sugar. In a Toronto study, Cohn et al. (2004a) found that the diet of 162 outpatients with schizophrenia was similar in calorie count to that of individuals in the general population but was high in simple carbohydrates, particularly easily available chips and soda—a diet that has been implicated in development of metabolic syndrome (McKeown et al. 2004). Findings regarding physical inactivity in samples of patients with schizophrenia have been more consistent. Multiple investigators have reported low levels of physical activity in patients compared with the general population (Brown et al. 1999; Cohn et al. 2004a; Daumit et al. 2005; Ussher et al. 2007). Daumit et al. (2005) pointed out that walking tended to be the only form of physical activity and that women and those without regular social contact were more inactive. Ussher et al. (2007) indicated that patients reported low levels of social support for exercising and that fatigue and illness were the most common barriers to activity.

Obesogenic Environment An important consideration is how the environment influences lifestyle and the development of obesity. The “obesogenicity” of an environment is the sum of influences that the surroundings, opportunities, or conditions of life have on promoting obesity in individuals or populations (Swinburn et al. 1999). The concept of the obesogenic environment has been applied to the built environment, particularly in cities and suburbs (Papas et al. 2007). Attempts have been made to analyze obesogenic factors in school systems and to promote healthier environments with access to nutritious foods and the promotion of physical activity (Nollen et al. 2007). However, little attention has been paid to the obesogenic environment in mental health settings. How environments are structured in psychiatric group homes, inpatient units, and community clinics, with provision of opportunities for physical exercise and healthy eating, is an important focus for future research.

Antipsychotic-Induced Weight Gain Antipsychotic medications are a mainstay in the treatment of schizophrenia, and in most cases long-term maintenance treatment is advised.

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Significant weight gain has been recognized as a common side effect, particularly with low-potency classic antipsychotics and certain second-generation antipsychotics. This issue, which is now recognized as a public health concern (Green et al. 2000), has garnered much attention, particularly over the past 10 years. In a comprehensive review of the published literature, including randomized clinical trials, Newcomer (2005) identified clozapine and olanzapine as being associated with the greatest risk of clinically significant weight gain; risperidone, quetiapine, amisulpride, and zotepine as having intermediate risk; and ziprasidone and aripiprazole as having the lowest risk. This view is consistent with the findings of a consensus development conference among the American Diabetes Association, American Psychiatric Association, American Association of Clinical Endocrinologists, and the North American Association for the Study of Obesity. The report, published simultaneously in two journals in 2004, similarly assigned antipsychotics to high, intermediate, and low risk for weight gain and attributed the associated risk for type 2 diabetes and dyslipidemia in the same rank order (American Diabetes Association et al. 2004). Antipsychotics are associated with both short-term (10–12 weeks) and long-term weight gain. Allison et al. (1999c) conducted a metaanalysis to compare the weight-gain liability of antipsychotics over the short term (10 weeks). Using a random-effects model, average weight gain was 4.5 kg with clozapine, 4.1 kg with olanzapine, 2.5 kg with chlorpromazine, 2.1 kg with risperidone, 1.1 kg with haloperidol, and 0.05 kg with ziprasidone (Allison et al. 1999c). Other investigators have reported the short-term weight gain to be 2.3 kg with quetiapine (Jones et al. 1999) and 0.6 kg with aripiprazole (Marder et al. 2003). Weight gain tends to be rapid, particularly during the first 3 months of treatment, with significant weight increases often noted within a few weeks of treatment (Newcomer 2005). Weight gain generally plateaus within 9 months or 1 year, although clozapine tends to have a longer weight-gain trajectory, with patients continuing to gain weight for up to 5 years (Henderson et al. 2000). Considerable interindividual variability in weight gain occurs, and average weight gain belies the fact that individual patients can gain a very large amount of weight (sometimes in excess of 45 kg) on a particular medication. Susceptibility to weight gain may be genetically determined, and at a future time genetic testing might be used for predicting which patients are prone to excessive weight gain (Müller and Kennedy 2006). Clinical experience has shown that the following variables predict weight gain:

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1. Type of antipsychotic: Antipsychotics differ considerably in weightgain liability. 2. Previous antipsychotic exposure: Patients who are antipsychotic naive or switched from a classic antipsychotic or an SGA with low weight-gain risk to an antipsychotic with high weight-gain risk are more susceptible to weight gain. In contrast, those switched from an antipsychotic with high to one with low weight-gain liability tend to lose weight. 3. Age: Children, adolescents, or young adults are more likely to gain weight; older patients are less susceptible to weight gain. 4. Baseline weight: Patients with a low baseline weight tend to gain more weight. 5. Race and ethnicity: Certain groups, including those of African, South Asian, Hispanic, and Native American descent, have higher baseline rates of metabolic disturbance and may also be more susceptible to weight gain. 6. Clinical response: Although controversial, a number of investigators have found an association between weight gain and antipsychotic response. 7. Antipsychotic dose and plasma level: These are generally not correlated with weight gain when prescribed within the recommended dose range, although clozapine may be an exception. Longer-term weight gain is difficult to compare across antipsychotics because of patient attrition and the difficulties adjusting for variables such as prior antipsychotic exposure. In a randomized, controlled trial of 263 first-episode patients with no or limited prior exposure to antipsychotics that compared olanzapine (mean modal dose 9.1 mg/day) and haloperidol (mean modal dose 4.4 mg/day), the weight gain after 2 years of treatment for olanzapine was 10.2 kg using a last-observationcarried-forward analysis and 14 kg for observed cases. For haloperidol, weight gain was 4 kg using a last-observation-carried-forward analysis and 7.5 kg for observed cases (Zipursky et al. 2005). The neuroendocrine mechanisms that underlie antipsychoticinduced weight gain are not fully understood. However, the relationship between neurotransmitter-binding profiles of different antipsychotics and their propensity to induce weight gain has been explored (Nasrallah 2008). Wirshing et al. (1999) astutely observed a correlation between weight gain and antipsychotic binding affinity for the histamine-1 (H1) receptor. Kroeze et al. (2003) more recently concluded that H 1 receptor affinity is positively correlated with weight gain among both typical and atypical antipsychotics. Others have confirmed this

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(S.F. Kim et al. 2007; Matsui-Sakata et al. 2005). S.F. Kim et al. (2007), using a mouse model, found that antipsychotics that induce weight gain selectively activate hypothalamic AMP-kinase via the H1 receptors. H1 activity is involved in appetite regulation and sedation, both relevant to weight gain. These findings may guide antipsychotic drug development toward drugs less implicit in weight gain. Other targets for investigation include the 5-HT2C gene (De Luca et al. 2007; Reynolds et al. 2002) and the SNAP-25, α-2a, leptin, and GNB3 genes (Müller and Kennedy 2006).

Managing Obesity in Schizophrenia The management of obesity includes an understanding and evaluation of risk factors, prevention of weight gain, metabolic assessment, and ongoing monitoring of the patient, as well as the application of pharmacological and nonpharmacological strategies of prevention and treatment. Clearly, psychiatrists cannot do this work alone. What is required is to develop a system of assessment and management in which roles and tasks are clearly defined and often delegated.

Tooling the Office or Clinic Clinicians should think through how to set up the environment, equipment, systems, and personnel within the office or clinic to facilitate care of patients who are obese (Kushner 2007). The clinic or office should be accessible for these patients. Hallways and doors should not be too narrow, washrooms need to be large enough, and the waiting area and examination or interview room should have a number of sturdy, armless chairs. Posters, artwork, and magazines should not overly promote “thinness.” However, posters promoting balanced healthy eating and physical activity are appropriate, as is information about weight-loss programs and services. The examination area should be equipped with appropriate equipment for assessing obese patients. Most office or hospital scales do not measure above 300–350 lb (135–160 kg). Clinics should obtain a scale with greater capacity and position it so the patient can be weighed privately and away from public view. A wall-mounted measure or an extendable height meter attached to the scale should be available for measuring the patient’s height. Also, a variety of cuff sizes should be provided for measuring blood pressure. “Miscuffing” is the most common error in measuring blood pressure, and undercuffing accounts for the majority of errors (Manning et al. 1983). Tape measures should be

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available for measuring waist circumference, and a calculator or chart is needed for determining BMI. Each office or clinic needs to establish a procedure for metabolic monitoring. The paper or electronic health record should allow for the recording and tracking of screening medical history questions, clinical measures, and laboratory tests used in metabolic monitoring. Commercial tracking sheets, usually sponsored by pharmaceutical companies, are available. The clinic where I work has developed an electronic tool that is integrated into the medical record and the patient care plan that allows for the tracking of metabolic parameters and performs calculations such as whether the patient has metabolic syndrome, Framingham risk score, target lipid values, and so forth (Khoury et al. 2008). Forms or computer systems should be readily available to order needed laboratory tests. Systems need to be in place for referring patients for primary care or specialist consultation and for referring patients for nutrition counseling and to professionals who promote physical activity. Larger clinics or programs should develop group-based interventions to promote healthy lifestyle changes. The roles and tasks of personnel should be clearly defined. Registered nurses can obtain the vital measurements, including weight, height, waist circumference, and blood pressure, and provide health teaching. Nurse practitioners can provide most components of primary health care. Co-location of primary health care (primary care physician or nurse practitioner) within psychiatric services is an excellent model for integrating health care (Druss et al. 2001). Office secretaries and assistants can facilitate referrals, remind patients of appointments, and distribute written material. Although the exact role and function of each team member varies from one setting to another, what is most important is that care is coordinated and that individuals work together as a team.

Assessment and Metabolic Monitoring of the Patient Patients can be assessed at various points—as a new antipsychotic medication is prescribed, after substantial weight has been gained, upon admission to hospital, at annual examinations, at each visit, and so on. Ideally, to inform care, these various assessments should be recorded and tracked, along with prescribed medications and intervention efforts. Electronic record systems are particularly helpful in this regard and can also provide reminders when assessments are due. We (Cohn and Sernyak 2006) have reviewed recommendations regarding metabolic monitoring published in various countries. Table 4–1

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provides a structure informed by these guidelines and used in our clinic for assessment of patients who are overweight or obese and are being treated with psychiatric medications associated with weight gain (antipsychotics, mood stabilizers, and antidepressants). Monitoring, which consists of medical history, measurements, and laboratory tests, is conducted at the first opportunity—when the patient first presents at the office of clinic or at the time of hospital admission. Monitoring is then repeated annually. A new baseline is established when a new antipsychotic (or mood medication) is started, with a follow-up evaluation 3 months later. Weight is measured at every visit and graphed over time across encounters (inpatient and outpatient). Diet, activity, motivation, and environmental factors (see “General and Lifestyle” column in Table 4–1) are evaluated during clinic visits. To evaluate diet and physical activity, we have found it useful in our clinic to have the patient, with the support of family or caregivers, complete 3 days of food records, a standard food frequency questionnaire, and a physical activity questionnaire prior to the initial appointment. We have been able to validate the reliability of the International Physical Activity Questionnaire (Craig et al. 2003) in a sample of patients with schizophrenia (Faulkner et al. 2006). These assessments are mailed to the patient before the appointment, reviewed during the initial consultation, and used to inform the development of a treatment plan. We have also found it useful to get a baseline measure of fitness by using the 6-minute walking test (ATS Committee on Proficiency Standards 2002), a simple structured assessment of the distance an individual walks over 6 minutes.

Strategies for the Prevention and Management of Obesity Behavioral lifestyle interventions focused on diet and physical activity should be combined with biological (mostly pharmacological) strategies to benefit patients who are obese (Faulkner and Cohn 2006). Figure 4–1 provides a recommended outline for the sequencing of interventions. Behavioral interventions are discussed in detail in Chapter 8, “Behavioral Treatments for Weight Management of Patients With Schizophrenia.” This section focuses on biological strategies. Medication Choice. Weight-gain liability should be factored in when choosing psychotropic medications. The choice of psychotropic medication may have the greatest influence on weight gain and associated metabolic disturbance. Good evidence exists for a range of weight-gain liability for antipsychotic medications (Allison et al. 1999c; Newcomer

TABLE 4–1.

Metabolic assessment of patients treated using antipsychotic medications Medical history

•

Medications • Current antipsychotic medication(s) • Previous antipsychotic trials • Newly prescribed antipsychotic (date) • Coprescribed mood stabilizers • Coprescribed antidepressants • Coprescribed lipid medication(s) • Coprescribed diabetes medication(s) • Coprescribed antihypertensive medication(s)

• •

•

Current psychiatric and medical contacts Income and source Living situation: Are meals provided? Who does the shopping and cooking? Recreational opportunities? Self-report of weight change over time

Physical activity • Premailed International Physical Activity Questionnaire 1 • Interest in and barriers to increasing physical activity • 6-Minute walking test 2 Diet • Premailed food frequency questionnaire and 3-day food diary • Interest in and feasibility of making dietary changes

Examination (measurement) Laboratory tests • • • •

Height Weight Waist circumference Blood pressure

For nondiabetic patients (No known diagnosis of diabetes) • Fasting glucosea Measuring guide • Fasting insulin Height: No shoes • Fasting lipid Weight: No shoes; single layer profile of clothing (Total, HDL, and Waist circumference: Standing LDL cholesterol position and triglycerides) Blood pressure: Average of two measures. Patient seated For diabetic patients Risk factors and resting for at least 5 • Race/ethnicity • Fasting glucose minutes, >30 minutes from • Family history of diabetes • Fasting lipid last cigarette or coffee. Arm • History of gestational diabetes profile relaxed and supported at • History of coronary vascular disease • HBA1C heart level. Choose (angina, myocardial infarction, or • Random urine appropriate cuff size as stroke) microalbuminb indicated by cuff markers. • Cigarette smoking

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a Patients with impaired fasting glucose (5.6–6.9 mmol or 100–125 mg/dL) have follow-up glucose tolerance test (fasting glucose and 2-hour glucose after 75-g oral glucose drink). bIf elevated, urine albumin/creatinine ratio. 1 Craig et al. 2003; Faulkner et al. 2006. 2ATS Committee on Proficiency Standards 2002. Source. Adapted from Cohn and Sernyak 2006.

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2005). Antidepressant and mood-stabilizing medications also contribute to weight gain (Aronne and Segal 2003; Fava 2000) because these medications are commonly coprescribed with antipsychotics. Lithium carbonate, valproic acid, selective serotonin reuptake inhibitors, and mirtazapine have all been implicated in weight gain. Young, first-episode patients are more susceptible to antipsychoticinduced weight gain (Zipursky et al. 2005) and also tend to have a robust response to antipsychotic medications (Perkins et al. 2004). Initial treatment with antipsychotic medications known to induce significant weight gain should be avoided. Care should also be taken in the choice of concomitant psychiatric medications. In patients who have gained significant weight or developed metabolic complications, all medications should be reviewed from both metabolic and psychiatric perspectives (Faulkner and Cohn 2006). Medication Switching. Switching from one antipsychotic medication to another can have significant effects on body weight and metabolic parameters. Reviews (Weiden 2007; Weiden and Buckley 2007) suggest that switching to low-liability antipsychotics (ziprasidone or aripiprazole) can have a more substantial impact on reversing weight gain and lipid disturbance than other intervention strategies, particularly if the weight gain and metabolic derangement clearly occurred during the course of prior treatment with an antipsychotic medication with greater metabolic liability. The metabolic benefit from switching is therefore dependent on the prior treatment. Outpatients, predominantly with schizophrenia, were switched from a previous antipsychotic—olanzapine (n = 104), risperidone (n = 58), or conventional antipsychotic (n =108)—to ziprasidone (mean dose 91 mg/day) and reevaluated after 6 weeks (Weiden et al. 2003a). Weight and metabolic benefit depended on which drug the patients were originally taking. Those switched from olanzapine experienced the greatest metabolic benefit, with significant reductions in body weight (1.76 kg), nonfasting total cholesterol, and triglycerides. Those switched from risperidone experienced less weight loss (0.86 kg) but similar reductions in nonfasting total cholesterol and triglycerides. However, those switched from conventional antipsychotics had no change in weight or lipid measures. A companion paper from the same data set (Weiden et al. 2003b) supported the view that stable but symptomatic patients can safely be switched from a previous antipsychotic using a variety of switching strategies (e.g., abrupt discontinuation of previous antipsychotic or gradual cross-titration), often with benefit to psychiatric symptomatology. An extension of this study provided long-

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Consider metabolic risk in choice of antipsychotic

Provide patient, family, and caregiver education about potential metabolic side effects

Conduct baseline screening and regular metabolic monitoring

Provide lifestyle counseling

With significant weight gain/ metabolic disturbance: Review all medications from a metabolic and psychiatric perspective; consider risk/benefit of switch

Provide referral to structured lifestyle intervention focused on diet, physical activity, and behavior change

If lifestyle intervention is unsuccessful, consider adjunctive pharmacotherapy; for severe obesity and significant disability, consider evaluation and workup for obesity surgery

FIGURE 4–1. Prevention and management of antipsychotic-related metabolic disturbance. Source.

Adapted from Faulkner and Cohn 2006.

term data for 153 patients followed for 58 weeks (Weiden et al. 2008). Average weight loss from baseline was 10.3% (9.8 kg) and 7.8% (6.9 kg) if the previous antipsychotic was olanzapine or risperidone, respectively. Those patients switched from olanzapine and risperidone also sustained significant reductions in nonfasting cholesterol and triglycerides, with maximum reductions occurring rapidly at 6 weeks after the switch. Those switched from conventional antipsychotics to ziprasidone did not change in body weight or lipid measures. Data from the CATIE study (Lieberman et al. 2005) also provide evidence in a randomized trial of differential effects on body weight

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when antipsychotics are switched. Patients switched to olanzapine gained 0.9 kg per month. Patients switched to quetiapine and risperidone also gained weight, but less (0.23 kg per month on quetiapine and 0.18 kg per month on risperidone). Those switched to ziprasidone and perphenazine lost 0.13 and 0.09 kg per month, respectively. Patients switched to aripiprazole (Casey et al. 2003) experience weight changes very similar to patients who are switched to ziprasidone. Again, weight change depended on the previous antipsychotic. Taken together, data from these studies indicate that weight loss and metabolic benefit can be achieved by switching medication, particularly if these problems clearly developed while a patient was taking the prior medication. However, switching is always hazardous because patients can decompensate. The biggest challenge is the patient who has been doing well psychiatrically while taking an antipsychotic but has gained weight or developed metabolic complications. In such a case, the risks of switching may be greater, and the patient and family need to be informed of the potential risks and benefits and then carefully consider whether to switch medication. Discontinuing or switching antipsychotics becomes a critical issue when diabetes or diabetic ketoacidosis can be clearly linked to an antipsychotic prescription, because resolution of diabetes can occur (Jin et al. 2004). Medication Addition. One strategy to prevent weight gain or to promote weight loss is to add a medication associated with weight loss to the antipsychotic medication regimen. In the general population, controlled clinical trials have established modest efficacy for obesity drugs in combination with lifestyle therapy (Li et al. 2005). Orlistat (lipase inhibitor) and sibutramine (serotonin/dopamine/norepinephrine reuptake inhibitor) are the only drugs currently approved for long-term weight loss. Average weight loss in the general population (psychiatric patients were excluded) at 12 months was 2.7 kg (95% CI 2.3–3.1) for individuals taking orlistat and 4.3 kg (95% CI 3.6–4.9) for those taking sibutramine (Padwal et al. 2003). In the context of antipsychoticinduced weight gain, brief (6–16 weeks) randomized controlled trials have been conducted in patients with schizophrenia using a number of compounds, as summarized in Table 4–2. In a Cochrane review, Faulkner et al. (2007b) focused on weight change to compare efficacy reported in studies identified using a systematic search and retrieval protocol. Unfortunately, no long-term studies have been published. In these studies, the weight loss medication is either added when the antipsychotic is first prescribed to prevent weight gain (e.g., reboxetine in first-episode psychosis being treated with olanzapine) (Poyurovsky

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et al. 2003, 2007) or added later when patients have already gained substantial weight (e.g., the use of metformin in children and adolescents whose weight had increased by more than 10% in less than 1 year while taking atypical antipsychotics) (Klein et al. 2006). Many of these studies have been conducted in patients taking clozapine and olanzapine. The studies have been heterogeneous, and results have been mixed. When there is a weight benefit, it tends to be modest (approximately 2–4 kg over 3 months). Negative results have been seen with fluoxetine and reboxetine addition. Sibutramine was found effective with patients on olanzapine (Henderson et al. 2005) (but the benefits were reversed when patients stopped taking sibutramine). Sibutramine was ineffective in clozapine-treated patients (Henderson et al. 2007). Topiramate has been more consistently effective for weight loss in open-label as well as double-blind studies (J.H. Kim et al. 2006; Ko et al. 2005), and doses of 200 mg/day have been more effective than 100 mg/day (Ko et al. 2005). However, topiramate has many side effects, both common (paresthesia) and potentially serious (cognitive impairment, narrowangle glaucoma, and metabolic acidosis). Metformin may be more helpful in reducing or preventing weight gain during the early stages of treatment for psychosis or in younger individuals. Metformin was found to be effective in reducing weight gain when coprescribed with olanzapine in patients treated for a first psychotic episode (Wu et al. 2008) and in reversing weight gain and improving insulin sensitivity in children and adolescents who had recently gained weight during treatment with atypical antipsychotics (Klein et al. 2006). However, metformin addition was not able to prevent weight gain in an adult sample of schizophrenia patients with a more chronic course who were switched to olanzapine (Baptista et al. 2006). The release of rimonabant, a selective cannabinoid CB1 receptor antagonist, was highly anticipated because of promising phase 3 results in weight loss, smoking cessation, and improvement of metabolic profiles in patients with metabolic syndrome, all of which would benefit patients with schizophrenia (Cox 2005). Rimonabant is currently approved in Europe but not in the United States or Canada. Because recent data indicate significant psychiatric adverse effects, primarily depression and anxiety, there was a recommendation against rimonabant approval in 2007 by the FDA (Rumsfeld and Nallamothu 2008). Given that H1 receptor affinity appears to be implicated in antipsychotic-associated weight gain, interest has been shown in the use of betahistine, an H1 receptor agonist and H3 antagonist, to prevent weight gain. Promising results were reported in a small open-label study (Poyurovsky et al. 2005). Placebo-controlled studies are still needed.

Antipsychotic × trial duration

Amantadine (antiparkinsonian) Famotidine (H2 receptor antagonist) D-Fenfluramine (removed from market) Fluoxetine (SSRI)

Olanzapine × 16 weeks (Deberdt et al. 2005) Olanzapine × 6 weeks (Poyurovsky et al. 2004) Typical depots × 12 weeks (Goodall et al. 1988) Olanzapine × 8 weeks (Poyurovsky et al. 2002) Olanzapine × 16 weeks (Bustillo et al. 2003) Olanzapine × 12 weeks (Wu et al. 2008) Atypical AP × 16 weeks (Klein et al. 2006) Olanzapine × 14 weeks (Baptista et al. 2006) Olanzapine × 8 weeks (Atmaca et al. 2003) Olanzapine × 16 weeks (Cavazzoni et al. 2003)

Metformin (antidiabetic)

Nizatidine (H2 receptor antagonist)

Agent dose: n for intervention group: outcome, expressed as weight change relative to placebo [95% CI] 100–300 mg: n= 35: −1.7 [−3.9, 0.5] kg 40 mg OD: n= 7: no effect 30 mg OD: n= 9: −2.6 [−5.5, −0.1] kg 20 mg OD: n= 15: no effect 60 mg OD: n= 15: no effect 250 mg tid: n= 18: −5.0 [−7.3, −2.7] kg 500 mg OD: n= 9 (ages 10–17): −4.1 [−7.3, −1.0] kg 850–1,750 mg: n= 20: no effect 150 mg bid: n =18: −6.8 [−7.9, −5.7] kg 300 mg bid: n =58: less wt gain, 3 and 4 wk; effect lost, 16 wk 150 mg bid: n =57: no effect

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TABLE 4–2. Randomized, controlled trials of medication addition for weight gain in schizophrenia

TABLE 4–2. Randomized, controlled trials of medication addition for weight gain in schizophrenia (continued) Antipsychotic × trial duration

Phenylpropanolamine (removed from market) Reboxetine (SNRI)

Clozapine × 12 weeks (Borovicka et al. 2002) Olanzapine × 6 weeks (Poyurovsky et al. 2003) Olanzapine × 6 weeks (Poyurovsky et al. 2007) Clozapine × 12 weeks (Henderson et al. 2007) Mixed × 16 weeks (Weiden et al. 2003c) Olanzapine × 12 weeks (Henderson et al. 2005) Atypical AP × 12 weeks (Ko et al. 2005)

Sibutramine (serotonin/ dopamine RI)

Topiramate (anticonvulsant)

Agent dose: n for intervention group: outcome, expressed as weight change relative to placebo [95% CI] 75 mg: n =8: no effect 4 mg/d: n =13: −3.0 [−5.6, −0.5] kg 4 mg/d: n =31: −1.5 [−2.9, −0.1] kg 15 mg: n =11: no effect 15 mg: n =29: no effect

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15 mg: n =19: −4.6 [−5.2, −4.0] kg 200 mg/d: n =17: −5.1 [−7.4, −2.7] kg 100 mg/d: n =16: −1.4 [−4.2, 1.5] kg

Note. RI= reuptake inhibitor; SNRI=serotonin-norepinephrine reuptake inhibitor; SSRI= selective serotonin reuptake inhibitor. Source.

Adapted from Faulkner and Cohn 2006.

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Insufficient data are available to suggest the routine use of medication additions (Faulkner and Cohn 2006). Each medication brings the potential of additional side effects, effect sizes are small, and accessing and covering the costs of these drugs are often problematic. Medication additions should, however, be contemplated when other approaches such as behavioral interventions have been exhausted and switching to a different antipsychotic has been ruled out. Obesity Surgery. Surgery is an effective intervention for treating severe obesity (Schneider and Mun 2005; Sharma and Iacobellis 2006), resulting in more significant and longer-lasting loss of weight than other treatments. Criteria for selecting patients for bariatric surgery include the following: 1) BMI > 40 kg/m2 or BMI > 35 kg/m 2 with significant obesity-related comorbidities; 2) repeated failure of other nonsurgical interventions; 3) psychologically stable patient with realistic expectations; and 4) absence of alcoholism, other addictions, or major psychopathology (NIH Conference 1991). These criteria make it difficult for patients with schizophrenia and other forms of severe mental illness to access surgical intervention. Surgical procedures can involve gastric restriction using vertical or adjustable bands to create a small neogastric pouch, or shortening the functional length of the intestinal surface for nutrient absorption, as in gastric bypass or biliopancreatic diversion. The current gold standard for bariatric surgery is the Roux-en-Y gastric bypass, which is a combination of the restrictive and bypass procedures (Sharma and Iacobellis 2006). Patients with schizophrenia require advocacy and very close medical follow-up and support to access and derive maximum benefit from any of these effective interventions.

Conclusion Although obesity is endemic in the general population, its prevalence and consequences are amplified for patients with schizophrenia. Responsibility for organizing health promotion and obesity interventions lies with the providers of psychiatric care, because these services are often not otherwise accessible and because medications used to treat schizophrenia contribute to the development of obesity. Genetic, medication, lifestyle, and environmental factors are determinants of obesity in patients with schizophrenia, but genetic prediction of an individual’s susceptibility to gain weight taking a particular medication is not yet a reality, and practitioners have to rely on clinical evaluation and

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ongoing monitoring. Clinicians and mental health services are challenged to set up systems for the assessment, monitoring, prevention, and treatment of obesity.

Key Clinical Points ◗

Obesity affects life expectancy and quality of life and is more common in patients with schizophrenia than in the general population.

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Genetics, psychotropic medications, lifestyle, and the environment are contributing factors.

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Clinical assessment of the patient includes a review of medical history, diet, and level of physical activity; physical measurements (weight, height, waist circumference, and blood pressure); and laboratory tests. These parameters should be tracked in an organized manner along with prescribed psychotropic medication (metabolic monitoring).

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The clinic or office should be set up to facilitate care of obese patients. Considerations include the environment, equipment, systems, and use of personnel.

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Prevention and management of obesity in schizophrenia require consideration of choice of psychotropic medication, health counseling and behavioral interventions, medication switching, medication addition, and obesity surgery.

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CHAPTER 5 Glucose Intolerance and Diabetes in Patients With Schizophrenia David C. Henderson, M.D. Kathleen Miley, B.S.

In recent years, tremendous progress has been made in the treatment of schizophrenia and other psychotic disorders. In particular, the introduction of atypical antipsychotic agents has helped numerous patients gain control of both positive and negative symptoms of schizophrenia. Studies also suggest that the newer antipsychotic agents increase compliance, prevent relapse (Csernansky et al. 2002), and may offer improvement in the treatment of cognitive dysfunction (Meltzer 2001). These treatment successes, combined with a lower risk of extrapyramidal symptoms (e.g., parkinsonism) and improved control of positive and negative symptoms, have led many psychiatrists to favor the newer, atypical antipsychotic medications over the older, typical agents. Furthermore, the atypical antipsychotic agent clozapine has been found to be a highly effective agent in improving symptoms for those patients who have had treatment resistance to other antipsychotic medications (Lewis et al. 2006). 91

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The use of atypical antipsychotic medications, however, has not proven to be trouble free. Numerous reports in the psychiatric and medical literature have suggested an association between atypical antipsychotic agents and impaired glucose metabolism, diabetes mellitus, and diabetic ketoacidosis (Elias and Hofflich 2008; Henderson 2002; Henderson et al. 2007; Perez-Iglesias et al. 2007; Saddichha et al. 2008). After a brief review of diabetes pathophysiology, especially type 2 diabetes mellitus, and its short- and long-term medical consequences, we examine glucose intolerance and diabetes in individuals with schizophrenia before and following the introduction of typical and atypical antipsychotic medications. Finally, we make recommendations for monitoring and screening for glucose intolerance and diabetes in patients with schizophrenia.

Diagnostic Criteria and Pathophysiology of Diabetes Mellitus Both diabetes and glucose intolerance are characterized by problems in glucose-insulin regulation. According to the American Diabetes Association (ADA), if an individual has the typical symptoms of diabetes, such as polyuria, polydipsia, and unexplained weight loss, plus a casual plasma glucose level ≥200 mg/dL (11.1 mmol/L), a fasting plasma glucose level ≥126 mg/dL (7.0 mmol/L), or a 2-hour plasma glucose level ≥200 mg/dL (11.1 mmol/L) post 75-g oral glucose load, then he or she has diabetes mellitus (American Diabetes Association 2008). Similarly, if an individual has a 2-hour plasma glucose level ≥140 mg/dL and <200 mg/dL post 75-g oral glucose load, he or she is said to have impaired glucose tolerance. Impaired fasting glucose is defined as a level from 100 to 125 mg/dL, whereas fasting glucose values <100 mg/dL are considered to be in the normal range (American Diabetes Association 2008). Two pathophysiological processes can lead to the development of glucose intolerance and diabetes mellitus, the first being a problem with insulin secretion, as in type 1 and the later stages of type 2 diabetes mellitus, and the second being a problem with insulin action, otherwise known as insulin resistance, as seen in type 2 diabetes mellitus (Lebovitz 2001). In the first case, the beta cells of the pancreas have been destroyed by an autoimmune process, and hyperglycemia occurs because not enough insulin is secreted to facilitate glucose uptake in skeletal muscle tissue, inhibit glucose production in hepatic tissue, and suppress lipolysis in adipose tissue. In type 2 diabetes mellitus, although

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enough insulin may be secreted, insulin resistance prevents the insulin from working at the sites of skeletal muscle, hepatic, and adipose tissues. Indeed, a reactive hyperinsulinemia may occur, which may help control plasma glucose levels initially, but eventually the beta cells in the pancreas begin to deteriorate at a genetically determined rate, and the compensatory hyperinsulinemia decreases (Lebovitz 2001). As this occurs, the postprandial plasma glucose levels increase progressively, and the individual progresses from normal glucose tolerance to impaired glucose tolerance to type 2 diabetes mellitus. Thus, patients with type 2 diabetes mellitus have both insulin resistance and an insulin secretory deficit due to decreased beta cell function. Both type 1 and type 2 diabetes mellitus are diseases with multifactorial inheritance. Researchers are confident that no single gene causes type 1 or type 2 diabetes mellitus, and that development of this heterogeneous group of disorders is likely the result of multiple genes and environmental factors. For example, the interaction of genetic factors such as beta cell abnormalities and a predisposition for central obesity with excess caloric intake, high fat ingestion, and decreased physical activity can lead to type 2 diabetes mellitus in some individuals (Lebovitz 2001). Drugs are another environmental factor that can cause diabetes mellitus by either destroying the beta cells in the pancreas or by causing insulin resistance by one of the following mechanisms: 1) increasing appetite and caloric intake, leading to obesity; 2) altering fat distribution (central obesity is a risk factor for diabetes mellitus); 3) decreasing physical activity because of increased sedation; 4) decreasing oxidative metabolism in tissues; 5) interfering with the insulin action cascade; 6) increasing counterregulatory hormones; or 7) increasing free fatty acid release from adipose tissue (Lebovitz 2001). Later in this chapter, we discuss the possible mechanisms by which atypical antipsychotic medications may cause glucose intolerance or diabetes mellitus, exacerbate existing diabetes, or induce diabetic ketoacidosis in patients with schizophrenia.

Medical Complications of Glucose Intolerance and Diabetes Mellitus Hyperglycemia and diabetes mellitus are associated with acute and chronic complications associated with significant morbidity and mortality. Diabetic ketoacidosis, an acute complication of diabetes mellitus, is seen more often in patients with type 1 than in patients with type 2 diabetes mellitus and is a serious and potentially fatal complication.

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Ketoacidosis is defined by low serum pH (≤7.35), low serum bicarbonate levels (≤15), and an anion gap in the presence of ketonemia (Westphal 1996). The diabetic patient is also susceptible to a variety of chronic complications that affect the cardiovascular system, nervous system, eyes, kidneys, and wound-healing capabilities. Most of these complications are a result of microvascular and macrovascular disease that is more extensive and appears much earlier in the diabetic patient than in the general population (Newcomer 2001). Macrovascular disease in the form of atherosclerosis increases the risk of cardiovascular and cerebrovascular events such as myocardial infarction and stroke, thus accounting for much of the disability and death among diabetic patients (Haupt and Newcomer 2001; Henderson 2001). Results from studies conducted with large samples of patients without diabetes show that even modest increases in fasting plasma glucose levels that do not meet the diagnostic criteria for diabetes mellitus put patients at increased risk for cardiovascular disease and complications, including coronary artery disease, myocardial infarction, and other vascular problems, as well as increased risk for cardiovascular death (Gerstein et al. 1999). In peripheral sites, atherosclerosis can cause claudication and “diabetic foot,” a condition in which patients develop nonhealing ulcers that are prone to infection on their lower extremities and feet as a result of vascular insufficiency and sensory deficits from impairments in the peripheral nervous system. Diabetic neuropathy is a complication that contributes significantly to morbidity in diabetic patients because it not only contributes to diabetic foot but also can affect any part of the nervous system, resulting in sensory deficits, paresthesias, motor abnormalities, or autonomic dysfunction (Henderson 2001). A large percentage of diabetic patients also experience ophthalmic complications such as diabetic retinopathy and diseases of the anterior chamber that affect vision (e.g., cataracts), leading to blindness and significant disability. Finally, many diabetic patients suffer a great deal from microvascular- and macrovascular-induced nephropathy, which can cause hypertension, proteinuria, and a decrease in the glomerular filtration rate, leading to renal failure. Indeed, diabetic nephropathy is the most prevalent cause of end-stage renal failure (Schernthaner 2008) and is a leading cause of morbidity and mortality in diabetic patients.

Metabolic Syndrome Obesity (especially visceral), insulin resistance, and dyslipidemia, along with hypertension (Henderson et al. 2004), are major, modifiable

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cardiovascular risk factors associated with macrovascular complications. These metabolic abnormalities and hypertension are key components of metabolic syndrome, which is highly predictive of overt type 2 diabetes mellitus and cardiovascular disease (Wannamethee et al. 2005). The prevalence of metabolic syndrome and cardiovascular disease in the schizophrenia population taking atypical antipsychotics is much higher than in the general population (Bobes et al. 2007; Casey et al. 2004; Newcomer 2004, 2007a, 2007b; Newcomer and Haupt 2006; Osby et al. 2000). McEvoy et al. (2005) found that the age-adjusted prevalence rates of metabolic syndrome in patients in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial were 40.9% based on criteria from the third report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults and 42.7% based on criteria from the American Heart Association.

Lifestyle Factors Allison et al. (2003) reported that patients treated with antipsychotic medications who have experienced weight gain have a reduced quality of life, poorer self-reported general health, and decreased vitality. By increasing a patient’s risk of obesity, antipsychotic agents may be placing patients at risk for associated morbidity and mortality (Pi-Sunyer 2002). Patients who gain greater than 7% of their total body weight are at risk for developing hypertension and type 2 diabetes mellitus. The risk for diabetes mellitus is increased approximately twofold in mildly obese, fivefold in moderately obese, and 10-fold in severely obese persons (Pi-Sunyer 1993). Although patients with schizophrenia tend to consume fewer calories, their food choices differ from those of the general population and they are less likely to make healthy dietary choices (Brown et al. 1999; Henderson et al. 2006a; McCreadie et al. 1998; Pereira et al. 1997; Strassnig et al. 2003). Studies suggest that high dietary saturated fat and low omega-3 polyunsaturated fatty acid play a key role in the development of type 2 diabetes mellitus (Peet 2004a) and contribute to a poor clinical outcome for people with schizophrenia (Christensen and Christensen 1988; Peet 2003, 2004b). No studies have reported on whether atypical antipsychotic-induced insulin resistance has any relationship to poor dietary profile in this population. However, one study showed that clozapine-treated patients with schizophrenia consumed almost twice as much sugar as those taking other antipsychotic agents (Stokes and Peet 2004). Coccurello et al. (2006) and Fell et al. (2007) observed that olanza-

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pine treatment in mice altered dietary macronutrient selection such that they preferred a diet high in fat and sugar. Identification of any link between poor dietary profile and glucose metabolism abnormalities induced by atypical antipsychotic drugs in the schizophrenia population would be helpful to emphasize preventive measures through dietary modification prior to taking aggressive therapeutic approaches. Central obesity is a significant risk factor for the development of type 2 diabetes mellitus in patients with schizophrenia as well as in the general population. The prevalence of obesity and overweight in people with type 2 diabetes mellitus is as high as 80%–90% (Carolino et al. 2008). Apparently, however, the duration of obesity is a greater determinant of risk than that conferred by simply being obese. That is, if a patient gains a considerable amount of weight and maintains this weight, his or her risk of developing hyperglycemia or type 2 diabetes mellitus appears to be increased (Henderson 2001).

Glucose Intolerance and Diabetes Mellitus in Patients With Schizophrenia Findings From the Pre-Antipsychotic Era Early reports dating back to the 1920s, before the use of antipsychotic agents, suggest that individuals with schizophrenia and other psychotic disorders exhibited an elevated risk for developing glucose intolerance or diabetes mellitus (Braceland et al. 1945; Haupt and Newcomer 2001; Marinow 1971; Saddichha et al. 2008; Waitzkin 1966). Specifically, the reports indicate a pattern of insulin resistance in patients with schizophrenia independent of adverse medication effects. These studies, however, suffered from several methodological problems: flaws in the diagnostic criteria for schizophrenia, and lack of control for age, weight, fat distribution, ethnicity, diet, or exercise, all of which are variables now known to play a role in an individual’s risk for developing glucoregulatory disturbances (Haupt and Newcomer 2001). Thus, because no well-controlled studies exist, the debate continues as to whether individuals with schizophrenia, when unmedicated, are at increased risk for developing diabetes compared with the general population.

Conventional Antipsychotic Agents, Diabetes, and Glucose Intolerance Conventional antipsychotic agents, which have primarily antidopaminergic activity, may alter glucose-insulin homeostasis (Hägg et al. 1998).

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In particular, the low-potency phenothiazines may induce diabetes mellitus or aggravate existing diabetes mellitus (Hägg et al. 1998; Haupt and Newcomer 2001). Because of this finding, chlorpromazine has been used to prevent hypoglycemia in patients with malignant insulinoma. Furthermore, chlorpromazine has been shown to induce hyperglycemia in healthy volunteers as well as in patients with latent diabetes (Hägg et al. 1998). Other conventional antipsychotic agents, such as the high-potency agent haloperidol, are associated with a decrease in the prevalence rate of diabetes in the schizophrenia population. For example, Mukherjee et al. (1996) found an overall diabetes prevalence rate of 15% in 95 patients with schizophrenia. In patients younger than age 50 years, there were no cases of diabetes mellitus. For patients ages 50–59 years, however, the prevalence rate was 12.9%, and for patients ages 60–69 years, the prevalence rate was 18.9%. Finally, for those ages 70–74 years, the prevalence rate was 16.7%. After controlling for age, gender, and cumulative duration of antipsychotic treatment, Mukherjee et al. (1996) found that medication-free patients were more likely to develop diabetes mellitus than were those receiving treatment with conventional agents. Of note, the prevalence rates quoted in this study exceeded those expected for type 2 diabetes mellitus in the general population, lending further evidence to the argument that schizophrenia may indeed be an independent risk factor for the development of diabetes mellitus (Henderson 2002; Henderson et al. 2005a). Several other reports have suggested higher rates of type 2 diabetes mellitus in patients with schizophrenia than in the general population, even before widespread use of atypical antipsychotics (Dixon et al. 2000). In a sample of 26 medication-naive first-episode schizophrenia patients, Ryan et al. (2003) found evidence of insulin resistance and impaired glucose tolerance, with 15% of subjects exhibiting abnormal glucose metabolism on an oral glucose tolerance test. Several more recent studies of neuroleptic-naive first-episode schizophrenia patients have also confirmed the presence of glucose-insulin homeostasis dysfunction in this patient population (Cohn et al. 2006; Spelman et al. 2007; van Nimwegen et al. 2008; Venkatasubramanian et al. 2007). In summary, examination of reports discussing the prevalence rates of diabetes mellitus or impaired glucose tolerance in patients with schizophrenia shows that among the conventional antipsychotic agents, the effects of glucose regulation may vary in magnitude across individual agents. Specifically, the phenothiazines may increase a patient’s susceptibility for developing diabetes mellitus, but no significant association has been found between diabetes mellitus and the use of other conventional antipsychotic medications.

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Atypical Antipsychotic Medications, Diabetes, and Glucose Intolerance The greatest benefits of the introduction of the atypical antipsychotic medications as a group—clozapine, olanzapine, quetiapine, risperidone, and ziprasidone—have been improvements in the treatment of negative symptoms and concomitant improvements in cognitive function (Lewis et al. 2006; Meltzer 2001). The improvements in cognitive function, which include the aspects of executive function, verbal fluency, attention, and memory and learning, can lead to improved functioning in both home and work environments (Meltzer 2001). However, these benefits have not come without a cost, because many atypical antipsychotic agents are associated with significant weight gain, which has an adverse effect on health and medication compliance. In the Clinical Antipsychotic Trials for Intervention Effectiveness (CATIE) schizophrenia study, funded by the National Institute of Mental Health, 74% of patients discontinued their study medication (either perphenazine, olanzapine, quetiapine, risperidone, or ziprasidone) before 18 months in phase 1 (Lieberman et al. 2005). The time to discontinuation of treatment for any cause was significantly longer in the group taking olanzapine. Although symptom outcomes were similar in phase 1 for all groups, as indicated by total scores on the Positive and Negative Syndrome Scale for Schizophrenia, the groups demonstrated significant differences in weight gain and significant glucose metabolism changes (with olanzapine resulting in the greatest negative effect). In the phase 2 tolerability arm, the time to treatment discontinuation was longer for both olanzapine (6.3 months) and risperidone (7 months) than for quetiapine (4 months). In subjects who had discontinued their previous phase 1 drug because of side effects and were switched to another drug, olanzapine was more effective than quetiapine and ziprasidone, and risperidone was more effective than quetiapine (Stroup et al. 2006). However, olanzapine, compared with the other agents, was again associated with greater and more significant weight gain and increases in lipids and glucose (Nasrallah 2006). The CATIE trial also found that at baseline, the subjects with schizophrenia had elevated rates of metabolic syndrome and its individual components compared with matched controls from the general population (McEvoy et al. 2005). Additionally, elevated risk for cardiovascular disease was observed at baseline compared with this same pool of matched controls (Goff et al. 2005). (For more discussion of the CATIE trial findings, see Chapter 3, “Medical Outcomes From the CATIE Schizophrenia Study.”)

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Although CATIE has been the largest randomized, double-blind, non-industry sponsored trial to report metabolic data, numerous earlier reports in the medical and psychiatric literature have linked the use of atypical antipsychotic agents to the development of glucose intolerance, new-onset diabetes mellitus, diabetic ketoacidosis, and exacerbation of existing type 1 or type 2 diabetes mellitus, even in patients who are not obese (Henderson 2002; Henderson et al. 2007). Koller and colleagues from the U.S. Food and Drug Administration research program conducted a MedWatch surveillance program analysis and reported 384 cases of clozapine-related diabetes (Koller et al. 2001), of which 242 were new-onset diabetes cases and 54 were cases of exacerbation in patients with preexisting diabetes. Their report also identified 80 cases of clozapine-induced probable diabetic ketoacidosis and 25 deaths. Of note, the majority of diabetic ketoacidosis episodes occurred within the first 6 months of clozapine treatment, and one patient developed diabetes mellitus immediately after he accidentally took a 500-mg dose of clozapine. In another study, Koller and Doraiswamy (2002) found a total of 289 cases of olanzapine-related diabetes, of which 225 were newonset diabetes, with 100 cases of diabetic ketoacidosis and 25 deaths. Given that the MedWatch surveillance program is able to identify only a small percentage of cases, the incidence of clozapine- and olanzapineinduced diabetes mellitus and diabetic ketoacidosis is likely much greater than reported. Hägg et al. (1998), using an oral glucose tolerance test, found that 12% of patients treated with clozapine developed type 2 diabetes and 10% developed impaired glucose tolerance compared to 6% and 3%, respectively, of patients treated with conventional depot antipsychotic medications. In an analysis of 45 published cases of new-onset diabetes mellitus or diabetic ketoacidosis following treatment with atypical antipsychotic agents, Jin et al. (2002) reported that 20 patients had received clozapine, 19 olanzapine, 3 quetiapine, and 3 risperidone. In a study of the association between the atypical antipsychotic agents and diabetes mellitus in patients with schizophrenia or related psychoses, Melkersson et al. (1999) found elevated fasting insulin levels and reduced growth hormone–dependent insulin-like growth factor I in 28 patients taking conventional antipsychotic agents compared with 13 patients taking clozapine, thus suggesting insulin resistance with secondary increased hyperinsulinemia related to clozapine therapy. Our group conducted a 5-year naturalistic study examining, in 96 patients with schizophrenia treated with clozapine, the incidence of treatment-emergent diabetes in relation to other factors such as weight gain, lipid level abnormalities, age, clozapine dose, and concomitant treat-

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ment with valproic acid (Henderson et al. 2000). Patients with diabetes prior to clozapine initiation experienced a twofold increase in insulin requirements or required a switch to insulin from an oral hypoglycemic agent. At baseline, the patients’ mean weight was 79.6 kg and mean body mass index was 26.9 kg/m2. Their mean age at the time of clozapine initiation was 36.4 years. The sample was 26.8% female and 91% Caucasian. During the 5-year follow-up, 30 patients (36%) were diagnosed with diabetes. Patients experienced significant weight gain, which continued until approximately month 46 from the beginning of clozapine treatment, but weight gain was not a significant risk factor for the development of diabetes in this study. After the conclusion of the 5-year study, this cohort was followed for an additional 5 years, resulting in a 10-year naturalistic study that examined the metabolic and cardiovascular side effects of clozapine treatment. At the end of the 10-year study, Henderson et al. (2005c) reported a mean weight gain of approximately 13.6 kg and an estimated 10-year cardiovascular disease mortality rate of 9%. Over the same period, 33 (34%) of the 96 patients developed diabetes, to generate a 43% estimated 10-year incidence rate of new-onset diabetes. In another study, we examined data for patients with schizophrenia treated at our hospital during a 7-year period and found that 18.4% of patients with schizophrenia were diagnosed with diabetes mellitus compared to 6.6% in the general hospital population (P< 0.001) (Henderson et al. 2007). Twenty-three patients with schizophrenia were identified with diabetic ketoacidosis; of these, 11 had new-onset diabetes presenting as diabetic ketoacidosis, 8 had diabetic ketoacidosis with known diabetes mellitus, 2 had new-onset diabetes mellitus– hyperosmolar hyperglycemic syndrome, and 2 had hyperosmolar hyperglycemic syndrome with known diabetes mellitus. The incidence of diabetes presenting as diabetic ketoacidosis in patients with schizophrenia was more than 10-fold higher than that reported in the general population: 14.93 per 10,000 patient years in patients with schizophrenia versus 1.4 per 10,000 patient years in the general population (P< 0.000001) and versus 1.98 per 10,000 patient years in the general hospital population (P<0.000001). The incidence of diabetic ketoacidosis in patients taking each of the atypical antipsychotic drugs over the 7-year period was as follows: clozapine, 2.2%; olanzapine, 0.8%; and risperidone, 0.2% (no incidence with ziprasidone or quetiapine). Of the 11 patients with diabetes presenting as diabetic ketoacidosis, the mean hemoglobin A1c level at admission was 13.3% ± 1.9% (10.4%–16.9%). The elevated hemoglobin A1c levels observed suggest that patients had undiagnosed diabetes mellitus for at least several weeks before their diabetic ketoacidosis episode.

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A few reports have linked the atypical antipsychotic agents risperidone and quetiapine to new-onset diabetes mellitus and glucose intolerance, but not nearly as many as those described for clozapine and olanzapine (Henderson 2001; Henderson et al. 2005a; Perez-Iglesias et al. 2007). Griffiths and Springuel (2001), using the Canadian Adverse Drug Reaction Monitoring Program, reported 37 cases of suspected glucose metabolism disorders associated with atypical antipsychotic agents. With clozapine there were 8 cases of diabetes mellitus, 5 cases of diabetic ketoacidosis, and 4 cases of hyperglycemia. For olanzapine 2 cases of diabetes mellitus were reported, along with 3 cases of diabetic ketoacidosis, 2 cases of diabetic coma, and 3 cases of hyperglycemia. For quetiapine, 1 case of diabetes mellitus and 2 cases of diabetic ketoacidosis were reported. Finally, for risperidone 1 case of diabetes mellitus, 1 case of labile blood glucose levels, 3 cases of hyperglycemia, and 2 cases of hypoglycemia in patients with a previous history of diabetes mellitus were reported. Of note, there were 3 deaths from the 10 cases of diabetic ketoacidosis. Wirshing et al. (2001) reported two cases of new-onset diabetes in risperidone-treated patients. Both subjects were African American, were overweight or obese prior to risperidone initiation, and gained significant weight while receiving treatment with risperidone. These cases highlight the importance of understanding risk factors for diabetes in patients receiving treatment with atypical antipsychotic agents. Finally, Fryburg et al. (2001) reported a double-blind controlled trial comparing olanzapine and ziprasidone therapy on the basis of metabolic indices. In a comparison of baseline to 6-week follow-up, olanzapine subjects showed a significant increase in body weight, fasting serum insulin, cholesterol, triglycerides and a parameter for insulin resistance, suggesting increased insulin resistance in the olanzapine group but not the ziprasidone group. Similarly, Perez-Iglesias et al. (2007) conducted a 12-week study in which 128 patients taking either haloperidol, olanzapine, or risperidone were assessed. Although all treatment groups showed a worsening lipid profile, increases in triglyceride levels were observed only in the olanzapine group. All of the reports indicate that the strength of the association between the atypical antipsychotic medications and disturbances in glucose regulation can vary across the different medications, with many more cases of medication-induced hyperglycemia, diabetes mellitus, and diabetic ketoacidosis occurring with clozapine and olanzapine treatment than with treatment with the atypical agents risperidone, quetiapine, and ziprasidone (Haupt and Newcomer 2001). Also, it is important to recognize that the reports of diabetic ketoacidosis associ-

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ated with clozapine and olanzapine treatments and the increased incidence of new-onset type 2 diabetes may represent two distinct populations with varying risks for developing the diseases (Henderson 2002; Henderson et al. 2007).

Causative Mechanisms With Atypical Antipsychotic Agents The atypical antipsychotic medications could lead to hyperglycemia and diabetes mellitus in a number of ways. As discussed earlier in this chapter, decreased sensitivity (increased resistance) to insulin and decreased insulin secretion as a result of decreased beta cell function are involved in the development of type 2 diabetes. A few controlled studies suggest that the atypical antipsychotic medications affect insulin resistance rather than causing a primary defect in insulin secretion (Henderson 2007; Henderson et al. 2005a). The insulin resistance seen during atypical antipsychotic treatment may be a result of increased central adiposity or may arise from the direct effect of the medication’s action on the glucose transporter function (Haupt and Newcomer 2001). Dwyer et al. (1999) studied the effects of atypical antipsychotic agents on glucose transporter function. They suggested that a structurefunction relationship exists in which similar drugs, such as clozapine and olanzapine, achieve relatively higher intracellular concentrations and bind to, and thus interfere with, the function of the glucose transporter proteins. Another mechanism by which the atypical antipsychotic agents may lead to hyperglycemia and diabetes mellitus is by antagonism of the serotonin 5-HT1A receptors. Antagonism of these receptors may decrease pancreatic beta cell responsiveness to blood sugar levels, thus resulting in disturbances in glucose metabolism secondary to decreased insulin secretion (Gilles et al. 2005). Melkersson et al. (2000), however, found that patients treated with olanzapine had higher fasting insulin levels on comparison of baseline to 5-month follow-up, suggesting that impaired beta cell function is an unlikely cause for olanzapine-associated diabetes mellitus. Their group found that although 11 of 14 (79%) olanzapine-treated patients were normoglycemic and only three showed increased blood glucose values, the majority of patients (10 of 14, or 71%) had insulin levels above the normal limit. The report also noted increased rates of hyperleptinemia, hypertriglyceridemia, and hypercholesterolemia. In short, Melkersson et al. found that olanzapine treatment was associated with weight gain and elevated levels of insulin, leptin, and blood levels as well as insulin resistance, with three patients

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diagnosed with diabetes mellitus. The elevated insulin values argue against the theory that antagonism of the serotonin receptors by some atypical antipsychotic agents, a property that could theoretically lead to decreased beta cell insulin production, causes hyperglycemia and diabetes mellitus. It is also worth noting that olanzapine has little affinity for 5-HT1A receptors. Notably, in several of the case studies and research studies mentioned in this chapter, weight gain was not associated with the development of diabetes mellitus or diabetic ketoacidosis during atypical antipsychotic therapy. Indeed, many of the individuals who developed diabetes mellitus or diabetic ketoacidosis were of normal weight. Thus, although all obese individuals are at increased risk for the development of type 2 diabetes, the added obesity caused by the atypical antipsychotic medications does not appear to be the sole reason for the development of diabetes mellitus or diabetic ketoacidosis in patients with schizophrenia. Nevertheless, if patients with schizophrenia gain considerable amounts of weight and maintain that weight, their risk of developing type 2 diabetes is significantly increased.

Interventions The potential benefit of improving health behavior was demonstrated in a longitudinal study of 85,000 nurses. Results indicated that 83% of coronary heart disease events were avoided by 3% of individuals who maintained a desirable weight, ate a healthy diet, exercised regularly, drank alcoholic beverages moderately, and did not smoke (Stampfer et al. 2000). In nurses who achieved three of the above components, 51% of coronary events were avoided. Although achieving a healthy lifestyle may be more difficult for patients with schizophrenia, the potential benefits warrant intensive efforts toward this goal on the part of patients and caregivers. Switching to a more weight-neutral atypical antipsychotic agent offers promise in halting or reversing weight gain and improving glucose metabolism, but many patients and their clinicians are reluctant to risk a worsening or return of psychotic symptoms and risk relapse (Casey et al. 2003; Luebbe et al. 2006; Spurling et al. 2007; Weiden et al. 2003). Menza et al. (2004) reported on a 52-week multimodal weight control program using nutrition, exercise, and behavioral interventions in 31 patients with schizophrenia or schizoaffective disorder and found, using a last observation carried forward (LOCF) analysis, a significant reduction in weight, body mass index (BMI), hemoglobin A1c, and systolic and diastolic blood pressure, with 20 of 31 completing the program.

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A number of pharmacological interventions have been evaluated to improve glucose metabolism. One study randomized 26 first-episode schizophrenia patients to either olanzapine 10 mg or olanzapine 10 mg plus reboxetine 4 mg (Poyurovsky et al. 2003). Patients receiving the combination had less weight gain (2.5 ±2.7 kg) than patients receiving olanzapine alone (5.5± 3.1 kg). In another study, fluoxetine was ineffective in diminishing olanzapine-induced weight gain in first-episode schizophrenia patients (Poyurovsky et al. 2002). In a 16-week doubleblind trial, Radulovic et al. (2002) evaluated the addition of sibutramine with behavioral weight counseling to an ongoing antipsychotic regimen in stable, overweight, or obese outpatients with schizophrenia. Twentyone patients were assigned to either sibutramine (up to 15 mg/day) or placebo in a 2:1 ratio. Nineteen completed at least 4 weeks of doubleblind treatment (sibutramine: 14; placebo: 5), with 11 completing the full 16 weeks. There were no significant differences between groups on weight loss (placebo group −4.2 kg; sibutramine group −3.7 kg) or BMI (−1.46 kg/m 2 in the placebo group; −1.32 kg/m 2 in the sibutramine group) in an LOCF analysis. The small sample size and high dropout rate may have limited the opportunity to detect differences between groups. In a placebo-controlled trial of sibutramine with a behavioral nutrition program in olanzapine-treated subjects (Henderson et al. 2005b), the mean weight loss was 3.8± 1.1 kg in the sibutramine group and 0.8 ±0.7 kg in the placebo group (P< 0.05). However, no improvements in lipids were detected in this study. Another study examined the effect of amantadine for weight loss in olanzapine-treated patients (Deberdt et al. 2005). An LOCF analysis indicated a modest but significant difference in change in weight comparing amantadine to placebo group at weeks 8, 12, and 16. At week 16 the result was −0.19±4.58 kg for amantadine versus 1.28± 4.26 kg for placebo (P= 0.045). In a study of 24 patients with treatment-resistant schizophrenia who began taking aripiprazole with decreased doses of clozapine, Karunakaren et al. (2006) reported an average weight loss of 5.1 kg over 34 weeks. Mitsonis et al. (2007) reported on 27 patients for whom aripiprazole was added to stable doses of clozapine. Although no significant weight loss was noted, patients’ total scores on the Positive and Negative Syndrome Scale for Schizophrenia improved significantly. In a 6-week open-label trial to examine the effects of adjunctive aripiprazole in 10 clozapine-treated subjects, patients decreased in weight (from 99.5± 18.1 kg to 96.9± 17.4 kg) (P=0.003) from baseline to study endpoint (Henderson et al. 2006b). Significant decreases were also seen in fasting total serum cholesterol (from 211 ±27 mg/dL to 184±27 mg/dL) (P=0.002) and triglycerides (from 274±229 to 176±106 mg/dL) (P=0.04).

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Morrison et al. (2002) openly treated 19 adolescents taking olanzapine, risperidone, quetiapine, or valproate, with metformin 500 mg three times a day. The mean weight loss at 12 weeks was 2.93 ±3.13 kg, with 15 of 19 patients losing some weight. In a 12-week study comparing the addition of fluvoxamine to low-dose clozapine (≤250 mg/day) with high-dose clozapine monotherapy (≤600 mg/day), Lu et al. (2004) found that subjects on monotherapy had significantly greater increases in weight, BMI, serum glucose, and triglyceride levels. Wu et al. (2008) randomized 40 first-episode schizophrenia patients to treatment with either olanzapine 15 mg/day plus metformin 750 mg/day or olanzapine plus placebo for 12 weeks. They found that weight, BMI, waist circumference, insulin, and insulin resistance increased less with the combination. Baptista et al. (2008) reported on a 12-week study with metformin (850–1,700 mg) plus sibutramine (10–20 mg, n = 13) or placebo (n =15) in olanzapine-treated patients with chronic schizophrenia. Weight loss was similar in both groups, although the combination did prevent a triglyceride increase.

Monitoring and Screening Recommendations The development of glucose intolerance and diabetes mellitus may be a very serious comorbid complication of treatment with antipsychotic agents, thus contributing to morbidity and mortality in patients with schizophrenia. The development of hyperglycemia in patients with schizophrenia often goes unrecognized, as it does in approximately 50% of the general population. Because patients taking antipsychotic medications may be at increased risk for developing diabetes, close monitoring and screening for obesity and hyperglycemia are imperative for individualizing treatment decisions and reducing the risks of morbidity and mortality. Before starting treatment with an atypical antipsychotic, the clinician should perform a risk factor assessment for diabetes mellitus and other metabolic disorders. This risk assessment should include baseline serum lipid and glucose values (preferably fasting), weight, BMI, age, ethnicity, family history of diabetes in a firstdegree relative, level of physical activity, and diet (American Diabetes Association et al. 2004). The American Diabetes Association (2008) recommends that routine screening for diabetes begin at age 45 in whites with no other risk factors for diabetes, and further recommends repeat testing for this group every 3 years thereafter if the results are within normal range.

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The association recommends beginning surveillance at an earlier age and more frequent monitoring for individuals with any of the following risk factors for diabetes and cardiovascular disease: obesity, a firstdegree relative with diabetes, membership in a high-risk ethnic population (African Americans; Hispanic Americans; Asian Americans, including Indian Asians; Pacific Islanders; and Native Americans), previous diagnosis of gestational diabetes or delivery of a baby larger than 4.4 kg, hypertension (>130/85 mmHg), a high-density lipoprotein level ≤40 mg/dL in men and ≤50 mg/dL in women, a triglyceride level ≥150 mg/dL, or previous diagnosis of impaired fasting glucose (fasting plasma glucose level ≥ 100 mg/dL but <126 mg/dL) or impaired glucose tolerance (oral glucose tolerance test revealing 2-hour postload glucose level of ≥ 140 mg/dL but <200 mg/dL). Because schizophrenia is associated with increased rates of diabetes mellitus or impaired glucose regulation, and because the newer, atypical antipsychotic agents appear to increase this risk even further, it seems reasonable that patients with schizophrenia, and especially patients taking atypical antipsychotic medications, should be screened for hyperglycemia before age 45 and monitored more frequently than every 3 years. This is especially appropriate in light of case reports of newonset diabetes mellitus associated with atypical antipsychotic therapy in patients under age 20. Additionally, patients with higher risk factors should be examined more closely. African American, Asian, and Latino patients should be monitored closely, particularly if they have other risk factors for diabetes independent of ethnicity. If factors such as weight gain, elevated lipids, or hypertension develop, early interventions are necessary to prevent the onset of diabetes. Although very little is known about the underlying reasons that some patients treated with atypical antipsychotic agents experience diabetic ketoacidosis, undertaking a risk assessment with each patient may help in choosing safer agents for each individual. We recommend monitoring weight changes and blood pressure at each office visit, as well as fasting glucose and lipids at baseline and every 3 months. Also, patients must be instructed to notify the treatment team if they experience any physical symptoms or medical disorders, because a number of diabetic ketoacidosis episodes have occurred in conjunction with other acute medical disorders such as infections and pancreatitis. A recent study found that hemoglobin A1c levels were significantly elevated in patients with schizophrenia with new-onset diabetes mellitus presenting as diabetic ketoacidosis (Henderson et al. 2007). Therefore, more frequent monitoring of hemoglobin A1c levels may aid in forewarning physicians of a patient’s risk for developing diabetes mellitus or diabetic ketoacidosis. Finally, pa-

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tients treated with atypical antipsychotic agents, particularly clozapine and olanzapine, should be screened more frequently. In contrast to use of some of the atypical antipsychotic agents, treatment with ziprasidone and aripiprazole are associated with minimal impact on metabolic parameters. Ziprasidone may offer significant advantages because it appears to be weight neutral (Allison et al. 1999; Gardner et al. 2005; Henderson 2007); however, additional clinical experience is necessary with this agent before definitive conclusions can be reached. Aripiprazole also appears to be associated with minimal weight gain and little or no negative impact on serum lipids or glucose metabolism (Melkersson and Dahl 2004). Therefore, a reasonable approach would be to take baseline measures (fasting blood glucose, lipids, weight, waist measurements, blood pressure) for all patients and to repeat fasting glucose and lipids every 6 months if possible. Weight and blood pressure can be monitored more frequently in the office. Monitoring of glycohemoglobin may be useful in this population if fasting glucose is difficult to obtain. However, glycohemoglobin may not be sensitive enough to detect lower levels of hyperglycemia, glycohemoglobin changes will lag 2–3 months behind changes in glucose homeostasis, and criteria for diagnosing diabetes with glycohemoglobin do not exist. Education and referral to weight reduction and exercise programs may play a significant preventive role. In addition, weight gain should initiate meaningful dietary intervention. Finally, the clinician should be alert to the possibility of diabetic ketoacidosis. If a patient develops diabetes while receiving treatment with an atypical antipsychotic agent, consideration should be given to switching to another antipsychotic agent. Although diabetic ketoacidosis appears to be uncommon, it is of great concern because it increases the risk of death. Patients who experience an episode of diabetic ketoacidosis should be switched to a different antipsychotic agent that has a lower impact on glucose metabolism. Reports and clinical experience suggest that in a case of atypical antipsychotic agent–associated diabetes or diabetic ketoacidosis, discontinuation of the antipsychotic agent may result in a complete resolution of the hyperglycemia and diabetes. Clozapine-treated patients have few options. Clozapine remains the most effective agent for the treatment-resistant schizophrenia population, and patients often have failed to benefit from several other antipsychotic agents. Interventions to reduce the factors that contribute to impaired glucose tolerance, such as weight loss programs, encouraging exercise, and lowering the clozapine dose, may lead to improvement. Other approaches, including augmentation with a more neutral anti-

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psychotic agent such as aripiprazole, may result in improvements in patients’ weight and metabolic parameters (Henderson et al. 2006b). For patients treated with other atypical agents, switching to another agent should be considered in addition to the preceding interventions. Finally, diabetic patients who are placed on these agents must be monitored more closely to prevent a worsening of glycemic control. The widely distributed guidelines published by the American Diabetes Association et al. (2004) recommend monitoring of all patients who are taking atypical antipsychotic agents by performing a baseline assessment, including fasting glucose and lipids, waist and weight measurements, and blood pressure. They recommend repeating the measures 3 months later and then annually. Regardless of whether these specific guidelines are followed, individual clinicians and programs should develop and adhere to a monitoring system to improve the safety of patients taking these medications.

Conclusion Atypical antipsychotic medications have helped to improve the lives of patients with schizophrenia by alleviating positive and negative symptoms and bringing some improvement in cognitive function. This improvement is helping patients to function in the home and in the workplace, thus improving the patients’ quality of life. At the same time, however, the atypical antipsychotics appear to be associated with the development of glucose intolerance, new-onset diabetes mellitus, diabetic ketoacidosis, and exacerbation of existing diabetes mellitus. These disturbances in glucose metabolism have their own medical consequences, including cardiovascular disease, cerebrovascular disease, diabetic retinopathy, neuropathy, and diabetic nephropathy, all of which can lead to considerable morbidity and mortality. Thus, to minimize morbidity and mortality associated with the use of atypical antipsychotic medications, close screening and monitoring for diabetes mellitus should become a priority for all clinicians treating patients with schizophrenia who are receiving atypical antipsychotic therapy.

Key Clinical Points ◗

Many clinicians choose to prescribe atypical antipsychotic medications, such as clozapine, olanzapine, quetiapine, risperidone, ziprasidone, and aripiprazole, instead of the older agents, because the newer agents have fewer extrapyramidal symptoms and may increase adherence and

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prevent relapse. However, these medications may also increase the risk of metabolic disorders, such as impaired glucose metabolism, diabetes mellitus, and diabetic ketoacidosis. ◗

The choice of antipsychotic medications should be based on perceived efficacy and knowledge of short- and long-term side effects. A generally reasonable approach is to choose the safest medications available first and, if the patient has no response, work the way up the risk ladder. For metabolic problems, prevention is preferable over intervention.

◗

Diabetes mellitus and glucose intolerance are characterized by problems in glucose-insulin regulation. The symptoms that warrant a diabetes diagnosis include polyuria, polydipsia, unexplained weight loss, a casual plasma glucose level ≥200 mg/dL, a fasting plasma glucose ≥126 mg/dL, or a 2-hour plasma glucose level ≥ 200 mg/dL post 75-g oral glucose load. Glucose intolerance is characterized by a 2-hour plasma glucose level ≥140 mg/dL and <200 mg/dL post 75-g oral glucose load.

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Glucose metabolism abnormalities, including onset of diabetes mellitus, diabetic ketoacidosis, cerebrovascular disease, cardiovascular disease, myocardial infarction and stroke, diabetic retinopathy, and neuropathy, are associated with considerable medical morbidity and mortality.

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Atypical antipsychotic agents have been associated with significant weight gain, particularly the development of central obesity, which can lead to several comorbid cardiovascular conditions as well as type 2 diabetes.

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The incidence of disturbances in glucose regulation varies across antipsychotics; many more cases of medication-induced hyperglycemia, diabetes mellitus, or diabetic ketoacidosis occur with clozapine and olanzapine than with risperidone, quetiapine, ziprasidone, and aripiprazole.

◗

Mechanisms by which atypical antipsychotic agents could lead to glucose abnormalities and diabetes mellitus include causing insulin resistance by either increasing central or visceral adiposity or affecting the glucose transporter function antagonism of serotonin 5-HT1A, which may decrease pancreatic beta cell responsiveness to blood sugar levels and treatment-induced weight gain.

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Close and frequent monitoring and screening for obesity and hyperglycemia is imperative for individualizing treatment decisions and reducing the risks for morbidity and mortality for patients with schizophrenia taking antipsychotic mediations.

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Lifestyle interventions and recommendations should be given at the start of the medications and reinforced at every visit.

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CHAPTER 6 Effects of Antipsychotics on Serum Lipids Jonathan M. Meyer, M.D.

Patients with severe mental illnesses, such as schizophrenia or bipolar disorder, are a medically vulnerable population at high risk for cardiovascular mortality (Newcomer and Hennekens 2007), with standardized mortality ratios from cardiovascular disease that are two times greater than in the general population (Osby et al. 2000, 2001). Although much of psychiatric care for individuals with schizophrenia is focused on suicide prevention, cardiovascular disease remains the single largest cause of death among males and females with schizophrenia. Given this sobering data, it is imperative that those who care for patients with severe mental illness have a working knowledge of the risks associated with cardiovascular disease and the patterns of risk factors seen in this patient population. Recognition and treatment of diabetes mellitus is covered in Chapter 5, “Glucose Intolerance and Diabetes in Patients With Schizophrenia,” but the importance of diabetes relates not only to the adverse effects of hyperglycemia but also to its impact on cardiovascular risk. Diabetes mellitus is considered equivalent to having established coronary heart disease (CHD) for future risk of major cardiovascular events (e.g., myocardial infarction, sudden death) 117

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(Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults 2001). This view of diabetes-related CHD risk is based on indications that patients with established diabetes have the same future myocardial infarction incidence as nondiabetics who have already experienced a myocardial infarction (Haffner et al. 1998). For nondiabetics, the focus for preventing cardiovascular disease remains on modification of the traditional risk factors of hypertension, hyperlipidemia, and smoking. Baseline data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE), sponsored by the National Institute of Mental Health, provide the most timely and complete picture of the risk patterns in patients with chronic schizophrenia residing in the United States (Goff et al. 2005). Among the 1,460 schizophrenia patients assessed at study entry, 10-year CHD risk, calculated using Framingham scores, was significantly elevated compared with age-, gender-, and race- and ethnicity-matched controls from a general population database in both males (9.4% vs. 7.0%) and females (6.3% vs. 4.2%) (P= 0.0001). In particular, schizophrenia patients compared with controls had significantly higher rates of smoking (68% vs. 35%), diabetes (13% vs. 3%), and hypertension (27% vs. 17%) and lower highdensity lipoprotein (HDL) cholesterol levels (43.7 vs. 49.3 mg/dL) (P< 0.001). Moreover, CATIE subjects also had greater prevalence of central adiposity and elevated serum triglycerides, both of which are components of the metabolic syndrome and are associated with insulin resistance and future diabetes risk (McEvoy et al. 2005). The importance of monitoring serum triglyceride values during antipsychotic treatment will become readily apparent, because this is the lipid parameter most greatly affected by offending medications. Another concerning finding from CATIE (covered in Chapter 3, “Medical Outcomes From the CATIE Schizophrenia Study”) was the significant undertreatment of hypertension and dyslipidemia, reinforcing the idea that clinicians must redouble efforts to both monitor and treat the basic cardiovascular risks in patients with schizophrenia (Nasrallah et al. 2006). The induction of hyperlipidemia during antipsychotic therapy thus represents a serious condition, not only because of its inherent impact on cardiovascular risk but also because of its occurrence in a group that already possesses considerable risk (Saari et al. 2004). What has become evident in recent years is that the atypical antipsychotics have a decreased liability for neurological side effects, but certain agents in this class have a marked propensity for adverse metabolic outcomes, especially hyperlipidemia (Meyer and Koro 2004). One is tempted to hypothesize that the widespread use of atypical antipsychotics with metabolic liabilities may be responsible for the widening mortality gap

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between schizophrenia patients and the general population (Saha et al. 2007), but the fact remains that more must be done to prevent morbidity and early mortality from CHD. This chapter is intended to guide the clinician in selecting medications and appropriate monitoring strategies for hyperlipidemia based on the best available data. This discussion is bolstered by the publication of the double-blind, controlled data from phases 1 and 2 of the CATIE schizophrenia trial (Daumit et al. 2008; Lieberman et al. 2005; Meyer et al. 2008a, 2008b; Stroup et al. 2006). The large population under study in CATIE is one of the best sources of prospective information regarding certain compounds, especially perphenazine and quetiapine, for which prospective data were previously sorely lacking. Due to increased interest in improving medical outcomes for patients with severe mental illness (Marder et al. 2004), minimization of iatrogenically induced lipid problems and appropriate monitoring of those at risk are increasingly becoming the standards of care for this patient population. Recognizing which antipsychotics impose the greatest risk for hyperlipidemia and understanding the common dyslipidemia patterns seen during use of these antipsychotics are necessary for providing high-quality care to antipsychotic-treated patients.

Hyperlipidemia and Coronary Heart Disease A complete review of lipid physiology is beyond the scope of this chapter; however, some information is worth noting herein. The major classes of lipoproteins are divided on the basis of their weight under centrifugation (Kwiterovich 2000). The lightest are chylomicrons derived from dietary triglycerides and very-low-density lipoproteins (VLDL) that are endogenously produced triglyceride-rich particles. The next heavier particles are low-density lipoproteins (LDL) and highdensity lipoproteins (HDL). Total cholesterol, as obtained on a lipid panel, reflects the combination of serum concentrations of VLDL (calculated as serum triglyceride levels divided by 5), LDL, and HDL. Normal serum total cholesterol concentration is defined as a fasting level under 200 mg/dL, normal HDL is ≥40 mg/dL, and the ideal serum LDL concentration is determined by cardiovascular risk factors as noted below. The rate-limiting step in cholesterol synthesis is a reaction catalyzed by the enzyme 3-hydroxy-3-methylglutaryl coenzyme A reductase, the target for a class of lipid-lowering agents called statins. The Multiple Risk Factor Intervention Trial clearly established the linear association

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between CHD and serum cholesterol, but further research clarified that risk is more properly associated with abnormalities involving the LDL and HDL cholesterol fractions and separately by serum triglycerides (Stamler et al. 1986). A series of landmark studies published in the mid-1990s demonstrated the significant association between reduction in LDL levels and reduced cardiovascular events and mortality. The Scandinavian Simvastatin Survival Study was a randomized, double-blind, placebocontrolled trial of cholesterol lowering in 4,444 patients with coronary heart disease who were already following a lipid-lowering diet and were followed for a median of 5.4 years (“Randomised Trial of Cholesterol Lowering” 1994). This secondary prevention study found that statin therapy reduced total cholesterol by 28% and LDL by 38%, and led to a 42% reduction in coronary deaths and a 30% decrease in all-cause mortality compared to the placebo cohort. A randomized, double-blind, placebo-controlled secondary prevention trial of pravastatin in 9,014 patients (ages 31–75) with ischemic heart disease followed for 6.1 years on average showed a 24% reduction in nonfatal myocardial infarction or death due to CHD (“Prevention of Cardiovascular Events and Death” 1998). A similar 24% reduction in nonfatal myocardial infarction or death due to CHD was seen in a randomized, double-blind, placebo-controlled secondary prevention trial of pravastatin after myocardial infarction in 4,159 patients who had normal cholesterol levels (Sacks et al. 1996). Moreover, two primary prevention studies of patients without CHD but with either hypercholesterolemia or low HDL levels and average total cholesterol identified profound benefits from statin therapy. The West of Scotland Coronary Prevention Study was a randomized, double-blind, placebo-controlled trial of pravastatin in 6,595 men, ages 45–64 years, with mean total cholesterol of 272 mg/dL and no history of myocardial infarction, followed for a mean of 4.9 years (Shepherd et al. 1995). A 32% reduction in the development of CHD and a 22% reduction in total mortality were found in this trial (Shepherd et al. 1995). The Air Force/Texas Coronary Atherosclerosis Prevention Study was a primary prevention trial of lovastatin versus placebo in men and women with no clinical evidence of cardiovascular disease and average total cholesterol and LDL levels, but low HDL (Downs et al. 1998). Over the 5.2 years of this study, a 37% reduction in risk of major coronary events was seen in the lovastatin group compared to the placebo group. To establish the 2001 National Cholesterol Education Program guidelines, the Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (2001) used the results of these

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and other studies to establish LDL goals based on the number of underlying major cardiovascular risk factors: smoking, hypertension (having blood pressure ≥140/90 mmHg or taking antihypertensive medication), low HDL cholesterol (<40 mg/dL), family history of premature CHD (CHD in male first-degree relative <55 years or female first-degree relative <65 years), and age (men ≥45 years or women ≥55 years). The fasting LDL goal is <160 mg/dL for those with zero or one risk factor, <130 mg/dL for those with two or more risk factors, and <100 mg/dL for those with CHD or CHD-equivalent disorders (e.g., diabetes mellitus). Recent updates to the 2001 guidelines suggest even lower LDL goals (<70 mg/dL) are appropriate for those who are at very high risk by virtue of having diabetes mellitus, multiple metabolic syndrome risk factors, and persistent risk factors such as smoking in conjunction with established CHD or acute coronary syndrome (Stone et al. 2005). Although LDL continues to be the main focus of lipid-lowering therapy due to evidence from multiple large studies, other lipid parameters must be addressed and are secondary targets for therapy. Significant data from the Framingham Heart Study show a 2%–4% increase in risk of CHD-related death for each 1-mg/dL decrease in HDL, with over 30% of deaths occurring in those with normal total cholesterol values (Wilson et al. 1988). Because low HDL is one of the metabolic syndrome criteria, the 2005 National Cholesterol Education Program update suggests targeting low HDL in those who have already met LDL goals but continue to manifest the characteristic dyslipidemia associated with metabolic syndrome (i.e., low HDL, elevated fasting triglycerides) (Stone et al. 2005). Elevated fasting triglycerides occur as a direct result of insulin resistance, because insulin-dependent lipases in fat cells are normally inhibited by insulin. As insulin resistance worsens, inappropriately high levels of lipolysis lead to the release of excess amounts of free fatty acids that are hepatically transformed into triglycerides (Smith 2007). Elevated fasting triglyceride levels thus become a sensitive marker of insulin resistance, and therefore are included as a metabolic syndrome criterion. Moreover, a fasting triglyceride:HDL cholesterol ratio ≥ 3.0 performs better than fasting glucose in predicting insulin resistance among prediabetic individuals (McLaughlin et al. 2003). The sensitivity of the triglyceride:HDL ratio to insulin resistance derives from the fact that increased triglyceride levels interfere with an important regulatory function governing the production of apolipoprotein B100, a core lipoprotein in very-low-density, intermediate-density, and low-density lipoprotein particles (Smith 2007). The overproduction of apolipoprotein B100 results in more of these triglyceride-rich particles,

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with resultant hypertriglyceridemia. In addition, the greater presence of these light triglyceride-rich lipoproteins causes the transfer of triglycerides to HDL at the expense of HDL cholesterol content. After passage through the liver, where triglyceride is cleaved by enzymatic processes, the remaining HDL particle is smaller than normal and more readily cleared in the kidney, resulting in the characteristic low serum HDL levels seen with insulin-resistant states (Smith 2007). The triglyceride:HDL ratio thus reflects the combined effects of low HDL and elevated triglycerides seen in insulin-resistant patients. Although serum triglyceride concentrations are considered a secondary focus of lipid-lowering treatment, evidence from several studies link elevated triglycerides (i.e., ≥200 mg/dL) to increased CHD risk (Cullen 2000; Jeppesen et al. 1998; Rubins 2000), an increased risk that is independent of HDL levels (Jeppesen et al. 1998). Evidence also has been reported that supports monitoring of nonfasting triglycerides, because atherosclerosis may be a postprandial phenomenon in which atherogenic remnant lipoproteins (chylomicrons and VLDL) play a critical role (Eberly et al. 2003). These triglyceride-rich particles are smaller than other lipid components and more readily penetrate arterial intimal cells. Individuals are in a nonfasting state most of the day with respect to serum triglycerides, with triglyceride levels peaking 4 hours after an oral fat load and returning to baseline values only after 8 hours (Nordestgaard et al. 2007). Large population studies indicate a significant linear correlation between nonfasting triglyceride values and directly measured remnant lipoproteins (Nordestgaard et al. 2007). Data from a prospective Copenhagen, Denmark, study (N =13,981, mean follow-up 26 years) solidified the link between nonfasting triglycerides and cardiovascular events by identifying the significant relationship between nonfasting triglyceride levels in men and women and risk of major cardiovascularrelated events, including CHD, myocardial infarction, and mortality (Nordestgaard et al. 2007). Compared with individuals with nonfasting triglyceride levels <88.5 mg/dL, women and men with levels of 177.0– 264.6 mg/dL had adjusted hazard ratios for myocardial infarction of 2.5 and 1.6, respectively. The superiority of nonfasting triglycerides over fasting triglycerides is also seen in prospective data from the Women’s Health Study (N = 26,509, median follow-up 11.4 years) (Bansal et al. 2007). Although no relationship was found between increasing tertiles of fasting triglyceride values and risk of cardiovascular events in fully adjusted models, nonfasting triglyceride tertiles were significantly associated with cardiovascular risk, with triglyceride levels measured 2–4 hours postprandially showing the strongest association. The impor-

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tance of fasting and nonfasting hypertriglyceridemia is of further concern for those who care for schizophrenia patients, given the association between elevated triglycerides and therapy with low-potency phenothiazines and the dibenzodiazepine-derived compounds clozapine, olanzapine, and quetiapine (a dibenzothiazepine).

Hyperlipidemia and Typical Antipsychotics Although typical antipsychotics are used in less than 10% of patients with schizophrenia in the United States, they are commonly available throughout the world and represent an important class of psychotropic medications. Moreover, a review of the lipid effects of typical antipsychotics illustrates an important concept seen in the atypical antipsychotic data: medications with similar modes of therapeutic action can have disparate metabolic profiles. Within a decade after the widespread use of chlorpromazine and other low-potency phenothiazines, several studies emerged examining the metabolic profiles of this class of antipsychotics (Clark and Johnson 1960; Clark et al. 1967; Mefferd et al. 1958). In general, these compounds were found to elevate serum triglycerides and total cholesterol but with greater effects on triglyceride concentrations. Subsequent studies of the phenothiazine chlorpromazine and related compounds (Clark et al. 1970, 1972) confirmed these findings that high serum triglycerides seemed to be the primary significant lipid abnormality, but elevated total cholesterol could also be found. What also emerged from this early literature was the fact that certain D2 antagonists did not exert the same changes on serum lipids as seen with the lower-potency phenothiazines. The lipid neutrality of high-potency typical antipsychotics was seen in the early uncontrolled studies of butyrophenone derivatives published in the mid-1960s (Braun and Paulonis 1967; Clark et al. 1968; Simpson and Cooper 1966; Simpson et al. 1967) and a placebo-controlled trial in 1971 (Serafetinides et al. 1971). Comparative trials of low-potency phenothiazines and butyrophenones (primarily haloperidol) published in the 1970s confirmed the lipid neutrality of high-potency agents, whereas low-potency phenothiazine treatment was associated with hyperlipidemia, primarily in the form of hypertriglyceridemia (Serafetinides et al. 1972; Vaisanen et al. 1979). Surprisingly, only a limited amount of subsequent work has been published in the past two decades covering lipid changes during typical antipsychotic therapy. Table 6–1, which is a summary of studies,

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case reports, and case series related to lipids and antipsychotics that have been published since 1980, demonstrates the paucity of controlled data on typical antipsychotics after 1980. Two papers were published by a Japanese group in 1984 and 1985 that analyzed serum total cholesterol and triglycerides in male chronic schizophrenia inpatients taking phenothiazines or butyrophenones compared with age- and sexmatched controls (Sasaki et al. 1984, 1985). The cohort exposed to phenothiazines had mean serum triglycerides of 163 mg/dL, compared with 104 mg/dL for the butyrophenone group and 127 mg/dL for the control group, with no significant differences in total cholesterol across the three groups. The phenothiazine cohort also had higher serum LDL cholesterol and decreased HDL cholesterol concentrations compared with the other study arms. Cross-sectional studies from Pakistan (Shafique et al. 1988) and a psychiatric hospital in Spain (Martínez et al. 1994) substantiated earlier findings, although specific analysis on the basis of type of neuroleptic prescribed was not performed in the Spanish study. Lastly, the CATIE schizophrenia trial employed a medium-potency phenothiazine, perphenazine, as one of its treatment arms in phase 1, thus providing controlled comparative data versus atypical antipsychotics in a randomized, double-blind study (Lieberman et al. 2005). As shown in Table 6–2, use of perphenazine was associated with modest increases in serum triglycerides and total cholesterol, with a greater effect on triglycerides. The extent of lipid changes related to perphenazine use in neuroleptic-naive patients might actually be greater than seen in CATIE phase 1, because 22% of the CATIE sample at baseline was taking olanzapine. Given olanzapine’s known effects on serum lipids, olanzapine-exposed patients switched to perphenazine in phase 1 would likely have minimal further increases in serum triglycerides. Further analysis of CATIE data at the end of phase 1 (Table 6–3), obtained after approximately 9 months of exposure, revealed that perphenazine exposure was associated with favorable effects on serum HDL in whites (+2.7 mg/dL) in a manner that was significantly different from olanzapine (−1.7 mg/dL); however, perphenazine induced a mean decrease of 1.3 mg/dL in nonwhites, and this was significantly different from that seen for ziprasidone (+4.3 mg/dL) (Meyer et al. 2008a). Whether this represents a specific moderating effect of race and ethnicity on perphenazine’s metabolic effects or merely the results of an unusual cohort remains to be seen. The effect of perphenazine on fasting triglycerides depended on the subject’s baseline triglyceride values—those with low fasting triglycerides experienced a mean increase of 28.7 mg/dL, comparable to most of the other agents studied,

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whereas those with high baseline triglycerides (>148 mg/dL) experienced a mean decrease of 27.5 mg/dL. With the increasing use of atypical antipsychotics throughout the world, these may be the last randomized, controlled data published on the lipid effects of a typical antipsychotic.

Hyperlipidemia and Atypical Antipsychotics Atypical antipsychotics have been designed primarily to mimic the identifiable features of clozapine’s pharmacology: weaker D 2 antagonism than typical antipsychotics, combined with potent serotonin 5-HT2A antagonism (Meyer and Simpson 1997). A recurring theme, related to the metabolic effects of this antipsychotic class, echoes the earlier findings for typical agents, namely that drugs with similar mechanisms of action may have disparate metabolic adverse effects. This analogy is more than superficial, because the structurally related dibenzodiazepine-derived atypical antipsychotics—olanzapine, clozapine, and quetiapine—all appear to have significantly greater effects on serum triglycerides than total cholesterol, much like the low-potency phenothiazines, whereas other atypical antipsychotics—ziprasidone, risperidone, and aripiprazole—have minimal lipid effects, as did the high-potency typical antipsychotics.

Clozapine Through 2002 virtually no randomized, prospective, controlled data had been published on the lipid effects of the atypical antipsychotics, but the early literature is replete with case reports and retrospective studies, primarily focused on clozapine, the only atypical antipsychotic available until 1994. The first reports of hyperlipidemia with atypical antipsychotics were small studies of fluperlapine, a dibenzodiazepinederived compound never marketed. Two trial reports published in the mid-1980s documented elevated triglycerides, in one case as high as 900 mg/dL (Fleischhacker et al. 1986; Müller-Oerlinghausen 1984). Despite clozapine’s use from the 1960s onward, the first case report of hyperlipidemia (presenting as hypertriglyceridemia) occurred in 1994 (Vampini et al. 1994) and was followed in 1995 by a report of four clozapine-treated patients with hypertriglyceridemia whose triglycerides normalized upon switching to risperidone (Ghaeli and Dufresne 1995). The following year (1996), the authors of that case series published

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a chart review comparing serum lipids in patients exposed to clozapine or typical antipsychotics (primarily butyrophenones) for at least 1 year with no prior history of hyperlipidemia or use of lipid-lowering agents (Ghaeli and Dufresne 1996). This retrospective study found serum triglycerides 114 mg/dL higher in the clozapine cohort (P < 0.001) but nearly identical total cholesterol levels (clozapine 217.0± 52.9 mg/dL vs. typical antipsychotics 215.0± 43.2 mg/dL). A 1998 study comparing 30 patients taking clozapine to 30 patients taking typical antipsychotics for at least 1 year also found higher triglycerides in the clozapine group (202.9 ± 131.1 mg/dL) compared with the typical group (134.4 ± 51.9 mg/dL), but again without significant differences in total cholesterol (clozapine 197.1±46.4 mg/dL vs. typical antipsychotics 194.9±51.5 mg/dL) (Spivak et al. 1998). A small prospective study (Dursun et al. 1999) and two subsequent chart reviews of long-term clozapine-treated patients, one with 70 patients (Spivak et al. 1999) and the other with 222 patients (Gaulin et al. 1999), demonstrated that the mean increase in serum triglycerides ranged from 41% to 45%. More recent cross-sectional and short- and long-term prospective clozapine studies have noted the same pattern of marked elevations of serum triglycerides with modest increases in total cholesterol (Atmaca et al. 2003b; Baymiller et al. 2003; Henderson et al. 2000; Leonard et al. 2002; Wirshing et al. 2002) compared with baseline and with typical antipsychotics (Lund et al. 2001). A 1-year prospective study of 50 clozapine-treated patients (Baymiller et al. 2003) found mean increases of 41.7% in serum triglycerides, exactly in the range predicted by prior retrospective data, and only a 7.5% increase in total cholesterol. The authors also noted that no significant changes occurred in HDL and LDL and that triglyceride elevations peaked between days 41 and 120 and then declined, but still remained elevated at the 1-year interval. As part of a 5-year naturalistic study of 82 clozapine-treated patients with schizophrenia, Henderson et al. (2000) found ongoing increases in serum triglycerides (linear coefficient 2.75 mg/dL per month, P=0.04). A subsequent 10-year follow-up study of clozapine-treated patients found that triglycerides had plateaued significantly, with a linear coefficient over that time frame of 0.5 mg/dL/month (P=0.04) (Henderson et al. 2005). In neither study were total cholesterol changes significant. Other cross-sectional, retrospective and other nonprospective clozapine studies are noted in Table 6–1, but the “efficacy” arm of CATIE phase 2 (hereafter referred to as phase 2b) generated prospective randomized data on a sample of 49 schizophrenia patients compared with 50 subjects assigned to other agents (McEvoy et al. 2006). As seen in Table 6–2, the exposure-adjusted mean increases in serum lipids for

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clozapine-treated subjects were greatest for triglycerides and substantially less for total cholesterol. The samples for each of the other phase 2b drug arms are extremely small (<15), so the findings for the other atypical antipsychotics in phase 2b are of limited reliability.

Olanzapine The first published studies of olanzapine-associated hypertriglyceridemia appeared in 1999 and revealed patterns of dyslipidemia similar to those reported for clozapine. A study of nine patients followed for an average of 16 months while taking olanzapine (mean age 41 years, mean olanzapine dose 19 mg/day) showed a mean increase in serum triglycerides of 41%, with no significant changes in total cholesterol levels and a mean weight gain of 10 kg (Sheitman et al. 1999). A subsequent report on 25 inpatients followed prospectively for 12 weeks found a mean fasting triglyceride increase of 37%. Both weight and triglyceride increases were significant (P <0.05), and a significant association was found between weight gain and triglyceride change (P<0.02); however, after controlling for baseline weight, analysis of covariance showed no independent increase in triglycerides (Osser et al. 1999). Subsequent work involving olanzapine illustrates not only its much greater effect on serum triglycerides than on total cholesterol, but also the risk of severe hypertriglyceridemia. Melkersson et al. (2000) followed a group of 14 patients with schizophrenia taking olanzapine for an average of 5 months and noted that 62% had elevated fasting triglycerides (mean 273.45 mg/dL) and 85% exhibited hypercholesterolemia (mean 257.14 mg/dL). Although these lipid changes were comparable to those reported for clozapine, the issue of severe hypertriglyceridemia was noted in Meyer’s (2001) case series of 12 olanzapine and two quetiapine patients with fasting triglyceride levels exceeding 500 mg/dL, including one patient taking olanzapine whose fasting serum triglyceride levels were measured at 7,688 mg/dL, and a subsequent case of olanzapineassociated severe hypertriglyceridemia (triglycerides 5,093 mg/dL) reported by Stoner et al. (2002) in a patient who also developed new-onset type 2 diabetes mellitus. As discussed later in the section “Monitoring Recommendations for Hyperlipidemia During Antipsychotic Therapy,” one concern with serum triglyceride levels of 1,000 mg/dL or greater is the development of acute pancreatitis, and the majority of cases that are associated with atypical antipsychotic treatment are related to olanzapine or clozapine exposure (Koller et al. 2003). The cases of severe hypertriglyceridemia are extreme findings, but the majority of studies published since 2001 have confirmed the greater

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effects of olanzapine on serum lipids, primarily on triglycerides, compared to more lipid-neutral medications such as high-potency typical antipsychotics or risperidone, ziprasidone, and aripiprazole. The earlier comparative literature comprised retrospective, cross-sectional, or small prospective studies, but confirmed the greater effects of olanzapine on serum lipids than other atypical antipsychotic medications (with the exception of clozapine) (Atmaca et al. 2003a, 2003b; Bouchard et al. 2001; Garyfallos et al. 2003; Kinon et al. 2001, 2004; Meyer 2002; Wirshing et al. 2002). Also, two retrospective large database studies were performed using data from a Great Britain General Practice Research Practice Database (Koro et al. 2002) and the state of California MediCal claims system (Lambert et al. 2005). Koro et al.’s (2002) casecontrol study of 18,309 schizophrenia patients, which included 1,268 incident cases of hyperlipidemia, compared typical antipsychotics, risperidone, and olanzapine to no antipsychotic usage, and found that risperidone use was not associated with increased odds of hyperlipidemia compared to typical antipsychotic use or no antipsychotic exposure, whereas olanzapine use was associated with a nearly fivefold increase in the odds of developing hyperlipidemia compared with no antipsychotic exposure and more than a threefold increase compared with typical antipsychotic use. Lambert et al.’s (2005) case-control study of MediCal claims after schizophrenia diagnosis, in patients with antipsychotic monotherapy within 12 weeks prior to hyperlipidemia claim, found greater risk of hyperlipidemia for olanzapine compared to typical antipsychotics or risperidone. Increasing the exposure window to 24 or 52 weeks did not affect the results. A cross-sectional study by Alméras et al. (2004) is noteworthy in that other lipid parameters were studied in addition to triglycerides and total cholesterol. In Quebec, Canada, the researchers examined only male schizophrenia patients treated with olanzapine (n =42) or risperidone (n = 45) for >6 months and compared the results of a comprehensive lipid panel with those from a reference group of nondiabetic males (mean ages: 28.4 risperidone; 31.7 olanzapine; 32.8 controls). The olanzapine-treated cohort had significantly higher serum cholesterol, LDL, triglycerides, cholesterol:HDL ratio, and apolipoprotein B, and significantly lower HDL, smaller LDL peak particle size, and lower apolipoprotein A1. Interestingly, compared to the control group, the olanzapine subjects had no significant differences on total cholesterol, triglycerides, or LDL, but they did have lower HDL levels and a higher cholesterol:HDL ratio. Additionally, the risperidone cohort had lower total cholesterol and LDL levels but lower HDL levels than the reference group.

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Given the modest size of the early prospective literature and the uncontrolled nature of many retrospective studies, questions were raised about the extent to which olanzapine induces greater dyslipidemia than risperidone. Phases 1 and 2a of the CATIE schizophrenia trial provided an answer (Lieberman et al. 2005; Meyer et al. 2008a; Stroup et al. 2006), as shown in Tables 6–2 and 6–3. This large, randomized study demonstrated convincingly that olanzapine is one of the greatest offending agents with respect to its effects on serum lipids, again mostly on serum triglycerides, whereas both risperidone and ziprasidone appear neutral. Phase 2a is likely more reflective of the true extent of olanzapine’s effects, as the CATIE trial design mandated that those who entered that arm of the trial not be exposed to an agent to which they had been randomized in phase 1. Thus, all of the subjects in the olanzapine arm of phase 2a were new starts to that medication. This fact explains why the triglyceride increase in phase 2a olanzapine subjects was 94.1 mg/dL, compared with only a 40.5-mg/dL increase seen in the phase 1 olanzapine cohort, 22% of whom were taking olanzapine at study baseline. The analysis of nonfasting triglycerides also revealed the greater deleterious impact of olanzapine compared with other agents, particularly when nonswitchers were removed from the analysis (Meyer et al. 2008b). The differential impact of olanzapine compared with other agents can also be seen in switch studies (Casey et al. 2003; Meyer et al. 2005; Spurling et al. 2007; Su et al. 2005; Weiden et al. 2003, 2007). Institutionalized populations may experience less adverse metabolic effects, as seen in a switch study of developmentally disabled adults (McKee et al. 2005) and two studies of olanzapine in elderly inpatient populations, one including patients with schizophrenia or schizoaffective disorder (Barak and Aizenberg 2003) and the other including patients with dementia of the Alzheimer type with behavioral disturbances or psychosis (De Deyn et al. 2004). For the latter two studies in particular, what is not known is whether it is subject age or the fact of being confined with a fixed dietary regimen that mitigates the development of dyslipidemia.

Quetiapine Quetiapine and zotepine are structurally related to the other dibenzodiazepine-derived antipsychotics clozapine and olanzapine, but limited information has been published regarding their metabolic effects. The extent of available information was so sparse that the American Diabetes Association et al.’s (2004) consensus paper on metabolic effects

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of atypical antipsychotics was unclear whether quetiapine could be differentiated from risperidone in its effects on serum lipids. Compared with clozapine and olanzapine, quetiapine generally has a lower risk of causing significant weight gain (Lieberman et al. 2005; Wetterling 2001). Nonetheless, the available data suggest that quetiapine shares the propensity with other benzodiazepine-derived atypical antipsychotics to elevate serum triglyceride levels, as illustrated by case reports by Domon and Cargile (2002) and Meyer (2001), two 6-week prospective comparative studies by Atmaca et al. (2003a, 2003b), and an 8-week study by Shaw et al. (2001). As with other dibenzodiazepine-derived atypical antipsychotics, there were lesser effects on total cholesterol than on triglycerides (Shaw et al. 2001). The extent of the lipid effects was best seen in the CATIE trials (Lieberman et al. 2005; Meyer et al. 2008a, 2008b; Stroup et al. 2006), especially phase 2a, in which quetiapine’s nearly 40-mg/dL elevation in serum triglycerides was second only to that of olanzapine and more than that for risperidone or ziprasidone, despite weight gain only marginally greater than for risperidone. Analysis of 3-month changes in nonfasting lipids during CATIE phase 1 also found that quetiapine was associated with a mean increase (+59.8 mg/dL) that was nearly identical to that of olanzapine (+61.5 mg/dL) when nonswitchers were removed from the analysis (Meyer et al. 2008b). Zotepine is associated with weight gain similar to that experienced with olanzapine and clozapine (Wetterling 2001), but the sum total of the published literature on lipid changes during zotepine therapy is one case report in which serum triglycerides peaked at 1,247 mg/dL and normalized upon switch to a high-potency typical agent (Wetterling 2002).

Nonbenzodiazepine Agents: Risperidone, Ziprasidone, and Aripiprazole The limited effects of the nonbenzodiazepine agents—risperidone, ziprasidone, and aripiprazole—on serum lipids has been demonstrated in large prospective trials, because the pharmaceutical industry routinely includes multiple lipid measures as part of study protocols. The more benign effects of risperidone were largely known from comparative trials versus olanzapine, as confirmed by the results from CATIE phases 1 and 2a (Lieberman et al. 2005; Meyer et al. 2008a, 2008b; Stroup et al. 2006). Although doubts about the differential effects of quetiapine and risperidone on serum lipids were expressed several years ago in the consensus paper by the American Diabetes Association et al. (2004),

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when quetiapine is prescribed in full therapeutic doses for schizophrenia, it appears to elevate serum triglycerides in a manner not typically seen with risperidone. Ziprasidone appears to have even less adverse effect on serum lipids than risperidone, as evidenced by the statistically significant improvement in serum triglycerides and total cholesterol over 6 weeks when patients were switched to ziprasidone from risperidone (Kingsbury et al. 2001). The lipid neutrality of ziprasidone has been subsequently confirmed in a retrospective chart review (Brown and Estoup 2005) and in multiple prospective trials of short duration (6 weeks) (Simpson et al. 2004; Weiden et al. 2003) and longer duration (≥26 weeks) (Breier et al. 2005; Cohen et al. 2004; Simpson et al. 2005; Weiden et al. 2007), including CATIE phases 1 and 2a (Lieberman et al. 2005; Meyer et al. 2008a, 2008b; Stroup et al. 2006) in which the net impact of ziprasidone treatment was to lower serum lipid levels. Early clinical trials data suggested that aripiprazole also had nominal effects on serum lipids (Goodnick and Jerry 2002), a finding confirmed in large prospective trials. In a 26-week trial versus olanzapine (McQuade et al. 2004), the mean change in fasting triglycerides was +79.4 mg/dL with olanzapine but only +6.5 mg/dL with aripiprazole (P< 0.05), whereas HDL decreased by 3.39 mg/dL with olanzapine and increased 3.61 mg/dL with aripiprazole (P< 0.05). Changes in serum LDL for the drug cohorts were not significantly different, but the incidence of new dyslipidemias was significantly greater for olanzapine on the basis of the proportion of new subjects with endpoint serum LDL >130 mg/dL (38% olanzapine vs. 19% aripiprazole, P< 0.05). Recent switch studies confirm that patients switched to aripiprazole from metabolically more offending medications experience improvements in serum lipids, again primarily triglycerides, but with measurable changes for other parameters (Spurling et al. 2007).

Reference

Lipid changes during antipsychotic therapy: 1984–2008 Study design

MüllerMulticenter fluperlapine trial in Oerlinghausen 43 schizophrenia and depression 1984 patients

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TABLE 6–1.

Findings In 16 of 28 patients, TG increased significantly and serum TC increased notably.

Chart review of chronic phenothiaPatients chronically treated with phenothiazines (chlorpromazine, zine users (mean exposure 8 years); levomepromazine, perphenazine) had significantly higher HDL 10-week prospective data in 8 new (P <0.001) and higher TG (P <0.05) than normal controls. HDL decreased 24% within 1 week of new phenothiazine exposure, with no phenothiazine-treated patients significant changes in TC and TG levels after 10 weeks.

Sasaki et al. 1985

Chart review of males with chronic schizophrenia; excluded patients with DM or taking lipid-lowering medication 17 phenothiazine 14 haloperidol 14 healthy controls

After mean 8 years of antipsychotic exposure, no effect of butyrophenones on lipids, but significantly elevated mean fasting TG levels for the phenothiazine group (163 mg/dL) compared to the butyrophenone group (104 mg/dL) and controls (127 mg/dL). No significant differences in TC, LDL, or HDL values across the three groups.

Fleischhacker et al. 1986

Double-blind, prospective 6-week study 6 haloperidol 6 fluperlapine

No significant differences in mean HDL or TC between groups or compared to baseline by day 28. One fluperlapine subject developed serum TG level of 900 mg/dL on day 7 and required treatment on day 28.

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Sasaki et al. 1984

TABLE 6–1.

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Shafique et al. 1988

Chart review of males with chronic schizophrenia treated for 6–12 months 35 phenothiazine 30 butyrophenone 22 combined drug classes

Significant elevations of TC, VLDL, and LDL levels in patients taking phenothiazines and LDL in patients taking butyrophenone. VLDL and LDL levels significantly higher and HDL levels lower in patients taking combined therapy.

Martínez et al. 1994

Chart review of 311 chronically Neuroleptic administration was associated with changes in HDL and TG hospitalized schizophrenia patients in males but not in females. 225 neuroleptic exposed (mostly haloperidol, thioridazine, or fluphenazine) for prior 2 years 86 no psychotropic medications

Vampini et al. 1994

Case report: 1 taking clozapine 400 mg/day

Increased TG levels after 15 months.

Ghaeli and Dufresne 1995

Case series: 4 clozapine-treated patients (doses 600–900 mg/day) switched to risperidone

Increased serum TG levels in patients taking clozapine decreased upon switching to risperidone, and increased upon clozapine rechallenge.

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Reference

133

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Ghaeli and Dufresne 1996

Chart review of 67 schizophrenia patients 39 clozapine 21 high-potency typical antipsychotics 2 medium-potency typical antipsychotics 5 low-potency typical antipsychotics

Mean TG significantly higher in clozapine vs. typical groups (264.6 mg/dL vs. 149.8 mg/dL, P<0.001). Difference was not explained by concomitant illness or medication, age, or gender. No significant difference in TC.

Spivak et al. 1998

Chart review of schizophrenia patients 30 clozapine (mean 295.0±165 mg/day) 30 typical antipsychotics (mean 348.9±298.8 mg/day in CPZ equivalents)

Mean TG significantly higher in clozapine vs. typical group after 1 year of treatment (202.9 mg/dL vs. 134.4 mg/dL, P<0.01). No significant difference in serum TC.

Dursun et al. 1999

Prospective 12-week study 8 clozapine (mean 352±73 mg/day)

Small increase in TG levels (11%) but no significant changes in other lipid levels after 12 weeks.

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Reference

134

TABLE 6–1.

TABLE 6–1.

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Findings

Gaulin et al. 1999

Chart review of schizophrenia patients 222 treated with clozapine or haloperidol

After a mean treatment period of 590 days for clozapine and 455 days for haloperidol, 45% increase in serum TG in clozapine-treated patients (P<0.01) and insignificant decrease in serum TG in haloperidol-treated patients.

Osser et al. 1999

Prospective study in schizophrenia patients 25 olanzapine (mean 13.8±4.4 mg/day)

37% (60 mg/dL) increase in fasting TG from baseline (P<0.05). Fasting TC did not increase.

Sheitman et al. 1999

Prospective study in schizophrenia patients 9 olanzapine (mean 19 mg/day)

After 16 months, mean increase in serum TG was 70 mg/dL (5 patients had >50% increase in TG). No significant change in TC, HDL, or LDL.

Spivak et al. 1999

Chart review of schizophrenia patients 70 clozapine (mean 332.9±168.1 mg/day) 30 typical antipsychotics (mean 347.3±247.3 mg/day in CPZ equivalents)

Mean TG increased in the clozapine group and decreased in the typical antipsychotic group after 6 months of treatment (P<0.005).

Henderson et al. 2000

5-year naturalistic study 82 clozapine

Significant changes in serum TG (P =0.04) (linear coefficient=2.75 mg/dL per month, SE=1.28).

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Effects of Antipsychotics on Serum Lipids

Reference

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Melkersson et al. 2000

Prospective cohort study 14 olanzapine (median 12.5 mg/day)

62% prevalence of hypertriglyceridemia (mean 273.45 mg/dL) and 85% prevalence of hypercholesterolemia (mean 257.14 mg/dL) after a median exposure of 5 months (range 2.4–16.8 months).

Wu et al. 2000

Case report: 1 Chinese male, age 25, taking clozapine

Dose-dependent increases in fasting serum TG and glucose.

Baptista et al. 2001

Cross-sectional cohort study of women matched for age, BMI, and day of menses 26 typical antipsychotics (>6 consecutive months of treatment) 26 controls

Antipsychotic-treated subjects had a trend for lower HDL and increased insulin resistance.

Bouchard et al. 2001

Retrospective study 22 olanzapine (mean 12.8±4.4 mg/day) 22 risperidone (mean 2.8±1.8 mg/day)

After mean exposure of 17.9 months (olanzapine) and 17.4 months (risperidone), olanzapine patients compared to risperidone patients had significantly higher TG (185 mg/dL vs. 115 mg/dL, P<0.01), significantly higher VLDL (0.9 mol/L vs. 0.5 mol/L, P<0.03), and a trend for a higher cholesterol/HDL ratio (5.3 vs. 4.3, P=0.06) and lower HDL (P=0.08). No significant differences in TC, fasting glucose, or insulin.

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Reference

136

TABLE 6–1.

TABLE 6–1.

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Findings

Domon and Webber 2001

Case report: After 3 months, weight 91 kg, fasting glucose 90 mg/dL, fasting TG 1 African American male, age 15, 155 mg/dL, fasting TC 131 mg/dL; 5 months later, weight peaked taking olanzapine 20 mg/day at 108 kg, then declined with onset of type 2 DM. Maximum TG 298 mg/dL with olanzapine. Both DM and hyperlipidemia resolved over 8 weeks after olanzapine was discontinued.

Kingsbury et al. 2001

Prospective 6-week switch study 37 ziprasidone (mean 124.3 mg/day) Prior meds: 15 from olanzapine 12 from risperidone 10 from typical antipsychotics

Significant decreases in serum TC (−17.57 mg/dL, P <0.001) and serum TG (−62.38 mg/dL, P=0.018). Change in TG correlated with weight change (r=0.409, P=0.018, r2 =0.167). Change in TC did not correlate with weight change.

Kinon et al. 2001

Retrospective cohort 573 olanzapine (5–20 mg/day) 103 haloperidol (5–20 mg/day)

Median nonfasting endpoint serum TC was significantly higher for olanzapine-treated than for haloperidol-treated patients (205.7 mg/dL vs. 189.9 mg/dL, P=0.002).

Lund et al. 2001

Retrospective cohort study 2,461 typical antipsychotics 552 clozapine

Clozapine significantly increased relative risk of hyperlipidemia in patients ages 20–34 years (RR 2.4; 95% CI 1.1–5.2) but not in older patients.

Meyer 2001

Case series 12 olanzapine (5–20 mg/day) 2 quetiapine (200–250 mg/day)

Hypertriglyceridemia reported up to 7,668 mg/dL with olanzapine and 1,932 mg/dL with quetiapine. Time to peak TG ranged from 1 to 23.5 months.

137

Study design

Effects of Antipsychotics on Serum Lipids

Reference

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Nguyen and Murphy 2001

Case report: 1 boy, age 10, taking olanzapine 5 mg/day for ADHD

Over 3 months, experienced 9-kg weight gain with resulting TC of 193 mg/dL and TG of 183 mg/dL. 5 weeks after olanzapine was discontinued, TC 151 mg/dL, TG 61 mg/dL, and over 9-kg weight loss.

Shaw et al. 2001

8-week open trial in adolescents with TC remained unchanged. psychosis 15 quetiapine (300–800 mg/day)

Domon and Cargile 2002

Case report: 1 African American female, age 17, taking quetiapine 600 mg/day and metformin 1,000 mg po bid for type 2 DM

Goodnick and Jerry 2002

Meta-analysis of trial data of 1,919 Meta-analysis of short-term trial data showed that increases in TC patients treated with one of the following aripiprazole administration were lower than for haloperidol, following: aripiprazole, olanzapine, risperidone, or placebo. A 26-week trial comparing aripiprazole to risperidone, haloperidol, or placebo olanzapine found significant differences after 4 weeks: olanzapine increased TC, whereas aripiprazole decreased TC. Data from a 1-year study found that aripiprazole produced less of an increase in TC than haloperidol.

On admission, TC 235 mg/dL, TG 456 mg/dL. Quetiapine discontinued with complete resolution of DM and hyperlipidemia. At 6 weeks postquetiapine (and 4 weeks without metformin), TC 226 mg/dL and TG 163 mg/dL.

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TABLE 6–1.

TABLE 6–1.

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Koro et al. 2002

Case-control database study of 18,309 Olanzapine use was associated with nearly a fivefold increase in the odds schizophrenia patients, with 1,268 of developing hyperlipidemia compared with no antipsychotic incident cases of hyperlipidemia; exposure and more than a threefold increase compared with those typical or atypical antipsychotic use receiving typical antipsychotics. analyzed

Leonard et al. 2002

Chart review, 13 males, 8 females 21 clozapine (mean 485 mg/day)

Martin and L’Ecuyer 2002

Retrospective chart review of child After mean exposure of 4.9±1.0 months, no significant changes in serum and adolescent inpatients, mean age TG or TC levels were seen in the group as a whole. 12.8 years 22 risperidone (mean 2.7±2.2 mg/day)

Meyer 2002

Retrospective chart review of 1-year exposure 47 risperidone 47 olanzapine

11 patients (52%) had hypertriglyceridemia, 3 (14%) had hypercholesterolemia. Mean TC 193±46 mg/dL (range 131–309 mg/dL), mean TG 196±142 mg/dL (range 39–665 mg/dL).

After 52 weeks, TC increased 24 mg/dL with olanzapine vs. 7 mg/dL with risperidone (P=0.029), and fasting TG increased by 88 mg/dL with olanzapine vs. 30 mg/dL with risperidone (P=0.042). In the nongeriatric cohort, TC increased 31 mg/dL with olanzapine vs. 7 mg/dL with risperidone (P =0.004), and fasting TG increased 105 mg/dL with olanzapine vs. 32 mg/dL with risperidone (P=0.037).

Effects of Antipsychotics on Serum Lipids

Reference

139

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Stoner et al. 2002

Case report: Baseline lipid panel: TC 227 mg/dL, TG 134 mg/dL, HDL 38 mg/dL. 1 African American male, age 42, After 8 weeks of olanzapine serum: TG 5,093 mg/dL, TC 375 mg/dL, with treated hyperlipidemia with evidence of new-onset type 2 DM (fasting glucose 395 mg/dL, taking olanzapine 15 mg/day hemoglobin A1c 11.9%).

Virkkunen et al. 2002

Case report: 1 male, age 48, taking olanzapine 10–15 mg/day for 1 month

6-kg weight gain; 3.6% decrease in basal and 11.4% decrease in 3-hour energy expenditure; decrease in HDL; increase in TG and LDL. No change in insulin sensitivity using euglycemic hyperinsulinemic clamp.

Wetterling 2002

Case report: 1 patient taking zotepine

Maximum TG of 1,247 mg/dL, which normalized upon switch to highpotency typical antipsychotic.

Wirshing et al. 2002

Chart review 39 clozapine 42 olanzapine 49 risperidone 13 quetiapine 41 haloperidol 41 fluphenazine

Clozapine was associated with greatest increase in TC, whereas risperidone and fluphenazine were associated with decreases. Clozapine and olanzapine were associated with greatest increase in TG levels.

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TABLE 6–1.

TABLE 6–1.

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Atmaca et al. 2003a

6-week prospective schizophrenia study 14 quetiapine (mean 535.7 mg/day) 14 olanzapine (mean 15.7 mg/day) 14 risperidone (mean 6.7 mg/day) 14 clozapine (mean 207.1 mg/day) 11 controls (no psychotropic medication)

Compared to controls, significant increases in fasting TG seen for olanzapine (+31.23 mg/dL, P <0.001), clozapine (+36.28 mg/dL, P<0.001), and quetiapine (+11.64 mg/dL, P<0.05), but not risperidone (+3.87 mg/dL, P<0.76).

Atmaca et al. 2003b

6-week prospective schizophrenia study 15 haloperidol 15 olanzapine 15 quetiapine

Serum TG increases were much greater for olanzapine compared to quetiapine or haloperidol, and for quetiapine compared to haloperidol.

Effects of Antipsychotics on Serum Lipids

Reference

141

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Barak and Aizenberg 2003

Prospective 6-month study of elderly inpatients (mean age 71.7) with schizophrenia or schizoaffective disorder (16 female, 5 male) 21 olanzapine (mean 12.9 mg/day)

After a mean duration of 289 days of olanzapine treatment, no significant change from baseline serum lipid levels was found for TG or TC.

Baymiller et al. 2003

Prospective 1-year open-label study 50 clozapine (mean 454±109 mg/day)

From baseline, 54.7 mg/dL (41.7%) increase in serum TG (P=0.001) and 14.4 mg/dL (7.5%) increase in TC (P<0.001). No significant changes in HDL or LDL. Serum TG peaked between days 41 and 120 and then declined, but still remained elevated. Use of propranolol exacerbated increases in TC and TG.

Garyfallos et al. 2003

8-week prospective randomized study of acute schizophrenia spectrum inpatients 25 olanzapine (mean 18.0 mg/day) 25 risperidone (mean 7.7 mg/day)

Compared to baseline, significant increases in fasting TG (+43.5 mg/dL, P<0.001) for olanzapine but not risperidone (+7.5 mg/dL, P>0.05). Nonsignificant increases in TC: +10.2 mg/dL for olanzapine, +0.7 mg/dL for risperidone. Between-group difference in change was significant for both TG and cholesterol parameters (P<0.001 for each).

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142

TABLE 6–1.

TABLE 6–1. Reference

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Weiden et al. 2003

6-week ziprasidone switch study; all labs were nonfasting; mean ziprasidone dose 91 mg Prior medications: 104 from olanzapine 58 from risperidone 108 from typical antipsychotics

Median changes from baseline for TG: −50 mg/dL in those switched from olanzapine (P<0.0001) and −29 mg/dL in those switched from risperidone (P <0.01). Median changes in cholesterol: −17 mg/dL (P<0.0001) in those switched from olanzapine and −12 mg/dL (P<0.005) for those switched from risperidone. Cholesterol levels declined in 76% of patients switched from olanzapine and 72% switched from risperidone. Reductions in lipid levels in patients switched from typical antipsychotics were nonsignificant.

Effects of Antipsychotics on Serum Lipids

Melkersson and Cross-sectional study of lipids and TG elevated in 44% of clozapine group and 56% of olanzapine group. Dahl 2003 insulin parameters in long-term Cholesterol elevated in 39% of clozapine group and 63% of olanzapine treatment (mean 8.2 years for group. High LDL in 17% of clozapine- and 38% of olanzapine-treated clozapine, 1.2 years for olanzapine) patients. Normal HDL in all but one of each drug group. No significant 18 clozapine between-group differences in hyperlipidemia rates or median lipid (median 400 mg/day) levels. 16 olanzapine (median 10 mg/day)

143

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Alméras et al. 2004

Cross-sectional study of male Risperidone subjects had significantly lower serum cholesterol, LDL, TG, schizophrenia patients in Canada; all cholesterol:HDL ratio, and apolipoprotein B. Risperidone cohort had subjects taking drug >6 months; significantly higher HDL, larger LDL peak particle size, and greater results compared with reference apolipoprotein A1. Compared to reference group, no differences for group of nondiabetic males (mean olanzapine group for cholesterol, TG, or LDL, but lower HDL and ages: 28.4 risperidone, 31.7 higher cholesterol:HDL ratio. Risperidone cohort had lower cholesterol olanzapine, 32.8 controls) and LDL but also lower HDL than the reference group. 42 olanzapine (mean 12.4 mg/day) 45 risperidone (mean 2.9 mg/day)

Cohen et al. 2004

Chart review of 10 autistic adults (mean Data on lipids available for only 5 subjects; 4 of 5 had a decrease in TC, age 43) switched to ziprasidone and but mean decrease (−2.6 mg/dL) was not significant; 3 of 5 had a followed >6 months decrease in serum TG, but mean decrease (−21.8 mg/dL) was not 10 ziprasidone significant. (mean 128 mg/day)

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144

TABLE 6–1.

TABLE 6–1.

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

De Deyn et al. 2004

Randomized, fixed-dose, 10-week Serum values not provided, but report states that cholesterol and TG trial of olanzapine (1.0, 2.5, 5.0, 7.5 levels were not significantly different among or between treatment mg/day) vs. placebo for psychosis/ groups. behavioral disturbance in patients with Alzheimer’s disease; mean age 76.6 years 520 olanzapine 129 placebo

Kinon et al. 2004

Randomized, prospective 4-month study comparing those who switched to olanzapine with those who continued prior medication 27 olanzapine 27 risperidone/typical antipsychotics

After 4 months, no significant within-group change in mean TC (−4.7 mg/dL, P=0.69) or TG (−6.6 mg/dL, P=0.81) in patients switched to olanzapine, or in those who continued taking typical antipsychotics/ risperidone (TC: −0.6 mg/dL, P =0.69; TG: +13.6 mg/dL, P=0.28). Elevations in lipids noted prior to month 4 in olanzapine cohort, but declined over time.

Effects of Antipsychotics on Serum Lipids

Reference

145

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

McQuade et al. 2004

26-week double-blind, randomized trial in acutely relapsed schizophrenia patients 156 aripiprazole (mean 25.1 mg/day) 161 olanzapine (mean 16.5 mg/day)

At week 26, mean change in fasting TG +79.4 mg/dL for olanzapine, +6.5 mg/dL for aripiprazole (P <0.05); HDL −3.39 mg/dL for olanzapine, +3.61 mg/dL for aripiprazole (P<0.05). Changes in TC and LDL favored aripiprazole but were not significant: TC +16.3 mg/dL olanzapine, −1.13 mg/dL aripiprazole; LDL +2.27 mg/ dL olanzapine, −3.86 mg/dL aripiprazole. Incidence of new dyslipidemias was significantly greater for olanzapine on the basis of elevated TC (>200 mg/dL: 47% olanzapine vs. 17% aripiprazole), LDL (>130 mg/dL: 38% olanzapine vs. 19% aripiprazole), and TG (>150 mg/dL: 50% olanzapine vs. 18% aripiprazole) (P<0.05 for each).

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146

TABLE 6–1.

TABLE 6–1.

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Simpson et al. 2004

6-week double-blind, randomized trial in patients with acute schizophrenia/schizoaffective disorder 136 ziprasidone (mean 129.9 mg/day) 133 olanzapine (mean 11.3 mg/day)

Endpoint change in fasting TC was significant for olanzapine (median +19.5 mg/dL, P<0.0001) vs. ziprasidone (median −1.0 mg/dL, P =0.48 from baseline) (P<0.0001 between groups). TG increased median +26 mg/dL for olanzapine (P =0.0003), and decreased a median of 2 mg/dL for ziprasidone group (P =0.77); between-group difference was significant (P<0.003). LDL increased by a median of 13 mg/dL for olanzapine (P<0.0001) and decreased 1 mg/dL for ziprasidone group (P=0.78); between-group difference was significant (P <0.0004). Apolipoprotein B increased 9.0 mg/dL for olanzapine (P <0.0001) and decreased 3.0 mg/dL for ziprasidone (P=0.17); between-group difference was significant (P<0.0001). No impact or between-group differences in HDL, apolipoprotein A1, or lipoprotein (a) levels.

Waage et al. 2004

Case report: 1 male, age 42, with chronic paranoid psychosis and olanzapine-induced pancreatitis

Baseline TC 189 mg/dL. After 7 months, TC 282 mg/dL. At time of admission with pancreatitis, 19 months after starting olanzapine, TC 552 mg/dL and TG 2,044 mg/dL.

Effects of Antipsychotics on Serum Lipids

Reference

147

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Ball et al. 2005

Case report: 1 male, age 42, with schizoaffective disorder and clozapine-induced hypercholesterolemia and hypertriglyceridemia that resolved after switch to aripiprazole

Peak lipid levels: TC 477 mg/dL and TG 4,758 mg/dL. Patient hospitalized subsequently due to noncompliance, with lipid levels at time of admission: cholesterol 213 mg/dL, TG 298 mg/dL, and LDL 146 mg/dL while taking simvastatin. Trial of aripiprazole, up to 45 mg/day for 5 weeks, with lipids (off of simvastatin): cholesterol 163 mg/dL, TG 145 mg/dL, LDL 100 mg/dL.

Breier et al. 2005

28-week randomized, double-blind All between-group lipid changes significantly favored ziprasidone. study in patients with schizophrenia Endpoint change in fasting TC for olanzapine (+3.09 mg/dL, P =0.07) 277 olanzapine vs. ziprasidone (−12.74 mg/dL, P=0.08) (P<0.0001 between groups). (mean 15.27 mg/day) TG increased +34.52 mg/dL for olanzapine (P=0.09) and decreased 271 ziprasidone 21.24 mg/dL for ziprasidone (P=0.11); between-group difference was (mean 115.96 mg/day) significant (P<0.001). LDL increased by a median of 0.77 mg/dL for olanzapine (P=0.06) and decreased 10.42 mg/dL for ziprasidone (P=0.07); between-group difference was significant (P <0.001). HDL decreased 2.32 mg/dL for olanzapine (P=0.02) and increased 0.77 mg/dL for ziprasidone (P=0.02); between-group difference was significant (P=0.001).

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TABLE 6–1.

TABLE 6–1.

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Brown and Estoup 2005

Chart review study from Veterans Administration medical center 88 ziprasidone 103 olanzapine

Olanzapine associated with significant increases in TC (+16 mg/dL, P=0.01) and TG (+61 mg/dL, P=0.05), but not HDL or LDL. Ziprasidone associated with significant decrease in TC (−15 mg/dL, P=0.01) and LDL (−18 mg/dL, P=0.001), and increase in HDL (+3 mg/dL, P =0.05). Among those who switched between agents, significant differences were found for TC (P=0.05) and LDL (P =0.01).

Graham et al. 2005

Prospective study of resting energy expenditure and metabolic outcomes in 9 adults started on olanzapine and followed 12 weeks 9 olanzapine (range 2.5–20 mg/day)

Median changes were −7 mg/dL for HDL (P =0.19), +1 mg/dL for LDL (P=0.47), +59 mg/dL for TG (P=0.04). The TG change was a 62.8% increase from baseline.

Henderson et al. 2005

Review of data on 96 subjects treated with clozapine and followed for 10 years

A significant linear increase in TG levels was found for the duration of the follow-up (0.5 mg/dL/month, P =0.04) but not for TC (P=0.13). Elevations in TG and TC were associated with new-onset DM but not cardiovascular mortality.

Effects of Antipsychotics on Serum Lipids

Reference

149

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Lambert et al. 2005

Case-control study of MediCal claims For the 12-week exposure window, olanzapine (OR 1.20, 95% after schizophrenia diagnosis and CI 1.08–1.33) was significantly associated with hyperlipidemia risk exposure to only one antipsychotic compared with typical agents, but not compared with exposure to within 12 weeks prior to clozapine, risperidone, or quetiapine. The odds ratio for olanzapine was hyperlipidemia claim; cases were greater than for risperidone (P=0.002). Increasing the exposure window age- and gender-matched to patients to 24 or 52 weeks did not affect the results, although clozapine’s with schizophrenia who did not association did become significant at 24 weeks (OR 1.22, develop hyperlipidemia 95% CI 1.03–1.45).

Lieberman et al. 2005

Phase 1 of CATIE schizophrenia trial (See Tables 6–2 and 6–3)

McKee et al. 2005

Chart review of 41 adults with At endpoint, no significant changes in serum TC, LDL, or TG. developmental delays switched from typical antipsychotics to olanzapine or risperidone (and some then to olanzapine) and followed up to 2 years. At endpoint: 33 olanzapine 8 risperidone

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150

TABLE 6–1.

TABLE 6–1.

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

Meyer et al. 2005

20-week switch study in overweight At endpoint, nonsignificant decreases in serum TG (−13.1 mg/dL) and or obese olanzapine-treated patients HDL (−1.6 mg/dL). Overall, the prevalence of metabolic syndrome with schizophrenia following decreased from 53.5% to 36.6% over 20 weeks (P <0.005). metabolic syndrome parameters 71 risperidone

Simpson et al. 2005

6-month continuation of prior 6-week There were significant within-group median increases from baseline in randomized, double-blind study of TC (+13.0 mg/dL, P=0.03) and LDL (+17.0 mg/dL, P =0.04) with olanzapine vs. ziprasidone olanzapine, and nonsignificant changes in TC (−1.0 mg/dL, P =0.98), 55 ziprasidone and LDL (9.0 mg/dL, P=0.29) with ziprasidone. (mean 135.2 mg/day) 71 olanzapine (mean 12.6 mg/day)

Su et al. 2005

Crossover switch study in 15 After switch to olanzapine, nonsignificant changes in LDL (−1.0 mg/dL), schizophrenia patients followed for HDL (+0.4 mg/dL), and TC (+20.5 mg/dL), but significant increase 3 months after switch in TG (+84.3 mg/dL, P<0.05). In those switched to risperidone, 7 risperidone → olanzapine nonsignificant changes in LDL (+5.9 mg/dL), HDL (+6.8 mg/dL), 8 olanzapine → risperidone and TC (−8.6 mg/dL), but significant decrease in TG (−86.0 mg/dL, P<0.05).

Effects of Antipsychotics on Serum Lipids

Reference

151

Lipid changes during antipsychotic therapy: 1984–2008 (continued) Study design

Findings

McEvoy et al. 2006

Phase 2 nonresponse arm of CATIE schizophrenia trial

(See Table 6–2, Phase 2b results)

Stroup et al. 2006

Phase 2 intolerability arm of CATIE schizophrenia trial

(See Table 6–2, Phase 2a results)

Meyer et al. 2008a

End of CATIE phase 1 detailed analysis

(See Table 6–3)

Meyer et al. 2008b

CATIE phase 1 nonfasting triglycerides analysis

Mean 3-month changes: quetiapine (+54.7 mg/dL), olanzapine (+23.4 mg/dL), ziprasidone (+0.0 mg/dL), risperidone (−18.4 mg/dL), perphenazine (−1.3 mg/dL).

Note. ADHD= attention-deficit/hyperactivity disorder; BMI= body mass index; CI=confidence interval; CPZ=chlorpromazine; DM=diabetes mellitus; HDL= high-density lipoprotein; LDL= low-density lipoprotein; OR=odds ratio; RR=relative risk; SE=standard error of measurement; TC =total cholesterol; TG = triglycerides; VLDL= very-low-density lipoprotein.

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TABLE 6–1.

TABLE 6–2. Exposure-adjusted lipid changes for CATIE schizophrenia trial phases 1, 2a, and 2b (mean± SE) Olanzapine

Perphenazine

Phase 1 (N=1,460)

—

9.4 ±2.4

1.5 ±2.7

Phase 2a (n= 444)

—

17.5 ±5.2

5.9 ±4.7

Phase 1 (N=1,460) Phase 2a (n= 444)

Quetiapine

Risperidone

Ziprasidone

6.6± 2.4

−1.3± 2.4

−8.2± 3.2

—

6.5± 5.3

−3.1± 5.2

−10.7± 5.1

1.0 ±7.1

—

−11.0± 8.1

7.4± 8.7

—

—

40.5 ±8.9

9.2± 10.1

21.2± 9.6

−2.4± 9.1

−16.5± 12.2

—

94.1 ±21.8

—

39.3± 22.1

−5.2± 21.6

−3.5± 20.9

43.8 ±21.2

−5.3 ±32.0

—

7.1± 36.2

30.0± 39.0

Cholesterol (mg/dL)

a

Phase 2b (n=99) Triglycerides (mg/dL)

a

Phase 2b (n=99) a

Blood chemistry change from phase 2 baseline to average of two largest values.

—

Effects of Antipsychotics on Serum Lipids

Clozapine

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TABLE 6–3. Mean changes in high-density lipoprotein (HDL) and fasting triglycerides at end of CATIE phase 1 HDL, mg/dLa Whites

Nonwhites

Fasting triglycerides, mg/dLb Below median Above median

Mean exposure (months)

9.2

9.9

9.9

9.8

Olanzapine

−1.7 (0.6) (n=171)

−0.9 (0.9) (n=115)

49.0 (10.8) (n=42)

5.2 (17.4) (n=51)

Perphenazine

2.7 (0.7) (n=130)

−1.3 (1.0) (n=88)

28.7 (11.6) (n=36)

−27.5 (22.3) (n=31)

Quetiapine

−0.2 (0.6) (n=186)

0.1 (1.1) (n=85)

29.8 (10.8) (n=42)

−13.0 (18.4) (n=46)

Risperidone

0.1 (0.6) (n=162)

0.9 (0.9) (n=109)

19.7 (11.2) (n=39)

−67.1 (21.2) (n=35)

Ziprasidone

0.6 (0.9) (n=90)

4.3 (1.4) (n=51)

26.0 (15.6) (n=20)

−96.4 (28.5) (n=19)

Overall treatment difference

<0.0011

0.0122

NS

0.0113

Note. Table entries are analysis of covariance least-squares adjusted means (standard error of measurement). NS=not significant (P≥ 0.05). a Data presented in separate columns due to significant race× treatment effect. b Data presented in separate columns due to significant baseline×treatment effect. Median triglyceride level=148 mg/dL. 1 Between-group comparisons significant for perphenazine vs. olanzapine (P<0.001) and for perphenazine vs. quetiapine (P=0.002). 2 Between-group comparisons significant for ziprasidone vs. olanzapine (P=0.002) and for ziprasidone vs. perphenazine (P= 0.001). 3 Between-group comparison significant for olanzapine vs. ziprasidone (P=0.003).

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155

Patient Variables and Possible Mechanisms for Antipsychotic-Related Hyperlipidemia Based on a review of data on certain metabolic outcomes, such as the development of type 2 diabetes mellitus or diabetic ketoacidosis, ethnicity and obesity stand out as important predictors of risk and are additive with that imposed by the antipsychotic medication itself (Jin et al. 2002, 2004). As of 2008, no important trends regarding patient risk for hyperlipidemia can be assigned on the basis of ethnicity, gender, patient weight, or even medication dosing within the range commonly used to treat schizophrenia. There are case reports of significant hypertriglyceridemia with low-dose olanzapine (e.g., 5 mg) (Meyer 2001) but no data for those medications employed at extremely low doses (relative to their antipsychotic dosing), such as quetiapine, which is frequently used in the United States as a sedative at doses of 25–100 mg. The only demographic variable that may be predictive of decreased risk for dyslipidemia is age, with the caveat that both olanzapine studies in older subjects previously cited were performed among subjects in controlled settings, presumably with controlled diets as well (Barak and Aizenberg 2003; De Deyn et al. 2004). Conversely, reports exist of dyslipidemia in adolescents exposed to antipsychotic medications, primarily olanzapine, so younger age is not protective (Domon and Cargile 2002; Domon and Webber 2001; Martin and L’Ecuyer 2002; Nguyen and Murphy 2001; Penzak and Chuck 2002; Shaw et al. 2001; Stigler et al. 2004). That an antipsychotic agent can induce dyslipidemia is not entirely surprising given that hyperlipidemia can occur with a variety of medications, including certain diuretics, progestins, β-adrenergic antagonists, immunosuppressive agents, protease inhibitors, and some anticonvulsants (Echevarria et al. 1999; Mantel-Teeuwisse et al. 2001; Penzak and Chuck 2002). In their comprehensive review of the subject, Mantel-Teeuwisse et al. (2001) noted that global changes in serum lipids are described with some medications, whereas certain agents appear to have specific effects on particular lipid fractions. For example, isotretinoin, acitretin, certain protease inhibitors, low-potency phenothiazines, and dibenzodiazepine-derived antipsychotics primarily elevate serum triglyceride levels. Moreover, in a manner that parallels the differential metabolic effects of the atypical antipsychotics, the protease inhibitors also vary dramatically in their metabolic effects (Penzak and Chuck 2002). Any agent may induce hyperlipidemia through several possible means, although none of these has been proven definitively for the

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atypical antipsychotics. Nonetheless, several biologically plausible hypotheses have been advanced, focusing on weight gain, dietary changes, and the development of insulin resistance, to explain the high incidence of hyperlipidemia with certain antipsychotic medications. The variation in weight gain liability is quite marked among the atypical antipsychotics (Allison et al. 1999), with clozapine and olanzapine associated with the greatest gains. Because obesity and weight gain have a demonstrable negative impact on serum lipid profiles, those atypical antipsychotics most likely to cause significant weight gain are also correlated with the greatest impact on serum lipids (Stone et al. 2005). Nonetheless, recent switch data suggest that the more metabolically offending medications may have direct, weight-independent effects on serum lipids. In a long-term switch study, Weiden et al. (2007) charted the time course of weight and lipid changes over 58 weeks after switching subjects from typical antipsychotics, risperidone, and olanzapine to ziprasidone. Those switching from high-potency typical antipsychotics experienced no significant lipid changes, but those previously taking olanzapine and risperidone experienced an immediate reduction in lipids (triglycerides more than total cholesterol) over the first 6 weeks after the switch, as well as slow but steady weight loss over the course of the study. The rapid improvement in serum lipids during a time frame when weight loss had been minimal points to a direct, weight-independent effect of certain antipsychotic medications on serum lipids. Accumulating data suggest that the metabolic pathway most likely to mediate the increase in serum triglycerides relates to the development of insulin resistance. In those who have become less sensitive to the action of insulin, the inability of insulin to adequately suppress lipolysis in adipose cells results in an outflow of free fatty acids and dyslipidemia, characterized primarily by elevated serum triglycerides (Reaven 2005). The literature certainly supports the concept that some patients who develop new-onset type 2 diabetes mellitus experience hypertriglyceridemia (Meyer 2001), often with reversal of these problems upon discontinuation of the offending agent (Casey et al. 2003; Meyer et al. 2005; Weiden et al. 2007). Although the majority of patients with elevated triglycerides related to antipsychotic treatment do not have overt type 2 diabetes mellitus, many do show signs of insulin resistance, as seen in studies of glucose-insulin parameters in patients taking clozapine or olanzapine (Melkersson and Dahl 2003). More recent data suggest that quetiapine might induce triglyceride changes by another mechanism. Prospective data presented at the 2007 American Psychiatric Association annual meeting (Newcomer et al.

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2007) indicated that quetiapine-exposed patients experienced changes in serum triglyceride levels without an apparent change in glucose tolerance, as measured by standard glucose tolerance testing. Compelling biological data support Weiden et al.’s (2007) switch study findings and point to direct effects of the more metabolically offending medications on insulin sensitivity independent of changes in adiposity. Single doses of medications such as olanzapine and clozapine have been shown to induce loss of insulin sensitivity in a dose-dependent fashion in laboratory animals in a manner not seen with risperidone or ziprasidone (Houseknecht et al. 2007). Evidence for this effect can be directly measured within 2 hours of drug exposure, using the hyperinsulinemiceuglycemic clamp technique, as both the decreased ability to metabolize glucose and the failure to adequately suppress endogenous glucose production from the liver. The means by which clozapine and olanzapine induce these effects is not known, but the propensity to cause insulin resistance with single doses strongly suggests that these two agents have weight-independent effects on glucose-insulin homeostasis, effects that will be exacerbated by future medication-related weight gain.

Monitoring Recommendations for Hyperlipidemia During Antipsychotic Therapy Because multiple cardiovascular risk factors exist in patients with schizophrenia (Goff et al. 2005), caution must be exercised in the choice of antipsychotic therapy to minimize the added morbidity and mortality of hyperlipidemia. Unfortunately, hyperlipidemia is undertreated in schizophrenia patients (Nasrallah et al. 2006), thereby exposing patients to ongoing substantial additional cardiovascular risk. For example, for a normotensive smoker exposed to a dibenzodiazepine-derived atypical antipsychotic, the 10-year risk for a major cardiovascular event (e.g., sudden death, acute myocardial infarction) might be increased significantly from baseline after only 12 weeks of therapy (Daumit et al. 2008). Hyperlipidemia is associated with long-term cardiovascular consequences, yet monitoring for hyperlipidemia is not solely a long-term issue, because severe hypertriglyceridemia also represents a risk for acute pancreatitis (Koller et al. 2003). The following guidelines are based on previously published recommendations (American Diabetes Association et al. 2004; De Hert et al. 2006; Marder et al. 2004; Melkersson et al. 2004; Meyer et al. 2006; Sernyak 2007) and my own clinical experience. Some of the consider-

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ations inherent in these recommendations include the following: patients with schizophrenia have multiple risk factors for cardiovascular disease; certain antipsychotics are associated with greater adverse effects on serum lipids; many health care providers outside of the psychiatric arena are unaware of the potential metabolic complications of atypical antipsychotic therapy; and schizophrenia patients often receive limited or no medical care outside of that provided by the mental health practitioner, so the burden of medical monitoring necessarily falls on those who prescribe antipsychotic medications. Although the following recommendations are specific to monitoring of serum lipids, these are understood to be part of the monitoring recommended elsewhere as part of routine medical care for those taking atypical antipsychotics.

Baseline Assessment • For each patient with schizophrenia, the clinician should document in the medical record the individual’s smoking status, as well as the patient’s and first-degree family members’ history of cardiovascular disease, hyperlipidemia, and glucose intolerance. • The clinician should obtain weight, waist circumference, blood pressure, and (ideally) fasting lipid panel for each patient. Total cholesterol and HDL values are valid on nonfasting specimens, but triglyceride and LDL levels are not. These measures are recommended for all patients with schizophrenia, regardless of medication regimen, given the limited health care access for these patients.

Follow-Up • For patients taking agents associated with lower risk for hyperlipidemia (high-potency typical antipsychotics, ziprasidone, risperidone, aripiprazole), an annual fasting lipid panel is sufficient unless dyslipidemia is suspected from the baseline evaluation. • For patients taking agents associated with higher risk for hyperlipidemia (low-potency typical antipsychotics, quetiapine, olanzapine, clozapine), a quarterly fasting lipid panel is necessary for the first year to detect cases of severe hypertriglyceridemia. Testing frequency may be decreased to semiannually if fasting lipids remain normal but should continue on a quarterly basis in those identified with abnormal values. • All patients with persistent dyslipidemia should be referred for lipid-lowering therapy or considered for switch to a less offending agent if possible.

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Key Clinical Points ◗

Patients with severe mental illness have twice the risk for cardiovascular mortality versus their non–mentally ill counterparts. Therefore, the induction of hyperlipidemia secondary to antipsychotic treatment represents a serious condition not only because of its impact on cardiovascular risk but also because it is occurring in a group that possesses considerable risk.

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High-potency typical antipsychotic agents (butyrophenones) are lipid neutral, whereas low-potency agents (phenothiazines) are associated with hyperlipidemia, primarily in the form of hypertriglyceridemia.

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The structurally related dibenzodiazepine-derived atypical antipsychotics (clozapine, olanzapine, and quetiapine) are associated with greater elevations in serum triglycerides than in total cholesterol, whereas the non-dibenzodiazepine agents (risperidone, ziprasidone, and aripiprazole) have minimal effects on lipids.

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Known mechanisms by which antipsychotics cause hyperlipidemia include weight gain, dietary changes, and the direct development of insulin resistance.

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A thorough baseline assessment in all patients should include a cardiovascular assessment. Subsequent monitoring for hyperlipidemia is recommended annually for all patients prescribed antipsychotics and as frequently as quarterly for those prescribed higher risk agents.

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CHAPTER 7 The Spectrum of Cardiovascular Disease in Patients With Schizophrenia Jimmi Nielsen, M.D. Egon Toft, M.D., F.E.S.C.

Life expectancy for patients with schizophrenia in the United States is 61 years, or 15 years shorter than for the general population (Hennekens et al. 2005), even after controlling for unnatural causes of death (e.g., accidents and suicide). Cardiovascular disease (CVD) is the major cause of excess mortality in patients with schizophrenia, and this patient cohort is twice as likely to die of coronary heart disease (CHD) as the general population (Brown et al. 2000). There are multiple sources of increased CVD risk, including sedentary lifestyle, smoking, and the metabolic side effects of antipsychotic treatment. Although seemingly of less clinical importance, much attention has also been paid to the increased risk of sudden cardiac death due to tachyarrhythmias, such as torsade de pointes (TdP), that are induced by antipsychotics. Interestingly, although several antipsychotics have been withdrawn from the market due to QTc interval prolongation and concern over torsade de pointes risk, among the antipsychotics associated with increased risk 169

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for CVD mortality mediated by substantial weight gain and dysmetabolic effects, none have been suspended. Although the evidence base is sparse, the accumulated literature suggests that antipsychotic exposure accounts for relatively few arrhythmia deaths compared to the expected greater numbers of deaths from myocardial and cerebral infarctions occurring secondary to antipsychotic-induced metabolic side effects and patient lifestyle factors. Our purpose in this chapter is to describe the spectrum of CVD, with a particular focus on those specific issues related to schizophrenia and the medications commonly used for schizophrenia treatment. The chapter is not a complete guide to CVD, but we hope to equip psychiatrists and other physicians with the basic tools required to meet the challenge of treating and preventing CVD in patients with schizophrenia. In this chapter, we first provide the reader with a general background for understanding the relationship between schizophrenia, medication treatment, and TdP, as this information is necessary for the understanding of arrhythmia risk related to medication effects, and later provide an overview of atherosclerotic disease and basic CHD risk management.

Sudden Cardiac Death The World Health Organization defines sudden cardiac death (SCD) as unexpected death within 1 hour of symptom onset if witnessed, or within 24 hours of the person having being alive and symptom free, if unwitnessed (Turakhia and Tseng 2007). CHD is involved in up to 70% of sudden death cases, and in many instances the first symptom of CHD is sudden death (Turakhia and Tseng 2007); however, establishing the exact cause of death can be difficult because several causes (overdose, suicide, cerebrovascular events, seizures, etc.) must be excluded. In most instances, an autopsy can determine the exact cause of death. If no structural disease is found, cardiac arrhythmia is the most likely etiology. Retrospective data suggest that the overall risk of SCD is increased 4.9 times in patients with schizophrenia compared with the general population (Ruschena et al. 2003), with multiple contributing etiologies. Patients with schizophrenia have more prevalent cardiovascular risk factors compared to the background population due to lack of exercise, obesity, smoking, diabetes, and dyslipidemia (Leucht et al. 2007). In schizophrenia patients, the prevalence of type 2 diabetes mellitus is increased twofold, smoking threefold, obesity twofold, and dyslipidemia

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up to fivefold. Substance abuse and dependence, especially alcohol and cocaine, are also more common in patients with schizophrenia and are linked to risk for sudden death. Furthermore, patients with schizophrenia are less likely to have proper preventive medical care and monitoring for metabolic disorders than the general population (Leucht et al. 2007) and, when a primary care provider is consulted, are less likely to follow instructions on diet or exercise. Antipsychotic treatment has also been linked to increased risk of SCD. A 2.4-fold increased risk of SCD was found in users of antipsychotics versus nonusers in a retrospective cohort study from Tennessee (Ray et al. 2001). Cardiac arrhythmia from previously undiagnosed CHD and risk from antipsychotic medication exposure are the two most plausible explanations, but other suggestions that have been put forth include respiratory dyskinesia, laryngeal-pharyngeal dystonia, and peripheral vasodilation leading to cardiovascular collapse and oversedation (Haddad and Anderson 2002; Titier et al. 2005). Although cardiac arrhythmia is the most common etiology for SCD, it is worthwhile distinguishing whether the arrhythmia is primary or whether it is secondary to structural changes related to cardiomyopathy, myocarditis, or acute myocardial infarction. Secondary ventricular arrhythmia is probably the most frequent form of fatal tachyarrhythmia, but the exact distribution of deaths due to structural changes (acute myocardial infarction or cardiomyopathy) or nonstructural changes (cardiac arrhythmia) is unclear because no large-scale mortality study with autopsy results has been carried out (Michelsen and Meyer 2007). In general, the incidence of drug-induced ventricular arrhythmia is largely unknown, partly due to underreporting of spontaneous adverse effects. Drug-induced TdP is a rare event, so extremely large sample sizes would be needed to detect a small increase in SCD risk. Further complicating the assignment of TdP as the cause of any arrhythmic death is the need to confirm the diagnosis with electrocardiographic (ECG) recordings obtained at the time of the event.

Electrophysiology of the Heart The electrophysiology of the heart is complex, and several ion channels are involved in the repolarization and depolarization of ventricular cells. The depolarization event, which includes the action potential, is primarily mediated by the rapid influx of sodium and is reflected on the electrocardiogram as the QRS complex (Figure 7–1). Blocking of the sodium channel is called a quinidine-like effect, named after the class I

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antiarrhythmic drug quinidine. This effect can be seen on the electrocardiogram as a widening of the QRS complex and increased PR interval, and drugs with quinidine-like properties are associated with increased risk of SCD due to ventricular arrhythmia. Some antipsychotics, such as thioridazine, have been shown to possess quinidine-like properties at high dosages, but among commonly used psychotropic medications, only tricyclic antidepressants affect depolarization to any significant extent.

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FIGURE 7–1. The role of ion channels during depolarization and repolarization. A. The monophasic action potential with notations for involved ion channels. B. The corresponding surface electrocardiogram. Source. Reprinted from Titier K, Girodet PO, Verdoux H, et al: “Atypical Antipsychotics: From Potassium Channels to Torsade de Pointes and Sudden Death.” Drug Safety 28:35–51, 2005. Used with permission.

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Repolarization is mediated primarily by the efflux of potassium via two families of potassium channels: the rapid IKr and the slow IKs channels. The IKr channel is encoded by the human ether-a-go-go related gene (HERG), polymorphisms of which are involved in the congenital long QT syndrome, type II. Patients with congenital long QT syndrome have one or more mutations in the genes encoding for ion channels involved in the repolarization and depolarization of the heart, with nine known genetic variants involved in this disease. The cardinal symptoms of congenital long QT syndrome are syncope or SCD, and in some cases the first symptom is sudden death (Priori et al. 2003). Many antipsychotic drugs block the IKr channel to an extent comparable with that seen in congenital long QT syndrome. Antagonism of IKr channels is the mechanism mostly responsible for instances of drug-induced QT prolongation and is the suspected mechanism for the majority of antipsychotic-induced sudden cardiac deaths. The prolongation of the repolarization process, and thereby of the QT interval, is thought to allow the development of spontaneous contractions of non-pacemaker cells called early after-depolarizations (EADs). The induction of EADs, whether drug-induced or genetic as in the congenital long QT syndrome, can also increase risk for ventricular arrhythmia, as the development of EADs is linked to an increased inward current and/or decreased outward current during the repolarization phase of the action potential (Glassman and Bigger 2001; Haverkamp et al. 2000).

Torsade de Pointes Torsade de pointes (TdP), which literally means “twisting points” in French, is a polymorphic ventricular arrhythmia and the most common drug-induced ventricular arrhythmia. The name is derived from the twisting of the QRS complex around the isoelectric line, as shown in Figure 7–2A. TdP can be asymptomatic or cause self-limiting palpitations, dizziness, syncope, and death. In approximately one-third of patients, TdP will lead to ventricular fibrillation, and in 10% result in SCD (Figure 7–2B) (Abdelmawla and Mitchell 2006). In one Swedish study, the annual incidence of drug-induced TdP was 4 per 100,000 patients, although the real incidence has been estimated to be at least 10 times higher (Wysowski and Bacsanyi 1996).

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A

B

FIGURE 7–2.

Examples of torsade de points (TdP).

A. Electrocardiogram shows a self-limited case of TdP. Notice the typical shift between an upward and a downward pointing of the complexes. B. A case of TdP deteriorating into ventricular fibrillation. Source. Reprinted from Yap YG, Camm AJ: “Drug Induced QT Prolongation and Torsades de Pointes.” Heart 89:1363–1372, 2003. Used with permission.

Risk Factors for Torsade de Pointes Risk factors for developing TdP are shown in Table 7–1 (Yap and Camm 2003). An important issue to consider when exploring drug-related causes is the potential for pharmacokinetic drug-drug interactions that increase the plasma levels of an offending drug and result in dosedependent QTc prolongation. Pharmacodynamic interactions can occur when two or more drugs are prescribed that prolong the QTc interval, with the combined effects resulting in significant QT prolongation. Medications with quinidine-like properties (e.g., tricyclic antidepressants) given together with QT prolonging antipsychotics is just a single example of a combination of psychiatric medications that may increase the risk of sudden death. An additional risk is that induced by biological variability. In 10%– 15% of patients with drug-induced TdP, mutations or polymorphisms were found in one of the congenital long QT genes (Yang et al. 2002). These patients have smaller repolarization reserve and are therefore more susceptible to drug-induced changes. Although genetic causes provide an obvious source of risk, most cases of TdP occur in patients with structural heart disease or other risk factors (Table 7–1). For this reason, drug-induced TdP is comparably rarer in young, healthy pa-

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TABLE 7–1.

175

Risk factors for developing drug-induced torsade de pointes (TdP)

• • • • • • • • • •

Female gender Hypokalemia (e.g., vomiting and diarrhea) Structural heart disease (e.g., cardiomyopathy or infarction) Atrioventricular block Bradycardia Prolonged QTc (>450 milliseconds) Significant T-wave abnormalities Genetic disposition/congenital long QT syndrome Prior drug-induced TdP Multiple QT-prolonging drugs or other drugs that interfere with their metabolism • Hepatic impairment • Drug-drug interactions

Source.

Adapted from Yap and Camm 2003.

tients than in older individuals, who have a greater likelihood of having established cardiac disease.

Estimating the Risk: Surrogate Markers Great interest has been shown in developing surrogate markers for the clinical evaluation of medication proarrhythmic effects, but so far no valid marker has been elucidated. The QTc interval is the most widely used marker for determining the proarrhythmic effects of any drug, but an exact estimate of risk cannot be derived solely from changes in the QTc interval. Even among patients with prolonged QTc intervals, the actual risk of TdP is often quite low. This fact alone poses great difficulties for the identification of patients at risk for TdP and SCD. The overall safety of an antipsychotic drug rests on the balance between protective and causative factors for SCD. QTc-prolonging drugs might also have actions that diminish the proarrhythmic risk, such as increasing the heart rate or altering other ion currents, which counteract the proarrhythmic effects (Taylor 2003a). Diminished long-term SCD risk can also result if the medication is associated with limited weight gain (or weight loss) and thereby lowers mortality by decreasing traditional CHD risk associated with obesity. For these reasons, the relationship between drug-induced QTc prolongation and the risk of sudden death is not simple, and false positives are seen with drugs that prolong

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the QTc interval but are only rarely associated with TdP. Amiodarone is a class III antiarrhythmic that is rarely associated with TdP but is known to significantly prolong the QTc interval (Hohnloser et al. 1994). Other examples include verapamil, ziprasidone, and sertindole, all of which prolong the QT interval significantly, but whose association with TdP is questionable (De Cicco et al. 1999; Haddad and Anderson 2002). Because QT effects by themselves do not always predict TdP risk, surrogate markers for drug-induced arrhythmia risk have been studied, as presented in the next section, including some recent and technologically more advanced parameters developed from electrocardiograms in patients with long QT syndrome. Although these studies are not commonly used in routine clinical practice, an understanding of changes in T-wave morphology may be very useful in the near future, and parameters based on T-wave morphological changes have evolved to the extent that they are expected to be employed in drug studies in the next few years (Couderc et al. 2008; Kanters et al. 2004; Struijk et al. 2006).

QT Interval Estimation The QT interval comprises the entire interval from the beginning of the QRS complex to the termination of the T-wave (Figure 7–3). The end of the T-wave is defined as the intercept between the isoelectric line and the tangent of the steepest part of the descending T-wave. Determination of the exact point of T-wave termination is critical to the estimation of QT interval duration and is subject to certain pitfalls. A U-wave incorporated in the T-wave often complicates QT measurement and can lead to the erroneous assessment of QTc prolongation because the Uwave is included in the interval. T-wave alterations, such as biphasic or flat T-waves (e.g., due to IKr blockade), can cause similar problems. A U-wave is most often present in lateral precordial leads, whereas biphasic T-waves are present in multiple leads. For cases where any of these features are present, manual estimation of the QT interval is a better option, with possible referral to a cardiologist for interpretation. Manual QT interval measurement should be derived from at least three to five cycles, and a mean value calculated across these cycles. Although the accuracy level of manual QT interval determination is 20–40 milliseconds (Goldenberg et al. 2006), the accuracy of automatic measurement of the QT interval varies greatly, because manufacturers have chosen varying algorithms for QT calculations (Goldenberg et al. 2006). The QT interval can be measured in any lead, yet the length of the interval can differ between leads. Although there is no consensus on which

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QRS complex R

T peak

T end TPTE interval

ST segment

PR interval P

U T asc.

Q

T desc.

S PR segment

FIGURE 7–3.

QT interval

Electrocardiogram.

As shown, finding the end of the T-wave can be difficult, particularly in cases where a U-wave is interfering. asc. =ascending; desc. =descending; TPTE=time from peak to end of T-wave. Source. Reprinted from Pater C: “Methodological Considerations in the Design of Trials for Safety Assessment of New Drugs and Chemical Entities.” Current Controlled Trials in Cardiovascular Medicine 6:1–13, 2005. Used with permission of Biomed Central Ltd.

leads must be used, V3 and V4 have generally been suggested as the preferred leads for QT estimation (Malik 2004; Sadanaga et al. 2006). Another source of potential confusion for QT estimation lies in the fact that the QT interval shortens with increasing heart rate, making correction necessary. Several correction formulas have been suggested (Figure 7–4), of which the Bazett formula is the most commonly used; however, it is less accurate at heart rates above 70 beats per minute (bpm) (Dogan et al. 2005). The Fridericia correction formula performs

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QT = QTcB 2 RR Bazett

FIGURE 7–4.

QT QTcF = 3 RR Fridericia

The most commonly used correction formulas.

The Fridericia formula is recommended and performs better than the Bazett formula in cases of tachycardia or bradycardia. QT is measured in milliseconds and RR in seconds. The RR interval used should be the preceding beat to the QT interval measured. The notation QTcB or QTcF can be used to indicate whether the method used was the Bazett or the Fridericia method.

better than Bazett at heart rates above 70 bpm and is often used in newer ECG machines and by the pharmaceutical industry for drug evaluation. Heart rate correction is especially important in patients receiving antipsychotic drugs, because most antipsychotics increase resting heart rate. The reference interval for the QTc interval associated with greater TdP risk is not clearly defined, but most agree that a QTc interval greater than 500 milliseconds indicates an area of increased risk. Females tend to have longer QTc intervals, in part related to the fact that testosterone decreases the QT interval (Gupta et al. 2007; Rautaharju et al. 1992), and 70% of TdP cases occur in women (Vieweg 2002). The importance of QT interval prolongation has been suggested to be 1.052X where X is prolongation above 440 milliseconds divided by 10. For example, prolongation from 440 milliseconds to 500 and 640 milliseconds would increase the risk for TdP by 1.0526 = 1.4 and 1.05220 =2.8 times, respectively (Moss 1993). In the general population, the risk for TdP is rare, and therefore a doubling would still mean a small increase in the number of cases. Furthermore, these data are based completely on findings from individuals with congenital long QT syndrome, and whether these calculations can be extrapolated to drug-induced TdP risk is unclear. The QT interval length fluctuates throughout the day related to several factors, including inherent diurnal variation, level of activity, and body weight. The QTc interval is longest during nights and shortest after awakening (Molnar et al. 1996); moreover, drug-induced prolongation of the QTc interval is greatest during the first half of the menstrual cycle (Rodriguez et al. 2001). The effect of weight gain on QTc prolon-

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gation has been quantified, with a 10-kg weight increase associated with an increase of over 5-milliseconds in QTc length (el-Gamal et al. 1995). Besides these biological factors, inaccurate measurement of and correction for heart rate add to the variation in reported QT intervals and complicate the assessment of drug-related effects on QTc and level of TdP risk. As alluded to earlier, some proposed surrogate markers for drug-related TdP risk have been tested and show promise. These include QT dispersion, time from the peak to the end of the T-wave (Tpeak–Tend, also called TPTE), T-wave morphology, and heart-rate variability (HRV).

QT Dispersion That the QT interval differs between different leads is partly due to differences in repolarization time between the various myocardial layers. The QT dispersion is the difference in time between the lead with the shortest and the lead with the longest QT interval and is thus a measure of myocardial heterogeneity during the repolarization process. A QT dispersion of more than 100 milliseconds, or an incremental difference of more than 100%, has been associated with proarrhythmic effects of medications (Haddad and Anderson 2002). Amiodarone, a class III antiarrhythmic drug that prolongs the QT interval but rarely induces TdP, was found to decrease repolarization heterogeneity and thereby decrease QT dispersion (Hii et al. 1992; Hohnloser 1997). Risperidone has been shown to increase the QT interval but without an incremental increase in QT dispersion, and thus would be not associated with TdP risk, a fact borne out by clinical experience (Yerrabolu et al. 2000). Arguments against the use of QT dispersion as a surrogate marker relate to the fact that the QT interval itself varies widely and in some leads can be difficult to estimate. Because QT dispersion relies on QT measurements in all 12 leads, there is added variability, leading some to argue that further studies are needed to determine the validity of QT dispersion as a surrogate marker for TdP risk.

T-Wave-Related Measurements Other proposed surrogate markers rely solely on T-wave-related measurements. One of these is the time from the peak to the end of the T-wave (see Figure 7–3). TPTE exists as an absolute value and also as a measure of dispersion as calculated in the QT dispersion equation. Although TPTE purportedly reflects transmural dispersion of repolarization (Antzelevitch et al. 2007), changes in T-wave morphology are another surrogate marker for TdP risk derived from changes seen in

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patients with congenital long QT syndrome (Malik and Camm 2001; Struijk et al. 2006). The congenital long QT syndrome type II is due to mutations in the HERG potassium channel gene, and the electrocardiogram in these individuals demonstrates T-wave flattening and notches. Unfortunately, the widespread use of T-wave morphology as a TdP risk marker has been complicated by difficulties in quantifying these morphological changes (Taylor 2003a), but newer data, derived from more intensive study of long QT patients, has overcome many of the technical hurdles to the extent that this parameter will be used to monitor TdP risk in future drug studies (Couderc et al. 2008; Kanters et al. 2004; Struijk et al. 2006).

Heart Rate Variability During inspiration and expiration, the heart rate accelerates and decelerates, creating an innate source of variability that is a measure of heart responsiveness. HRV thus relates to these beat-to-beat alterations in the heart rate and is usually derived from a 24-hour Holter recording. HRV reflects peripheral autonomic tone, and drugs with anticholinergic properties reduce HRV (Rechlin et al. 1998). The importance of reduced HRV for arrhythmia risk is based on findings from post-myocardial infarction studies indicating that decreased HRV is associated with increased mortality (Zuanetti et al. 1996). Olanzapine and clozapine have been found to reduce HRV, but the importance of this finding is unclear (Mueck-Weymann et al. 2002; Rechlin et al. 1994). On the other hand, thioridazine, which is associated with significant QTc prolongation and sudden death, was found to improve HRV (Silke et al. 2002). Interestingly, reduced HRV is seen not only in antipsychotic-treated individuals but also in drug-naive patients with schizophrenia (Malaspina et al. 2002), suggesting that decreased HRV might be related to the disease itself, through inherent biological mechanisms or an inactive lifestyle. As with other markers, more studies are needed to clarify the importance of HRV in studying the impact of antipsychotics on SCD risk.

Antipsychotic Drugs Virtually all antipsychotic drugs prolong the QT interval to some measurable extent (Figure 7–5), and patients treated with antipsychotic drugs typically have longer QTc intervals and higher heart rates than do controls (Cohen et al. 2001). A critical issue when estimating the extent of drug-induced QT prolongation is the baseline QT value. Because

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patients are rarely drug-free at baseline for most clinical trials, the true extent of QT prolongation from the drug under study can be underestimated if the baseline medication also prolongs the QT interval. Furthermore, kinetic or dynamic drug-drug interactions can increase measured QT prolongation. In general, atypical antipsychotics are associated with a lower risk of arrhythmia than conventional antipsychotics (Sicouri and Antzelevitch 2008), yet conclusions drawn from such findings often fail to account for the long-term impact of metabolic side effects on cardiac risk. One paper estimated that 416 patients per 100,000 treated will die from the sequelae of clozapine-induced weight gain within a 10-year period (Fontaine et al. 2001), a figure that is much higher than mortality rates from directly induced drug-related cardiac arrhythmia. Moreover, in this same 10-year time frame, only 10–15 clozapine-treated patients would die from agranulocytosis.

Conventional Antipsychotic Drugs Conventional antipsychotic drugs were approved at a time when the demand for cardiac safety data was less strict. As a consequence, many widely used conventional antipsychotic drugs have not been thoroughly investigated, although some have gained notoriety based on newer safety data. Thioridazine and the related compound meso-

40 QTc change (milliseconds)

35 30 25 20 15 10 5

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QTc prolongation with antipsychotics.

Adapted from Glassman and Bigger 2001.

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ridazine (which is metabolized to thioridazine) received black-box warnings in the U.S. market in 2001 due to QTc data that emerged from premarketing studies for ziprasidone. In these studies, the mean QTc prolongation during treatment with thioridazine was 35 milliseconds (Salih et al. 2007). The Pfizer data were not the sole source for the warning; clinical data indicated an increased risk of developing TdP and SCD with thioridazine (Reilly et al. 2002). In one Finnish study analyzing 49 sudden deaths during treatment with antipsychotics, thioridazine was involved in more than half of the cases, a finding that could not be explained by its relative market share (Mehtonen et al. 1991). Other drugs under suspicion or withdrawn from various markets include droperidol and pimozide. In some instances, the suspicion or withdrawal was based solely on measured QTc effects, despite a paucity of clinical cases of drug-induced TdP or SCD. Haloperidol has been widely used for many years and is in general considered to have a wide margin of cardiac safety based on overdose and other data accumulated over decades of use. Although haloperidol is associated with an average 5-millisecond QTc prolongation, more than 20 cases of haloperidol-induced TdP have been published (Yap and Camm 2003). This impression of safety might explain the cases of TdP, because haloperidol is often prescribed in intensive care units and other critical care hospital settings among a cohort of patients with overt cardiac comorbidity. Patients with cardiac complications are more vulnerable and often monitored more intensely with electrocardiography, a fact that might increase the number of detected TdPs, some of which may be incidental to the use of haloperidol and are the result of underlying comorbid conditions (e.g., electrolyte disturbances, use of other medications).

Atypical Antipsychotics Sertindole was introduced in 1997 as an atypical antipsychotic but was voluntarily withdrawn from the market a year later due to a possible link to sudden death. Despite the early concerns, subsequent postmarketing surveillance studies failed to show an increased risk of sudden death or arrhythmia (Peuskens et al. 2007). The mean QTc prolongation from sertindole is 20 milliseconds at therapeutic dosages, but so far no TdP cases with sertindole as the offending agent have been published. Based on further surveillance data documenting a general pattern of low SCD risk, sertindole was reintroduced in several European countries in 2006 but with restricted use as a second-line agent and with mandatory baseline and follow-up ECG monitoring.

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Ziprasidone also prolongs the QTc interval about 20 milliseconds but has not been associated with TdP (Glassman and Bigger 2001). Maximal QTc prolongation is reached at low therapeutic dosages. Reported exposures to ziprasidone dosages above 12 g have not resulted in TdP, confirming the medication’s lack of TdP risk; moreover, the majority of ziprasidone’s metabolism is through the aldehyde oxidase pathway, one that is neither saturable nor inhibitable by medications, a feature that decreases the risk for drug interactions (Taylor 2003b).

Clinical Implications Basic monitoring for elements of cardiovascular risk should include body weight, a measure of central adiposity (e.g., waist circumference or hip:waist ratio), blood pressure, fasting lipids, and fasting glucose. Whether routine ECG monitoring will decrease morbidity or mortality in patients with schizophrenia has not been extensively studied; however, electrocardiography is a cheap and noninvasive procedure that provides important information about cardiac status. Experts at the 2004 Mount Sinai Conference on the Pharmacotherapy of Schizophrenia concluded that electrocardiography is recommended when prescribing thioridazine, pimozide, or ziprasidone only when cardiac complications, such as congenital long QT syndrome, known heart disease, history of syncope, or genetic disposition to sudden death (for individuals under age 40), are present (Marder et al. 2004). In contrast, the Danish Health Board recommends obtaining an electrocardiogram at baseline, after 12 weeks, and annually in all patients treated with antipsychotic drugs (Sundhedsstyrelsen 2007). The Maudsley Prescribing Guidelines (Taylor et al. 2007) suggest monitoring with electrocardiography when patients are treated with high-dose antipsychotics or combinations of drugs that have the propensity to prolong the QT interval. In conclusion, the evidence for routine ECG monitoring in patients treated with antipsychotics is sparse, but we recommend ECG monitoring in patients with vulnerability to arrhythmia (e.g., electrolyte abnormalities, bradycardia, structural heart disease) and in those receiving clozapine or drugs that significantly prolong the QT interval, have the propensity to cause TdP, or have such monitoring mandated in the text of the package insert. When electrocardiograms are obtained, we recommend using automated calculations of the QTc interval, because most psychiatric clinics and mental health professionals have less experience with manual reading. Machine-read electrocardiograms tend to overestimate the QT duration compared to manual readings, so in cases of significant QT

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prolongation based on machine interpretation, one should seek cardiologist confirmation. Many ECG machines still use the Bazett correction formula; when that formula indicates that the heart rate is >70 bpm, manual reading and correction using Fridericia’s method are recommended. The correction formula used by the machine can be found in the manual, so one can state in the patient record which formula was used for QT correction (e.g., QTcF indicates that Fridericia’s formula has been used). The following QTc parameters should lead to a discussion with the patient about discontinuation of potentially offending medications or, at the minimum, a reevaluation of benefits and risks of the current antipsychotic treatment (Sicouri and Antzelevitch 2008): • QTc prolongation >60 milliseconds • QTc interval >500 milliseconds Drugs that significantly prolong the QTc interval (ziprasidone, sertindole) or are associated with TdP (e.g., thioridazine or pimozide) should be avoided in patients with prolonged QTc interval and electrolyte abnormalities. When significant prolongations of QTc interval are detected in patients, serum potassium should be monitored and corrected. Finally, patients experiencing syncope or palpitations should be referred for thorough examination to exclude other physical causes, including long QT syndrome.

Sudden Death and the Combination of Benzodiazepines and Antipsychotics Because the combination of antipsychotics and benzodiazepines has been associated with sudden death, a black-box warning is provided regarding the use of parenteral olanzapine in combination with parenteral benzodiazepines (American Psychiatric Association 2005) based on eight fatal events. Benzodiazepines and sedating antipsychotics have respiratory depressant effects, and intramuscular administration increases the risk for respiratory collapse due to rapid systemic absorption with no first-pass metabolism. Concomitant use of parenteral benzodiazepines and sedating antipsychotics (especially clozapine and parenteral olanzapine) should prompt careful monitoring of blood pressure, respiratory rate, and oxygen saturation using an oximeter with an alarm (if available). In cases of respiratory depression, flumazenil can reverse the effect of benzodiazepines. The risk of sudden death associated with the combination of benzodiazepines and an antipsychotic has been best described for clozapine and benzodiazepines (Rup-

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precht et al. 2004), and this risk is probably due to the sedative and hypotensive effects of clozapine. Especially during the initial titration of clozapine, when patients are not yet tolerant to its sedative properties, precautions should be taken with the concomitant use of benzodiazepines (Borentain et al. 2002).

Cardiac Aspects of Clozapine Treatment Clozapine remains the drug of choice for patients with treatment-resistant schizophrenia and for schizophrenia patients with suicidal ideation. According to most treatment guidelines, a trial of clozapine should be initiated after failed trials of two or three other antipsychotics. The superior efficacy of clozapine compared with other antipsychotics has been established in several trials, but clozapine is not considered a firstline drug due to the risk of agranulocytosis. Clozapine is also associated with several cardiac complications, and the estimated number of deaths due to CVD is actually higher than the actual number of deaths due to hematological causes (Fontaine et al. 2001; A.M. Walker et al. 1997). The hematological monitoring system required for all clozapine patients prevents the vast majority of agranulocytosis cases from being fatal, but unrecognized cardiac complications remain a potentially serious source of morbidity and mortality. One early retrospective study found that clozapine exposure was associated with 3.8 times increased risk of SCD compared with use of nonclozapine antipsychotics, based on six deaths in the clozapine group; however, the control group was not matched for basic demographic variables such as severity of disease and duration of illness (Modai et al. 2000). The absence of matching is a serious methodological issue related to prescription bias, because clozapine is typically prescribed for more chronic patients who, by virtue of age and prior medication exposure, might possess more SCD risk factors. Furthermore, an autopsy was performed in only one SCD patient, so the etiology of SCD in some cases might be related to other etiologies (e.g., structural diseases). Given the small volume of published data, it is not clear whether clozapine treatment is associated with an increased mortality risk from SCD compared to treatment with other antipsychotics. Any added mortality risk associated with clozapine is ascribable primarily to other cardiac diseases, such as cardiomyopathy or myocarditis, or to the secondary cardiovascular effects of clozapine-induced weight gain and metabolic changes (Fontaine et al. 2001). Myocarditis and Pericarditis. Although clozapine is unlikely to directly induce SCD, clozapine has been associated with some unique

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cardiac complications, including myocarditis and cardiomyopathy. Myocarditis is an inflammation of the myocardial cells reported to occur within the first months of clozapine initiation. The development of this condition is probably due to immunoglobulin E–mediated hypersensitivity, a type 3 allergic reaction, but direct toxic effects on the myocardium (Killian et al. 1999) and even low selenium induced by clozapine have also been proposed as mechanisms (Vaddadi et al. 2003). The incidence of clozapine-induced myocarditis is estimated to be 1 in 500 and is fatal in up to 50% of cases (Killian et al. 1999). The presentation of myocarditis includes flulike symptoms, fever, dyspnea, sinus tachycardia, palpitations, fatigue, respiration-dependent pain, and chest discomfort. Pain is usually present only if the pericardium is involved. The primary ECG findings are ST elevations and T-wave inversions, and common laboratory abnormalities include elevated serum creatine kinase, leukocytosis, and eosinophilia. Eosinophilia is common in patients developing myocarditis but also occurs without myocarditis. Usually the eosinophilia is transient. Within the first months of treatment with clozapine, clinicians should carefully examine any patients with flulike symptoms, fever, sinus tachycardia, and other cardiac symptoms to exclude myocarditis, because the presentation may be subtle. The optimal way to diagnose myocarditis is to measure blood troponin levels, because troponin reflects myocardial damage (Kay et al. 2002; Merrill et al. 2006). Some clinicians have suggested regular troponin testing during the initial treatment with clozapine to increase the chances for prompt detection of myocarditis, but no prospective data exist to endorse this as a routine measure (Kay et al. 2002). In cases of myocarditis, clozapine must be discontinued immediately and treatment with corticosteroids initiated. Rechallenge with clozapine should be performed only in severe refractory schizophrenia cases without other viable treatment options, if the benefits are considered to outweigh the possible serious risks, and with close cardiac monitoring (Reid 2001). Complicating the diagnosis of myocarditis is the finding that approximately 20% of patients treated with clozapine develop benign hyperthermia within the first 3 weeks of treatment (Tham and Dickson 2002). Benign hyperthermia is often misdiagnosed as neuroleptic malignant syndrome, flu, or infection; however, the symptoms of benign hyperthermia are similar to those of myocarditis, so in these instances a careful examination must be performed. When benign hyperthermia occurs in the beginning of clozapine treatment, a white blood count, electrocardiogram, and troponin levels should be obtained to exclude myocarditis.

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Cardiomyopathy. The three types of cardiomyopathy are dilated (congestive), hypertrophic, and restrictive. Although dilated cardiomyopathy is a rare occurrence in the general population, in patients treated with clozapine, it accounts for more than 60% of cardiomyopathy cases (Meyer et al. 2007). Dilated cardiomyopathy typically starts in the left ventricle where myocardial muscle fibers stretch and become thinner, leading to chamber enlargement, and later spread to the right ventricle and to the atria. As with myocarditis, the underlying mechanism is unclear, but one explanation is that in some patients, clozapine might have a direct toxic effect on myocytes mediated by free radicals that induce myocardial injury and resultant myopathy. Another explanation relies on the fact that some cases of clozapine-induced cardiomyopathy have evolved from myocarditis. The hypothesis is that prior myocarditis may initiate an autoimmune process that further injures myocardial cells. The myocarditis episode might have been subclinical and resolved without treatment, but the latent autoimmune process explains the relatively late onset of cardiomyopathy during treatment compared with the earlier presentation of myocarditis. Clozapine-induced cardiomyopathy has also been related to low selenium levels, but it is unknown whether selenium supplementation can reduce the risk of cardiomyopathy or myocarditis. Although case reports have been published, there is some debate whether clozapine increases the risk for cardiomyopathy. Novartis reported that patients treated with clozapine had a cardiomyopathy incidence comparable to that of the U.S. population (Meyer et al. 2007); however, failure to show a difference may be related to type II error (given the infrequent occurrence in the general population) or might be due to underreporting of spontaneous adverse events. Killian et al. (1999) estimated the risk of clozapine-induced cardiomyopathy to be 51.5 per 100,000 patient-years, a fivefold increased risk over that seen in the general population. The other issue in ascribing causality relates to the fact that patients treated with clozapine have several known cardiomyopathy risk factors, including sinus tachycardia (a feature of clozapine treatment discussed below), alcohol abuse or dependence, CHD, smoking, obesity, and metabolic disorders. In more than 65% of reported cases, cardiomyopathy occurs after 6 months of clozapine treatment, with a 20% fatality rate (Merrill et al. 2005). Because cardiomyopathy is likely underreported, the incidence may be higher. With cardiomyopathy, as with myocarditis, no dosage dependency has been found. The physical symptoms are those related to heart failure: exertional dyspnea, fatigue, peripheral edema, orthopnea, and chest pain. Diagnosing cardiomyopathy can be difficult in

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patients with schizophrenia because many patients already experience dyspnea, peripheral edema, and fatigue due to poor physical conditioning. The electrocardiographic findings include sinus tachycardia, atrial and ventricular arrhythmias, and ST-segment, T-wave, and P-wave abnormalities, but the electrocardiogram can remain normal in earlier, less severe stages. Echocardiography is the most sensitive test for diagnosing cardiomyopathy, but it is unclear whether routine echocardiography is feasible or cost effective. Nonetheless, it should be performed early and with short notice in cases where cardiomyopathy is suspected. When cardiomyopathy is diagnosed, clozapine must be discontinued, and the focus of medical treatment should be on treating the complications of heart failure. Clozapine-induced cardiomyopathy can be reversible if it is detected early and clozapine is promptly discontinued. Sinus Tachycardia. One-fourth of patients treated with clozapine will develop a 10- to 15-bpm increase in pulse rate. This effect is due to the combination of anticholinergic vagal inhibition and an increase in circulation of catecholamines due to α1-adrenergic blockade (Safferman et al. 1991). Clozapine-induced tachycardia is dosage dependent but can occur at low dosages in sensitive individuals. Sinus tachycardia is particularly prominent during the initial titration, so a slower titration schedule might resolve the problem in certain individuals. Sinus tachycardia is often asymptomatic, but some patients complain of increased heart rate. As tachyphylaxis can occur during the first 4–6 weeks of treatment, β-adrenergic blocker treatment need not be initiated during this period. Clinicians need to remember that tachycardia is a symptom of both myocarditis and cardiomyopathy, so treatment with a β-adrenergic blocker might complicate the diagnosis of these conditions. Whether asymptomatic clozapine-induced sinus tachycardia should be corrected is unclear, but in general, persistent tachycardia (>100 bpm) is a known cardiomyopathy risk factor, so β-adrenergic blockers are often used in those patients with chronic tachycardia, although there is no compelling data that this treatment reduces myopathy risk. Symptomatic sinus tachycardia should be treated with a cardioselective β-adrenergic blocker (e.g., metoprolol) to avoid the possible effects of nonspecific beta blockade (e.g., exacerbation of restrictive airway disease) (Young et al. 1998); monitoring of blood pressure is also recommended. Nonspecific T-Wave Changes. T-wave changes are common during treatment with clozapine, and up to 20% of patients will develop ECG abnormalities when switched to clozapine (Kang et al. 2000). The typical T-wave changes that occur during clozapine therapy include flattening,

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inversion, and depression. The significance of these changes is unknown, and they are most likely benign; however, it is important to exclude other conditions causing T-wave changes such as myocarditis, myocardial infarction, or cardiomyopathy. Asymptomatic ST-segment elevation with no relation to ischemia can also occur during treatment with clozapine and probably has no clinical significance. As with certain T-wave changes, the clinician should thoroughly exclude other potentially serious diagnoses related to ST-segment elevations, such as myocardial infarction, ischemia, myocarditis, and cardiomyopathy (Kang et al. 2000). In addition to electrocardiogram, other tests—echocardiography, serum troponin levels, or stress tests—might be indicated on the basis of ECG changes and the clinical picture so as to rule out other diagnoses. QTc Prolongation. Clozapine has been associated with QTc prolongation (Kang et al. 2000; Lin et al. 2004), but the ability of clozapine to prolong the QT interval is questionable, in part due to the common occurrence of clozapine-induced sinus tachycardia. Because many ECG machines use the Bazett formula, the tendency is to overestimate the corrected QT interval due to Bazett’s limitations at heart rates >70 bpm (Dogan et al. 2005); moreover, the frequent presence of T-wave abnormalities with clozapine exposure creates further difficulties for the exact estimation of the QT interval. Orthostatic Hypotension. Orthostatic hypotension is defined as a sustained decrease in blood pressure exceeding 20 mmHg systolic or 10 mmHg diastolic occurring within 3 minutes of upright posture. Several antipsychotic drugs have the propensity to induce orthostatic hypotension due to potent α1-adrenergic antagonism. Among the atypical antipsychotics, clozapine and quetiapine are more often associated with orthostatic hypotension, which generally seems to be dosage dependent, with dizziness corresponding roughly to the extent of postural change. Orthostatic hypotension is often the limiting factor during the up-titration of clozapine, but tachyphylaxis will occur within weeks, so slowing the pace of titration may resolve the problem.

Cardiac Complications With Nonclozapine Antipsychotics Myocarditis and cardiomyopathy have been reported with antipsychotic drugs other than clozapine, but whether these cases are clearly medication related is unknown. The most common cardiac-related complications from nonclozapine antipsychotic drugs are due to ortho-

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static hypotension and QT prolongation, but one should not discount the long-term effects of dyslipidemia and weight gain on cardiovascular risk. Orthostatic hypotension is especially problematic for elderly patients due to poor vasomotor tone and can be troublesome due to the increased risk of falls. Slower titration schedules may permit tolerance to medication-induced postural changes and thereby diminish the risk of falls and syncope.

Coronary Heart Disease Coronary heart disease refers to the failure of coronary circulation, whereas cardiovascular disease reflects all consequences of atherosclerotic diseases, including stroke and diseases of the heart. In CHD patients, inadequate circulation to the myocardium leads to ischemia and eventually to angina or acute myocardial infarction. The typical cause of CHD is atherosclerosis due to an accumulation of cholesterol-laden atheromatous plaques in vessel walls that are prone to inflammation and eventual rupture with vessel thrombosis. CHD is the most common cause of death in Western societies and is responsible for about 20% of all deaths (British Heart Foundation 2007). Using baseline data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial, Goff et al. (2005) estimated 10-year CHD risk with the algorithm derived from the Framingham heart study (see Figures 7–6A and 7–6B) and found that patients with schizophrenia had an increased risk for CVD compared with matched subjects in the general population: 9.4% versus 7.0% for males and 6.3% versus 4.2% for females. Several factors are involved in this level of risk, including high smoking prevalence, sedentary lifestyle, obesity, medication effects, and perhaps the disease itself. Activity in the hypothalamic-pituitary-adrenal axis is increased in patients with schizophrenia and leads to increased levels of catecholamines and cortisol (E. Walker et al. 2008). Increased hypothalamic-pituitaryadrenal axis activity increases the risk for CVD, dyslipidemia, hypertension, vasoconstriction, and platelet activation, and might be another mechanism that increases CHD risk in schizophrenia patients. The CHD risk for any individual represents the sum of both nonmodifiable and modifiable factors. Nonmodifiable factors include age, gender, history of CVD, and genetic predisposition. Modifiable factors have been identified by large prospective trials, such as the INTERHEART study (Yusuf et al. 2004), and include the following:

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Smoking Diabetes Hypertension Abdominal obesity Inadequate daily consumption of fruits and vegetables Psychosocial factors, stress, and depression Insufficient exercise Alcohol intake

Risk factors are additive, and several lifestyle risk factors are known to be increased in patients with schizophrenia. Dyslipidemia is one modifiable CVD risk factor that is more prevalent in patients with schizophrenia. Certain antipsychotic drugs are associated with deleterious changes in serum cholesterol and triglyceride levels; moreover, the effects of these changes are compounded by the fact that patients with schizophrenia are less likely to receive treatment with statins (Hennekens et al. 2005). (See Chapter 6, “Effects of Antipsychotics on Serum Lipids,” for more information about dyslipidemia and antipsychotics.) Smoking increases CVD mortality risk by 60%–80%, and up to 80% of patients with schizophrenia smoke cigarettes (Hughes et al. 1986). Not only is smoking prevalence increased in this patient population, but smokers with schizophrenia inhale more deeply and extract more compounds from the cigarettes than do other smokers (Olincy et al. 1997). (For further information about smoking and schizophrenia, see Chapter 9, “Nicotine and Tobacco Use in Patients With Schizophrenia.”) Diabetes mellitus increases CHD risk by two- to threefold in men and three- to sixfold in women (Hennekens et al. 2005), and the prevalence of diabetes mellitus and prediabetic states such as metabolic syndrome are 1.5 to 2 times greater in patients with schizophrenia (Mukherjee et al. 1996) (see Chapter 4, “Obesity and Schizophrenia,” and Chapter 5, “Glucose Intolerance and Diabetes in Patients With Schizophrenia”). Alcohol and substance use are also more common in patients with schizophrenia (see Chapter 11, “Substance Abuse and Schizophrenia”). Lastly, a direct effect of antipsychotic drugs on myocardial infarction risk has been hypothesized as being mediated by vasospasm or induction of thrombosis. This suggestion emanates from epidemiological studies showing that patients receiving psychotropic medications have an increased risk of cardiovascular events; however, as discussed previously, this might be a confounding by indication more than a direct effect of antipsychotics.

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Hypertension Hypertension is defined as blood pressure >140/90 mmHg and is a well-established risk factor for CVD, including stroke and myocardial infarction (Wang et al. 2007). Patients with schizophrenia do not seem to be more prone to hypertension, but conflicting data have been reported on this subject. Clozapine has been shown in some studies to increase blood pressure during long-term treatment, but not all studies have shown similar findings (Henderson et al. 2004; Lund et al. 2001). However, the increase in weight associated with clozapine and olanzapine increases future hypertension risk, although this effect is often not seen for years.

Managing Coronary Heart Disease in Patients With Schizophrenia Treatment of CVD in schizophrenia is similar to that for the general population, although patient factors, including lack of motivation, poor communication skills, and poor medication compliance, make it difficult to achieve the same results. The first step in managing CVD risk is to obtain baseline data, including history of CVD, family CVD history, level of physical activity, tobacco and alcohol use, presence of other physical diseases conferring risk (especially diabetes and hypertension), and current medications. Obtaining a good medical history takes time, and more than one session might be needed for more severely ill patients. The clinician should talk to the patients about the nature and history of prior physical diseases, because some patients will deny or be reluctant to discuss these issues. Furthermore, a thorough physical examination is needed, including weight, central adiposity (waist circumference or hip:waist ratio), body mass index, and blood pressure. Laboratory values are also important and must include a fasting glucose and lipid panel, as well as an electrocardiogram in certain circumstances. The most important aspect of preventive CVD treatment is to reduce or remove modifiable risk factors by promoting smoking cessation, increased exercise, and healthier eating habits. The extent to which any interventions are successful will always depend on the patient’s motivation; however, one should bear in mind that patients with schizophrenia can achieve meaningful results but may need more motivational support. Ten-year risk of CHD can be estimated from the Framingham heart study algorithm (see Figure 7–6). For patients with

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two or more cardiovascular risk factors, the clinician should estimate their 10-year risk and provide appropriate interventions. In addition to lifestyle interventions that require active efforts on the part of the patient, other interventions require activity by the physician. These include treating the patient’s hypertension, recommending aspirin therapy, and carefully considering appropriate antipsychotic medication.

Treating Hypertension Before treating hypertension, the clinician should ensure that the patient has verifiable hypertension and not hypertension due to “whitecoat syndrome.” Blood pressure should be measured after having the patient sit in a chair or lie on a bed for 10 minutes. An end-of-visit blood pressure reading is likely to be more reflective of the patient’s true resting blood pressure than that obtained when the anxious patient first enters the office or clinic. The width of the cuff selected should be at least 40% of the circumference of the limb to be used. A common mistake is to use the wrong cuff size: a small cuff tends to overestimate blood pressure. Also, blood pressure measures should be repeated at least two times at two different occasions before hypertension is diagnosed. According to consensus guidelines, blood pressure should be monitored before antipsychotic treatment is initiated, 12 weeks after initiation, and then annually (American Diabetes Association et al. 2004). No formal guidelines exist for treating hypertension in patients with schizophrenia, but the clinician should inform patients about nonpharmacological interventions (e.g., exercise, weight loss, restriction of salt intake) and allow a period of up to 3 months to assess the effects of lifestyle modification. When medications are required, possible additive hypotensive effects with other medications should be taken into consideration, but otherwise a reasonable approach is to adapt general guidelines for hypertension treatment.

Aspirin Aspirin reduces myocardial infarction and stroke risk but at the expense of increased risk for gastrointestinal bleeding. The anticoagulant effect of aspirin is mediated through irreversible blockade of thromboxane A2 formation in platelets. Daily low-dose aspirin (81 mg) should be considered for patients with a history of CVD or CVD-equivalent disorders (e.g., diabetes mellitus, severe peripheral vascular disease) or for patients with moderate to high risk. Patients with schizophrenia should be educated about symptoms of gastritis and gastrointestinal bleeding

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Age

Points

Age

Points

20–34

–9

55–59

8

35–39

–4

60–64

10

40–44

0

65–69

11

45–49

3

70–74

12

50–54

6

75–79

13

Age 20–39

Total cholesterol mg/dL (mmol/L)

Age 40–49

Age 50–59

Age 60–69

Age 70–79

< 160 (< 4.1)

0

0

0

0

0

160–199 (4.1–5.2)

4

3

2

1

1

200–239 (5.3–6.2)

7

5

3

1

0

240–279 (6.3–7.2)

9

6

4

2

1

11

8

5

3

1

≥ 280 (≥ 7.3) Age 20–39

Age 40–49

Age 50–59

Age 60–69

Age 70–79

Nonsmoker

0

0

0

0

0

Smoker

8

5

3

1

1

Tobacco

HDL mg/dL (mmol/L)

Points

≥ 60 (≥1.6)

–1

50–59 (1.3–1.5)

0

40–49 (1.0–1.2)

1

< 40 (< 1.0)

2

Point total

If untreated

If treated

< 120

Systolic BP (mmHg)

0

0

120–129

0

1

130–139

1

2

140–159

1

2

≥160

2

3

10-Year cardiovascular risk (%)

Point total

10-Year cardiovascular risk (%)

<1

11

8

<0 0–4

1

12

10

5

2

13

12

6

2

14

16

7

3

15

20

8

4

16

25

9

5

≥17

≥ 30

10

6

FIGURE 7–6A. for males.

Framingham 10-year cardiovascular risk estimation charts

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Age

Points

Age

195

Points

20–34

–7

55–59

8

35–39

–3

60–64

10

40–44

0

65–69

12

45–49

3

70–74

14

50–54

6

75–79

16

Age 20–39

Total cholesterol mg/dL (mmol/L)

Age 40–49

Age 50–59

Age 60–69

Age 70–79

< 160 (< 4.1)

0

0

0

0

0

160–199 (4.1–5.2)

4

3

2

1

1

200–239 (5.3–6.2)

8

6

4

2

1

240–279 (6.3–7.2)

11

8

5

3

2

≥ 280 (≥ 7.3)

13

10

7

4

2

Age 20–39

Age 40–49

Age 50–59

Age 60–69

Age 70–79

Nonsmoker

0

0

0

0

0

Smoker

9

7

4

2

1

Tobacco

HDL mg/dL (mmol/L)

Points

≥ 60 (≥1.6)

–1

50–59 (1.3–1.5)

0

40–49 (1.0–1.2)

1

< 40 (< 1.0)

2

Point total

Systolic BP (mmHg)

If untreated

If treated

< 120

0

0

120–129

1

3

130–139

2

4

140–159

3

5

≥160

4

6

10-Year cardiovascular risk (%)

Point total

<1

19

8

1

20

11 14

<9 9–12

10-Year cardiovascular risk (%)

13

2

21

14

2

22

17

15

3

23

22

16

4

24

27

17

5

≥ 25

≥ 30

18

6

FIGURE 7–6B. for females.

Framingham 10-year cardiovascular risk estimation charts

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(e.g., tarry stools, midepigastric pain between meals), and those taking aspirin should be questioned about gastrointestinal side effects because their self-report rates are lower than for the general population.

Type of Antipsychotic Medication The metabolic side effects of atypical antipsychotic drugs differ greatly. Although olanzapine and clozapine are associated with greater risk for weight gain than the other atypical antipsychotics, in practice almost any of these drugs is associated with greater weight gain than placebo. Switching from a drug with high metabolic liabilities to a lower-risk drug can lead to substantial weight loss and other metabolic improvement, but in some cases switching to a lower-risk drug is not possible due to risk of psychotic relapse, especially in patients treated with clozapine. For clozapine-treated patients, standard treatment for dyslipidemia and glucose intolerance should be offered, and some data indicate that adding a metabolically low-risk atypical antipsychotic (e.g., aripiprazole) combined with judicious reduction of the clozapine dosage can be beneficial, although evidence for this combination remains sparse. Treating patients with schizophrenia always requires a balance between efficacy and side effects. Causing diabetes due to direct drug-related mechanisms or secondary to antipsychotic-induced weight gain is devastating, but not treating schizophrenia can be fatal. Any choice of an agent should be balanced by the knowledge that this is a patient population at high risk for cardiovascular disease and related mortality; therefore, every effort should be made to minimize the iatrogenic contributions to this risk equation.

Access to Somatic Treatment Patients with schizophrenia are less likely than the general population to receive proper treatment for their medical comorbidities (Goldman 1999), a fact related to patient lifestyle variables, lack of health insurance, and systemic health care issues. (See Chapter 1, “Improving Physical Health Care for Patients With Serious Mental Illness,” for more discussion of these topics.) Patients with schizophrenia often have negative symptoms that result in less motivation to seek care and decreased drive to maintain good physical health. Poor communication skills and decreased pain sensitivity can lead to underreporting of symptoms, making diagnosis of health conditions more difficult (Singh et al. 2006). Marchand (1955) reported that up to 85% of psychotic patients were noted to have experienced an acute myocardial infarction without having any pain, compared with 29% of acute myocardial infarction pa-

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tients in the Framingham heart study. In acute myocardial infarction cases presenting without pain, the infarction is often untreated and first recognized on a subsequent routine electrocardiogram or postmortem during an autopsy. This lack of pain sensitivity emphasizes the need for monitoring of cardiovascular risk elements in all patients with schizophrenia, because the actual myocardial infarction event may go unrecognized and untreated. An important theme throughout this book is the need for psychiatric providers to assume responsibility for physical health monitoring of patients with schizophrenia. Many patients with schizophrenia do not regularly receive primary care, and primary care providers might be reluctant to monitor and treat physical disease due to the barriers posed by presence of a severe mental illness. As discussed in Chapter 1, “Improving Physical Health Care for Patients With Serious Mental Illness,” several possible models have been proposed for integrating psychiatric care and medical care for this patient population, but the fact remains that all doctors caring for schizophrenia patients must be alert for signs of physical disease and be prepared to perform basic physical health monitoring (Brown 1997).

Key Clinical Points ◗

Cardiovascular heart disease is the most common cause of death in patients with schizophrenia.

◗

Drug-induced torsade de pointes is rare and accounts for a fraction of sudden-death cases.

◗

Reducing risk factors and treating comorbidities (e.g., obesity, hypertension, dyslipidemia, smoking) are the cornerstones of the treatment and prevention of cardiovascular disease.

◗

Clozapine is associated with both myocarditis and cardiomyopathy. Cardiovascular disease attributable to clozapine’s metabolic properties is estimated to cause more deaths than agranulocytosis.

◗

Switching antipsychotic medications to a metabolically lower-risk drug can lead to substantial weight loss and metabolic improvements.

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CHAPTER 8 Behavioral Treatments for Weight Management of Patients With Schizophrenia Rohan Ganguli, M.D., F.R.C.P.C. Tony Cohn, M.B.Ch.B., M.Sc., F.R.C.P.C. Guy Faulkner, B.Ed., M.Sc., Ph.D.

An explosion of articles in the last decade has called attention to the high prevalence of metabolic abnormalities, such as obesity, diabetes, dyslipidemias, and associated problems, in persons with severe mental illness. As pointed out in Chapter 2, “Excessive Mortality and Morbidity Associated With Schizophrenia,” increasingly robust evidence also indicates that in Europe and North America, people with schizophrenia and other serious mental illnesses die 20–25 years earlier on average than comparable persons in the general population (Hennekens et al. 2005; McGrath et al. 2008; Osby et al. 2000; Saha et al. 2007). Data also suggest that the increased prevalence of some risk factors for early mortality from cardiovascular disease and diabetes may have been present in individuals with psychotic illnesses as long as 100 years ago. For 203

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example, long before the advent of modern antipsychotic medications, astute clinicians had noted that recovery in psychotic illness is often accompanied by weight gain (Jaspers 1923; Kraepelin 1919). Much of the recent attention to metabolic issues in serious mental illness is linked to the widespread use of novel antipsychotics. However, patients and some observant practitioners had already highlighted medication-associated weight gain as a common side effect of most antipsychotics from the class now called first-generation antipsychotics (see Ganguli 1999 for a review). For example, Buis (1992) reported that weight gain was one of patients’ most frequent complaints about the side effects of conventional depot antipsychotics. Although some novel antipsychotics, notably clozapine and olanzapine, are associated with especially high risk of weight gain (and insulin resistance and diabetes), all antipsychotics except molindone result in more clinically significant weight gain than placebo in randomized clinical trials (Casey et al. 2004). Despite the long-standing nature of the problem and its importance to consumers and to their general health status, few intervention studies have addressed weight gain and its associated risks for people with schizophrenia. From a practical perspective, the interventions that have been used for persons with schizophrenia have focused almost exclusively on weight reduction. Focusing on weight reduction as a strategy to reduce the risk of cardiovascular disease and diabetes is completely consistent with the approach being taken in studies funded by the National Institutes of Health, such as the LOOK-AHEAD study (Ryan et al. 2003; see also Look AHEAD Research Group 2007), and with National Heart, Lung, and Blood Institute (1998) recommendations. Thus, in this chapter we focus on studies aimed at weight reduction. With respect to nonpharmacological approaches to weight reduction, the majority of studies have used techniques based on behavioral therapy principles, so before discussing the approaches, we briefly review the behavioral techniques common to most weight loss programs.

Principles of Behavioral Approaches to Weight Loss As reviewed by Wing (2004), the systematic application of behavioral therapy techniques to induce weight loss started in the late 1960s. The early studies tended to treat milder forms of overweightness and obesity, through a focus on stimulus control rather than on specific calorie-

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intake goals or exercise and activity. In reviewing these early programs, Wadden et al. (2004) noted that weight loss of 4–5 kg was common in programs typically lasting 10 weeks. During the 1970s and 1980s, as the prevalence of obesity grew, treatments became more sophisticated and comprehensive, and tended to last for longer. By the mid-1990s, average weight loss in behavioral programs, which typically lasted for 6 months, had risen to about 9 kg, or about double what had been reported in the 1960s (Wing 2004). Probably one of the most persuasive demonstrations of the efficacy of behavioral methods for weight loss was the Diabetes Prevention Trial, in which over 3,000 overweight or obese individuals with impaired glucose tolerance were randomized to a lifestyle intervention aimed at weight loss, metformin, or placebo. Not only was significant weight reduction achieved in the lifestyle group, but progression to diabetes was also reduced (Knowler et al. 2002). Furthermore, not only was behavioral treatment twice as effective as metformin in producing weight loss, but the intervention was so effective in preventing the progression of prediabetes to diabetes that the trial was stopped prematurely (Knowler et al. 2002). The key components for the nonpharmacological management of overweight and obesity are identified in Table 8–1. Most approaches to the treatment of obesity are described as “behavioral” and are based on learning theory (Wing 2004) and the principles of classical conditioning (Wadden and Foster 2000). In the last 20 years or so, cognitive approaches have been added to behavioral therapy to restructure and correct distorted and irrational thoughts that undermine motivation and progress in treatment (Wadden and Foster 2000). Common components of most behavioral weight reduction programs include 1) goal-setting, especially establishing realistic short-term goals (Bandura 1977); 2) self-monitoring (Kazdin 1974) of nutritional intake and physical activity; 3) a nutritional focus, with teaching and demonstrating of healthy eating habits (Brownell 2004; Wing 1989); and 4) strategies to increase exercise and decrease sedentary behavior (Jakicic 2002; Jakicic and Gallagher 2003; Jakicic et al. 2004). Stimulus control, by changing the environment to alter cues so as to increase appropriate (and decrease inappropriate) eating behavior, was also an early component of behavioral programs (Ferster et al. 1962; Stuart 1967). Problem solving (D’Zurilla and Goldfried 1971) is often included to help individuals develop strategies individualized to their own unique situations (Wing 2004). Once weight loss is achieved, most programs move participants to relapse prevention or weight maintenance regimens (Brownell et al. 1986; Jeffery and French 1997; Klem et al. 2000; Perri et al. 2001; Wadden et al. 2004). Because these strategies are often offered

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TABLE 8–1.

Key components for the management of overweightness and obesity

Component

Key points for management

Diet

Energy intake should be reduced by 500–1,000 kcal/day. Dietary fat should be restricted to <30% of energy intake. Optimal intakes of carbohydrate and protein have not been established.

Exercise

Significant health benefits will occur with 150 minutes of moderate exercise (at 55%–69% of maximum heart rate) per week. Overweight and obese individuals should increase moderate exercise to 200–300 minutes per week.

Behavioral therapy

Training should be given in behavioral concepts (e.g., problem solving, goal setting, social support). Such training is associated with improved long-term outcomes.

Source.

Adapted from Jakicic et al. (2001).

as a package, determining which program components are essential to the efficacy of the treatments is difficult. Recently, cognitive-behavioral therapy (CBT) has attempted to distinguish itself from behavioral therapy by pointing out that the former specifically includes restructuring cognitive processes (Cooper and Fairburn 2002). In the studies of weight loss in individuals with schizophrenia, the approaches have included one or more elements of common behavioral approaches, but in many instances, the precise theoretical underpinnings of the program components have not been specified. A selective review of interventions for weight loss in schizophrenia follows.

Behavioral and Nutritional Interventions in Schizophrenia One of the earliest published attempts to assist psychotic patients with weight loss was carried out in a state hospital in the United States, more than 40 years ago, by Harmatz and Lapuc (1968). This pioneering study involved a rigorous behavioral program using negative reinforcement:

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one group of patients lost money if they failed to lose weight. Two comparison groups included a group that discussed weight loss strategies and provided peer support and a group that received nutritional counseling. The subjects were randomly assigned to one of the three groups. The group assigned to contingent negative reinforcement had significantly greater mean weight loss than the other two groups (−7% of initial body weight over 10 weeks). In a second historically important study, Rotatori et al. (1980) recruited patients with psychotic illness residing in community-based group homes. Patients were then randomly assigned to either a 14-week behavioral weight loss group intervention, closely resembling most modern weight loss programs, or to no intervention (“usual care”). The group randomly assigned to behavioral treatment lost significantly more weight (mean −3.3 kg) than the control group (mean +0.02 kg). The Rotatori et al. study is notable for the use of a well-developed manual for the delivery of treatment, and the behavioral techniques employed had already been refined in earlier studies of patients with Down syndrome. We highlight these early studies because they dealt with populations that are still relevant today: severely mentally ill persons who are in long-stay hospitals as well as those in community residential services. These early (first-generation) studies also deserve more recognition for the following reasons: 1) they demonstrated that patients with psychotic illnesses could participate successfully in nonpharmacological weight loss interventions, and 2) even though these were pioneering studies, they were well-designed randomized trials, in the best traditions of generating evidence for clinical practice. Surprisingly, the second generation of published studies was, for the most part, uncontrolled, or failed to employ random assignment to the intervention or comparison conditions. Fortunately, the most recent generation (third generation) of reports is predominantly from randomized controlled trials, and thus a good evidence base is growing. Numerous reviews have been published of behavioral and nutritional interventions for weight loss in patients with schizophrenia (e.g., Alvarez-Jiménez et al. 2008; Faulkner and Cohn 2006; Faulkner et al. 2007; Ganguli 2007; Loh et al. 2006; Strassnig and Ganguli 2007; Werneke et al. 2003). All reviews concluded that modest short-term weight loss is possible in this population. In a recent meta-analysis that examined randomized controlled trials only, Alvarez-Jiménez et al. (2008) reported a statistically significant reduction in mean body weight for those in the nonpharmacological intervention groups compared with those on treatment as usual (weighted mean difference [WMD]=−2.56 kg, 95% CI −3.20 to −1.92, P<0.001) at the end of treat-

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ment. The effect was slightly larger but not significant in studies designed to prevent weight gain. Additionally, no statistically significant or practically important differences were evident between therapeutic approaches using individual compared with group interventions or using CBT compared with nutritional counseling (Alvarez-Jiménez et al. 2008). Rather than review each of the included randomized clinical trials in detail, we summarize them in Table 8–2. Seven of the 12 included trials investigated CBT strategies (Alvarez-Jiménez et al. 2006; Brar et al. 2005; Jean-Baptiste et al. 2007; Khazaal et al. 2007; Kwon et al. 2006; McKibbin et al. 2006; Weber and Wyne 2006); three described nutritional counseling interventions (Evans et al. 2005; Littrell et al. 2003; Scocco et al. 2006); and two combined nutritional and exercise interventions and compared this type of intervention with standard care (Wu et al. 2007) or metformin alone or in combination (Wu et al. 2008). Six trials tested group intervention formats (Brar et al. 2005; Jean-Baptiste et al. 2007; Khazaal et al. 2007; Littrell et al. 2003; McKibbon et al. 2006; Weber and Wyne 2006), and the remaining six examined individual interventions (Alvarez-Jiménez et al. 2006; Evans et al. 2005; Kwon et al. 2006; Scocco et al. 2006; Wu et al. 2007, 2008). Eight studies were designed to treat weight gain, whereas the remaining four studies were designed to prevent weight gain, typically after patients started taking or were switched to an atypical antipsychotic (Alvarez-Jiménez et al. 2006; Evans et al. 2005; Littrell et al. 2003; Scocco et al. 2006). Participants were generally outpatients, except three studies included inpatients (Alvarez-Jiménez et al. 2006; Wu et al. 2007) or a combination (Khazaal et al. 2007). Interventions lasted from 8 to 24 weeks, with an average of approximately 15 weeks. Five studies reported a follow-up assessment of 8 weeks (Littrell et al. 2003), 24 weeks (Evans et al. 2005; Khazaal et al. 2007; Scocco et al. 2006), or 6 months (McKibbin et al. 2006). In the next paragraphs, we highlight some of these studies that bring up issues we address in the discussion, including two studies (Jean-Baptiste et al. 2007; Wu et al. 2008) not incorporated in Alvarez-Jiménez et al.’s (2008) meta-analysis. In the first of the randomized controlled clinical trials, Litrell et al. (2003) provided a 16-week psychoeducational program, focusing on nutrition, exercise, and healthy lifestyle, to patients who had been switched to olanzapine from other antipsychotics. That all the patients in this study were on one drug is notable, because in many other studies, treatment effects are potentially confounded by medication effects and interactions. Litrell et al. reported little weight change in the intervention subjects as opposed to a statistically significant weight gain in

TABLE 8–2. Randomized, controlled trials of behavioral interventions for weight gain in schizophrenia Intervention

Littrell et al. 2003 (N=70) Prior conventional antipsychotics, commencing olanzapine at study entry

16 weekly 1-hour group sessions Intervention: −0.3 kg; usual care: +4.3 kg. Compliance rate of 92% to program sessions. No dropout rate for diet and exercise education vs. usual care; 2-month follow-up reported.

Brar et al. 2005 (N =72) BMI> 26, switched from olanzapine to risperidone

Two sessions per week for 6 weeks then one session per week for 8 weeks of diet and exercise education vs. usual care (encouraged to lose weight)

Intervention: −2.0 kg; usual care: −1.1 kg (NS). 5% weight loss in 32.1% of intervention subjects vs. 10.8% in control group. 15/28 patients attended all 20 sessions. 21% dropout rate in treatment group.

Evans et al. 2005 (N = 51) Commenced olanzapine within 12 weeks of study entry

Six 1-hour individual nutrition education sessions over 3 months (every 2 weeks) vs. usual care (plus passive nutrition information)

Intervention: +2.0 kg; usual care: +9.9 kg. Fewer patients in experimental group (13%) than in control group (64%) increased initial body weight by more than 7%. Compliance not reported. 21% dropout rate in treatment group.

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Outcome at final assessment (weight change), compliance, and attrition

Authors and participants

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TABLE 8–2. Randomized, controlled trials of behavioral interventions for weight gain in schizophrenia (continued) Outcome at final assessment (weight change), compliance, and attrition

Intervention

Alvarez-Jiménez et al. 2006 (N =61) First-episode psychosis and <6 weeks antipsychotic exposure. Treated with: risperidone, olanzapine, haloperidol

10–14 individual sessions Intervention: +4.1 kg; usual care: +6.9 kg. Fewer patients (psychoeducation, behavioral in experimental group (39.3%) than in control group therapy, dietary counseling, (78.8%) increased initial body weight by more than 7%. exercise program) for 3 months Compliance not reported. No dropouts, and all patients vs. usual care completed study.

Kwon et al. 2006 (N= 48) More than 7% body weight gain on olanzapine

Weekly individual sessions with dietitian and exercise coordinator over 12 weeks (weekly for first 4 weeks, then every 2 weeks) vs. usual care

McKibbin et al. 2006 (N =64) Schizophrenia and diabetes diagnosis

Weekly 90-minute group sessions Intervention: −2.3 kg; usual care: +3.1 kg. 5% weight loss in 38% of intervention subjects vs. 12% of control group. for 24 weeks focused on 80% of treatment group attended at least half of diabetes education, nutrition, and exercise vs. usual care (plus intervention sessions. No difference in dropout rates between intervention and usual care groups. passive information)

Intervention: −3.9 kg; usual care: −1.5 kg. Diet group: all were over 80% compliant; exercise group: 36% were over 80% compliant. 33% dropout rate in treatment group.

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Authors and participants

TABLE 8–2. Randomized, controlled trials of behavioral interventions for weight gain in schizophrenia (continued) Intervention

Scocco et al. 2006 (N = 20) 8-week individual dietary Switched to olanzapine from intervention provided by a conventional antipsychotics nutritionist

Outcome at final assessment (weight change), compliance, and attrition Intervention: +0.99 kg; control: +2.96 kg. Compliance not clearly reported. Dropouts: intervention 0/10, control 2/10.

Weber and Wyne 2006 (N =17) 16 weekly 1-hour group sessions Intervention: −2.5 kg; usual care: −0.6 kg (NS). BMI> 25, taking secondfor diet and exercise education Compliance not reported. No dropout in treatment generation antipsychotics vs. usual care group. Intervention: −2.8 kg; usual care: +2.7 kg. Compliance Jean-Baptiste et al. 2007 (N =18) Weekly group sessions for BMI> 30, taking any 16 weeks with psychoeducation, not reported. 14/18 completed intervention. antipsychotic goal setting, self-monitoring; $25/week for healthy foods Khazaal et al. 2007 (N= 61) >2 kg weight gain over 6 months on any antipsychotic

Weekly 2-hour group cognitivebehavioral therapy plus psychoeducation for 12 weeks vs. a single 2-hour nutrition education session

Intervention: −2.9 kg; usual care: −0.8 kg. At end of treatment, 16.1% of experimental group vs. 13.3% of control group had lost 5% or more of initial BMI. This increased to 22.6% and 16.7% at 12-week follow-up.

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Follow-up (12 weeks postintervention): Intervention : −3.5 kg; usual care: +1.7 kg. Compliance not reported. Dropouts: intervention 8/31, control 7/30.

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Authors and participants

Outcome at final assessment (weight change), compliance, and attrition

Intervention

Wu et al. 2007 (N = 56) BMI≥ 27, clozapine (≥300 mg/day) for at least 1 year

Diet (inpatients) reduced by Intervention: −4.2 kg; usual care: +1 kg. Compliance not 200–300 kcal/day; walking reported. No dropouts in treatment group. (level and stairs) for 60 minutes 3 days a week for 6 months

Wu et al. 2008 (N = 128) First-episode schizophrenia, gained more than 10% of body weight

Psychoeducation, diet, and exercise (lifestyle intervention) over 12 weeks vs. usual care (placebo), metformin, and lifestyle plus metformin

BMI=body mass index; NS=not signficant.

Lifestyle intervention: −1.4 kg; usual care: +3.1 kg; metformin: +3.2 kg; lifestyle plus metformin: −4.7 kg. Compliance: Diet 61%–84%; exercise 50%–60%. Dropouts: Lifestyle plus metformin 2/32, lifestyle only 3/32.

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Authors and participants

Note.

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TABLE 8–2. Randomized, controlled trials of behavioral interventions for weight gain in schizophrenia (continued)

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the control group. Thus, the benefit of the intervention might have been to prevent weight gain rather than to produce weight loss. Because olanzapine carries a very high risk of clinically significant weight gain (Newcomer 2005), and weight gain in adulthood is a powerful predictor of cardiovascular disease (Nanas et al. 1987; Pan et al. 1986), prevention of weight gain is a worthwhile benefit of treatment. Prevention of weight gain was the focus of a study reported by Alvarez-Jiménez et al. (2006). In an early behavioral intervention group, 10–14 individual sessions were completed with a clinical psychologist within the first 3 months of antipsychotic treatment. The sessions consisted of a weight check, agenda setting, review of self-monitoring records, and assigning new homework. Modules were available on engagement and assessment, psychoeducation, dietary counseling, exercise, and behavioral therapy. Selection of the intervention strategies was based on a collaborative formulation after initial assessment between the therapist and the patient. At the end of treatment, significantly fewer patients in the intervention group increased their baseline weight by more than 7% (39.3% vs. 78.8%). All participants randomized completed the trial. Brar et al. (2005) developed a manualized 16-week intervention, adapted from the study conducted by Rotatori et al. (1980). This study also controlled for confounding effects of medication by first switching all subjects to the same antipsychotic (risperidone). This is also one of the few studies to use blinded raters. Participants enrolled because they desired to lose weight. Also of note, regular mental health clinicians, as opposed to specialists in behavioral therapy or nutrition, delivered the intervention, following the manual. This approach was an attempt to make the results more likely transferable to routine clinical care. Mean weight loss in this study was larger in those randomly assigned to the intervention, but both groups lost weight, and the difference was not statistically significant. However, the proportion of subjects who lost 5% or more of their baseline body weight was three times larger in subjects randomized to the intervention than in controls (32.1% vs. 10.8%), and the difference was statistically significant. Jean-Baptiste et al. (2007) published data from an outpatient study that used standard behavioral techniques from a widely accepted program (Brownell 2004); however, to the standard nutrition and exercise program, they added a novel indirect method of food provision. Subjects were given lists of “healthy” food choices and then, at weekly group sessions, were reimbursed for the cost of these foods, provided they had receipts showing that they had purchased these food items in the previous week. Mean weight loss was statistically significantly

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greater in the intervention group than in controls. Jean-Baptiste et al. (2007) also conducted a 6-month follow-up and reported continuing weight loss of participants, but the number of subjects was only 12, leaving some uncertainty about the robustness of the results. Nevertheless, this is a promising rigorous evaluation of a multimodal approach and needs to be followed up. Focusing on patients with both schizophrenia and diabetes, McKibbin et al. (2006) recruited patients from board-and-care and community clubhouse settings. Optimal diabetes management requires active selfmanagement, including weight control and weight loss. Patients with schizophrenia often have difficulty accessing and participating in comprehensive diabetes management programs. This study illustrates the effectiveness of a well-constructed intervention geared for patients with schizophrenia and diabetes. The 24-week training program was developed in collaboration with a community advisory board that comprised consumers, family members, and community clinicians and consisted of weekly, 90-minute group sessions addressing diabetes education, nutrition, and exercise. Educational material was adapted by limiting text, introducing one or two topics per session, providing an overview and summary of material, and using a teach-and-query training method and mnemonic aids. Concrete behavior change strategies included weekly weigh-ins, pedometers, healthy food sampling, and reinforcements (raffle tickets for small health gains). Patients in the intervention group lost a mean of 2.3 kg, compared with a mean weight gain of 2.7 kg in those receiving usual care (medical follow-up and written diabetes information). The intervention group also showed significant improvements in diabetes knowledge and self-efficacy, as well as self-reported physical activity, but not in fasting plasma glucose or glycosylated hemoglobin. In the largest study to date (Wu et al. 2008), 128 first-episode schizophrenia patients were randomly assigned to one of the following: 12 weeks of placebo, 750 mg/day of metformin alone, 750 mg/day of metformin and lifestyle intervention, or lifestyle intervention only. The lifestyle intervention included psychoeducational, dietary, and exercise programs. Psychoeducation focused on the role of eating and activity in weight management. Dietary intervention followed the American Heart Association Step II diet, which recommends less than 30% of total calories from fat (<7% saturated fat and <200 mg of cholesterol), 55% from carbohydrates, more than 15% from protein daily, and fiber intake of at least 15 g per 100 kcal. Participants maintained a 3-day food diary at baseline, and a dietitian reviewed their diets and provided feedback at follow-up sessions. In the first week, exercise sessions were directed

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by an exercise physiologist, and participants performed exercise (walking or jogging) on a treadmill seven times a week for 30 minutes at each session. After the first week, exercise was home-based, with recommendations to exercise 30 minutes per day. At the end of the trial, the lifestyle intervention plus metformin group (−4.7 kg, 95% CI −5.7 to −3.4) had results superior to those of either the lifestyle intervention alone (−1.4 kg, 95% CI −2.0 to −0.7) or the metformin alone (−3.2 kg, 95% CI −3.9 to −2.5) groups. Metformin alone was more effective in weight loss and improving insulin sensitivity than lifestyle interventions alone. Notably, although considerable rigor is required to induce weight loss, in terms of maintaining a negative energy balance, in all of the identified randomized clinical trials, dropouts have generally not been a concern in the treatment arm. This might suggest that patients can be motivated to initiate and then adhere to a lifestyle intervention for weight management, at least in the short term. Dropout rates have not been as high as reported in a recent review (Loh et al. 2006), although attention must be given to the development of retention strategies to minimize dropouts (Faulkner and Cohn 2006). Furthermore, no adverse effects explicitly linked to participating in a lifestyle intervention program have been reported.

Discussion The results achieved from weight loss interventions in persons with schizophrenia (WMD =−2.56 kg; Alvarez-Jiménez et al. 2008) are within the range of those reportedly obtained by commercial weight loss programs in the general population (Heshka et al. 2003), although not as great as suggested by a meta-analysis of randomized clinical trials of CBT combined with a diet and exercise intervention (WMD =−4.9 kg, CI −7.3 to −2.4; Shaw et al. 2005). However, a reasonable question is whether such modest improvements actually translate into measurable improvements in health status or risk of cardiovascular disease and diabetes. The general agreement is that in obese individuals, even a 5% weight loss can produce measurable health benefits. For example, in the Finnish Diabetes Prevention Study, a modest weight loss of 4.8% of initial body weight was associated with a 58% reduction in the risk of developing diabetes over the following 3 years (Tuomilehto et al. 2001). As little as 3–4 kg of weight loss over 3 years results in clinically significant reductions in systolic and diastolic blood pressure (Mertens and Van Gaal 2000). Also, accumulating evidence from prospective observational studies indicates that increasing physical activity is effective in improving the health profile of individuals who are overweight and

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obese (e.g., Lee et al. 1999). Weight loss might be considered a primary goal, but clinicians should keep in mind that small, sustained positive changes in physical activity and dietary intake may be associated with significant health benefits irrespective of weight loss per se. With very few exceptions, even randomized controlled interventions have rarely followed patients for longer than 6 months. Weight loss is challenging, but even more challenging is weight loss maintenance (Wing et al. 2006). Obesity is unquestionably a chronic condition, and it is likely that long-term success may require some form of maintenance treatment. Hence, the real health benefits of weight loss interventions, even for those who respond to interventions, will be known only when data from longer studies become available. Fortunately, several ongoing clinical trials have up to 2 years of follow-up in their designs. Overall, interventions will probably need to set realistic goals, be highly structured, provide early and intensive support initially, and offer reduced but continued support over time if not indefinitely (Faulkner and Cohn 2006). Most currently published research has evaluated pharmacological and nonpharmacological treatments for weight loss in separate studies (pharmacological treatments are reviewed in Chapter 4, “Obesity and Schizophrenia”). However, evidence is accumulating that combining behavioral and pharmacological weight loss interventions can be more effective than either approach alone (Wadden et al. 2005). One study has been published that demonstrates the greater effectiveness of combined weight loss interventions specifically in patients with schizophrenia (Wu et al. 2008). However, given concerns about potential polypharmacy, the demands of adding further medication to an existing medical regimen, and the cost of medication, we suggest that adjunctive pharmacotherapy for weight loss be reserved for patients who do not respond adequately to lifestyle interventions alone (Faulkner et al. 2007). Further studies evaluating the combination of behavioral and pharmacological weight loss therapies are required before routinely recommending such a dual approach in clinical practice. Switching a patient to an antipsychotic medication with low liability for weight gain has also emerged as an effective strategy for weight loss and metabolic benefit, particularly when the increase in weight was clearly associated with prior antipsychotic treatment (Weiden 2007; Weiden and Buckley 2007) (see Chapter 4). No studies to date have investigated the combination of antipsychotic switching and behavioral strategies for weight loss.

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Given that the current system of care for persons with severe mental illness is routinely described as underfunded and overburdened (Frank and Glied 2006), economic considerations may well determine which interventions for weight loss, if any, will make it to the front lines of community mental health. Thus, cost-benefit analyses should be included in the evaluation of proposed interventions. At this point, such analyses are almost entirely missing from the evidence base on this subject. Even without sophisticated economic analyses, clinicians should be able to evaluate the potential benefit of investing time and resources in particular interventions if the published results systematically reported the proportions of subjects who benefited and, preferably, the number needed to treat for each threshold of response. Unfortunately, most studies already published limit the results to reporting mean changes in body weight.

Conclusion On the basis of existing studies, we can conclude that persons with schizophrenia want to and will participate in behavioral weight loss interventions. For individuals who are unmotivated or difficult to engage, consideration could be given to broader environmental interventions that aim to shape the environment in ways that are conducive to encouraging greater physical activity while restricting energy intake (Gorczynski et al. 2008). Taken together, the evidence from controlled trials indicates that patients who do participate in weight loss interventions increase their chances of losing weight. The results of simple and practical interventions are modest but clinically meaningful. The data on long-term maintenance of weight loss is essentially lacking, but some ongoing studies will provide data in the next few years. The data on preventing weight gain in persons with schizophrenia is developing and looking positive. With these observations in mind, standard behavioral weight loss interventions should be widely and routinely offered to patients with schizophrenia who are overweight or obese. In addition, discussion about the risk of weight gain and monitoring of weight should be routinely offered to all patients with schizophrenia. Given that the current trend is for the rates of obesity to continue to increase, research into enhancing the effectiveness of current interventions and the development of new approaches to weight loss need to be urgently funded.

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Key Clinical Points ◗

Education about the health hazards of being overweight or becoming overweight should be included in the psychoeducational interventions offered to persons with schizophrenia, along with simple advice about health nutrition and exercise measures.

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Regular measurement of body weight should be part of routine care in mental health settings, and patients should be given feedback on their own weight regularly. Patients should also be encouraged to weigh themselves.

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Patients who ask for active interventions to help them lose weight should be offered group or individual interventions, preferably within the mental health treatment setting.

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Referral to specialized programs, including the full range of options for severe and/or treatment-resistant obesity, should be pursued for patients who are in need of these services.

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CHAPTER 9 Nicotine and Tobacco Use in Patients With Schizophrenia Andrea H. Weinberger, Ph.D. Tony P. George, M.D., F.R.C.P.C.

Epidemiology and Significance of the Problem Patients with schizophrenia have a high prevalence of cigarette smoking based on clinical (58%–88%) and population-based (45%) samples (Kalman et al. 2005) compared to the general population rate of approximately 20.5% (Giovino 2007). Also, smoking cessation rates are lower in patients with schizophrenia than in nonpsychiatric control smokers

We thank Erin L. Reutenauer, B.A., for assistance with this work. This work was supported by National Institute on Drug Abuse grants K02-DA16611, R01DA13672, R01-DA14039 (to Dr. George), and K12-DA000167 (to Dr. Weinberger); National Alliance for Research in Schizophrenia and Depression (NARSAD) Young Investigator (to Dr. Weinberger) and Independent Investigator (to Dr. George) Awards; and the University Chair in Addiction Psychiatry at the University of Toronto (to Dr. George).

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(Kalman et al. 2005). Despite the fact that patients with schizophrenia constitute only about 1% of the general population, the medical and economic burden of cigarette smoking on mentally ill persons is enormous (Kalman et al. 2005). For example, the rates of smoking-related illnesses such as cardiovascular disease and certain cancers appear to be higher in patients with schizophrenia than in the general population (Capasso et al. 2008). Hence, an urgent need exists to address tobacco addiction in this population through the development of effective treatments, both pharmacological and behavioral. A better understanding of the biology of tobacco addiction in patients with schizophrenia may assist in the development of better treatments for tobacco use in this vulnerable population.

Pathophysiology of Schizophrenia: Relationship to Nicotinic, Dopaminergic, and Glutamatergic Effects Over the past 20 years, scientific understanding of both the neurobiology of schizophrenia and nicotine addiction has been increasing. For the purposes of this discussion, nicotine is assumed to be the active ingredient in tobacco and cigarette smoking that exerts psychopharmacological effects, although other components of tobacco smoke may be active in this respect (George and O’Malley 2004). There are three possible reasons for the high comorbid rates of nicotine addiction and schizophrenia: 1) self-medication of clinical and cognitive deficits associated with schizophrenia by tobacco use; 2) abnormalities in brain reward pathways in patients with schizophrenia that make these patients vulnerable to tobacco (and other drug) use; 3) common genetic and environmental factors that are independently associated with both smoking and schizophrenia. We briefly describe next the pharmacological effects of nicotine, including its effects on neurotransmitter systems critical to the neurobiology of schizophrenia, and how such effects may link nicotine addiction with schizophrenia. Nicotine alters the function of neurotransmitter systems implicated in the pathogenesis of major psychiatric disorders, including dopamine, norepinephrine, serotonin, glutamate, gamma-aminobutyric acid (GABA), and endogenous opioid peptides (Dani and Bertrand 2007). Nicotine’s receptor in the brain is the nicotinic acetylcholine receptor (nAChR), where stimulation of presynaptic nAChRs on neurons increases transmitter release and metabolism (Dani and Bertrand 2007; Picciotto 2003). The two general families of central nAChRs are high-

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affinity receptors (β2 subunit–containing nAChRs, which exist in a heteropentameric configuration of α subunits combined with β subunits) and low-affinity receptors (α7 subunit–containing nAChR homopentameric complexes) (see Dani and Bertrand 2007 for review). Both highand low-affinity nAChRs appear to be present on mesocorticolimbic dopamine neurons (Wooltorton et al. 2003), and α7 nAChRs are enriched in the hippocampus and cortex and appear to facilitate information processing and sensory integration (Leonard and Bertrand 2001). Chronic administration of nicotine, unlike most agonists, leads to desensitization and inactivation of nAChRs, with subsequent upregulation of nAChR sites, a process that might explain why many smokers report that the most satisfying cigarette of the day is the first one in the morning, at which time upregulated nAChRs are resensitized. Mesolimbic dopamine (reward pathway) neurons possess presynaptic nAChRs and may be of particular importance in mediating the rewarding effects of nicotine through projections from the ventral tegmental area in the midbrain to anterior forebrain structures such as the nucleus accumbens and cingulate cortex (Dani and Bertrand 2007). Domino et al. (2004) proposed that individuals with schizophrenia have a relative hyperfunction of subcortical dopamine systems and a relative hypofunction of prefrontal cortex dopamine systems. It is a well-known fact that chemical or physical lesioning of the prefrontal cortex produces hyperfunctional mesolimbic dopamine neurons. Preclinical studies in nonhuman primates suggest that chronic treatment with the N-methyl-D-aspartate receptor antagonist MK-801 produces a depletion of prefrontal cortex dopamine levels, which is accompanied by an increase in D 1 receptor binding and an impairment in working memory performance (Tsukada et al. 2005b). Interestingly, acute intravenous administration of nicotine normalizes prefrontal cortex dopamine levels, and D1 receptor binding, and improves working memory performance in these MK-801 exposed monkeys (Tsukada et al. 2005a). This animal model of schizophrenia may provide an outstanding opportunity to study the interactive effects of nicotine on the putative pathophysiological processes associated with schizophrenic disorders and their frequent comorbidity with tobacco dependence (Domino et al. 2004). Converging lines of evidence suggest that dysregulation of both high- and low-affinity nAChRs occur in the brains of individuals with schizophrenia. Evidence indicates that high-affinity nAChR expression is reduced in postmortem brains of patients with schizophrenia (Leonard et al. 2000) and that the expected upregulation of nAChRs with tobacco exposure is blunted in patients with schizophrenia com-

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pared with control smokers and nonsmokers; however, most of these data come from cross-sectional comparisons, and within-subject changes in nAChR levels have not been studied either with respect to smoking initiation or smoking cessation. Schizophrenia is associated with a number of neurocognitive deficits, including attention, verbal learning and memory, spatial working memory, and executive function (Green et al. 2004), and nicotine is thought to have procognitive effects (Sacco et al. 2005). Acetylcholine is associated with arousal, learning, and memory, and cholinergic inhibitors are used clinically to enhance memory (Levin et al. 2006; Newhouse et al. 2004; Sacco et al. 2004). The use of selective nAChR agonists and partial agonists to treat cognitive deficits in schizophrenia is thought to be the most appealing area of treatment possibilities at this time. The Measurement and Treatment Research to Improve Cognition in Schizophrenia consortium has identified several classes of compounds that may be effective for this purpose; topping this list are α7 nicotinic receptor partial agonists (Marder 2006; Tamminga 2006). One promising medication is the α7 agent dimethoxybenzylidene anabaseine (DXMB-A), which is likely to alter deficits of P50 auditory evoked potential inhibition and smooth pursuit eye movements in this population (Olincy et al. 2006). In addition, varenicline (Chantix), as an α4β2 nAChR-selective partial agonist, might be considered for its potential effects on visuospatial working memory, attention, and prepulse inhibition. Other novel medications used off-label, such as galantamine hydrobromide (Razadyne), an nAChR allosteric modulator (Coyle and Kershaw 2001), are also currently being used to study nAChR mechanisms relevant to neurocognition in patients with schizophrenia and other neuropsychiatric disorders. The development of other novel selective nAChR agents will allow more careful exploration of the therapeutic potential of nicotinic agents for the treatment of neurocognitive dysfunction associated with schizophrenia.

Pharmacokinetic Implications of Smoking for Psychotropic Drug Use in Schizophrenia Strong evidence indicates that tobacco smoking induces the liver cytochrome P450 1A2 (CYP1A2) enzyme system, a major route for the metabolism of antipsychotic drugs such as olanzapine and clozapine (Kroon 2007). Accordingly, smoking cessation would be expected to lead to increases in plasma concentrations of antipsychotic drugs metabolized by the CYP1A2 system, a finding demonstrated repeatedly

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in both prospective and retrospective studies (Kroon 2007). Such an increase in circulating levels would be expected to increase the likelihood of extrapyramidal reactions and other antipsychotic drug side effects. Although no smoking cessation study of patients with schizophrenia to date has prospectively measured antipsychotic plasma levels before and after smoking cessation, several case reports and case series suggest increases in medication levels with smoking cessation. In one of the larger case series, Meyer (2001) reported on serial clozapine levels measured in 11 patients with schizophrenia or schizoaffective disorder treated with stable dosages in a state hospital before and after a hospital-wide ban on smoking. A mean increase of 57.4% was noted in these clozapine-treated patients who quit smoking; one patient in particular had an increase in his serum clozapine level to over 3,000 ng/ml that was associated with aspiration. In the few published controlled smoking cessation trials in this population (Addington et al. 1998; George et al. 2000a), no significant increases in medication side effects have been noted in patients who quit smoking, including those treated with medications known to be metabolized by CYP1A2, but clearly further study is warranted.

Effects of Smoking on Clinical and Cognitive Deficits Associated With Schizophrenia Several cross-sectional studies have examined the effects of cigarette smoking on psychotic symptoms in patients with schizophrenia, with mixed results (e.g., Barnes et al. 2006; Goff et al. 1992; Patkar et al. 2002; Tang et al. 2007; Ziedonis et al. 1994). Goff et al. (1992) found that compared with nonsmokers with schizophrenia, smokers with schizophrenia had higher Brief Psychiatric Rating Scale (BPRS) total scores and higher subscale scores for both positive and negative symptoms. Tang et al. (2007) found no differences in overall BPRS scores between smoking and nonsmoking patients with schizophrenia but did find that smokers had a lower score on the BPRS Depressive and Anxious Symptoms subscale. Ziedonis et al. (1994) found that patients with schizophrenia who smoked had increased positive symptom scores and reduced negative symptom scores compared with nonsmoking patients with schizophrenia, with heavy smokers having the highest positive and lowest negative symptom scores. Patkar et al. (2002) found that higher levels of nicotine dependence were associated with higher

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negative symptoms but not with positive symptoms. A study by our group found that patients with schizophrenia who were former smokers had higher negative symptoms than current smokers, after adjusting for differences in age, depressive symptoms, and education (George et al. 2002a). Two recent reports found no differences in positive or negative symptoms of schizophrenia when comparing patients who were smokers with those who did not smoke (Barnes et al. 2006; Tang et al. 2007). Clearly, the interpretation of data from cross-sectional studies is confounded by methodological differences. Few direct studies have been done of the effects of smoking or nicotine administration on clinical symptoms in patients with schizophrenia. In contrast to results from cross-sectional studies, controlled laboratory studies of smoking abstinence (George et al. 2002a) and nicotine patch administration (Dalack et al. 1999) have not shown significant effects on the clinical symptoms of schizophrenia. One study (Smith et al. 2002) found that although high-nicotine cigarettes led to a greater decrease in negative symptoms than denicotinized cigarettes, the type of cigarette did not affect positive symptoms, anxiety, or depression. In this study, nicotine nasal spray did not alter clinical symptoms. Furthermore, data from smoking cessation trials (Addington et al. 1998; Baker et al. 2006; Evins et al. 2005, 2007; Gallagher et al. 2007; George et al. 2000a, 2008), all of which used the nicotine patch, found no evidence for significant changes in psychotic symptoms with smoking abstinence in patients with schizophrenia. Thus, the effects of cigarette smoking and smoking abstinence on schizophrenia symptoms are not clear. Perhaps some trait differences in psychotic symptoms in smokers versus nonsmokers with schizophrenia (e.g., more refractory symptoms in nonsmokers) might explain these findings, independent of smoking status (George et al. 2002a). Several human laboratory studies have suggested that patients with schizophrenia possess deficits in auditory information processing (P50 event-related potentials), which can be transiently normalized by cigarette smoking or administration of nicotine gum (Adler et al. 1998). Similarly, Griffith et al. (1998) reported a smaller but still significant improvement in P50 auditory gating after providing a nicotine patch to smokers with schizophrenia following a 2-hour period of abstinence from smoking. Leonard et al. (2002) found that these P50 response deficits may be linked to a locus on chromosome 15 (q14) near the coding region for the α 7 nicotinic acetylcholine receptor. This subtype of nAChR has been strongly implicated in P50 responses, leading to speculation that if some schizophrenia patients possess defective α 7 nAChR-mediated neurotransmission, they may smoke heavily to overcome the related neurophysiological deficits.

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In addition, patients with schizophrenia have abnormalities in another auditory information processing response known as prepulse inhibition of the acoustic startle reflex. The neural substrates mediating this response appear to be distinct from those mediating P50 responses (Swerdlow et al. 1992). Nicotine seems to improve performance on prepulse inhibition for smokers with schizophrenia. Kumari et al. (2001) found that when male patients with schizophrenia were acutely smoking, their prepulse inhibition was higher than that in smokingdeprived or nonsmoking patients with schizophrenia, whereas Postma et al. (2006) found that subcutaneous nicotine improves prepulse inhibition in smokers with schizophrenia. Moreover, George et al. (2006) showed that deprived smokers with schizophrenia demonstrated reduced prepulse inhibition but that baseline performance was reinstated upon resumption of smoking. However, the nicotinic antagonist mecamylamine dose-dependently blocked reinstatement in the schizophrenia group, whereas no effect was found in nonpsychiatric control subjects, suggesting that stimulation of central nAChRs mediates cigarette smoking–induced improvement of prepulse inhibition in patients with schizophrenia. Thus, patients with schizophrenia may be using cigarette smoking to ameliorate defects in cognitive function, further supporting the self-medication hypothesis of cigarette smoking in schizophrenia. A growing body of research has examined cognitive function in patients with schizophrenia and nonpsychiatric control subjects as a function of smoking status. In addition to P50 gating and prepulse inhibition, nicotine appears to enhance areas of cognition including working memory and sustained attention. Smokers with schizophrenia demonstrate a deficit in visual-spatial working memory function after overnight abstinence, with an immediate improvement in performance with resumption of cigarette smoking (Sacco et al. 2005) or after administration of nicotine nasal spray (Smith et al. 2006). Furthermore, such persistent effects on visual-spatial working memory are observed with longer-term abstinence. Smokers who remained abstinent from cigarettes over a 10-week period demonstrated enduring decrements in visual-spatial working memory (George et al. 2002a). Similar cognitive enhancement is achieved with nicotine gum administration, as seen using an auditory N-back task with a high verbal working memory demand (Jacobsen et al. 2004), and with nicotine patch, nasal spray, or cigarettes on measures of sustained attention using the Conners’ Continuous Performance Test (Sacco et al. 2005). In summary, nicotine administration appears to enhance several areas of cognitive function in patients with schizophrenia, including working memory, specifically

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spatial working memory; sustained attention; P50 gating; smooth pursuit eye movement; and prepulse inhibition.

Effects of Atypical Versus Typical Antipsychotic Drugs on Smoking in Schizophrenia Cross-sectional research has shown lower levels of smoking in patients taking atypical antipsychotic medications than in those taking typical antipsychotics (e.g., Barnes et al. 2006). Our group has found that switching smokers with schizophrenia from typical antipsychotic agents to clozapine leads to reductions in self-reported cigarette smoking, especially in heavier smokers (George et al. 1995). Similar findings were reported by McEvoy and colleagues, who found that the degree of reduction may be dependent on clozapine plasma levels (McEvoy et al. 1995b). A related study found that compared to a baseline medicationfree condition, taking the typical antipsychotic drug haloperidol leads to increased smoking in patients with schizophrenia (McEvoy et al. 1995a). Thus, a role for atypical antipsychotic drugs in reducing smoking behavior is suggested. Use of the transdermal nicotine patch (TNP) is known to facilitate smoking reduction and cessation (Addington et al. 1998; George et al. 2000b) in smokers with schizophrenia, albeit at lower rates (36%–42% at trial endpoint) than in healthy control smokers (50%–70%) (George and O’Malley 2004). Nonetheless, nicotine patch use at the dosage of 21 mg/day appears to effectively reduce cigarette smoking and nicotine withdrawal symptoms in smokers with schizophrenia (Addington et al. 1998; George et al. 2000b). Other studies indicate that the combination of TNP with the atypical antipsychotic risperidone or olanzapine may enhance smoking cessation rates compared with the combination of typical antipsychotic drugs and TNP among smokers with schizophrenia with high motivation to quit smoking (George et al. 2000b). Data from a preliminary placebo-controlled trial comparing bupropion versus placebo in smokers with schizophrenia suggest that atypical antipsychotic treatment significantly enhances smoking cessation responses to bupropion (George et al. 2002b). One can speculate that in patients with schizophrenia, atypical antipsychotic drugs may be helpful for smoking cessation compared with typical neuroleptic agents for the following reasons: 1) atypical agents have fewer extrapyramidal side effects and improve negative symp-

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toms, both of which may be further improved by cigarette smoking; 2) treatment with atypical agents is associated with improvement in certain neuropsychological functional deficits, which also appear to be alleviated by smoking; 3) sensory gating deficits (e.g., P50 responses, prepulse inhibition) that are transiently normalized by nicotine administration or cigarette smoking are also ameliorated by atypical antipsychotic drugs; and 4) atypical agents are associated with augmentation of dopamine release in the prefrontal cortex in rodent studies, and these agents may normalize those presumed deficits in cortical dopamine function in schizophrenia that are remediated by nicotine administration via cigarette smoking.

Optimizing Cessation Treatments to Prevent Smoking-Related Medical Illness Despite the enhanced quality of life possibly afforded to individuals with schizophrenia through the use of atypical antipsychotics, smokers with schizophrenia are more vulnerable than the general population of smokers to developing smoking-related morbidity and mortality, including an increased risk of cardiovascular disease (Capasso et al. 2008). Previous epidemiological studies suggested that smokers with schizophrenia were protected against the development of malignancies (Tsuang et al. 1983), and this was thought to relate to neuroleptic drug exposure (Mortensen 1987). In addition, evidence suggests that urinary levels of the peptide bombesin, a possible marker of precancerous cigarette smoking–induced lung damage, are lower in patients with schizophrenia than in controls (Olincy et al. 1999). This reduction in urinary bombesin levels is independent of smoking status in patients with schizophrenia, supporting the notion that these patients may be less vulnerable to the development of cancer. However, several subsequent epidemiological studies have found no evidence for a decreased risk of lung cancer in patients with schizophrenia or other patients with serious mental disorders (Lichtermann et al. 2001). Previous studies may have been confounded by selection bias, because rates of these medical illnesses in older patients with schizophrenia are lower, likely related to the fact that much of this cohort had died from other causes related to their psychiatric illness (e.g., suicide) by the time they reached the age when cancer risk is substantially increased (age 50 years or older). Thus, disease prevention through smoking cessation or reduction in this population is an important public health issue, especially because patients with schizophrenia constitute 1% of the U.S. population.

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Although the interest in smoking cessation by patients with schizophrenia is generally thought to be low, approximately 20%–40% have substantial desire to quit smoking (Ziedonis and Trudeau 1997), based on ratings of motivational level using the Stages of Change scale (e.g., preparation or action stages) (Prochaska and DiClemente 1983). In many cases where smoking cessation is not possible, a reduction in smoking consumption (e.g., a “harm reduction” approach) might accrue some health benefits for smokers with schizophrenia (McChargue et al. 2002); however, no studies have been published to suggest that reducing smoking can reduce the risk of developing smoking-related illness in nonpsychiatric individuals or smokers with schizophrenia. In fact, one study suggests that a 50% reduction in smoking does not reduce the risk of developing cardiac and pulmonary disease, compared with the risk in persistent heavy smokers (Tverdal and Bjartveit 2006). Thus, the approach to treatment of tobacco dependence in these patients should focus on the ultimate goal of smoking cessation, although given the difficulties of cessation in patients with schizophrenia, more flexible approaches (McChargue et al. 2002), including reduction as a transition to abstinence, should be encouraged. Thus, an understanding of biological and psychosocial factors that render schizophrenia patients at high risk for developing nicotine addiction and that contribute to their low intrinsic motivation to change smoking behaviors is critical to guiding efforts directed toward improving smoking cessation treatment in this population. One study using a single motivational interview versus an educational program in smokers with schizophrenia (Steinberg et al. 2004) found that motivational interventions were associated with a significant increase in the chance that these smokers initiated smoking cessation treatment. Experience in controlled treatment research studies for smoking cessation in schizophrenia has suggested the need to optimize both pharmacological and psychosocial interventions (see Table 9–1). Although use of atypical antipsychotic drugs may be one patient factor that predicts better smoking cessation or reduction outcomes, the reality is that patients with schizophrenia need persistent encouragement to cease smoking through the use of motivational enhancement therapies and, once smoking abstinence has been achieved, require ongoing teaching in methods to prevent smoking relapse (Addington et al. 1998; Ziedonis and Trudeau 1997). Steinberg et al. (2004) found that a larger percentage of smokers with schizophrenia attended a session of tobacco dependence treatment after receiving a motivational interviewing session than after receiving standard psychoeducational treatment or brief advice. In addition, educating patients about the dangers of smoking

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for their health is helpful, because they often know surprisingly little about the adverse effects of tobacco. Finally, drug refusal techniques are important, because peer pressure is typically very high on these individuals to resume smoking after successful abstinence. Accrued experience in the Yale Program for Research in Smokers with Mental Illness indicates that teaching assertiveness skills (in the context of social skills training) has been quite effective for helping patients who maintain high motivation to remain tobacco-free. Standard smoking cessation pharmacotherapies approved by the U.S. Food and Drug Administration (FDA), such as the transdermal nicotine patch (TNP) (Addington et al. 1998; Baker et al. 2006; Chou et al. 2004; George et al. 2000b), nicotine nasal spray (Williams et al. 2004), and sustained-release bupropion (Evins et al. 2001, 2005; Fatemi et al. 2005; George et al. 2002b; Weiner et al. 2001), appear to be safe and efficacious treatments for smoking cessation in patients with schizophrenia during the course of controlled studies. A summary of treatment and nontreatment studies directed at addressing tobacco addiction in patients with schizophrenia is presented in Table 9–1. The smoking cessation rates of patients with schizophrenia at the end of drug treatment are in the range of 30%–42% with the nicotine patch (Addington et al. 1998; Baker et al. 2006; Chou et al. 2004; George et al. 2000b), and 11%–50% with bupropion (Evins et al. 2001, 2005; George et al. 2002b; Weiner et al. 2001), which are modest compared to rates achieved in nonschizophrenic control smokers (50%–75%) (Hughes et al. 1999) but may be improved when patients are prescribed atypical antipsychotic agents (George et al. 2000b, 2002b). Recently, the combination of TNP and bupropion has been found to be safe and to increase shortterm abstinence rates in comparison to TNP alone (Evins et al. 2007; George et al. 2008). Differences in study design, patient variables (e.g., level of motivation to quit smoking), medication dosage (in the studies with bupropion, used at 150–300 mg/day), and criteria used to determine smoking abstinence may explain the variability in cessation rates across these studies. In studies that have used TNP, patients are expected to stop all smoking on the designated “quit date” (when they begin TNP). When using the TNP, patients should be cautioned not to smoke while wearing the patch due to concerns about nicotine toxicity, symptoms of which can include tremor, nausea and vomiting, dizziness, and in rare cases seizures, arrhythmias, and death. In our research clinic, we have not encountered nicotine toxicity to be a significant problem, but we tell patients who feel they must smoke to remove the patch and wait 1–2 hours before resuming smoking. The craving to smoke and continuing withdrawal symptoms typically indicate incomplete nicotine

Study

Smoking cessation and reduction approaches using pharmacotherapies in schizophrenia: summary of controlled studies Sample

Bupropion Evins et al. 2001 Weiner et al. 2001

Short-term abstinence rates Long-term abstinence rates

Open-label trial of TNP +group counseling TNP +group counseling

42% at study endpoint ∼35%

3 months: 15%; 6 months: 12% ∼10%

TNP vs. no-patch control group Nicotine nasal spray

26.9% vs. 0%

3 months: 26.9% vs. 0% 3 months: 42%

TNP +CBT/MI vs. CBT/MI

18 outpatients

BUP+ CBT vs. PLA+CBT

8 outpatients

Open-label BUP +supportive group counseling

3 months: 30.0% vs. 6.0%; 6 months: 18.6% vs. 4.0%; 12 months: 18.6% vs. 6.6% 66% vs. 11% (≥50% reduction in smoking) 0% quit smoking; reduction in CO levels

6 months: 11% vs. 0% (sustained abstinence) NA

Medical Illness and Schizophrenia

Nicotine replacement therapy Addington 50 outpatients et al. 1998 George et al. 45 outpatients 2000b Chou et al. 68 inpatients 2004 Williams et al. 12 outpatients 2004 Baker et al. 298 outpatients with 2006 nonacute psychotic disorders

Study design

234

TABLE 9–1.

TABLE 9–1.

Smoking cessation and reduction approaches using pharmacotherapies in schizophrenia: summary of controlled studies (continued) Sample

Study design

Short-term abstinence rates Long-term abstinence rates

George et al. 2002b Evins et al. 2005 Fatemi et al. 2005

32 outpatients

BUP+ counseling vs. PLA + counseling BUP+ CBT vs. PLA+CBT

50% vs. 12.5%

18.8% vs. 6.3%

16% vs. 0%

3 months: 4% vs. 3.6%

Crossover design BUP and placebo

Trend for reduction in CO, cotinine, and nicotine levels

BUP+ NRT+CBT vs. PLA+NRT +CBT BUP+ TNP+ counseling vs. PLA + TNP+ counseling

36% vs. 19%

53 outpatients 10 outpatients

Combination treatments Evins et al. 51 outpatients 2007 George et al. 58 outpatients 2008 Varenicline Stapleton et al. 2007

71.7% vs. 55.2%

235

Open-label varenicline vs. 111 patients with TNP “mental health disorders” (31 with psychosis or psychosis + depression)

34.5% vs. 10.3%

6 months: 20% vs. 8%; 12 months: 12% vs. 8% 6 months: 13.8% vs. 0%

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Study

Smoking cessation and reduction approaches using pharmacotherapies in schizophrenia: summary of controlled studies (continued) Sample

Study design

Short-term abstinence rates Long-term abstinence rates

Evins and Goff 2008

19 outpatients

Open-label varenicline

68%

29 outpatients

Retrospective study of clozapine Within-subjects study of clozapine Within-subjects study of clozapine TNP +counseling; compared ATP vs. TYP medication

Reduction in smoking NA with clozapine treatment Reduction in smoking NA with clozapine treatment Reduction in smoking with clozapine treatment 55.6% (ATP) vs. 22.2% 6 months: 16.7% vs. 7.4% (TYP)

Other George et al. 1995 McEvoy et al. 1995b McEvoy et al. 1999 George et al. 2000b

12 inpatients 70 inpatients 45 outpatients

6 months: 68% (4 patients reported slips but regained abstinence within a week)

Note. All abstinence percentage rates are for 7-day point prevalence unless otherwise noted. ATP=atypical; BUP=bupropion; CBT=cognitive-behavioral therapy; CO=carbon monoxide; MI=motivational interviewing; NRT=nicotine replacement therapy; PLA=placebo; TNP=transdermal nicotine patch; TYP=typical.

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Study

236

TABLE 9–1.

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replacement; if needed, another patch of 7–21 mg/day can be added to therapy with the 21-mg/day TNP. For bupropion, controlled studies have started dosing at 150 mg/day orally, with an increase to 150 mg twice daily by the fourth day of treatment. The “quit date” is typically set once levels reach steady-state, usually 3–4 days after beginning the full 300-mg/day dosage. A history of seizures of any etiology is a contraindication to the use of bupropion, as indicated by the product labeling, and we recommend not exceeding 300 mg/day, because some antipsychotic drugs may reduce seizure threshold. At the same time, bupropion at 150–300 mg/day does not appear to worsen positive symptoms of schizophrenia and may reduce negative symptoms (Evins et al. 2001, 2005; Fatemi et al. 2005; George et al. 2002b; Weiner et al. 2001). The typical duration of therapy studied in patients with schizophrenia with these agents is 8–12 weeks; studies with longer durations of treatment in this population have not yet been conducted. Varenicline tartrate (Chantix in the United States, Champix in Europe and Canada), an α4β2 nAChR partial agonist, is the newest medication approved by the FDA as a first-line smoking cessation agent. Although clinical trials of varenicline with psychiatric smokers have not yet been published, case reports suggested temporary increases in psychiatric symptoms in a patient with schizophrenia (Freedman 2007) and a patient with bipolar disorder (Kohen and Kremen 2007). An open case series of 19 smokers with schizophrenia reported that 13 patients were able to maintain abstinence (verified by measuring carbon monoxide level) for ≥12 weeks (Evins and Goff 2008). Over 6 months, four patients reported “slips” and were able to regain abstinence within a week. None of the 19 patients showed significant worsening of psychiatric symptoms, psychotic relapse, or hospitalization. Finally, a recent study (Stapleton et al. 2007) compared the effectiveness of varenicline and nicotine replacement in 412 smokers with and without psychiatric disorders. Of the 111 patients with mental health disorders, 7 were diagnosed with psychosis and 24 were diagnosed with combined psychosis and depression. Of those 111 patients with psychiatric disorders, 53 patients received varenicline and 58 patients received TNP. The results of this study suggested that varenicline was equally effective in patients with and without mental illness, that varenicline was more effective than TNP, and that there was no evidence that taking varenicline exacerbated psychiatric symptoms (Stapleton et al. 2007). Further controlled research is needed to determine the safety and efficacy of varenicline for patients with schizophrenia and other psychiatric disorders.

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Key Clinical Points ◗

Smokers with schizophrenia smoke at higher rates and have lower smoking cessation rates than the general population. This group of smokers also shows higher rates of smoking-related illnesses, making the development of effective treatments for this population an important priority.

◗

Motivation to quit smoking is often low in patients with schizophrenia, and efforts need to be undertaken to increase the awareness of both patients and their clinicians of the dangers of habitual tobacco smoking. Motivational interviewing and relapse-prevention methods are the mainstays of behavioral treatment for tobacco dependence in these patients.

◗

The high rates of comorbid tobacco dependence in patients with schizophrenia may relate to abnormal biology of nicotinic receptor systems and central dopaminergic, glutamatergic, and GABAergic pathways associated with this disorder.

◗

Nicotine administration enhances several areas of cognitive function in patients with schizophrenia, including working memory (specifically spatial working memory), sustained attention, P50 gating, smooth pursuit eye movement, and prepulse inhibition, which may contribute to the initiation and maintenance of tobacco dependence in these patients.

◗

Controlled studies have suggested that treatments for tobacco dependence (e.g., nicotine replacement therapy, bupropion) are safe and improve smoking cessation outcomes for patients with schizophrenia. Recent studies have examined the efficacy of combining medications and newer pharmacological agents (e.g., varenicline) to further improve short- and long-term smoking cessation rates.

◗

Although there is little evidence from controlled clinical studies that smoking cessation produces a deterioration of clinical function (e.g., positive and negative symptoms) in stabilized patients, further research is needed, especially for newer agents such as varenicline that have not been tested in controlled trials. Clinicians should not encourage patients with schizophrenia to quit smoking when they are clinically unstable, because the likelihood of success is low and the risk of symptom exacerbation may be elevated.

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PART III Special Topics and Populations

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CHAPTER 10 HIV and Hepatitis C in Patients With Schizophrenia Milton L. Wainberg, M.D. Francine Cournos, M.D. Karen McKinnon, M.A. Alan Berkman, M.D. Mark Drew Crosland Guimarães, M.D., D.Sc., M.P.H.

Among the chronic health conditions experienced by people with schizophrenia, infection with human immunodeficiency virus (HIV) and hepatitis C virus (HCV) occur with concerning frequency. People who contract HIV or HCV face chronic illness, the possibility of premature death, complicated medication regimens, barriers to medical care, and the neuropsychiatric sequelae of treatment or infection itself. Estimates are that approximately one-quarter of those infected with HIV and the majority of those with HCV in the United States do not know they are infected (Agency for Healthcare Research and Quality 2002; Marks et al. 2006). HIV and HCV are acquired by similar routes of transmission, although HIV is much more likely to be sexually transmitted than HCV. In the United States, rates of both diseases are higher among African Americans and Latinos than among Caucasians. Both infections are 247

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overrepresented among people with severe mental illness, including those with schizophrenia, especially when comorbid substance use is present. Published rates of HIV infection among psychiatric patients in the United States are 3.1%–23.9% (Cournos and McKinnon 1997; Rosenberg et al. 2001), at least eight times higher than the general population estimate of 0.6% (UNAIDS 2007). HIV infection rates among patients with schizophrenia rarely have been differentiated from rates among others with psychotic disorders, but when they have, no significant differences have emerged. In the United States, estimates of HCV infection in samples of patients with mental illness, including schizophrenia, have ranged from 8.2% to 38.0% (Al Jurdi and Burruss 2003; Butterfield et al. 2003, 2004; Dinwiddie et al. 2003; Freudenreich et al. 2007; Huckans et al. 2006; Klinkenberg et al. 2003; Meyer 2003; Rosenberg et al. 2001; Tabibian et al. 2008). These rates are higher than the general population rate of approximately 1.6% (Centers for Disease Control and Prevention 2008). Psychiatric symptoms and disabilities may increase risk of HIV or HCV among people with severe mental illness, either by directly affecting behavior or by interfering with the opportunity or ability to acquire and/or use information about these illnesses to practice safer behaviors. Psychiatrists and other mental health care providers often are in the best position to enhance patients’ skills in modifying risk behaviors and to connect patients to the medical services they need.

Sexual Risk Behaviors and Psychiatric or Situational Factors Studies of sexual risk behavior among people with psychiatric disorders have thus far not linked behaviors to biological outcomes, and few studies have differentiated risk behaviors by psychiatric diagnosis. However, risk behaviors among people in psychiatric treatment in the United States are common, with interview studies revealing that a majority of patients were sexually active with a partner in the previous year and that the sexual activity of people with severe mental illness is characterized by having multiple sex partners and by a lack of condom use in a majority of sexual occasions for both men and women (Meade and Sikkema 2005). Being sexually active has been found to be associated with a diagnosis of schizophrenia but not with bipolar disorder, and trading sex for money or drugs was more than three times as likely among patients with schizophrenia than among those with other diagnoses, and more than five times as likely among those with certain positive symptoms such as delusions (McKinnon et al. 1996; Meade and Sikkema 2007). Diagnosis

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has not been shown to be associated with number of sex partners or condom use (Meade and Sikkema 2007), although greater psychiatric symptoms were associated with increased HIV risk (Rosenberg et al. 2001). Extended periods of institutionalization on same-sex units in hospitals, shelters, or prisons may foster high-risk same-sex activity, often among those who do not self-identify as gay or lesbian. One study that directly compared psychiatric patients with nonpsychiatric groups found that psychiatric patients are more likely to engage in same-sex activity (McDermott et al. 1994). This behavior is particularly risky for men. Recurrent institutionalization, homelessness, transient living circumstances, alienation from supportive social relationships, and lack of privacy can all interrupt long-term relationships, reinforcing the tendency to have unfamiliar partners. Studies report that 10%–16% of psychiatric patients had sex in the past year with someone they had known less than 24 hours (Kalichman et al. 1994; Kelly et al. 1992). These conditions also may make changing risk behaviors difficult for people with severe mental illness or may limit sexual opportunities to those that confer greater risk. Unemployment, which is common among adults with severe mental illness, also may contribute to greater sexual risk taking (Meade and Sikkema 2007), possibly through pressures toward survival sex or commercial sex work. Sexual victimization, which increases the likelihood of unprotected intercourse, has been widely reported by psychiatric inpatients (Malow et al. 2006). Among outpatients, one in eight reported having been pressured, coerced, or forced into unwanted sex in the past year (Carey et al. 1997). Having a sexually transmitted infection, which renders a person biologically more susceptible to acquiring subsequent infections when exposed, is common among people with severe mental illness. Between 9% and 36% of psychiatric inpatients and outpatients are diagnosed with one or more sexually transmitted infections at some time in their lives (Carey et al. 1997; Rosenberg et al. 2001). Moreover, some patients may have sexually transmitted infections without being aware of them and will likely remain untreated unless screened for sexually transmitted infections.

Substance Use Risk Behaviors and Psychiatric or Situational Factors In the United States, psychiatric patients with identified comorbid alcohol or other drug use disorders have a significantly higher rate of HIV infection than those without (McKinnon and Cournos 1998), even if they have never injected drugs. In this population, any lifetime drug injection or

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needle sharing appears to increase the risk of being infected with HIV more than sixfold (Rosenberg et al. 2001). As in the general population, HCV infection in psychiatric patients is most strongly associated with injection drug use, and to a lesser extent with other drug use (including sniffing and smoking forms of cocaine), unsafe sexual practices, and poverty. A history of drug injection has been noted among 1%–26% of psychiatric patients, and 5%–12% report having ever shared needles or other injection paraphernalia (Carey et al. 1997; Rosenberg et al. 2001). Moreover, psychiatric patients who inject tend to do so intermittently rather than regularly, so drug injection histories often are overlooked in mental health settings, and no conclusive evidence has been found to link injection drug use with psychiatric diagnosis, chronicity, level of functioning, or psychiatric symptoms. As in the general population, alcohol or other drugs often are part of psychiatric patients’ sexual experience and may decrease the motivation or ability to have protected sex. Of psychiatric inpatients and outpatients, 15%–45% reported using substances during sex in the past year (Carey et al. 1997; Menon and Pomerantz 1997), with comparable rates seen in men and women.

Knowledge About HIV/HCV Among People With Severe Mental Illness and Their Providers Knowledge about HIV and acquired immune deficiency syndrome (AIDS) among U.S. psychiatric patients appears to be relatively good. Correct responses to AIDS knowledge questionnaires in a variety of psychiatric patient groups ranged from 63% to 80%, a comparable accuracy rate to that found in the general U.S. population (Meade and Sikkema 2005). Still, many psychiatric patients held critical misinterpretations about HIV and related risks. In one study, for example, 48% of outpatients believed that careful cleansing after sex would provide protection from the virus (Otto-Salaj et al. 1998). Comparable studies about HCV knowledge among psychiatric patients have not been completed.

HIV/AIDS: Overview of Course of Illness and Treatment As of 2007, approximately 1.3 million persons in North America and 33 million persons worldwide were living with HIV (UNAIDS 2007), which was first identified in 1983. HIV infection is a chronic condition

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that normally runs its course over many years, with AIDS being a latestage manifestation of HIV infection, characterized by increasing viral load of HIV in the blood and declining immune function (as measured by CD4 T-cell counts), leading to a broad spectrum of diseases. According to the Centers for Disease Control and Prevention ([CDC] 2008), the diagnosis of AIDS is made in an HIV-positive individual who has at least one of 25 AIDS-defining conditions (e.g., Pneumocystis carinii pneumonia, HIV-associated dementia, or a CD4 T-cell count lower than 200 cells per cubic millimeter). HIV has been identified as the cause of AIDS (Barre-Sinoussi et al. 1983). The virus invades the nervous system, causes persistent viremia, and weakens the humoral and cellular immune response. HIV has a remarkably complex viral genome, which probably underlies its profound pathogenicity. HIV mutates rapidly, making drug resistance a major problem and contributing to difficulties in producing an effective vaccine. HIV-1 is the most common type of HIV virus in the United States and much of the rest of the world. HIV-2 occurs in West Africa, with scattered cases appearing in Asia. HIV-2 is associated with considerably slower disease progression than HIV-1. Having either virus does not alter the susceptibility to infection with the other strain. All vaccine trials thus far have failed to show protection against acquiring HIV, and one trial even suggested increased susceptibility among a subgroup of those vaccinated, leading to a call for more basic science research to further clarify vaccine development strategies (Walker and Burton 2008).

HIV Transmissibility Although HIV has been isolated from a variety of body fluids, including blood, semen and preseminal fluid, vaginal secretions, breast milk, urine, saliva, and tears, the risk of transmission is a consequence of the viral load of the fluid. HIV is found in such small quantities in tears, saliva, and urine that casual contact with these fluids is a very unlikely mode of transmission. Epidemiological studies indicate that semen and preseminal fluid, cervical and vaginal secretions, breast milk, and blood and blood products are the predominant, if not exclusive, vehicles for viral transmission (Staprans and Feinberg 1997). HIV is typically spread by sexual contact, exposure to infected blood (transfusions, blood products, percutaneous and intravenous injections with contaminated syringes or needles, etc.), and through perinatal transmission from mother to child. Although uncommon, infection is possible through the exposure of cuts in skin or mucous membranes to HIV-infected blood.

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Penile-vaginal and penile-anal intercourse are considered the highest-risk sexual behaviors, in addition to activities that cause a rupture of tissue and the presence of blood. Although infection risk is somewhat higher for the recipient of semen than for the insertive partner, transmission has been documented in both directions. Male circumcision significantly reduces the risk of HIV acquisition and transmission by men during penile-vaginal sex; however, condoms are still needed. Oral sex has also been documented as a mode of transmission for the recipient of fluids, as has the sharing of sexual toys, although to a lesser extent. Certain cofactors enhance the risk of sexual transmission of HIV, including the presence of sexually transmitted infections, genital lesions, or genital or mucous membrane bruising during sexual activity. Sharing needles or other equipment during injection is a very efficient means of transmitting HIV and amounts to a direct inoculation of viral particles from the infected to the noninfected person. As with other routes of transmission, the likelihood increases with the size of the viral inoculum. Even noninjection substance use may increase the risk for HIV by increasing the chance that an individual will engage in high-risk behaviors due to lowered sexual inhibitions, impaired judgment, increased impulsiveness, or the exchange of sex for drugs or money to buy drugs. Transfusion with infected blood and the use of infected blood products almost always results in acquisition of HIV, although testing of donated blood and blood products has almost eliminated the chances of this occurrence in the industrialized countries.

HIV Testing The most commonly used HIV test is the enzyme-linked immunosorbent assay (ELISA), which, if positive, is followed by Western blot testing. The Western blot test is needed to rule out false positives on the ELISA test. Antibody-based assays are available as rapid (20-minute) tests of either blood or saliva, but the blood test is more accurate; positive results on either test must be confirmed by Western blot. These tests detect antibodies produced by the host as an immune response to certain genetic components of the virus but do not detect the virus itself. Although sensitive and specific, even the Western blot can give falsenegative or indeterminate results, especially during the first few weeks of infection. However, direct measurement of viral presence using the polymerase chain reaction assay will usually show extremely high levels of virus during this window period. False-positive results may occur as well. Despite the latter concern, the CDC now recommends routine

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opt-out HIV testing (testing for HIV as part of routine medical care unless the patient refuses) in all medical settings (Branson et al. 2006).

Viral Load and Resistance Assays Viral load, a quantifiable measurement of how many viral particles are present in a milliliter of blood, can be determined by several different assays, some of which detect as few as 50 viral particles per milliliter of blood. Below that threshold of measurement, the result is reported as “nondetectable.” This does not indicate that there is no virus present in blood at all, nor does it measure the amount of virus in lymphoid tissue or in the central nervous system (CNS). Viral load is a strong predictor of disease progression in untreated patients. For those on antiretroviral therapy, CD4 T-cell counts are the stronger predictor of clinical outcome. Both CD4 T-cell counts and viral load are used to monitor clinical response to therapy (Hulgan et al. 2007). Predicting responses to antiviral medications can be accomplished by testing for drug resistance, a problem increasingly seen in clinical practice. Resistance assays include genotyping to examine the patient’s virus for mutations known to confer drug resistance; phenotyping to test the susceptibility of the patient’s virus to specific medications; and virtual phenotyping, which uses a large database that associates genotypes with phenotypes to predict drug susceptibility.

Natural History of HIV Disease HIV contains ribonucleic acid (RNA) as its genetic material. HIV targets host CD4 T-lymphocytes and other susceptible cells by identifying surface molecules and attaching to and entering the cells (Staprans and Feinberg 1997). This begins the process of using the viral reverse transcriptase enzyme to transcribe viral RNA to deoxyribonucleic acid (DNA), which then allows the virus to use the host cell’s machinery to replicate itself. The replicated virus particles must be split apart into virions by the protease enzyme before they are extruded from the host cell so as to become functional and capable of infecting other CD4+ cells, leading to ongoing damage to the immune system. As the host produces circulating antibodies against HIV, the host is said to seroconvert. Genetic information to reproduce the virus is also integrated into the host cell’s genome. The immune system may initially contain but does not clear the infection; the course is set for chronic persistent viral replication. Without treatment, near complete destruction of the CD4 Tlymphocyte population eventually occurs in the vast majority of infected people. A person’s initial viral “setpoint,” the capacity of his or

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her immune system to limit viral replication, is the strongest predictor of untreated disease progression (Staprans and Feinberg 1997). The range and severity of symptoms in acute HIV infection vary considerably, with approximately 40%–90% of patients developing a retroviral syndrome characterized by a variety of symptoms that may include fever, lymphadenopathy, pharyngitis, malaise, myalgia, arthralgia, rash, headache, stiff neck, and other meningeal signs and symptoms. Acute HIV infection is highly transmissible due to transient intense viremia, and is accompanied by an acute fall in CD4 T-cell counts in the peripheral blood from its normal range of 800–1,200 cells/ mm3 (Soogoor and Daar 2005). The more severe this syndrome is, the more likely the untreated patient will progress rapidly to AIDS (Fidler et al. 2008). Although there are reasons to believe that favorable treatment during acute HIV infection can alter its long-term course, this is not yet established beyond question, and patients are encouraged to enroll in clinical trials studying the course of acute HIV infection (http:// www.aidsinfo.nih.gov). Once the symptoms of primary infection subside and an antiviral immune response appears, patients usually enter a chronic, clinically asymptomatic or minimally symptomatic state despite continuous active viral replication. This period may last only a few years in some infected individuals, but the majority of HIV-positive patients develop overt immunodeficiency in approximately 8–10 years, and a small cohort demonstrates sustained long-term (>10 years), symptom-free HIV infection (Staprans and Feinberg 1997). During chronic infection, the development of symptoms, a low CD4 cell count, and a high viral load should initiate a discussion between clinician and patient about antiretroviral treatment. The patient’s ability to adhere to the regimen is, of course, pivotal to the decision. The spectrum of HIV-associated illnesses that eventually develop includes constitutional symptoms (e.g., weight loss, fatigue, fever, night sweats) and involvement of multiple organ systems. Opportunistic infections (OIs) are multiple and can occur throughout the body. These include fungal infections (e.g., oral or esophageal candidiasis [thrush], cryptococcal infection, Pneumocystis carinii pneumonia); protozoan infections (e.g., toxoplasmosis); mycobacterial infections (e.g., tuberculosis and Mycobacterium avium complex); and bacterial and viral infections (e.g., recurrent pulmonary and gynecological infections). Cancers, such as Kaposi’s sarcoma and lymphoma, are other manifestations of severe immunosuppression. Prophylactic regimens can reduce the occurrence of many OIs in immunocompromised patients.

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Neuropsychiatric Manifestations of HIV HIV infection presents a spectrum of neuropsychiatric sequelae that can pose diagnostic and treatment quandaries for clinicians. In patients with serious and persistent psychiatric illness, some of the early, subtle neuropsychiatric symptoms may be difficult to differentiate from preexisting symptoms of psychiatric illness. HIV is neurotropic and enters the CNS soon after infection. Long-term clinical sequelae of CNS infection range from subtle neurocognitive impairment to frank dementia, and their incidence increases with HIV illness progression. Opportunistic infections and neoplasms that follow immunosuppression can also affect the CNS, resulting in mood disorders, psychosis, cognitive disorders, delirium, and other neuropsychiatric abnormalities. In addition, prescribed and recreational psychoactive substance use may create neuropsychiatric complications and must be considered in the differential diagnosis of patients who present with new mental status changes (American Psychiatric Association 2000; Wainberg et al. 2000). HIV-associated neurocognitive disorders (HAND) are diagnoses of exclusion made after other etiologies have been ruled out through a comprehensive evaluation. Table 10–1 describes the diagnostic criteria for the three categories of HAND: asymptomatic cognitive disorder, mild neurocognitive disorder, and dementia. (Antinori et al. 2007). HAND are subcortical disorders that affect primarily and initially the CNS white matter and, as time progresses, other CNS tissues. Although the exact pathophysiology of HAND remains unclear, diagnosis of HAND is relatively common, particularly in more advanced stages of HIV infection. Effective antiretroviral treatment has dramatically reduced the incidence of HAND. Antiretroviral treatment should be initiated or the regimen evaluated following diagnosis of symptomatic HAND, and other medications can be prescribed to treat associated symptoms (e.g., antidepressants, stimulants, testosterone). Psychiatric symptoms due to HIV-related medical conditions are most common in advanced stages of illness (American Psychiatric Association 2000). Therefore, among patients with advanced HIV who have a preexisting severe mental illness, psychiatric changes should not be attributed to a relapse until a complete medical workup has ruled out other causes. Mental status changes that can have a medical etiology include shifts in level of consciousness characteristic of delirium, cognitive impairment, mood changes, and psychotic symptoms. The differential diagnosis includes not only the neuropsychiatric manifestations of HIV itself but also opportunistic infections (e.g., toxoplasmosis,

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TABLE 10–1. Criteria for HIV-associated neurocognitive disorders (HAND) HIV-associated asymptomatic neurocognitive impairment (ANI)a 1. Acquired impairment in cognitive functioning, involving at least two ability domains, documented by performance of at least 1 standard deviation (SD) below the mean for age- and educationappropriate norms on standardized neuropsychological tests. The neuropsychological assessment must survey at least the following abilities: verbal/language; attention/working memory; abstraction/executive; memory (learning, recall); speed of information processing; sensory-perceptual and motor skills. 2. The cognitive impairment does not interfere with everyday functioning. 3. The cognitive impairment does not meet criteria for delirium or dementia. 4. There is no evidence of another preexisting cause for the ANI.b HIV-1–associated mild neurocognitive disorder (MND)c 1. Acquired impairment in cognitive functioning, involving at least two ability domains, documented by performance of at least 1 SD below the mean for age- and education-appropriate norms on standardized neuropsychological tests. The neuropsychological assessment must survey at least the following abilities: verbal/ language; attention/working memory; abstraction/executive; memory (learning, recall); speed of information processing; sensory-perceptual and motor skills. 2. The cognitive impairment produces at least mild interference in daily functioning (at least one of the following): a) Self-report of reduced mental acuity or of inefficiency in work, homemaking, or social functioning. b) Observation by knowledgeable others that the individual has undergone at least mild decline in mental acuity with resultant inefficiency in work, homemaking, or social functioning. 3. The cognitive impairment does not meet criteria for delirium or dementia. 4. There is no evidence of another preexisting cause for the MND.d

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TABLE 10–1. Criteria for HIV-associated neurocognitive disorders (HAND) (continued) HIV-1–associated dementia (HAD)e 1. Marked acquired impairment in cognitive functioning, involving at least two ability domains; typically the impairment is in multiple domains, especially in learning of new information, slowed information processing, and defective attention/ concentration. The cognitive impairment must be ascertained by neuropsychological testing with at least two domains reduced by 2 SD or greater than demographically corrected means. (Note that where neuropsychological testing is not available, standard neurological evaluation and simple bedside testing may be used, but this should be done using well-defined criteria.) 2. The cognitive impairment produces marked interference with day-to-day functioning (work, home life, social activities). 3. The pattern of cognitive impairment does not meet criteria for delirium (e.g., clouding of consciousness is not a prominent feature), or if delirium is present, criteria for dementia need to have been met on a prior examination when delirium was not present. 4. There is no evidence of another, preexisting cause for the dementia (e.g., other central nervous system [CNS] infection, CNS neoplasm, cerebrovascular disease, preexisting neurological disease, or severe substance abuse compatible with CNS disorder).f a

If the patient had a prior diagnosis of ANI but currently does not meet criteria, the diagnosis of ANI in remission can be made. b

If the individual with suspected ANI also satisfies criteria for a major depressive episode or substance dependence, the diagnosis of ANI should be deferred to a subsequent examination conducted at a time when the major depression has remitted or at least 1 month after cessation of substance use.

c

If the patient had a prior diagnosis of MND but currently does not meet criteria, the diagnosis of MND in remission can be made.

d

If the individual with suspected MND also satisfies criteria for 1) a severe episode of major depression with significant functional limitations or psychotic features or 2) substance dependence, the diagnosis of MND should be deferred to a subsequent examination conducted at a time when the major depression has remitted or at least 1 month after cessation of substance use. e

If the patient had a prior diagnosis of HAD but currently does not meet criteria, the diagnosis of HAD in remission can be made.

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TABLE 10–1. Criteria for HIV-associated neurocognitive disorders (HAND) (continued) f

If the individual with suspected HAD also satisfies criteria for 1) a severe episode of major depression with significant functional limitations or psychotic features or 2) substance dependence, the diagnosis of HAD should be deferred to a subsequent examination conducted at a time when the major depression has remitted or at least 1 month after cessation of substance use. Note that the consensus was that even when major depression and HAD occurred together, there is little evidence that pseudodementia exists and the cognitive deficits do not generally improve with treatment of depression.

Source.

Adapted from Antinori et al. 2007.

cryptococcus, tuberculous meningitis), lymphoma, or delirium from metabolic derangement, substance use, or drug toxicity (Wainberg et al. 2000).

HIV/AIDS Treatment Clinical management of HIV/AIDS is intended to maximally and durably suppress viral load, restore and preserve immune function, provide prophylaxis against opportunistic infections as appropriate, treat OIs when present, and decrease morbidity and mortality. Guidelines for the prophylaxis of OIs are based on the prevalence of each OI at various stages of immunodeficiency. In addition to the diagnosis of AIDS, other indications for treatment in an HIV-positive person include pregnancy, HIV-associated nephropathy, symptomatic HAND, and a CD4 cell count between 200 and 350. The need to treat other infections, such as hepatitis B and tuberculosis, also affects the timing and choice of antiretroviral agents for HIV. Guidelines for treatment of HIV infection are continually updated as new medications and more data from clinical trials become available. U.S. recommendations can be found at http:// AIDSinfo.NIH.gov. This site, maintained by the U.S. Department of Health and Human Services, also includes guidelines for postexposure prophylaxis following either an injury that carries risk in the health care setting or a sexual exposure. Part of instituting antiretroviral therapy involves ensuring that patients recognize their HIV infection, have access to health care, develop ongoing provider relationships, and are motivated to adhere to treatment, even during an asymptomatic phase of infection. When patients are not ready to adhere to antiretroviral therapy (e.g., because of chaotic

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life due to psychiatric instability, substance use, and/or homelessness; lack of motivation; insufficient social supports), barriers to adherence should be addressed first. High levels of adherence are required to suppress fully the replication of virus that is sensitive to the regimen being administered and to prevent the emergence of drug resistance. Mental health professionals often have important roles in assessing and promoting adherence. As of June 2008, the U.S. Food and Drug Administration had approved 22 individual antiretroviral medications, which are classified into six categories according to the specific step inhibited in the HIV life cycle (see Table 10–2). Individually, these agents are not very potent, but by combining three or more agents, effective viral suppression can be achieved even among many patients with resistant strains. Moreover, many regimens are simpler and contain fewer pills than in the past.

HCV: Overview of Course of Illness and Treatment Approximately 4 million persons in the United States and 170 million persons worldwide are infected with hepatitis C. The virus causes persistent infection in a majority of infected people, although most have relatively mild disease with slow progression. However, chronic and progressive HCV carries significant morbidity and mortality and is a major cause of cirrhosis, end-stage liver disease, and liver cancer. Six different genotypes have been identified. Most people in the United States who have HCV have genotype 1, which is difficult to treat. Development of an effective HCV vaccine is not imminent but continues to be pursued, because current therapy for HCV is poorly tolerated and not effective for a substantial number of patients.

HCV Transmission HCV is spread primarily through infected blood and is therefore a common complication of injection drug use and sharing of razors or tattooing equipment. HCV may also be spread by maternal fetal transmission and noninjection drug use activities. Although HCV is sexually transmissible, its efficiency of transmission via this mode is far less than other blood-borne viruses, including HIV (Clarke and Kulasegaram 2006).

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TABLE 10–2. Medications for HIV infection approved by the U.S. Food and Drug Administration as of June 2008 Generic name

Trade name

Nucleoside/nucleotide reverse transcriptase inhibitors Abacavir Ziagen Didanosine Videx EC Emtricitabine Emtriva Lamivudine Epivir Stavudine Zerit Tenofovir Viread Zidovudine Retrovir Non-nucleoside reverse transcriptase inhibitors Delavirdine Rescriptor Efavirenz Sustiva Nevirapine Viramune Protease inhibitors Atazanavir Darunavir Fosamprenavir Indinavir Lopinavir/ritonavir Nelfinavir Ritonavir Saquinavir Tipranavir

Reyataz Prezista Lexiva Crixivan Kaletra Viracept Norvir Invirase Aptivus

Fusion inhibitor Enfuvirtide

Fuzeon

CCR5 inhibitor Maraviroc

Selzentry

Integrase inhibitor Raltegravir

Isentress

Combination reverse transcriptase inhibitors Abacavir and lamivudine Abacavir, zidovudine, and lamivudine Efavirenz, tenofovir, emtricitabine Tenofovir and emtricitabine Zidovudine and lamivudine

Epzicom Trizivir Atripla Truvada Combivir

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HCV Testing Testing for HCV does not involve the counseling, confidentiality, or stigma issues usually associated with HIV testing. Providers vary greatly in how they proceed after identifying HCV-positive patients. Given that about 20%–33% of patients with severe mental illness in the United States are infected with HCV, a strong argument can be made that all such persons should be screened for the virus (Goldberg and Seth 2008). Certainly, all patients known to be infected with HIV should be screened for anti-HCV antibodies as part of their initial evaluation, as should those with high-risk behavior. HCV infection should be confirmed with qualitative polymerase chain reaction assay if the patient is at low risk and the diagnosis seems in doubt. Moreover, there is a small but measurable false-negative rate for antibody testing in patients who are severely immunosuppressed.

Natural History of HCV Disease Acute HCV disease is usually asymptomatic, but 25%–35% of patients develop some constitutional symptoms or jaundice. Serum alanine aminotransferase levels frequently rise, fluctuate, and fall again, suggesting recovery from the acute phase. However, following acute infection, HCV is not easily cleared by the immune system, and 75%–80% of acute HCV infections become chronic, as evidenced by persistent or intermittent HCV viremia. Chronic HCV infection can cause inflammatory infiltration, particularly of the portal tracts, as well as focal liver cell necrosis and fibrosis that bridges between portal tracts. Hepatitis C is the leading cause of liver transplantation in the United States. About 10%–20% of chronically infected patients progress to cirrhosis within 20–30 years of infection, and among those with cirrhosis, 1%–4% per year will develop hepatocellular carcinoma. Patients infected with HCV should be advised to minimize or preferably discontinue intake of alcohol. Immunosuppression associated with HIV significantly alters the natural history and clinical course of HCV, with HCV-associated cirrhosis occurring more frequently in patients with HCV/HIV co-infection (33%) than in HCV alone (11%). People with concurrent HCV do not tolerate highly active antiretroviral therapy as well as people with HIV alone, and this can interfere with effective HIV treatment (Soriano et al. 2008). Liver failure due to HCV is the leading non-AIDS cause of death in HIVinfected individuals (de Lédinghen et al. 2008). Because of increased risk of severe liver damage, all patients with HCV and/or HIV should be screened for immunity to hepatitis A and B and immunized accordingly.

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Neuropsychiatric Manifestations of HCV HCV-related cognitive impairment was previously assumed to be a consequence of cirrhosis-associated hepatic encephalopathy. Recent evidence suggests that one-third of people with chronic HCV experience cognitive impairment even in the absence of cirrhosis and that its occurrence is unrelated to laboratory values, viral load, and genotype (Perry et al. 2008). Attention, concentration, and psychomotor speed are the most impaired cognitive functions and may influence adherence to medical care and medications. HCV injury to the brain can occur via infection of resident (e.g., astrocytes) and migrating (e.g., macrophages) cells of the central nervous system; adaptation to neural cells; inflammation of basal ganglia and white matter; or neuronal loss (Letendre 2008).

HCV Treatment Diagnostic testing to determine the presence of HCV viremia and the extent of liver pathology should be completed as early as possible in the care of a patient infected with HCV. Patients with active HCV infection or evidence of chronic liver disease should be referred for care to a specialist with experience in treating hepatitis C. Not all patients with HCV require or benefit from treatment. Table 10–3 describes the treatment guidelines according to patient characteristics. In patients who are also HIV positive, antiretroviral therapy may need to be modified, delayed, or interrupted to complete an adequate course of therapy for HCV. The effectiveness of treatment is assessed by following HCV viral load. The goal of treatment is cure of HCV infection, manifested by reduction in hepatitis C viral load to undetectable, normalization of transaminases (alanine aminotransferase and aspartate transaminase), and cessation of liver disease progression. Combination therapy with daily oral ribavirin and once-weekly subcutaneous peginterferon alpha-2b is the standard therapy for HCV (Deutsch and Hadziyannis 2008). Exacerbation of psychotic symptoms during HCV treatment with interferon has been reported in sporadic cases, especially in patients with a history of abuse of various drugs, including hallucinogens. Interferon and ribavirin have potential neuropsychiatric side effects, including apathy, cognitive changes, irritability, depression, psychosis, and suicidal thoughts. Prospective studies with psychiatric patients, including people with schizophrenia (n=38), found that the response rates and adherence during treatment with standard interferon and ribavirin were similar to those of patients in a nonpsychiatric control group (Schaefer et al. 2007). Psychiatric patients were also not at increased risk of worsening depression or psychosis during antiviral treatment compared with con-

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TABLE 10–3. Hepatitis C virus (HCV) treatment guidelines Patient characteristics

Treatment recommendations

HCV genotype 2 or 3 with persistent HCV viremia

Treat with pegylated interferon plus ribavirin for 24 weeks. Liver biopsy is optional, but treat regardless.

HCV genotype 1 with persistent viremia and 1.

liver biopsy showing portal or bridging fibrosis, compensated cirrhosis, or moderate inflammation or necrosis

Treat with pegylated interferon plus ribavirin if no contraindications (assess risks and benefits on a case-by-case basis). If HCV viral load decreases within the initial 6–12 weeks of therapy, continue treatment for 48 weeks; if no decrease, discontinue treatment.

2.

no or minimal fibrosis on liver biopsy

Follow with observation, serial alanine aminotransferase measures, and liver biopsy every 3–5 years.

Decompensated cirrhosis, any genotype

Consider evaluation for liver transplant.

trols. Of note is that clinical trials using interferon as an add-on treatment for patients with schizophrenia have shown improvement in psychotic symptoms and reduction in the daily dosage of antipsychotic medication needed (Freudenreich et al. 2007). Nonetheless, patients with depression, psychotic disorders, or drug addiction should be carefully monitored for the development of psychiatric symptoms during interferon treatment, with interdisciplinary involvement to optimize adherence and response rates and to manage potential side effects. The neurocognitive complications of HCV itself, together with the symptoms of liver failure, such as fatigue, loss of appetite, loss of sexual drive, and impotence, can overlap with the complications of interferon treatment, the symptoms of psychiatric disorders, and the side effects of psychotropic drugs. Unfortunately, the majority of people with schizophrenia are not tested for HCV, and among those who are tested and are diagnosed with chronic

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HCV infection, few receive treatment. Among a sample of 108 outpatients with severe mental illness, only 32% reported having been previously tested for HCV (Goldberg and Seth 2008). Of those newly identified as HCV infected (n =18) within the study, half received an HCV-specific medical follow-up, and only one person was started on treatment.

Clinical Considerations Risk-Reduction Interventions and Strategies for HIV and HCV The most successful HIV prevention interventions are those addressing perinatal transmission, which has been reduced to approximately 1% in the United States with the effective use of antiretroviral treatment, and may be further reduced by intrapartum delivery strategies (Jamieson et al. 2007). However, a variety of interventions and strategies have been recommended to lower the risk of transmitting HIV and HCV. Harm reduction is the ultimate goal for both drug-related and sexual risk behaviors. The use of prevention strategies for injection drug users (e.g., syringe exchange and syringe availability at pharmacies) has reduced HIV and HCV transmission among injection drug users in the United States and in a number of other countries (Des Jarlais and Semaan 2008). No studies have been done of interventions to address the intermittent injection drug use that has been documented in the population with severe mental illness. Engaging patients in efficacious individual and group interventions to practice assertive behaviors and negotiation skills to increase selfprotective behaviors, including condom use, is necessary to stem new infections in this highly affected population. The best predictor of using a condom is having a condom. Institutional obstacles to condom acquisition are likely to impede patients’ initiative and ability to practice safer sex. Making condoms available anonymously to all patients, including inpatients with off-ward privileges or who engage in consensual sex on the ward, has been shown to be a cost-effective primary prevention intervention (Carmen and Brady 1990). HIV prevention programs that primarily dispense AIDS information have not been shown to influence risk behavior. As evidence indicates, knowledge is necessary but not sufficient to produce behavioral changes. Intensive, small-group programs that simultaneously target knowledge, attitudes, motivations, and cognitive and behavioral skills have been tried and found to produce reductions in high-risk sexual behaviors, including some that are substance related, among people with severe men-

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tal illness. Effective elements from randomized controlled trials of these HIV risk-reduction interventions (Wainberg et al. 2007) include 1) providing risk information; 2) enhancing awareness of attitudes, intentions, and readiness for change; 3) acquiring and rehearsing sexual risk-reduction behavioral skills; 4) problem solving for handling triggers for sexual risk taking; and 5) reinforcing behavior changes between intervention sessions. Mental health programs need to provide an environment in which healthy sexuality can be discussed. Patients can benefit from participating in mixed–HIV serostatus prevention groups; participants need not reveal their HIV status unless they wish to do so. Whatever the group’s composition, group leaders should leave time at the end of each session to discuss patients’ personal issues privately and to address their needs by making appropriate referrals, including for HIV testing. Because HCV shares modes of transmission with HIV, groups focused on HIV risk reduction may also wish to impart information about HCV infection through high-risk behaviors. Prevention efforts aimed at HCV are essential for patients who are currently (or at risk for) injecting drugs, because injection drug use is the risk factor responsible for a majority of HCV cases in the United States. Once staff have received training to do prevention interventions, they typically become motivated to start intervention groups for patients. Groups work best in longer-term day programs and outpatient programs. On inpatient units, short lengths of stay may limit the number of sessions patients can attend, but that issue should not discourage staff from setting up such programs. Individual counseling can reinforce patients’ motivations to protect themselves and others. Clinicians can encourage patients with HIV or HCV to disclose their illness to drug-use partners or sex partners and to use condoms. Fully informed decisions about risk and protection of others are the goals.

Accessing HIV- and HCV-Related Services That Psychiatric Patients Need Mental health service settings vary in their ability to offer HIV- and HCV-related screening, testing, and prevention interventions, and the range of services available may not yet be meeting the needs of people with severe mental illness (Goldberg and Seth 2008; Satriano et al. 2007). Risk assessment for HIV or HCV is intended to elicit specific information about patients’ sexual behaviors and drug use. Most patients, when asked in a direct, nonjudgmental way, are cooperative and forthcoming. Rather than asking “Have you ever...,” asking “How often have you...”

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is more likely to elicit useful risk information without raising a patient’s defenses by implying that the clinician will judge such behaviors negatively or consider them unusual. The ease with which the clinician is able to discuss sex and drug use will set the anxiety level for the patient, and normalizing any patient discomfort can create a more relaxed tone. HIV testing is guided by regulations that vary from state to state, but the CDC-recommended opt-out testing does not require counseling. To better prepare patients for potential positive results, mental health programs may want to provide pretest and posttest counseling that is coordinated with medical care or conduct the testing themselves. The initial diagnosis of HIV infection may occur when a patient first becomes infected or has advanced AIDS, or any time in between. Shock and disbelief may be followed by depression, anxiety, and fear in adjusting to having contracted a serious and potentially deadly illness. Like severe mental illness, HIV and AIDS can be highly stigmatizing, possibly resulting in rejection, abandonment, and further social isolation. If a worsening of psychiatric symptoms follows the initial HIV diagnosis, the most effective intervention is individual counseling and supportive therapy geared to the patient’s current mental status and his or her knowledge and understanding of HIV infection. Legal regulations or guidelines for confidentiality and the disclosure of HIV- or AIDS-related information set the stage for upholding humane and responsible individual and public health standards. Contact notification by physicians may not be required, but legal statutes may allow doctors or public health officers to inform a contact who is at significant risk if they determine that a patient will not do so. Laws that are applicable to the locality should be consulted when making decisions that involve confidentiality and contact notification. For HIV-infected psychiatric patients who are asymptomatic, supportive groups may encourage behavioral change and promote ways to preserve physical health in the community and within the psychiatric setting. This kind of group intervention can prevent worsening of psychiatric symptoms and provide a sense of community that can decrease social isolation, reinforce safer peer norms, and encourage altruism, which appeals to ego strengths and gives patients a sense of worth and accomplishment. Services may be directed at patients on the basis of their suspected or presumed risks rather than thorough individual risk assessments (Brunette et al. 2000; McKinnon et al. 1999). This model of risk evaluation is typically relied upon when there are unmet needs for staff training. Training is one important way to improve service delivery systems.

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Testing for HCV can occur at any point and does not require special consent. Routine screening for HCV, followed by referral for evaluation of every HCV-positive patient, including those with schizophrenia whose psychiatric condition is stable, is warranted. Clinicians need to explain the test result to patients found to be HCV positive and to refer such patients for further evaluation and, as appropriate, hepatitis A and B immunization. Clinicians may be in the best position to help their patients access HIV and HCV testing, treatment, and prevention opportunities. They can employ many strategies to help their patients determine their risk of acquiring or transmitting HIV or HCV, prevent new infections, promote healthier behaviors, and reduce the impact of HIV- and HCVrelated illness on this vulnerable population. Clinicians also are uniquely qualified to help their patients manage the many medications required to maintain their psychiatric and physical health.

Psychopharmacology for People With HIV or HCV and Schizophrenia Important points to keep in mind when prescribing psychotropic medication to people with schizophrenia who have comorbid HIV or HCV infection are listed in Table 10–4. Notably, as HIV progresses, people with preexisting psychiatric conditions may develop new or increased side effects when taking medications they were previously able to tolerate. In the course of the medical management of HIV infection, particularly in later stages of HIV disease, a large number of medications may be prescribed, including antibacterial, antifungal, antineoplastic, antiretroviral, and other antiviral agents (Wainberg et al. 2000). Any attempt to diagnose drug-induced neuropsychiatric syndromes requires an appreciation of both the therapeutic use and potential side effects of these medications. Some of these are described in the Practice Guidelines of the American Psychiatric Association (American Psychiatric Association 2000), but new antiretroviral agents are being developed at a rapid pace and existing medications to treat HIV-related infections and neoplasms are too numerous to describe fully. Neuropsychiatric side effects of antiretrovirals have been reported most commonly with efavirenz and occasionally with nevirapine. Despite predictions of drug-drug interactions (which can be found in handheld databases, through hospital pharmacies, and at a variety of Web sites), experienced prescribers generally find they can effectively use the full range

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of psychotropic medications. Overlapping toxicities between different medications must also be taken into consideration. Because advanced HIV infection is associated with greater sensitivity to both the therapeutic effects and side effects of psychotropic medications, the best approach is to start a patient taking the lowest possible dosage and increase the dosage slowly. Drug levels, if available, should be monitored closely, especially when patients are on complex medication regimens. Methadone, recreational drugs, and herbal preparations also can affect medication levels. Most psychiatric medications are metabolized by the liver and therefore may require more careful monitoring in patients chronically infected with HCV. In particular, for patients who manifest clinical or laboratory signs of liver failure, medication metabolism can be dangerously reduced such that the patients may accumulate toxic levels of drugs at dosages they were previously able to tolerate. In general, the use of most psychiatric medications is relatively safe with both HIV and HCV treatments. For patients with HCV illness, periodic liver function tests are the standard of care. Because some psychotropic medications (e.g., antidepressants, lithium, valproic acid, carbamazepine) may elevate liver enzymes in HCV-infected patients, it is important to check these at baseline, early after initiation of therapy (after 2–4 weeks), and every 2–3 months thereafter. However, alanine aminotransferase elevations may be due to fluctuations in the HCV itself or other factors (e.g., unacknowledged alcohol use) (Felker et al. 2003). Combined toxicities are important to consider, particularly during treatment with medications that can have an impact on bone marrow activity (e.g., clozapine, carbamazepine, zidovudine, interferon, ribavirin) or cause other additive side effects. Psychiatric patients, like medical patients, are often nonadherent to medication, which they may perceive as one of the few aspects of their lives they can control. It is important to time the beginning of an antiviral regimen with a commitment to the treatment and to help patients see that following an HIV or HCV medication regimen can be part of gaining control. Working with a patient to promote adherence to psychotropic medications will be the best predictor of whether the patient can follow an HIV or HCV medication regimen. The clinician and infectious disease specialist must communicate about the patient’s need for and readiness to begin antivirals; select, in concert with the patient, regimens that minimize drug-drug interactions; keep the number and dosages of pills the patient has to take to the minimum necessary; and coordinate their treatment plans.

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TABLE 10–4. Psychotropic medication in patients with schizophrenia with comorbid HIV and/or HCV infection Medically asymptomatic and not receiving antiviral treatment HIV Most psychotropics can be used as usual. Monitor use of typical antipsychotics for increased incidence of extrapyramidal side effects. Evaluate for testosterone deficiency if depressed or fatigued. HCV Whenever possible, avoid drugs that cause liver toxicity. Follow liver enzymes. Medically ill and/or receiving antiviral treatment HIV For most psychotropics, start with low doses and increase slowly. Check for interactions and overlapping toxicities between psychotropics and antiretrovirals. Note that protease inhibitors are potent inhibitors of one or more cytochrome P450 enzymes, which may have implications for interactions with psychiatric and other medications. Monitor use of typical antipsychotics for severe and rapid onset of extrapyramidal side effects. Monitor use of atypical antipsychotics with antiretroviral medications, which overlap in causing metabolic abnormalities. Avoid carbamazepine, which lowers antiretrovirals. Avoid lithium with HIV-associated nephropathy. Consider that antianxiety drugs metabolized by glucuronidation have fewer drug interactions with antiretrovirals (i.e., clorazepate, lorazepam, oxazepam, temazepam). Evaluate for testosterone deficiency if depressed or fatigued. Be aware that antiretrovirals alter levels of methadone and buprenorphine, usually by decreasing them. Check effects of specific antiretroviral regimens and modify doses as needed. Caution against St. John’s wort, which lowers antiretrovirals. HCV Avoid drugs that cause liver toxicity. Follow liver enzymes. Monitor for depression and worsening of psychotic symptoms while on antiviral therapy; treat as necessary. Source: American Psychiatric Association 2000 and http://www.nynjaetc.org/ cem.html.

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Conclusion Understanding the HIV and HCV epidemics and their underpinnings among people with severe mental illness can help clinicians to recognize when their patients with schizophrenia are at risk of acquiring or transmitting these viruses and to intervene appropriately and effectively with preventive, counseling and testing, medical, and supportive services. It is critical for clinicians to receive training to enhance their knowledge and skills in these areas, to ask comfortably and nonjudgmentally about their patients’ risks rather than wait until patients are ill to learn about risk behaviors, and to continually access up-to-date information and technical assistance about how to prevent and treat these infections among their patients.

Key Clinical Points ◗

People with schizophrenia are at heightened risk for acquiring HIV and HCV infection, and both of these infections can result in increased morbidity and mortality.

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Both HIV and HCV enter the central nervous system and can cause neurocognitive symptoms that complicate the psychiatric presentations and treatment of people with schizophrenia.

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Improvements in the treatments for HIV and HCV infections warrant assertive efforts to identify patients who are infected.

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Testing for HIV and HCV infection and offering prevention interventions should be part of routine care for people with schizophrenia.

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Patients who test positive for either HIV or HCV should routinely be referred to medical providers who can assess and treat these conditions. Mental health care providers need to stay involved to ensure patient adherence to medical care and help manage mental health complications of treatment.

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Mental health providers often need to advocate to ensure that people with schizophrenia are not rejected from HIV and HCV treatment solely because they have a mental illness.

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References Agency for Healthcare Research and Quality: Management of chronic hepatitis C. June 2002. Available at: http://www.ahrq.gov/clinic/tp/hepctp.htm. Accessed October 25, 2008. Al Jurdi RK, Burruss JW: Prevalence of hepatitis C in psychiatric institutions. Psychosomatics 44:439–440, 2003 American Psychiatric Association: APA practice guidelines: treatment of patients with HIV/AIDS. November 2000. Available at: http://www.psychiatryonline .com/pracGuide/pracGuideChapToc_4.aspx. Accessed October 25, 2008. Antinori A, Arendt G, Becker JT, et al: Updated research nosology for HIVassociated neurocognitive disorders. Neurology 69:1789–1799, 2007 Barre-Sinoussi F, Chermann JC, Rey F, et al: Isolation of a T-lymphotropic retrovirus from a patient at risk for acquired immunodeficiency syndrome. Science 220:868–871, 1983 Branson BM, Handsfield HH, Lampe MA, et al; Centers for Disease Control and Prevention (CDC). Revised recommendations for HIV testing of adults, adolescents, and pregnant women in health-care settings. MMWR Recomm Rep 55:1–17, 2006 Brunette MF, Mercer CC, Carlson CL, et al: HIV-related services for persons with severe mental illness: policy and practice in New Hampshire community mental health. J Behav Health Serv Res 27:347–353, 2000 Butterfield MI, Bosworth HB, Meador KG, et al: Gender differences in hepatitis C infection and risks among persons with severe mental illness. Psychiatr Serv 54:848–853, 2003 Butterfield MI, Bosworth HB, Stechuchak KM, et al: Racial differences in hepatitis B and hepatitis C and associated risk behaviors in veterans with severe mental illness. J Natl Med Assoc 96:43–52, 2004 Carey MP, Carey KB, Kalichman SC: Risk for human immunodeficiency virus (HIV) infection among persons with severe mental illnesses. Clin Psychol Rev 17:271–291, 1997 Carmen E, Brady SM: AIDS risk and prevention for the chronic mentally ill. Hosp Community Psychiatry 41:652–657, 1990 Centers for Disease Control and Prevention, Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention: Revised surveillance case definitions for HIV infection among adults, adolescents, and children aged <18 months and for HIV infection and AIDS among children aged 18 months to <13 years—United States, 2008. MMWR Morb Mortal Wkly Rep 57(RR10):1–8, 2008 Clarke A, Kulasegaram R: Hepatitis C transmission: where are we now? Int J STD AIDS 17:74–80, 2006 Cournos F, McKinnon K: HIV seroprevalence among people with severe mental illness in the United States: a critical review. Clin Psychol Rev 17:259–269, 1997

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de Lédinghen V, Barreiro P, Foucher J, et al: Liver fibrosis on account of chronic hepatitis C is more severe in HIV-positive than HIV-negative patients despite antiretroviral therapy. J Viral Hepat 15:427–433, 2008 Des Jarlais DC, Semaan S: HIV prevention for injecting drug users: the first 25 years and counting. Psychosom Med 70:606–611, 2008 Deutsch M, Hadziyannis SJ: Old and emerging therapies in chronic hepatitis C: an update. J Viral Hepat 15:2–11, 2008 Dinwiddie SH, Shicker L, Newman T: Prevalence of hepatitis C among psychiatric patients in the public sector. Am J Psychiatry 160:172–174, 2003 Felker BL, Sloan KL, Dominitz JA, et al: The safety of valproic acid use for patients with hepatitis C infection. Am J Psychiatry 160:174–178, 2003 Fidler S, Fox J, Porter K, et al: Primary HIV infection: to treat or not to treat? Curr Opin Infect Dis 21:4–10, 2008 Freudenreich O, Gandhi RT, Walsh JP, et al: Hepatitis C in schizophrenia: screening experience in a community-dwelling clozapine cohort. Psychosomatics 48:405–411, 2007 Goldberg RW, Seth P: Hepatitis C services and individuals with serious mental illness. Community Ment Health J 44:381–384, 2008 Huckans MS, Blackwell AD, Harms TA, et al: Management of hepatitis C disease among VA patients with schizophrenia and substance use disorders. Psychiatr Serv 57:403–406, 2006 Hulgan T, Shepherd BE, Raffanti SP, et al: Absolute count and percentage of CD4+ lymphocytes are independent predictors of disease progression in HIV-infected persons initiating highly active antiretroviral therapy. J Infect Dis 195:425–431, 2007 Jamieson DJ, Read JS, Kourtis AP, et al: Cesarean delivery for HIV-infected women: recommendations and controversies. Am J Obstet Gynecol 197 (suppl 3): S96–S100, 2007 Kalichman SC, Kelly JA, Johnson JR, et al: Factors associated with risk for HIV infection among chronic mentally ill adults. Am J Psychiatry 151:221–227, 1994 Kelly JA, Murphy DA, Bahr GR, et al: AIDS/HIV risk behavior among the chronic mentally ill. Am J Psychiatry 149:886–889, 1992 Klinkenberg WD, Caslyn RJ, Morse GA, et al: Prevalence of human immunodeficiency virus, hepatitis B, and hepatitis C among homeless persons with co-occurring severe mental illness and substance use disorders. Compr Psychiatry 44:293–302, 2003 Letendre SL: Neurocognitive effects of HCV, methamphetamine abuse, and HIV: multiple risks and mechanisms. Ann Gen Psychiatry 7 (suppl 1):S39, 2008 Malow RM, Devieux JG, Martinez L, et al: History of traumatic abuse and HIV risk behaviors in severely mentally ill substance abusing adults. J Fam Violence 21:127–135, 2006 Marks G, Crepaz N, Janssen RS: Estimating sexual transmission of HIV from persons aware and unaware that they are infected with the virus in the USA. AIDS 20:1447–1450, 2006

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McDermott BE, Sautter FJ, Winstead DK, et al: Diagnosis, health beliefs, and risk of HIV infection in psychiatric patients. Hosp Community Psychiatry 45:580–585, 1994 McKinnon K, Cournos F: HIV infection linked to substance use among hospitalized patients with severe mental illness. Psychiatr Serv 49:1269, 1998 McKinnon K, Cournos F, Sugden R, et al: The relative contributions of psychiatric symptoms and AIDS knowledge to HIV risk behaviors among people with severe mental illness. J Clin Psychiatry 57:506–513, 1996 McKinnon K, Cournos F, Herman R, et al: AIDS-related services and training in outpatient mental health care agencies in New York. Psychiatr Serv 50:1225–1228, 1999 Meade CS, Sikkema KJ: HIV risk behavior among adults with severe mental illness: a systematic review. Clin Psychol Rev 25:433–457, 2005 Meade CS, Sikkema KJ: Psychiatric and psychosocial correlates of sexual risk behavior among adults with severe mental illness. Community Ment Health J 43:153–169, 2007 Menon AS, Pomerantz S: Substance use during sex and unsafe sexual behaviors among acute psychiatric inpatients. Psychiatr Serv 48:1070–1072, 1997 Meyer JM: Prevalence of hepatitis A, hepatitis B and HIV among hepatitis C seropositive state hospital patients: results from Oregon State Hospital. J Clin Psychiatry 64:540–545, 2003 Otto-Salaj LL, Heckman TG, Stevenson LY, et al: Patterns, predictors and gender differences in HIV risk among severely mentally ill men and women. Community Ment Health J 34:175–190, 1998 Perry W, Hilsabeck RC, Hassanein TI: Cognitive dysfunction in chronic hepatitis C: a review. Dig Dis Sci 53:307–321, 2008 Rosenberg SD, Goodman LA, Osher FC, et al: Prevalence of HIV, hepatitis B, and hepatitis C in people with severe mental illness. Am J Public Health 91:31–37, 2001 Satriano J, McKinnon K, Adoff S: HIV service provision for people with severe mental illness in outpatient mental health care settings in New York. J Prev Interv Community 33:95–108, 2007 Schaefer M, Hinzpeter A, Mohmand A, et al: Hepatitis C treatment in “difficultto-treat” psychiatric patients with pegylated interferon-alpha and ribavirin: response and psychiatric side effects. Hepatology 46:991–998, 2007 Soogoor M, Daar ES: Primary human immunodeficiency virus type 1 infection. Curr HIV/AIDS Rep 2:55–60, 2005 Soriano V, Puoti M, Garcia-Gascó P, et al: Antiretroviral drugs and liver injury. AIDS 22:1–13, 2008 Staprans SI, Feinberg MB: Natural history and immunopathogenesis of HIV-1 disease, in The Medical Management of AIDS, 5th Edition. Edited by Sande MA, Volberding PA. Philadelphia, PA, WB Saunders, 1997, pp 29–56 Tabibian JH, Wirshing DA, Pierre JM, et al: Hepatitis B and C among veterans on a psychiatric ward. Dig Dis Sci 53:1693–1698, 2008

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CHAPTER 11 Substance Abuse and Schizophrenia Peter F. Buckley, M.D. Jonathan M. Meyer, M.D.

The co-occurrence of schizophrenia and substance use or abuse is common and presents complex issues for mental health practitioners. Approximately 50% of individuals with schizophrenia will develop substance use disorders at some point during their lives, and about half of this group will exhibit current substance abuse or dependence (Buckley 2006). The abuse of drugs and alcohol by persons with severe mental illnesses has a wide range of adverse effects on the course of mental illness and psychosocial functioning, including compliance, prognosis, and rates of acute service utilization. Overall, substance abuse comorbidity substantially complicates the course and management of schizophrenia. In this chapter, we provide a brief overview of the scope of the problem, with a detailed focus on the demographics of substance use, the adverse consequences of the major drugs of abuse in patients with schizophrenia, and the clinical approach to patients with dual diagnoses.

Demographics of Substance Use in Patients With Schizophrenia The proportion of patients with schizophrenia who have a comorbid drug or alcohol use disorder varies tremendously in published studies, 275

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from as low as 10% to as high as 70% (Mueser et al. 1990). This wide range is partially due to variability in the diagnostic criteria employed for schizophrenia, sample demographic characteristics (e.g., male vs. female, urban vs. rural), types of patient populations studied (e.g., inpatient vs. outpatient), and criteria for defining drug and alcohol disorders (e.g., Diagnostic and Statistical Manual of Mental Disorders [DSM] diagnosis, positive urine toxicology screens, rating scales) (Mueser et al. 1990). Although structured clinical interviews have been found to produce the most reliable diagnoses, these are time consuming and expensive due to the need for trained personnel and, therefore, are not often used in clinical studies (Mueser et al. 1995). Surveys conducted exclusively in inpatient settings tend to produce higher rates of substance use disorders, in part because persons with dual disorders (i.e., substance use and another major Axis I disorder) are more likely to enter into treatment because exacerbation of either problem may become a focus of clinical attention (Mueser et al. 1995). The Epidemiologic Catchment Area (ECA) study revealed that 47% of all individuals in the United States with a lifetime diagnosis of schizophrenia or schizophreniform disorder met criteria for some form of substance abuse or dependence (33.7% for alcohol disorder and 27.5% for another drug abuse disorder) (Regier et al. 1990). In addition to the lifetime prevalence data, the ECA study found that the odds of having a substance abuse diagnosis were 4.6 times greater for persons with schizophrenia compared with the rest of the population, with the odds of having an alcohol disorder over 3 times greater and of having another drug disorder 6 times greater (Regier et al. 1990). This finding was replicated in the National Comorbidity Survey (Kessler et al. 1997) and again in the most recent National Comorbidity Survey Replication (Merikangas et al. 2007). The high rate of comorbidity is comparable with the range of 40%–60% lifetime prevalence gleaned from an analysis of 47 published studies with sample sizes of at least 30 patients with schizophrenia and in which the criteria for abuse or dependence were clearly delineated (Cantor-Graae et al. 2001). Cantor-Graae et al. (2001) also found that studies in which more than one method of diagnosis was employed (e.g., chart review plus interview) yielded higher prevalence rates compared with those that relied on a single method. Regardless of method, in community samples of patients with schizophrenia that are not comprised solely of inpatient groups, a figure of approximately 50% lifetime prevalence is found repeatedly. Additionally, studies from all over the world confirm a strong association between schizophrenia and substance abuse (O’Dely et al. 2005). For example, a Swedish study combining both structured interview and chart review

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of 87 patients with schizophrenia noted a lifetime prevalence of any substance use disorder of 48.3% (47.1% for alcohol alone or in combination with other drugs, 26.4% for alcohol alone) (Cantor-Graae et al. 2001). A British study of 168 patients prospectively evaluated at the time of their first episode of psychosis found that 37% of patients were abusing drugs or alcohol (Cantwell et al. 1999). Nicotine is clearly the most frequently abused agent by patients with schizophrenia, with prevalences ranging from 70% to 90%, over three times greater than use by the general population (De Leon et al. 2002, 2007; see also Chapter 9, “Nicotine and Tobacco Use in Patients With Schizophrenia”). Excluding nicotine use, the ECA study results are consistent with other prevalence studies of schizophrenia demonstrating that alcohol tends to be the most frequently abused agent (20%–60%), followed by cannabis (12%–42%) and cocaine (15%–50%) (Chambers et al. 2001). Use of amphetamines (2%–25%), hallucinogens, opiates, and sedatives/hypnotics is less common. Findings from a British firstepisode study (Barnett et al. 2007) indicated that 43% of patients abused alcohol, 51% abused cannabis, and 38% had a pattern of polysubstance abuse. Archie et al. (2007) reported a small shift in these abuse patterns when patients are followed over time. Harrison et al. (2008) reported an almost 50% decline in overall substance use, except smoking (which rose from 60% to 64%) when patients are reassessed after 1 year. Aside from nicotine, alcohol and marijuana were the most frequently abused substances, and this also remained constant after 14 months of mean follow-up. In the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study, marijuana was the most commonly used drug by patients with schizophrenia, followed by cocaine and opiates (Swartz et al. 2008). Polysubstance abuse was also common in the CATIE sample. The most consistent findings with regard to demographic characteristics are that those who are younger, were younger at age of schizophrenia onset, or are male are more likely than those who are older and female to abuse drugs or alcohol (Barnett et al. 2007; Hambrecht and Hafner 2000). Males were more frequent among the abuser group (81%) than among the nonabuser group (69%) in the CATIE study (Swartz et al. 2008). It is important to note, however, that evidence is accumulating to document that substance use difficulties among women are not sufficiently recognized, and that women with schizophrenia and comorbid substance disorders are less likely to receive substance abuse treatment (Alexander 1996; Comtois and Ries 1995). The undertreatment of women may lead to unrealistically low prevalence estimates in retrospective chart review studies, yet even in interview studies male gender appears as an independent risk factor after the disparities in gender

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frequency are controlling for among study participants (Cantor-Graae et al. 2001). Also, evidence from a Malmo, Sweden, cohort (CantorGraae et al. 2001) and other studies indicates that the onset of substance use in schizophrenia occurs at a younger age in males than in females (O’Dely et al. 2005; Salyers and Mueser 2001). Conflicting data have been reported regarding the functional capabilities of substance-using patients compared with non-substanceusing patients with severe mental illness. In one of the first studies to examine this issue, Mueser et al. (1990) reported findings on 149 recently hospitalized patients who met DSM-III-R criteria for schizophrenia, schizoaffective disorder, or schizophreniform disorder, and found lower educational levels among those with substance abuse disorders than among those without substance use disorders. Arndt et al. (1992), in a study of 131 schizophrenia patients with and without comorbid substance abuse disorder (n = 64 and 67, respectively) matched for symptomatology and clinical history, noted better premorbid adjustment among the so-called pathological substance users (Arndt et al. 1992). In another study, Zisook et al. (1992) compared 34 patients with schizophrenia who had histories of substance abuse with 17 patients with schizophrenia who were abstinent and found that the substance abusers were more likely to have been married or gainfully employed. In the CATIE study (Swartz et al. 2008), abusers were overall similar in terms of marital status and years of education. They were also similar on overall functioning, based on their Clinical Global Impression Scale scores. Salyers and Mueser (2001) examined 404 patients with a history of recent hospitalization (i.e., prior 3 months) recruited from within a large multicenter psychosocial treatment strategies study. Individuals were ages 18–55, agreed to receive fluphenazine decanoate but not other major psychotropic agents, and received at least three of the monthly assessments of psychiatric symptoms, social functioning, side effects, and substance use over the 3- to 6-month follow-up period. Notably, those who were homeless or transient and patients with active ongoing physical dependence (or suspected drug-induced psychosis but not schizophrenia) were excluded from the study. In this study, those patients who consistently reported low or no use of substances scored significantly higher than regular drug or alcohol users on assessments of negative symptoms, particularly the social amotivation and diminished expression scores, although the groups were comparable on ratings of psychotic symptoms (Brief Psychiatric Rating Scale) and distress (Symptom Checklist–90) (Salyers and Mueser 2001). Also, users and nonusers had no significant differences in ratings of tardive dyski-

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nesia, parkinsonism, or akathisia, although those who reported the greatest frequency of social problems had higher akathisia ratings irrespective of degree of substance use. As one might expect from those who manifest greater negative symptomatology, the low- or no-use group also demonstrated more severe impairment in leisure activities and less frequent social contacts. Although the substance users enjoyed a higher level of social functioning, the drug users in particular reported significantly greater interpersonal problems compared to the low- or no-use group. Interestingly, despite the greater social functional status of substance users, this group had an earlier age of onset for their mental illness and more hospitalizations than the low- or no-use group. In the CATIE study (Swartz et al. 2008), symptom measures were similar between abusers and nonabusers, although abusers had more prior illness relapses and an earlier age at onset. Demographic differences exist between urban and rural groups with schizophrenia, especially with regard to housing, and data also suggest that patterns of substance use differ between the two groups. The use of alcohol alone or in combination with cannabis is common among schizophrenia patients living in a rural setting, whereas the use of multiple substances, particularly cocaine, is common among those living in urban settings (Mueser et al. 2001). Also, patients with a dual diagnosis of schizophrenia and substance use or abuse tend to engage in a variety of risky behaviors that result in a higher prevalence of human immunodeficiency virus (HIV), hepatitis B, and hepatitis C (Meyer 2003; Wirshing et al. 2005; also see Chapter 10, “HIV and Hepatitis C in Patients With Schizophrenia,” in this volume). Whereas the former may be transmitted sexually, hepatitis C in the United States is transmitted primarily by use of shared needles among intravenous drug users. Although patients with schizophrenia are more likely to engage in high-risk behavior resulting in HIV or hepatitis C infection, limited data are available about the extent of intravenous drug abuse by individuals with this disorder. In one large study of persons with mental illness (65% of whom had schizophrenia or schizoaffective disorder), 62.1% of those infected with hepatitis C (n =145) reported a lifetime history of intravenous drug abuse (IVDA), whereas only 5.1% of the hepatitis C–negative group (n =604) reported a history of IVDA (Rosenberg et al. 2001). Among the HIV-positive persons with severe mental illness, the lifetime prevalence of IVDA was 8.6% compared with 1.4% for the HIV-negative group (Rosenberg et al. 2001). A smaller study of 91 patients with schizophrenia employing two self-reporting measures found a 22.4% lifetime prevalence of injected drug use; moreover, despite IVDA and high-risk sexual behaviors, 65%

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reported no concern with HIV infection, and AIDS knowledge was significantly lower among the patients with schizophrenia than the control group, particularly among those with long-standing illness and multiple psychiatric admissions (Grassi et al. 1999). Meyer (2003) showed a high rate of hepatitis exposure in long-stay patients at a state hospital. Wirshing et al. (2005) showed similar findings in the Veterans Administration dual-diagnosis population (schizophrenia plus substance abuse).

Patterns of Substance Abuse Among Persons With Schizophrenia Although substance use disorders occur significantly more frequently in persons diagnosed with schizophrenia than in the general population, little evidence is available to suggest that persons with schizophrenia abuse substances for different reasons than the general population. Specifically, the literature demonstrates that patients with schizophrenia do not differentially choose to abuse specific drugs to ameliorate specific psychic states. Multiple studies indicate that patients with schizophrenia do not preferentially abuse certain agents and that choice of agent does not correlate with extent of psychopathology; rather, these individuals use those substances that are most available and affordable (Cantor-Graae et al. 2001; Chambers et al. 2001; Mueser et al. 1992). For the most part, research has also failed to find different patterns of drug choice between persons with schizophrenia and groups of patients with other major mental disorders. Thus, although the causes of dysphoria in schizophrenia may be linked to the illness (e.g., neuroleptic side effects, negative symptoms, demoralization), data simply do not support the notion that patients with schizophrenia uniquely prefer certain drugs (Degenhardt et al. 2007). The notion that schizophrenia patients abuse substances to alleviate certain mental states or medication side effects (the “self-medication” hypothesis) derives from research focusing on patients’ reported reasons for substance use. Dixon et al. (1991) found that persons with schizophrenia abuse drugs for reasons that are similar to those for persons without schizophrenia (i.e., to get high, to feel better, to escape, and to be less depressed), rather than for symptom control. Other observational data lend credence to the hypothesis that addictive behavior occurs independently as an inherent aspect of the neural abnormalities that contribute to schizophrenia, as opposed to being motivated or driven secondarily by symptoms of the disorder or negative psychic states induced by medication. In a review of the literature on

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the biological basis for substance abuse in schizophrenia, Chambers et al. (2001) noted that some individuals do report symptomatic improvement during substance use, whereas others note symptom exacerbation but nevertheless persist in the use of substances. Moreover, self-reports of improvement are often at variance with the clinical observation of symptomatic worsening. In addition, substances of abuse have widely divergent effects on neurotransmitters, thereby weakening the assertion that the concurrent use of agents with opposing effects is intended to ameliorate a specific psychic state. Dervaux et al. (2001) used diagnostic interview to assess the reasons for and extent of substance use in a study of 100 patients with schizophrenia. Other assessment tools in this study included the Positive and Negative Syndrome Scale (PANSS), self-report measures of impulsivity and sensation seeking, and a self-report measure of anhedonia. Fortyone percent of this cohort met lifetime criteria for substance abuse or dependence, but this group did not differ from the nonabusing patients with schizophrenia on the basis of ratings of anhedonia, or in symptom severity (as rated by PANSS). Interestingly, this study did not find differences between users and nonusers on the basis of age of first psychiatric contact and number of hospitalizations. Nonetheless, the substance abusers rated significantly higher on the measures of impulsivity and sensation seeking, in a manner consistent with substance users without schizophrenia; moreover, these measures were elevated even among the subgroup reporting only past abuse or dependence, leading the authors to suggest that impulsivity and drug-seeking behavior may not be induced by the use of substances, but rather are inherent aspects of schizophrenia or correspond to the traits of novelty seeking and impulsivity that are seen in the general population who abuse drugs. Indeed, Swann et al. (2004) invoked a model of heightened impulsivity as well as behavioral sensitization to explain the high rates of comorbid substance abuse in patients with bipolar disorder. Notably, some studies have found higher reported rates of depression among patients with comorbid substance abuse (Duke et al. 1994; Hambrecht and Hafner 2000), although others have not replicated this finding (Drake et al. 1989; Mueser et al. 1990). Recently, Degenhardt et al. (2007) found no difference in depression between schizophrenia patients with and those without cannabis abuse. Additionally, cannabis abuse was not associated with worsening of depressive symptoms. The research on antipsychotic side effects and substance abuse has generally produced mixed results when investigators examined tardive dyskinesia or other measures of extrapyramidal side effects. Akathisia and related dysphoria have been found in some studies to be associated

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with current alcohol use and increased risk of future alcohol use (Duke et al. 1994; Voruganti et al. 1997). However, these reasons may be less relevant in the current era of treatment with second-generation antipsychotic medications, which are generally considered to have low rates of extrapyramidal side effects and to have mood stabilization and enhancing properties (Green et al. 2008). Other observations suggesting that schizophrenia and addictive behavior are independent manifestations of common underlying dysregulation of neural circuitry are that use of both drugs and alcohol commonly precedes psychosis and that 77% of first-episode patients are smokers prior to neuroleptic treatment (Chambers et al. 2001). The relationship between substance use and symptom onset is thus an area of intense scrutiny for those who see the predilection toward psychosis and addictive behavior as independent but parallel processes engendered by common neuropsychiatric deficits. In the literature review cited earlier, Cantor-Graae et al. (2001) noted two questions involving schizophrenia and substance use that are not clearly answerable with the current body of data. The first is “the extent to which substance use (especially psychoactive substance use) contributes to the development of schizophrenia, whether as an independent risk factor in itself or by precipitating illness onset in vulnerable individuals” (p. 72). The second, discussed in the following section, is “the degree to which history of substance abuse is associated with a more chronic clinical course of schizophrenia” (p. 72). Because comorbidity is not merely a chance co-occurrence of two disorders and because self-relief of symptoms and side effects also appears to be an inadequate explanation of drug use by people with schizophrenia, a reasonable question is whether drug use actually causes schizophrenia. This is a vexing question (and often comes across as a “chicken and egg” problem), especially at the first presentation of psychosis, where substance abuse is common. Moreover, studies have produced some evidence that patients at high clinical risk for psychosis who abuse drugs during the vulnerable prodromal stage are at great risk of conversion to frank psychosis (Cannon et al. 2008). Caton et al. (2005) examined this relationship among patients who were presenting with their first psychotic episode, all of whom were actively abusing drugs. On the basis of longitudinal evaluation, the authors reported that key predictors can help determine whether a patient has substanceinduced psychosis or primary schizophrenia. In the longitudinal evaluation of patients who presented as acutely psychotic, 44% were later classified as having a drug-induced psychosis and 56% received a diagnosis of schizophrenia. Patients with a drug-related psychosis had

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fewer positive and negative symptoms but more visual hallucinations. They were also more likely to have a family history of substance abuse. Mathias et al. (2008) pointed out that little is known about substanceinduced psychosis. This nosology may get an “extreme makeover” in the workings toward DSM-V (see Mathias et al. 2008). Because use of substances, particularly psychotomimetic agents (e.g., hallucinogens) and stimulants, may increase the likelihood of developing psychosis, investigators have attempted to determine the course of substance use in relation to onset of psychosis. To assess the temporal sequence of substance abuse and illness onset, Buhler et al. (2002) performed a structured interview of 232 first-episode patients with schizophrenia, and then prospectively interviewed and followed another sample of 115 first-episode patients representing 86% of consecutive admissions in the local area. The investigators found that 62% of those patients with drug abuse and 51% with alcohol abuse began their habit before any signs of schizophrenia were manifest, including prodromal nonpsychotic symptoms. Importantly, no correlation was found between onset of substance abuse and onset of psychotic symptoms, although the onset of abuse and the psychotic disorder occurred in the same month in 18.2% who abused alcohol and 34.6% who used drugs, implying that in a subset of schizophrenia patients, development of psychotic symptoms was speeded up or precipitated by substance use, particularly cannabis use. These data from the combined pools of first-episode patients are similar to those reported for the original group of 232 first-episode patients analyzed separately (Hambrecht and Hafner 2000), of whom 27.5% had a cannabis use problem more than 1 year (often more than 5 years) before onset of prodromal schizophrenia symptoms, 34.6% had the onset of symptoms and cannabis use in the same month, and 37.9% had symptoms of schizophrenia before beginning substance use. Archie et al. (2007) illustrated the opportunity to reduce the rates of substance abuse early in the course of schizophrenia.

Impact of Substance Use Disorders on Development and Course of Illness Some researchers have attempted to determine which drugs, if any, are most likely to affect the development and course of schizophrenia. Despite having other negative medical consequences, alcohol does not appear to increase the risk of developing schizophrenia. The evidence for illicit drugs such as cocaine, heroin, methamphetamines, and

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3,4-methylenedioxymethamphetamine (ecstasy) is at best mixed. The most compelling evidence exists for cannabis causing schizophrenia. Overall, the prevalence of cannabis abuse disorders in patients with schizophrenia is about 4.5 times higher than in the general population. There is also some (albeit less robust) evidence suggestive of a dose dependency in that the more cannabis consumed, the greater the chance of developing schizophrenia. The public health significance of these data is considerable, and these data have fueled fierce debate (especially in England and Canada) regarding the legalization of marijuana. However, most people who abuse cannabis do not develop schizophrenia, and even if cannabis “causes” schizophrenia, it is probably only in a small minority of patients (O’Dely et al. 2005). In attempting to tease out this vulnerability, Caspi et al. (2005) conducted a genetic analysis of blood samples from participants in a large epidemiological study of schizophrenia in New Zealand. The authors reported that adolescents who abused cannabis and who had the most inefficient allele of the catechol-O-methyltransferase gene had the earliest onset of schizophrenia. This study is important not just because of this finding, but also because it serves as a yardstick for the application of neurobiological research probes to the study of dual diagnosis. Kishimoto et al. (2008) described an association between the dysbindin gene and methamphetamine-related psychosis. This report is of interest because of the already substantial genetic evidence for the dysbindin gene in schizophrenia, and this study suggests that this vulnerability might extend to drug-related psychosis. Yucel et al. (2008) reported on magnetic resonance imaging in people with no prior psychiatric history who were chronic abusers of cannabis. They found bilateral loss of hippocampal and amygdalar tissue. Interestingly, those who were heavy abusers showed a relationship between hippocampal tissue loss and mild paranoia. In an earlier study, Scheller-Gilkey et al. (1999) examined differences in magnetic resonance imaging scans for 176 patients with schizophrenia. The investigators noted that the rate of gross brain abnormalities among both alcohol and drug abusers was less than half the rate found among patients with no history of alcohol or substance abuse, although this finding did not reach the 0.05 level of statistical significance (Scheller-Gilkey et al. 1999). There is now a growing appreciation that the shared vulnerability for substance abuse and schizophrenia may be due to dopamine sensitization (Chambers et al. 2007; O’Dely et al. 2005); in this model, patients may abuse drugs because of chronic dysregulation of dopamine, particularly in the amygdala. Although research on the impact of drug and alcohol use on the course of illness has produced variable results, the overwhelming

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weight of evidence points toward substance abuse and dependence having adverse short-term and long-term effects. Overall, persons with schizophrenia who abuse drugs and/or alcohol have more psychotic symptoms and psychotic relapses than do persons with schizophrenia without substance use disorders (Degenhardt et al. 2007; Harrison et al. 2008; Negrete et al. 1986). In one of the first short-term prospective studies of recent-onset schizophrenia patients, Linszen et al. (1994) found that significantly more and earlier psychotic relapses occurred in those who abused cannabis. This finding was replicated in a long-term follow-up case-control study of 39 cannabis-abusing schizophrenia patients without other major drug use matched for age, gender, and year of admission with 39 non–cannabis using schizophrenia controls (Caspari 1999). After a mean 68.7± 28.3 months of follow-up, the cannabis abusers had a significantly greater hospitalization rate, higher symptom ratings, and greater unemployment. A larger study of relapse rates was performed in Australia using a recently hospitalized sample of 99 patients, ages 18–65, with schizophrenia or related disorders who were followed prospectively for 4 years (Hunt et al. 2002). Of the 99 who entered into the study, 66 were still being followed after 4 years. Demographically, compared with nonusers, the substance users were more likely to be male, to be younger, and to have a forensic history, although no differences were found in age of schizophrenia onset or number of prior hospitalizations. The investigators found that the median time until rehospitalization was 10 months for medication-compliant patients who used substances and 37 months for medication-compliant nonusers. Among medication-noncompliant patients, the survival times to rehospitalization were 5 months for substance users and 10 months for nonusers. Although the medicationnoncompliant substance users composed 28.3% of the total study sample, they accounted for 57% of all psychiatric admissions recorded by study participants, with an average of 1.5 per year. Overall, the substance users had an average of 3.6 admissions over the 4 years compared with 1.1 for nonusers (P< 0.05) and were significantly more likely to be medication noncompliant (users 67% vs. nonusers 34%, P<0.05). In a first-episode study in London, in which patients with dual diagnosis were followed for 1 year, Harrison et al. (2008) found that overall the extent of substance abuse had fallen by half. Those who continued to abuse drugs or alcohol were more symptomatic. The abuse of cocaine and stimulants, due to their direct effects on dopamine, has obviously been linked to exacerbation of psychotic symptoms (Dixon et al. 1990), yet increased severity of positive symptoms is seen in users of all substances. Caspari (1999) found higher Brief

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Psychiatric Rating Scale ratings in a long-term case-control study of cannabis abusers, some of whom subsequently also abused alcohol but not cocaine or stimulants. Similarly, Buhler et al. (2002) noted a greater extent of positive symptoms during 5 years of follow-up in a group of 29 first-episode schizophrenia patients who were users of various substances compared with matched nonusing control subjects. In particular, hallucinations were present for 1.8 months per year for substance users compared with 0.6 months per year for nonusers (P<0.05). The study’s findings also indicated a trend toward fewer negative symptoms among users, which reached statistical significance at the 5-year endpoint (P<0.03).

Violence Substance use disorders in patients with schizophrenia have been associated with violent behavior toward others, suicide (Barry et al. 1996; Dassori et al. 1990; Drake et al. 1989; Fulwiler et al. 1997), and increased risk for contact with the legal system (Buckley et al. 2004; Hunt et al. 2002). The association of violence with substance use is not unique to schizophrenia or severe mental illness, and has been observed among patients with other mental disorders (Cuffel et al. 1994; Swartz et al. 1998); moreover, this association between substance use and increased risk for violent behavior among persons with severe mental illness has also been described in patient populations outside the United States. Rasanen et al. (1998) completed a prospective study in Finland on an 11,017-person unselected birth cohort followed to age 26, which showed that men with schizophrenia who abused alcohol were 25.2 times more likely to commit violent crimes than men without mental illness, whereas nonalcoholic men with mental illness were only 3.6 times more likely to commit violent crimes than males without any psychiatric diagnosis. Buckley et al. (2004) found that approximately 50% of patients with schizophrenia who committed violent acts were abusing alcohol or drugs at the time of the incident.

Housing Instability and Homelessness Persons with comorbid substance use disorders and schizophrenia are at increased risk for homelessness (Drake et al. 1991). In Caton et al.’s (1994) case-control study comparing 100 homeless men with severe mental illness with 100 men with schizophrenia who were not homeless, homeless subjects had significantly higher rates of drug abuse. Studies of innovative service models for persons who are homeless and mentally ill have found that persons with substance use comorbidity do

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not benefit as much from these programs as do those who do not use substances, in part due to the fact that substance-using patients with severe mental illness lead a more transient lifestyle. In one study of assertive community treatment for individuals who are homeless and mentally ill, homeless persons with substance use disorders had more moves during the treatment year than other patients with severe mental illness (Holohan et al. 1997). Providing residential support is a key aspect of management for this problem (Drake 2007).

Medical Consequences of the Most Commonly Abused Substances in Schizophrenia Alcohol In the general population, alcohol is the most widely used substance of abuse. Sequelae of ethanol use disorders represent the third leading cause of death in the United States, with an estimated 111,000 deaths per year directly attributable to alcohol ingestion. The most common causes of death in alcohol-related disorders are suicide, cancer, heart disease, and hepatic disease (Schuckit 1999). Chronic liver disease and cirrhosis together are rated the twelfth leading cause of death in the United States (Centers for Disease Control and Prevention 2008). The acute action of ethanol in the central nervous system (CNS) derives from two main mechanisms: ethanol 1) facilitates the activation of gamma aminobutyric acid type A (GABAA) receptors, the main inhibitory neurotransmitter system in the CNS, and 2) inhibits the N-methylD-aspartate (NMDA) subtype of glutamate receptors, the main excitatory neurotransmitter receptor system in the CNS. The net effects of GABA are thereby potentiated, leading to sedation, and inhibition of NMDA receptors via allosteric modulation appears to be responsible for the intoxicating effects (Schuckit 1999). Sudden cessation of ethanol use by a chronic, heavy drinker often results in an uncomplicated withdrawal syndrome characterized by mild confusion associated with diaphoresis, tremulousness, and increased heart rate, blood pressure, and temperature, all of which can be blocked by administration of GABAacting drugs such as benzodiazepines. In about 5%–10% of patients with alcohol dependence, this syndrome may progress to delirium tremens (DTs), characterized by significant autonomic instability, marked confusion, disorientation, agitation, tremulousness, and hallucinations (auditory, visual, and tactile). The mortality rate for untreated DTs is

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approximately 5%. Alcohol withdrawal seizures (“rum fits”) may also develop independently of DTs, typically within the first 24–48 hours after cessation of alcohol use (Schuckit 1998). Alcohol consumption plays a role in acute or chronic medical illness through a variety of mechanisms, some or all of which may be operative in a specific individual (Schuckit 1998). Repeated exposure may lead to alcoholic hepatitis and eventually cirrhosis, with secondary cognitive impairment via hepatic encephalopathy in advanced cirrhosis due to the accumulation of nitrogenous compounds that are inadequately metabolized by the compromised liver. The cirrhotic changes of the liver are also manifested in impaired synthetic function (e.g., decreased production of clotting factors) and reduced metabolism of exogenous toxins such as medications. In the CNS, prolonged alcohol abuse leads to cerebellar degeneration, presenting as unsteady gait and mild nystagmus, in about 1% of patients with chronic alcoholism. These symptoms are irreversible and often accompanied by global cognitive decline from direct or indirect effects of chronic alcohol consumption (e.g., head injury, nutritional deficiency, direct neurotoxicity). Finally, peripheral neuropathy is seen in approximately 5%–15% of alcoholics due to nutritional deficiency and direct toxic effects of alcohol on neuronal axons (Schuckit 1998). Alcohol abuse increases blood pressure and serum triglycerides, and may lead to cardiomyopathy and arrhythmias via toxic effects on cardiac muscle (Schuckit 1998). During the acute intoxication period, tests for blood alcohol level, serum electrolytes, glucose, aspartate transaminase, alanine transaminase, gamma-glutamyltransferase, hematocrit, and amylase can be useful. For the chronic alcoholic, additional laboratory values that should be monitored include albumin, red blood cell indices, white blood cell count, platelet count, prothrombin time, hepatitis B and C screening, vitamin B12, and folate.

Cocaine and Amphetamines Cocaine is derived from the coca plant, native to South America, and is typically insufflated nasally (snorted), smoked (in the form of freebase or crack), or injected intravenously. Amphetamines, which are analogs of naturally occurring ephedrine, have been abused in various forms since their original synthesis in 1887. Currently, d-methamphetamine (“crystal meth” or “meth”) is the most popular form of amphetamine abused, and, in some areas of the country, such as the West Coast, abuse of methamphetamine is more prevalent than cocaine. Cocaine acts as a competitive blocker of dopamine reuptake in the synaptic cleft, which

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increases the concentration in the cleft, with resultant activation of dopamine type 1 and 2 receptors. In addition, cocaine increases norepinephrine and serotonin neurotransmission via reuptake inhibition, but these monoamines do not play the dominant role in its CNS effects (Jaffe 1999b). By contrast, amphetamine increases the availability of all synaptic monoamines by stimulating the release of catecholamines, particularly dopamine, from the presynaptic terminals. This effect is especially potent for dopaminergic neurons projecting from the ventral tegmental area to the cerebral cortex and limbic areas, known as the “reward pathway.” Patients with schizophrenia who abuse stimulants experience significant increases in the extent of positive symptoms of their psychosis. In comparison to patients with schizophrenia, cocaine-abusing patients without underlying psychotic disorders tend to seek treatment more often for depression and anxiety than for psychosis (Serper et al. 1999). Withdrawal following heavy stimulant use may be associated with significant lethargy and depression and an increased risk for suicide (Gawin and Kleber 1986). Cocaine and amphetamines have similar health effects based on their similar pharmacological activities that result in increased synaptic dopamine and other monoamines. The resultant sympathomimetic and vasoconstrictive properties of these agents are responsible for many of the acute (e.g., myocardial infarction, cardiac arrhythmias, cerebrovascular accidents, seizures) and chronic (e.g., hypertension) effects of ingestion (Jaffe 1999a). The nasal route of administration can lead to general sinus congestion and septal perforation due to chronic ischemia. Not only does the intravenous route of administration increase the transmission risk of HIV and hepatitis B and C viruses, but intravenous and subcutaneous (“skin popping”) use may result in significant cellulitis, bone and joint infections, endocarditis, and renal failure (usually as a result of adulterants to the drug). Smoking cocaine can exacerbate preexisting asthma or chronic obstructive pulmonary disease, and can produce specific, fibrotic lung changes known as “crack lung” (Tashkin 2001). Chronic use of stimulants often results in significant weight loss due to the anorexic effects of these agents.

Cannabis Cannabis plants and derived products (e.g., hashish) contain many substances that are believed to have psychoactive properties, although the most important of these is delta-9-tetrahydrocannabinol (THC). The endogenous cannabis receptor is a member of the G protein–linked family

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of anandamide receptors, found in the highest concentration in the basal ganglia, hippocampus, and cerebellum. In animal studies, activation of the receptor has an effect on monoamine oxidase and GABA (Chaperon and Thiebot 1999). The peak intoxication from smoking cannabis occurs after 10–30 minutes. THC and its metabolites accumulate in fat cells and have a half-life of approximately 50 hours (Franklin and Frances 1999). In an intoxicated state, behavioral changes include a heightened sensitivity to external stimuli, derealization, impaired motor skills, increased reaction time, and euphoria. Panic attacks can occur in inexperienced users. The drug is usually smoked, but users may ingest orally (e.g., hashish brownies). Psychosis can also occur during the intoxicated period, evidenced by transient paranoid ideation and, rarely, frank hallucinations. Subjective reported effects of acute cannabis intoxication in individuals with schizophrenia include a decrease in anxiety and depression and an increase in suspiciousness (Dixon et al. 1990). In addition, chronic heavy cannabis use can result in an amotivational syndrome that is described as passivity, decreased drive, diminished goal-directed activity, decreased memory, fatigue, problem-solving deficits, and apathy that can last for weeks following abstinence (Degenhardt et al. 2007). This has been described by various authors in uncontrolled studies, although controversy still exists regarding the exact nature of the syndrome (Franklin and Frances 1999). The deleterious health effects of cannabis are related to route of administration and direct effects on body systems. Cannabis cigarettes (“joints” or “blunts”) have more tar and respiratory irritants than tobacco and are more carcinogenic to laboratory animals. Long-term use has been found to lead to large airway obstruction. Smoking cannabis also has direct inhibitory effects on pulmonary antibacterial mechanisms such as destruction of alveolar macrophages, neutrophils, and lymphocytes. In addition, cannabis can cause variations in heart rate and blood pressure, which can lead to an increase in oxygen consumption and increased risk of myocardial infarction in individuals with coronary artery disease (Woody and MacFadden 1996).

Screening for Substance Use Clearly, case finding remains a priority if patients are to be offered any form of treatment aimed at reduction in substance use. Simply put, clinicians must take the initiative to identify patients who have substance use comorbidity. The first step requires screening and assessment. Most

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patients will not spontaneously volunteer that they are using substances. Thus, clinicians must actively seek out this information, with best results achieved using nonjudgmental forms of inquiry such as “How often have you used.. .” instead of “Do you use . ..” Given the prevalence of substance use, a high index of suspicion is essential. Clinicians should routinely ask all patients about use of alcohol or other drugs and should continue to inquire on a periodic basis, especially with newer patients who may be reluctant to discuss substance abuse with a new clinician. Because patients sometimes deny their drug use, a multimodal strategy is optimal, including urine toxicology screens, interviews with collateral sources, records from recent hospitalizations, and consultation with other care providers or family if permitted by the patient. The extent to which each approach adds to the confirmation of substance abuse has been studied. In a French comparative study of selfreport versus confirmatory, biological measures of substance abuse among over 400 inpatients, the authors found that patients underreported their abuse of illicit drugs in 52% of cases (De Beaurepaire et al. 2007). Patients underreported abuse of alcohol in 56% of cases. In a study in a U.S. community mental health center using the timeline follow-back method (an intensive, research-based retrospective reconstruction of abuse patterns), poor correlation was found between subject self-report and collateral information (Stasiewicz et al. 2008). Once a patient acknowledges using substances, a first step in treatment is to conduct a specialized assessment. In addition to questioning the amount and frequency of substance use, the clinician should get an understanding of each patient’s personal economy of using substances. What benefits and costs does the patient perceive to result from using substances? What are the patient’s motivations and expectations? A detailed understanding of patients’ perspectives on these questions is critical to engaging them in treatment and helping them to negotiate the phases of treatment to recovery.

Treatment of Patients With Dual Diagnoses The President’s New Freedom Commission on Mental Health (2003) noted that the failure to integrate substance abuse services and psychiatric/mental health services leaves people with dual diagnoses in “no man’s land.” These patients present complex addiction, medical, and mental health challenges that are beyond the scope of isolated, independent services, thus posing administrative, policy, and service delivery

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issues that systems of care have been grappling with. Additionally, advocacy and self-help groups have realized that the needs of patients with dual diagnoses are complex and best served with specialized supports such as Double Trouble in Recovery peer support (rather than Alcoholics Anonymous or Narcotics Anonymous groups). Treatment of substance use by people with schizophrenia requires an integrated approach, given the extent to which these problems interact and are interconnected (Drake 2007; Hellerstein et al. 2001). Although the deleterious effects of comorbid substance use on relapse rates are clear, the literature on interventions offers little guidance due to the paucity of controlled studies. Bennett et al. (2001) noted that only seven studies available in the literature through 1998 employed experimental designs, five of which examined “inpatient care or intensive outpatient case management for serious mentally ill clients (primarily for homeless populations), and are not directly applicable to the treatment of the broader population of people with schizophrenia living in the community” (p. 164). Of the remaining two studies, both involving outpatient treatment, one was a controlled study that found decreased substance abuse and psychiatric severity among patients who remained in treatment over several months, and the other was a semicontrolled study that found that both behavioral skills training and intensive case management were more effective than a 12-step program on several outcome measures, but with minimal effects on substance use. “Interestingly, the behavioral treatment was the most effective even though it was not designed specifically to address substance abuse problems and sessions were only held once per week” (p. 164). More recent controlled studies of integrated dual-diagnosis treatment have demonstrated the efficacy of this approach (Drake 2007). McHugo et al. (1999) showed that programs with high fidelity to dualdiagnosis treatment principles had markedly greater rates of sobriety than other treatment strategies. After 36 months, patients in high-fidelity programs had a 55% rate of stable remission, whereas only about 15% of patients in low-fidelity programs were in stable remission. In Manchester, United Kingdom, Barrowclough et al. (2001) conducted a controlled 12-month study comparing outcomes in 18 patients with schizophrenia and substance use disorders employing an integrated approach of motivational interviewing, family interventions (including a family support worker), and cognitive-behavioral therapy, with outcomes in 12 patients receiving care as usual. The integrated care group had a high retention rate (94%) and significant improvements compared with the usual care group on the Global Assessment of Functioning scale, PANSS positive symptom scores, and relapse rates. The

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benefits of a combined, integrated approach, particularly with respect to retention, are also seen in the results of a randomized controlled study by the Combined Psychiatric and Addictive Disorders Program (COPAD) at Beth Israel Medical Center in New York. The components of the COPAD treatment approach include supportive group substance abuse counseling, a multifaceted educational program (mental illness, psychiatric medications, alcohol and drug abuse, HIV), ongoing assessment of substance use via weekly urine toxicology, encouragement to attend self-help groups, monthly psychiatric medication visits, regular communication with other clinicians involved in the patient’s care, and as-needed communication with family members (Hellerstein et al. 2001). After 8 months, 11 of 23 patients in the COPAD cohort remained in treatment versus only 6 of 24 usual-care patients. Bennett et al. (2001) delineated what they perceived to be the necessary qualities of a dual-diagnosis program geared toward patients with schizophrenia in their description of the Behavioral Treatment for Substance Abuse in Schizophrenia (BTSAS) model. The special requirements of an effective substance abuse treatment program for the schizophrenia population derive from the findings of low motivation for decreasing substance use (41%–60% depending on the substance[s] abused) in schizophrenia patients, and the cognitive and social skills deficits present with schizophrenia. In creating the BTSAS program, the investigators relied on social skills training, “a behavioral approach for rehabilitation of schizophrenia patients that has been successfully employed for the past 25 years...that employs instruction, modeling, roleplaying, and social reinforcement” (p. 165). The components of BTSAS include monthly motivational interviews to discuss treatment goals; urinalysis with rewards for abstinence; social skills training, which teaches patients how to refuse offers of drugs; education on the effects of drug use in schizophrenia; and problemsolving and relapse prevention training to help patients cope with urges and high-risk situations. Most skills groups meet twice per week, a similar frequency to the group counseling in COPAD. Recognizing that schizophrenia patients have difficulty in changing behavior and that many are abusing multiple substances, the BTSAS model does not mandate need to be abstinent or commitment to total abstinence to participate. Any decrement in use is seen “as a positive step that will reduce patients’ overall level of harm” (p. 165) and bring the patient closer to an eventual goal. Drake et al. (2001, 2007) described several other critical components for integrated programs, including staged interventions for those at different stages of the recovery process, assertive outreach to engage

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clients (especially the homeless), the need to maintain a long-term perspective on the chronic and relapsing problems of substance use, and cultural sensitivity. They also noted the barriers that exist in implementing such integrated programs, including administrative issues (policy, programmatic barriers), clinician barriers due to lack of dualdiagnosis training, and consumer barriers due to denial or low motivation. Although the preceding models have not focused on intensive case management, the problems with medication noncompliance, housing, and psychosocial issues associated with substance use often warrant a case management approach, especially for those who are frequent utilizers of inpatient services. The federal government has also articulated what the best practices are for treating recurring disorders (Substance Abuse and Mental Health Services Administration 2008). For all schizophrenia patients, including those with dual diagnoses, antipsychotic medication is a fundamental aspect of treatment. Although medication-compliant substance users have psychotic relapses at higher rates than nonusers, the greatest risk for relapse is with medication-noncompliant substance users (Hunt et al. 2002). In general, there are no absolute contraindications to the prescription of antipsychotics for patients with schizophrenia currently using substances, apart from those who are medically compromised (e.g., hepatic disease, HIV), in whom dosage adjustment may be necessary. However, clinicians must use reasonable caution in the use of the more sedating agents in patients abusing alcohol or other CNS depressants such as opiates. That antipsychotic medication will reduce the likelihood of psychotic relapse, even in the presence of ongoing use, is substantiated by data from an Australian 4-year prospective study (Hunt et al. 2002), yet findings from some recent studies indicate that the use of atypical antipsychotics might be associated with reductions in substance use. The data are most compelling for clozapine (Green et al. 2008). One 3-year prospective study of 151 patients with dual diagnoses found that 79.0% of patients taking clozapine (n= 36) achieved full remission from alcohol use for 6 months or longer, compared with 33.7% of clozapine nonrecipients (Drake et al. 2000). Some relatively less convincing support has been published for the use of other antipsychotics in patients with schizophrenia and drug abuse diagnoses. Several studies have shown that aripiprazole might reduce abuse in this group (Green et al. 2008; Littrell et al. 2001; Smelson et al. 2002). Some studies also support the use of risperidone, olanzapine, and quetiapine (Green et al. 2008). Also, an ongoing study (P. Buckley, principal investigator) is being done of risperidone microspheres in this patient group. No information is available yet on pali-

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peridone in this group, although the pharmacokinetic profile of this drug should be more favorable for patients with dual diagnoses and alcohol-related liver damage. There is no information directly on ziprasidone in this group, apart from what can be gleaned from the CATIE study (Swartz et al. 2008). This examination of CATIE data from phase showed that the superiority of olanzapine over ziprasidone in prolonging time to discontinuation of treatment was still present but was attenuated in the subgroup of substance users compared with the nonabusing sample. Curiously, some case reports describe abuse of quetiapine (Paparrigopoulos et al. 2008) and olanzapine (Reeves 2007). In any regard, the evidence (albeit not compelling) is strongest for clozapine, although of course clozapine is not indicated for substance abuse and is only indicated for treatment-refractory or antipsychotic-intolerant patients. Although patients with dual diagnoses may be more sensitive to the extrapyramidal side effects and the side-effect profile of first-generation antipsychotics (Green et al. 2008; Voruganti et al. 1997), their higher rate of medical comorbidity should lead to careful consideration about the use of second-generation antipsychotic medications, which have a greater risk of diabetes mellitus and metabolic syndrome (Green et al. 2008; see also Chapter 3, “Medical Outcomes From the CATIE Schizophrenia Study,” in this text). The study of medications in patients with dual diagnoses is advancing more rapidly now in an era of more effective, pragmatic treatment trials. The treatment options for nicotine dependence in schizophrenia are reviewed by Montoya and Vocci (2007), as well as in Chapter 9, “Nicotine and Tobacco Use in Patients With Schizophrenia,” in this volume.

Conclusion Schizophrenia appears to carry with it the propensity for substance abuse, an independent but parallel process that often precedes by many years the onset of psychotic symptoms (Buckley 2006). The most commonly abused substances by patients with schizophrenia are alcohol, cocaine, and cannabis, with the choice of substance based on affordability and availability, and not on inherent aspects of psychopathology. Because the medical sequelae of abuse are numerous, periodic monitoring of urine toxicology and appropriate laboratory values should be considered as part of the routine care for schizophrenia patients with established or suspected substance use disorders. Given the likelihood that any schizophrenia patient has a past or ongoing substance use problem, a high index of suspicion must be maintained even with patients who deny or minimize the extent of their substance abuse. The

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greatest chance for optimizing outcomes and reducing the morbidity of substance abuse comes from identification of patients and enrollment into an integrated dual-diagnosis treatment modality designed specifically for substance-abusing or substance-dependent persons with schizophrenia (Drake et al. 2007). Routine screening for and increased recognition of substance use disorders in those with schizophrenia must be considered a standard part of psychiatric and medical care for this population (Substance Abuse and Mental Health Services Administration 2008).

Key Clinical Points ◗

The odds of having any substance use disorder are 4.6 times greater for persons with schizophrenia than for the rest of the population.

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Substance use is an inherent aspect of the neurobiology of schizophrenia, and increased rates of substance abuse can be seen in prodromal patients.

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Little evidence is available to suggest that substances are used specifically to ameliorate certain symptom states.

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The impact of substance use on poor psychiatric outcomes is mediated primarily by medication nonadherence.

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Screening for substance use disorders includes open-ended nonjudgmental inquiry, routine biological fluid testing, and screening for associated medical disorders (e.g., hepatitis C, HIV).

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Effective programs for patients with schizophrenia who use substances must account for the lower levels of motivation and the cognitive deficits seen in this population, and must strongly emphasize role-playing, social reinforcement, and problem solving as core aspects of relapse prevention, typically in ongoing skill-building group sessions.

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CHAPTER 12 Sexual Dysfunction and Schizophrenia Heidi J. Wehring, Pharm.D., B.C.P.P. Deanna L. Kelly, Pharm.D., B.C.P.P.

The sexuality of people with schizophrenia has received relatively little attention in the past. Evidence suggests that patients with schizophrenia identify sexual function and medication-related sexual side effects as important issues, yet much remains unknown regarding sexual dysfunction in this population. Multiple factors have contributed to this lack of knowledge, including lack of basic information on what constitutes “normal” sexual functioning of patients with schizophrenia. Earlier studies and theories suggested that sexuality is best not discussed with patients with schizophrenia, that identifying and treating sexual issues and side effects might exacerbate illness or lengthen recovery, and that sexual activity could even contribute to the development of schizophrenia (Pinderhughes et al. 1972). This perception has changed dramatically in recent years, and modern data indicate that the sexual activity, desire, fantasies, and expectations of patients with schizophrenia, although more autoerotic in nature, are not likely to be much different from those of the general population (Kelly et al. 2006). Although addressing clinical symptoms in patients with schizophrenia generally takes precedence over discussions of sexual function, clinicians often underestimate the prevalence of sexual dysfunction and the significance that sexual side effects may have on psychotropic adherence and outcomes. In one prevalence study, sexual dysfunction occurred in more 303

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than 50% of subjects with schizophrenia, yet the treating nurses and physicians reported significantly lower rates of sexual dysfunction in these same individuals (Dossenbach et al. 2005). In responding to a survey, patients with schizophrenia rated the area of “sexual expression” as the third most significant unmet treatment need (Grinshpoon and Ponizovsky 2008). One contributing element to the underrecognition of sexual dysfunction and its importance for patients with schizophrenia could be that this patient population may be unwilling or embarrassed to broach the topic of sexual concerns and not comfortable in discussing their sexuality. Moreover, because clinicians do not routinely focus on sexual symptoms or issues, patients with schizophrenia may think that clinicians do not take these concerns seriously or believe that their concerns are important. Given the high prevalence of sexual dysfunction in patients with schizophrenia and the fact that its occurrence may be associated with lower quality of life and poorer psychiatric outcomes, this chapter is intended to serve as a guide for clinicians on the extent of and contributors to these problems and the means to address unmet needs in this area. Improving the focus on this domain of treatment could lead to more integrated and comprehensive psychiatric and medical care and a better step toward the path to recovery.

Prevalence Sexual dysfunction is common in the general population, with estimates of 43% of women and 31% of men in the United States reporting some type of sexual dysfunction (Laumann et al. 1999). The prevalence of sexual dysfunction in patients with schizophrenia has been more difficult to ascertain but is considered to be higher than in the general population, with reported rates averaging 50%–75% (Kelly and Conley 2004). Several reasons may explain the wide range of reported prevalence rates in patients with schizophrenia, including the nature of the patient population studied (illness severity and acuity, location of study, men vs. women, partner vs. no partner), medication status of patients (treated vs. untreated, type of antipsychotic medication and concomitant medications used), method of data collection (spontaneous report vs. standardized assessment tool), source of data (clinician vs. patient), time frame of study, and definition of sexual dysfunction measured. Some studies have suggested that higher psychopathology rating scores have been associated with greater impairment in sexual function (Fan et al. 2007; Kockott and Pfeiffer 1996); however, these findings have not been widely replicated, and more work is needed to ascertain this relationship. Antipsychotic treatment is known to cause sexual impairment, yet some

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authors (Aizenberg et al. 1995; Bitter et al. 2005) have reported sexual dysfunction in treatment-naive patients with schizophrenia, suggesting that a treatment-independent factor contributes to this clinical problem. Evidence indicates that males and females experience different forms of sexual dysfunction and at different rates, but the bulk of the schizophrenia literature has focused on males, possibly due to reporting bias. Although a review by Howes et al. (2007) found that the odds ratios of patients with schizophrenia having sexual dysfunction, compared with the general population, were 15.2 and 3.7 for women and men, respectively, one recent study of 827 patients on antipsychotic medications found that 58% of women but only 43% of men reported sexual dysfunction (Üçok et al. 2007). Despite higher sexual dysfunction rates, females are less likely to spontaneously complain about sexual dysfunction in treatment settings, leading to an underestimation of prevalence. A survey study in a diagnostically heterogeneous group of psychiatric outpatients found that among those with sexual side effects, 80% of women versus 26.7% of men “never or infrequently” discussed their sexual lives with clinicians (Rosenberg et al. 2003). Another methodological issue in interpreting sexual dysfunction prevalence rates relates to the fact that many studies include only those with sexual partners, thereby excluding a significant portion of the schizophrenia population, because patients with schizophrenia are less likely to be married or in a relationship than those in the general population (Aizenberg et al. 2001). Medications, other mental and physical comorbidities, and substance and tobacco use may also affect sexual function. The prevalence rates of environmental exposures to substances and tobacco vary considerably between schizophrenia patients and the general population.

Types of Sexual Dysfunction Sexual dysfunction in patients with schizophrenia may occur in any of the areas of the sexual response cycle. Generally speaking, this cycle includes the following domains: • Interest (libido) • Arousal (vaginal lubrication in women, erectile function in men) • Orgasm The breadth of what is covered by the term sexual dysfunction and what has been measured in studies varies greatly, sometimes causing difficulty in providing consensus regarding types of sexual dysfunction that may occur in the schizophrenia population.

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Men Men with schizophrenia who have sexual dysfunction typically complain of decreased libido and erectile, ejaculatory, and orgasmic dysfunction. The reported erectile and ejaculatory disturbances are generally related to difficulty achieving and maintaining erections, delayed or inhibited ejaculation, and diminished orgasm quality. The prevalence of these sexual impairments ranges widely; however, most reports indicate that problems with desire and arousal as well as problems with ejaculatory disturbances are present in up to 60% of men with schizophrenia (Bobes et al. 2003; Olfson et al. 2005). Spontaneous and premature ejaculation also occurs more commonly in men with schizophrenia than in the general population (Aizenberg et al. 1995). Galactorrhea and gynecomastia are uncommon in men but may occur in males treated with antipsychotics. Gynecomastia has been reported in 1%–2% of men taking antipsychotic medications, with some estimates up to 11%, whereas galactorrhea is thought to occur more rarely (Byerly et al. 2007). Priapism is an infrequently reported but serious side effect associated with antipsychotic medications. Priapism, a prolonged, painful erection not usually associated with sexual stimuli, requires emergency urological evaluation to minimize potentially serious long-term consequences such as erectile dysfunction (Compton and Miller 2001).

Women Women may experience sexual dysfunction across any area of sexual response, including libido, arousal, and orgasm. Women can also experience dyspareunia associated with vaginal atrophy and dryness, and are at risk of suffering menstrual disturbances and galactorrhea, particularly if they are taking prolactin-elevating antipsychotics. Many of the reports in the literature cite high rates (>60%) of loss of libido and arousal, including problems with vaginal lubrication and pleasure (Fan et al. 2007; Teusch et al. 1995; Üçok et al. 2007). Additionally, women with schizophrenia report low rates of orgasm, with papers suggesting that over half of women with schizophrenia have never experienced an orgasm (Friedman and Harrison 1984). The reported prevalence of galactorrhea in women treated with antipsychotics ranges from 10% to 90% but differs according to the type of antipsychotic (Byerly et al. 2007). Although not directly related to sexual function, menstrual abnormalities are frequently co-occurring antipsychotic adverse effects that often go unrecognized in clinical trials

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because this information is not volunteered and clinical investigators may not specifically evaluate this side effect. Numerous cross-sectional studies of menstrual irregularities in antipsychotic-treated women with schizophrenia indicate that the propensity to elevate prolactin remains a common mechanism for this complaint. In these studies, the occurrence of menstrual abnormalities ranges from 25% to 100%, with the average prevalence around 50% (Kelly and Conley 2004).

Impact of Sexual Dysfunction on Patient Outcomes Long-term quality-of-life outcomes in schizophrenia are often less than ideal, with reduced life expectancy, high suicide rates, and low rates of marriage and employment. The mental health field is increasingly aware of the need to strive for recovery and to incorporate both medical and psychological care along with psychiatric symptom control into treatment planning. Sexuality, which is a vital component of the self and provides a sense of personal satisfaction, remains a significant unmet need hindering full recovery for patients with schizophrenia. Importantly, sexual dysfunction has negative effects on critical aspects of care necessary to achieving sustained psychiatric outcomes, namely medication adherence and self-rated quality of life and well-being.

Adherence Adherence to antipsychotic treatment is the cornerstone of schizophrenia management and relapse prevention, yet nonadherence rates typically range from 40% to 50% (Lacro et al. 2002). A myriad of factors contribute to nonadherence, including the following: • Lack of illness insight • Poor relationship to health care provider • Belief that treatment may not improve symptoms or prevent recurrence of symptoms • Negative attitude toward medications • Medication side effects Sexual dysfunction is distressing to patients, particularly when perceived as a side effect of psychotropic medications, and the limited research on this topic indicates that impairment in sexual function can negatively affect adherence to antipsychotic medications. In a survey of

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outpatients with severe mental illness, Rosenberg et al. (2003) found that 43% of those who experienced sexual dysfunction said they had considered stopping medications because of sexual side effects, and 27.5% claimed that they had actually stopped medications one or more times due to sexual side effects. As discussed in the later section on etiology, sexual dysfunction has many possibly etiologies, yet several studies report that patients often attribute their sexual dysfunction to antipsychotic treatment (Lambert et al. 2004; Olfson et al. 2005).

Quality of Life Quality of life is a broad term that includes subjective well-being and both mental and physical function, and has become an outcome of great interest in the treatment of schizophrenia. Those with schizophrenia experiencing sexual dysfunction may report any of the following (Olfson et al. 2005): • • • •

Poorer quality of life Lower levels of enjoyment in life Low satisfaction with the quality of romantic relationships Fewer romantic partners

Although limited formal data have been reported in this area, the few existing studies document that sexual dysfunction is associated with lower quality of life among patients with schizophrenia. These patients describe sexual dysfunction as a troublesome side effect associated with a worse subjective quality of life, with some men complaining that medication-related impotence is more bothersome than their psychotic symptoms (Finn et al. 1990). Not surprisingly, one study found that men with schizophrenia who reported sexual dysfunction also reported a lower global quality of life compared with male patients without sexual dysfunction (Olfson et al. 2005). Moreover, in a large study assessing satisfaction and quality of life in patients with schizophrenia, lack of sexual activity was one of the top four reasons for low ratings of life satisfaction (S. Chan and Yu 2004).

Etiology Multiple factors contribute to sexual dysfunction in patients with schizophrenia, and the etiologies for any one patient can be complex. The symptoms of schizophrenia, including psychosocial difficulties, a lack of personal relationships, negative symptoms, anhedonia, and impulsivity, are potential contributing factors. The following physical

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effects of antipsychotic treatment may also contribute to sexual dysfunction (Kelly and Conley 2004): • • • •

Obesity and weight gain Sedation Tardive dyskinesia Extrapyramidal side effects

Over 100 medications or classes of medications have been associated with sexual dysfunction, although the quality of evidence is not uniform (Thomas 2003) (see Table 12–1). A lengthier discussion of medication effects follows in the next section, but it is worthwhile noting here that other physical and mental illnesses can affect sexual functioning, including the following: • • • • • •

Diabetes Cardiovascular disease Hypertension Alcoholism Peripheral neuropathy Depression

Human sexual physiology is complex, involving endocrine, central nervous, peripheral nervous, and vascular systems. The endocrine system is thought to be responsible for libido, so reductions in sex hormones such as testosterone may impair erectile function and libido in males. In females, low testosterone levels have been theorized to be associated with low sexual desire and sexual dysfunction; however, this has not been supported by direct evidence, and some conflicting reports failed to find low androgen levels to be predictive of low sexual function in women (Davis et al. 2005). The limbic system mediates arousal mechanisms, and neurohormones in the central nervous system (CNS) also mediate sexual function, with the monoamine neurotransmitter serotonin acting primarily in an inhibitory role and dopamine in a stimulatory role. Because dopamine is related to motivation and reward in the CNS, dopaminergic receptor antagonism may contribute to decreased libido. Additionally, dopamine antagonism may lead to prolactin elevation and associated consequences of sexual dysfunction, as described later in this section. The peripheral nervous system participates in sexual function through sensory input mediated by adrenergic (sympathetic) and cholinergic (parasympathetic) stimulation (Thomas 2003), with ejaculation

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TABLE 12–1. Medications associated with sexual dysfunction (not a comprehensive list) Medications (U.S. brand name), by class

Reported effect on sexual function

Anticonvulsants Medications inducing cytochrome P450 enzymes Carbamazepine (Tegretol) Phenytoin (Dilantin)

Increased metabolism of androgens, possibly affecting sexual function

Antidepressants Monoamine oxidase inhibitors Isocarboxazid (Marplan) Phenelzine (Nardil) Tranylcypromine (Parnate) Selective serotonin reuptake inhibitors Citalopram (Celexa) Escitalopram (Lexapro) Fluoxetine (Prozac) Fluvoxamine (Luvox) Paroxetine (Paxil) Sertraline (Zoloft) Other antidepressants Mirtazapine (Remeron)

Antihypertensives α-Adrenergic blockers Prazosin (Minipress) Terazosin (Hytrin) Mixed α-β-adrenergic blocker Labetalol (Normodyne, Trandate) β-Adrenergic antagonists Atenolol (Tenormin) Metoprolol (Lopressor) Propranolol (Inderal)

Differences in risk of sexual side effects may exist between medications in class (inhibited ejaculation, decreased libido) Differences in risk of sexual side effects may exist between medications within class (decreased libido, delayed orgasm/ejaculation, anorgasmia, decreased vaginal lubrication)

Decreased libido, delayed orgasm/ejaculation, anorgasmia, erectile dysfunction, decreased vaginal lubrication Ejaculatory disturbances (retrograde) Inhibited ejaculation

Erectile dysfunction, decreased libido

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TABLE 12–1. Medications associated with sexual dysfunction (not a comprehensive list) (continued) Medications (U.S. brand name), by class

Reported effect on sexual function

Centrally acting agents Clonidine (Catapres) Methyldopa (Aldomet) Reserpine (Reserpine) Diuretics Spironolactone (Aldactone) Thiazides (various)

Erectile dysfunction, decreased libido (methyldopa and reserpine)

Antihypertensives, other Guanethidine (sympathetic nerve blocker) (Ismelin) Cardiac medications Digoxin (Lanoxin) Gastrointestinal medication Cimetidine (Tagamet) Other Hormonal contraceptives (various)

Spironolactone: decreased libido, breast swelling, erectile dysfunction Thiazides: erectile dysfunction Erectile dysfunction, ejaculatory disturbances (retrograde)

Erectile dysfunction, gynecomastia Decreased libido, impotence, gynecomastia Decreased libido

Source. Adapted from American Association of Clinical Endocrinologists Male Sexual Dysfunction Task Force: “American Association of Clinical Endocrinologists Medical Guidelines for Clinical Practice for the Evaluation and Treatment of Male Sexual Dysfunction: A Couple’s Problem—2003 Update.” Endocrine Practice 9:77–95, 2003.

in particular mediated by α-adrenergic and β-adrenergic systems, as well as motor nerves. Potent α-adrenergic blockade has been associated with ejaculatory disturbances and priapism (Compton and Miller 2001; Wang et al. 2006). Cholinergic receptor antagonism may affect erectile function, and calcium channel blockade may also contribute to sexual dysfunction (Cutler 2003; Gitlin 1994; Haddad and Wieck 2004). Serotonergic neurotransmission in the peripheral system has vasoconstriction/vasodilatory effects and plays a role in the normal sexual response cycle, and serotonin agonists (typically in the form of selective seroto-

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nin reuptake inhibitor [SSRI] antidepressants) are notorious inducers of sexual dysfunction. Finally, sedation and diminished arousal due to histamine receptor antagonism may also contribute to sexual dysfunction. Cigarette smoking status should be obtained during the inquiry into sexual complaints, because up to 80% of persons with schizophrenia smoke (Kelly et al. 2007), and smoking is associated with erectile dysfunction. Smoking is also a risk factor for coronary heart disease and peripheral vascular disease, with the result that smoking-induced inflammation and dyslipidemia become important contributors to vascular erectile dysfunction and must be considered in all males with erectile complaints, regardless of the type of antipsychotic treatment. Given the complex neurobiology of sexual function, antipsychotic medications can be associated with sexual dysfunction through any of the mechanisms described, including effects on the following systems: • • • • •

Dopaminergic Cholinergic Adrenergic Histaminic Serotonergic

As noted in the later section on medication effects, certain classes of antipsychotics are associated with specific risks for sexual dysfunction, but prolactin elevation is a common problem with many antipsychotics. Prolactin elevation from antipsychotic treatment primarily occurs by dopamine blockade at the pituitary level and is the cause of the majority of sexual dysfunction specifically attributable to antipsychotic treatment. A recent article indicated that prolactin elevation explained 40% of all sexual dysfunction present in patients with schizophrenia (Knegtering et al. 2008). Prolactin inhibits gonadotropin-releasing hormone and, by function of feedback loop between pituitary and hypothalamus, subsequently inhibits luteinizing hormone and follicle-stimulating hormone. Hyperprolactinemia may be associated with a decrease in testosterone levels, which is thought to lead to reduction in sexual activity (Barnes and Harvey 1993). Direct correlations between sexual dysfunction and prolactin levels have not been routinely found in all studies, but those individuals with higher prolactin levels generally have higher rates of sexual dysfunction (Byerly et al. 2007). The effects of hyperprolactinemia include both sexual and hormonal consequences. Hyperprolactinemia is associated with galactorrhea, gynecomastia, oligomenorrhea, amenorrhea, and libido changes in

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women; with galactorrhea, gynecomastia, changes in libido, and erectile and ejaculatory dysfunction in men; and possibly with effects on bone mineral density and risk of cancer (Haddad and Wieck 2004). Although not a sexual side effect, galactorrhea can be very distressing and has been reported in 10%–90% of women treated with prolactin-elevating antipsychotics (Byerly et al. 2007). As noted earlier, gynecomastia and galactorrhea occur only rarely in men exposed to antipsychotics.

Prolactin and Osteoporosis Accumulating evidence suggests that hyperprolactinemia may increase the loss of bone mineral density in patients with schizophrenia during long-term antipsychotic drug treatment, either through secondary hypogonadism or hyperprolactinemia itself. Previous studies have demonstrated that between 32% and 65% of patients treated with antipsychotic drugs suffer from bone mineral loss, leading to osteoporosis (Meaney et al. 2004). One study found that among women with schizophrenia treated with haloperidol, 18 of 21 (86%) had significant bone mineral density loss compared with 9 of 23 (39%) normal control subjects (Jung et al. 2006). Bone fractures in patients with schizophrenia taking antipsychotics also occur more frequently than in the nonpsychiatric population. Other evidence suggests that amenorrhea and prolactin-elevating antipsychotic drugs are associated with a higher risk for osteoporosis and fracture (Becker et al. 2003; Bilici et al. 2002; Csermely et al. 2007; Meaney and O’Keane 2007).

Prolactin and Cancer Risk Long-term treatment with antipsychotics in mice has led to the development of pituitary adenomas and adenocarcinomas. Pharmacovigilance studies in humans have found a significantly greater proportion of pituitary tumors reported with risperidone than with the other available antipsychotics (Doraiswamy et al. 2007), although the increased level of prolactin monitoring (and subsequent computed tomographic or magnetic resonance imaging) in risperidone-treated patients may account for a significant aspect of this discrepancy. Another prospective study found that pituitary volume significantly increases over 1 year in people treated with prolactin-elevating antipsychotics (MacMaster et al. 2007), although the true risk of pituitary tumor with prolactin-elevating medications remains unclear. Among the few studies that have addressed whether dopamine receptor antagonists increase risk of breast cancer, results have been conflicting (Wang et al. 2002). Some recent evidence suggests that endometrial cancer is related to a hormonal imbal-

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ance and that endometrial thickening and cancer may be related to prolactin elevations secondary to antipsychotic treatment (Yamazawa et al. 2003). One report estimated a fivefold increase in endometrial cancer risk with use of prolactin-raising antipsychotics in premenopausal women (Yamazawa et al. 2003). In summary, the etiology of sexual dysfunction in schizophrenia is complex, although elevated serum prolactin levels contribute to a majority, but not all, of the impairments noted in the schizophrenia population. Hormonal side effects are clearly related to prolactin elevation; however, other effects of hyperprolactinemia on osteoporosis and cancer risk remain somewhat speculative and warrant further study.

Medication Effects and Sexual Dysfunction As mentioned above, medications can be associated with sexual dysfunction through a variety of mechanisms, and Table 12–1 lists common drugs that have been associated with impairments in sexual functioning. In this chapter, we focus primarily on antipsychotic medications but also comment on sexual dysfunction associated with other commonly used treatments in this population.

First-Generation Antipsychotics First-generation antipsychotics (FGAs) have been associated with a variety of symptoms of sexual dysfunction. Diminished libido, orgasm changes and/or anorgasmia, erectile dysfunction, delayed or retrograde ejaculation, oligomenorrhea, amenorrhea, galactorrhea, and gynecomastia have all been reported in patients treated with FGAs. Overall estimates of sexual dysfunction in patients treated with FGAs range from 30% to 70% (Dossenbach et al. 2006). Smith et al. (2002) reported that males treated with FGAs were 6.3 times more likely to complain of sexual dysfunction and have 3.7 times greater rates of erectile dysfunction and 16.4 times greater rates of ejaculatory dysfunction than the general male population, whereas females treated with FGAs were 9.6 times more likely to complain of orgasmic dysfunction than the general female population. Haloperidol and other high-potency dopamine antagonists are associated with greater prolactin elevation and hormonal side effects compared with low-potency agents, with data suggesting a correlation between serum haloperidol concentrations and serum prolactin levels (Byerly et al. 2007; Shim et al. 2007). Studies have reported that threefourths of females and one-third of males experience hyperprolactin-

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emia when taking FGAs (Smith et al. 2002). The prevalence of sexual dysfunction among patients receiving haloperidol may reach 70% and includes reduced libido in up to 68% and erectile dysfunction in 40%–50% (Dossenbach et al. 2006; Olfson et al. 2005). The lowerpotency phenothiazines are associated with ejaculatory problems and retrograde ejaculation, the result of α-adrenergic blockade. Retrograde ejaculation may occur in up to 60% of males treated with thioridazine, and priapism is also reported with certain low-potency antipsychotics, most notably chlorpromazine and thioridazine.

Second-Generation Antipsychotics Compared with the FGAs, second-generation antipsychotics (SGAs) are associated with fewer overall sexual disturbances, with the exception of risperidone and paliperidone, which have a relatively high affinity for the dopamine D 2 receptor and which are associated with hyperprolactinemia to a greater degree than the more potent dopamine antagonist haloperidol. With the exception of these two agents, comparative studies have shown lower rates of sexual dysfunction with the SGA class. The following text details information regarding prolactin elevations and sexual dysfunction with use of the SGAs available in the United States. Risperidone. Risperidone, a serotonin-dopamine antagonist, is associated with a greater risk for hyperprolactinemia compared with most antipsychotics (Kelly and Conley 2006). Mean prolactin levels may reach 30–60 ng/mL at therapeutic dosages of risperidone (Knegtering et al. 2003); however, prolactin levels are typically higher in women and have been reported to be 60–150 ng/mL in women at routine risperidone dosages (Kelly and Conley 2006). In the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial, risperidone was associated with an exposure-adjusted prolactin increase of 13.8 ng/mL during treatment; however, the data were not broken down by gender, and the population was 74% male (Lieberman et al. 2005). Risperidone treatment has been reported to cause dysfunction in all areas of sexual response—libido, arousal (erectile dysfunction, ejaculatory difficulties, decreased vaginal lubrication), and orgasm—as well as to result in hormone-related effects such as menstrual irregularities, amenorrhea, galactorrhea, and gynecomastia (Dossenbach et al. 2006; Kelly and Conley 2004). In observational studies, sexual dysfunction during risperidone treatment occurs in 60%–70% of patients with

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schizophrenia (Dossenbach et al. 2006). Results from comparative studies also indicate that risperidone is associated with higher rates of sexual dysfunction compared with other antipsychotics (Kelly and Conley 2006). In the CATIE trial, 27% of subjects taking risperidone had decreased sex drive, arousal, or ability to reach orgasm; 4% experienced gynecomastia or galactorrhea; and 18% of the women reported menstrual irregularities. These rates may be underestimates due to the lack of specific rating instruments for assessing these side effects (Lieberman et al. 2005). Of 860 subjects treated with risperidone for 12 months in the Intercontinental Schizophrenia Outpatient Health Outcomes study, 60% experienced loss of libido and 46% had impotence and other types of sexual dysfunction (Dossenbach et al. 2006). Other reports on risperidone have noted rates of menstrual abnormalities as high as 50%–100% (Kelly and Conley 2006). Risperidone’s α-adrenergic antagonism is also thought to play a role in the occurrence of sexual side effects, and this may partially explain why prolactin elevations with risperidone are not always correlated with sexual dysfunction in males. Olanzapine. Olanzapine causes transient elevations in plasma prolactin levels due to its antagonist properties at the D 2 receptor, but the inhibitory potential (Ki) is approximately one-third that of risperidone. The mean prolactin level of patients during daily treatment with olanzapine at dosages of 10–30 mg is 17 ng/mL, which is higher than that of normal controls, drug-free patients, and clozapine-treated patients (Markianos et al. 2001). In most studies, olanzapine has been shown to cause less prolactin elevation than haloperidol and risperidone, and its impact on serum prolactin levels appears to be a dosage-related phenomenon (Crawford et al. 1997). With prolonged olanzapine exposure, prolactin levels generally return to normal in most patients (Kelly and Conley 2004); however, in a 28-week study one-third of olanzapinetreated patients continued to have measurable elevations in prolactin levels (Tran et al. 1997). In the CATIE schizophrenia trial, prolactin change during olanzapine treatment was –8.1 ng/mL (exposureadjusted mean) (Lieberman et al. 2005). Because olanzapine use in treatment-naive subjects is associated with modest increases, this decrease in serum prolactin represents the removal of prolactin-elevating effects of previous treatments. Dossenbach et al. (2006) reported in one comparative clinical trial that the odds of patients perceiving sexual problems or being unable to perform sexually was greater in risperidone and haloperidol groups than in the olanzapine group, and that females taking olanzapine (14%) or quetiapine (8%) experienced fewer menstrual irregularities than

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those taking risperidone (23%) or haloperidol (29%). Other researchers have also reported fewer sexual impairments in patients taking olanzapine than in patients taking FGAs or risperidone (Bobes et al. 2003; Knegtering et al. 2006). In the CATIE schizophrenia trial, decreased sexual drive, arousal, or ability to reach orgasm occurred in 27% of patients (Lieberman et al. 2005), and menstrual abnormalities occurred in 12% of women. Prescribing information derived from olanzapine clinical trials cites dysmenorrhea rates of 2%, which are equal to or less than placebo, and infrequent (<1%) complaints of abnormal ejaculation, amenorrhea, breast pain, decreased menstruation, female lactation, gynecomastia, impotence, increased menstruation, menorrhagia, and metrorrhagia (Zyprexa Prescribing Information 2008). However, as has been reported with other medications, these percentages are likely to be underestimates of the true sexual dysfunction incidence in a real-world population. Priapism associated with olanzapine use is rare but has been reported in the literature, as has one case report of olanzapine-associated clitoral priapism (Bucur and Mahmood 2004; Childers et al. 2003; Compton and Miller 2001; Jagadheesan et al. 2004; Songer and Barclay 2001). Quetiapine. Quetiapine is a serotonin-dopamine antagonist with a low affinity for the D 2 receptor and a quick rate of dissociation. Quetiapine has not been shown to have a propensity to increase prolactin levels, which suggests that the risk of hyperprolactinemia-related adverse effects is less than with other antipsychotic agents such as risperidone and paliperidone. Prolactin levels have been reported to decrease during quetiapine treatment, and did not differ from placebo in clinical trials (Arvanitis and Miller 1997). In the CATIE schizophrenia trial, exposure-adjusted mean prolactin changes decreased 10.6 ng/mL during quetiapine treatment, although this probably represents a removal of prior drug effect rather than any direct prolactin-lowering property of quetiapine. Despite the prolactin-sparing effects of quetiapine, sexual side effects have been reported, and published studies have noted sexual dysfunction occurring in 8%–50% of patients treated with quetiapine (Kelly and Conley 2006). In a study of 36 patients with schizophrenia receiving quetiapine for over 4 weeks, Atmaca et al. (2005) found that diminished libido occurred in about one-third of male and female patients. In a study of schizophrenia patients, Bobes et al. (2003) reported that sexual dysfunction occurred in 18% of quetiapine-exposed subjects compared with almost 40% of patients taking haloperidol. Byerly et al. (2006a), in a one-time rating of a large group of patients with schizophrenia or

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schizoaffective disorder, also found the severity of sexual dysfunction to be lower in the quetiapine group than in the risperidone or olanzapine group. In a randomized, open-label, 6-week trial, Knegtering et al. (2004) found that 4 of 25 (16%) quetiapine-treated patients and 12 of 24 (50%) risperidone-treated patients experienced sexual dysfunction. Byerly et al. (2004) performed an open-label switch to quetiapine and found that eight patients (seven switched from risperidone and one from haloperidol) who described significantly improved sexual function had decreased prolactin levels. Fewer menstrual irregularities also occur in females taking this medication compared with risperidone and FGAs, with the prevalence in the CATIE schizophrenia trial reported at 6% (Kelly and Conley 2006; Lieberman et al. 2005). Finally, a 12-week double-blind trial comparing quetiapine to risperidone found that quetiapine was associated with better improvement in sexual function compared with risperidone or fluphenazine (Kelly and Conley 2006), but that approximately one-half of subjects taking quetiapine were experiencing sexual dysfunction, indicating that prolactin-independent mechanisms may be at work in the etiology of sexual complaints. Prescribing information for quetiapine lists the following as adverse effects: infrequently reported adverse effects in clinical trials included (<1%) dysmenorrhea, menorrhagia, impotence, abnormal ejaculation, amenorrhea and leucorrhea, while gynecomastia was rarely (<0.1%) reported (Seroquel Prescribing Information 2008). Several case reports of quetiapine-associated priapism have been reported, including one reported in quetiapine overdose (Casiano et al. 2007; Davol and Rukstalis 2005; Harrison et al. 2006; Pais and Ayvazian 2001). Ziprasidone. Ziprasidone is a serotonin dopamine antagonist with a D2 affinity lower than that of risperidone and higher than that of olanzapine. It is associated with only minor prolactin-elevating effects, which are measurable but are generally transient and not clinically problematic. In a 52-week double-blind study, prolactin levels at endpoint were 19 ng/mL for ziprasidone, compared with 60 ng/mL for risperidone (Ananth et al. 1998). Scattered case reports of prolactin elevation have appeared in the literature, but in the CATIE schizophrenia trial, the exposure-adjusted mean prolactin decreases were –5.6 ng/mL during ziprasidone treatment (Lieberman et al. 2005). The effects of ziprasidone on sexual dysfunction have not been extensively reported in the published literature, but the CATIE study found decreased sex drive, arousal, and ability to reach orgasm in 19% of ziprasidone-treated subjects and menstrual irregularities in 14% of women. Prolonged erections and priapism have rarely been associated with ziprasidone use,

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but in clinical trials, impotence, abnormal ejaculation, amenorrhea, menorrhagia, female lactation, metrorrhagia, male sexual dysfunction, and anorgasmia were listed as infrequent (<1%) adverse effects, and gynecomastia was listed as a rare (<0.1%) adverse event (Geodon Prescribing Information 2007). Again, these reported rates in pivotal clinical trials likely underestimate the true prevalence of sexual dysfunction. Aripiprazole. Aripiprazole differs in mechanism from other SGAs in that it acts as a partial dopamine agonist at D2 receptors. The mechanism of action suggests a lack of prolactin elevation, which has been confirmed in the published literature. Aripiprazole exerts dopamine agonism in pituitary cells at the molecular level; thus, lactotroph cells are not inhibited by aripiprazole treatment. Serum prolactin levels have been found to decrease significantly from baseline during treatment trials with aripiprazole. In a 6-week, double-blind, randomized trial by Kane et al. (2007), mean prolactin levels decreased in the aripiprazole group from 33.4 ng/mL to 5.2 ng/mL, whereas prolactin levels in the perphenazine group remained unchanged (35.8 ng/mL to 35.5 ng/mL). In a 4-week study, prolactin levels decreased significantly in the aripiprazole group (–9.0 ng/mL), whereas the risperidone group experienced a mean increase of 55.4 ng/mL (H.Y. Chan et al. 2007). The prevalence of sexual dysfunction with aripiprazole has not been widely studied. In a recent review of antipsychotic trials published between 2002 and 2008, Baggaley (2008) reported aripiprazole to be associated with the lowest rate of sexual dysfunction. An open-label study found improvements in prolactin levels, hormonal side effects, and sexual dysfunction in patients who switched to aripiprazole or who had aripiprazole added to current regimens (Mir et al. 2008). In a randomized, double-blind trial, adding adjunctive aripiprazole to haloperidol significantly decreased prolactin levels and improved hormonal side effects in the majority of women (Shim et al. 2007), although this study did not measure sexual dysfunction. In premarketing trials, less than 1% of patients complained of irregular menstruation, amenorrhea, breast pain, or erectile dysfunction, and less than 0.1% of patients complained of gynecomastia and priapism (Abilify Prescribing Information 2008), although two cases of priapism have been reported in patients treated with aripiprazole (Mago et al. 2006; Negin and Murphy 2005). Paliperidone. Paliperidone is the active metabolite of risperidone (9-hydroxyrisperidone), with similar affinity for D 2 receptors, but is marketed as a unique drug entity. Data from three 6-week industry-

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sponsored trials showed that median prolactin elevations were 81 ng/ mL for women and 24 ng/mL for men in a pooled analysis of all dosages. Four percent of patients receiving extended-release paliperidone 15 mg/day reported potential prolactin-related adverse events, whereas 1%–2% of patients receiving placebo or extended-release paliperidone 3–12 mg/day spontaneously reported potential prolactinrelated events (Meltzer et al. 2008). No controlled trials specifically addressing sexual dysfunction in patients using paliperidone have been published to date, but paliperidone’s propensity to increase serum prolactin is nearly identical to that of risperidone, and most of the information regarding this compound has been reported in studies using the parent compound, risperidone. Knegtering et al. (2005) and Melkersson (2006) demonstrated in small studies of risperidone that plasma concentration of 9-hydroxyrisperidone correlated with increases in prolactin and may be the main contributor to increased levels of serum prolactin in many patients treated with risperidone. One double-blind, 6-week, randomized, placebocontrolled study (Marder et al. 2007) of 444 subjects (222 receiving paliperidone) found that prolactin-related adverse effects were reported in two men and one woman taking paliperidone (lactation and decreased libido) and two patients taking placebo. No systematic assessment of sexual function was utilized, however. Clozapine. Clozapine has weak affinity for D2 receptors and dissociates fairly quickly, resulting in only transient prolactin elevations (Volavka et al. 2004). These transient changes are measurable in the laboratory, but clinical hyperprolactinemia generally does not occur with this antipsychotic. Not surprisingly, most studies suggest that clozapine has less impact on sexual functioning than do other antipsychotics, especially risperidone and FGAs. Nonetheless, clozapine does have high affinity for muscarinic cholinergic and α-adrenergic receptors, and may induce sexual dysfunction through these mechanisms. An open-label study of 103 subjects taking clozapine found that 57 (55%) patients reported sexual side effects. Interestingly, only three of the patients reported these complaints based on an open question as to whether they experienced side effects from clozapine, whereas the other 54 patients reported sexual dysfunction during systematic inquiry (Yusufi et al. 2007). Although prolactin-related adverse effects are unlikely to occur, anticholinergic and antiadrenergic activity of clozapine can be associated with ejaculatory or erectile problems in males. Case reports of priapism and impotence have been reported with clozapine treatment (Compton and Miller 2001). According to prescribing information, 1%

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of patients may experience abnormal ejaculation (Clozaril Prescribing Information 2005). In the United States, clozapine is reserved for use in patients with schizophrenia that is refractory to other antipsychotics; thus, it is difficult to determine whether illness severity or other potential differences within this patient population may impact sexual dysfunction prevalence. Other Frequently Used Medications. People with schizophrenia are often treated with other psychotropic medications that have the potential to cause sexual dysfunction. Antidepressants may be associated with sexual side effects in differing degrees, based on their mechanisms of action. Although most published data regarding sexual side effects in patients treated with antidepressants have come from the depression literature (e.g., Clayton and Montejo 2006; Segraves 2007; Werneke et al. 2006), it is expected that these medication effects would generalize to other populations, such as patients with anxiety or schizophrenia. • SSRIs are associated with anorgasmia and delayed orgasm in up to 30%–40% of treated patients, decreased libido in up to 20% of patients, and erectile difficulties in up to 10% of patients. • Tricyclic antidepressants, due to varied noradrenergic, serotonergic, cholinergic, and histaminic effects, have been associated with sexual dysfunction. • Monoamine oxidase inhibitors may be associated with sexual dysfunction through effects on the serotonergic system. • Trazodone, at dosages ≥150 mg, has been associated with priapism in rare cases, thought to be at least partially explained by α-adrenergic antagonism. • Other antidepressants, such as mirtazapine, are thought to exert fewer sexual side effects; however, erectile dysfunction may occur as a result of noradrenergic activity. • Venlafaxine, duloxetine, and bupropion have been associated with less sexual dysfunction than have SSRIs. Valproate, although not extensively reported to cause sexual dysfunction, has also been associated with reproductive endocrine abnormalities (Morris and Vanderkolk 2005). Limited data are available regarding sexual dysfunction risk from other mood-stabilizing agents and benzodiazepines; however, reports suggest that treatment with the following may contribute in varying degrees to sexual dysfunction: lithium; anticonvulsants such as carbamazepine, valproate, or lamotrigine; and benzodiazepines (Ghadirian et al. 1982; Herzog et al. 2005).

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Assessment The assessment of sexual dysfunction among patients with schizophrenia has not been uniform in clinical research or practice. Few standardized and validated instruments have been used in studies of sexual dysfunction for this patient population, and definitions of sexual dysfunction and the parameters measured within these instruments are quite heterogeneous. Nonetheless, the higher prevalence rates reported following focused inquiry suggest that in clinical practice, directly addressing sexual function may be the most effective way to identify patient concerns about sexual disturbances. According to several reports, patients may be unlikely to spontaneously report sexual dysfunction for a number of reasons, and women may be less likely to report sexual dysfunction or suspected sexual side effects than men (Knegtering et al. 1999). Knegtering et al. (2006) demonstrated that although only 8.7% of patients complained of sexual dysfunction spontaneously after 6 weeks of antipsychotic treatment, 30.4% of patients in the study reported sexual dysfunction in response to a semistructured interview. In a survey of individuals with severe mental illness (not exclusively schizophrenia), patients reported various reasons they had not discussed sexual function with their clinicians, including they thought it would be embarrassing for them (28%), they thought nothing could be done (20%), and their sexual function did not bother them (16%) (Rosenberg et al. 2003). Recommendations from consensus panels, such as the Mt. Sinai Conference on Health Monitoring of Patients With Schizophrenia, indicate that mental health providers should directly question patients about changes in menstruation, libido, galactorrhea, and erectile and ejaculatory function. If patients are receiving a prolactin-elevating antipsychotic, direct patient questioning should occur at each visit until a stable dosage is reached, then at least yearly thereafter (Marder et al. 2004). Clinicians should understand that broaching the subject of sexual behavior and questioning patients about changes in sexual function are integral to the treatment of patients with schizophrenia, because of quality-of-life reasons and the impact that sexual side effects may have on medication adherence. Measuring sexual dysfunction in patients with schizophrenia has received far less attention than in the general population, and few biological indices may be reliably measured to screen for sexual dysfunction. Serum prolactin levels can be assessed, but these do not reliably predict sexual dysfunction (Knegtering et al. 2008). Most assessment techniques have employed rating instruments, but Kelly and Conley (2004) noted that for studies published prior to 2002, a total of 15 different

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scales were employed in the 16 published studies. Since then, a few scales have become validated and more widely used in this patient population, yet no gold-standard instruments exist. Patients with schizophrenia have fewer partners and relationships than do people in the general population; therefore, not all rating instruments reliably assess sexual complaints of schizophrenia patients. Much of the existing literature for sexual assessment in patients with mental illness comes from studies in depression. Clayton (2001) put forth criteria for assessment tools to measure sexual dysfunction in patients with depression, and subsequent authors (Kelly and Conley 2004) suggested that these criteria may also be useful in the schizophrenia population. Among those elements thought to be most useful for any assessment of sexual dysfunction in patients with schizophrenia are the following: • Assess premorbid and lifelong function compared to current function • Track changes across time • Assess phase-specific sexual functioning • Separate medication effects from illness • Include gender-specific questions • Be brief • Be nonintrusive Table 12–2 summarizes some of the most commonly used rating scales and information to help guide clinicians in the assessment of these symptoms.

Management Psychosocial Issues to Discuss Both men and women have reported that one area with the highest proportion of unmet needs is counseling about intimate relationships. Additionally, studies addressing sexual issues have generally concluded that patients with schizophrenia are prepared and open to discuss issues relating to sexual activity, and the majority of patients with schizophrenia believe that discussing sexual issues may actually be beneficial for their outcomes (Lewis and Scott 1997). Furthermore, concern about sexual dysfunction may exacerbate psychiatric symptoms (Sullivan and Lukoff 1990).

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TABLE 12–2. Rating instruments for sexual function used in schizophrenia Assessment

Administration format

Number of items

Domains

Bous et al. Semistructured Based on UKU sex- Based on UKU; libido, 2003 interview ual dysfunction orgasm, erection/ items (4 for men, ejaculation, vaginal 5 for women) lubrication McGahuey Self-report 5 for men Drive, arousal, penile et al. 2000 5 for women erection, vaginal lubrication, orgasm satisfaction Changes in Sexual Clayton et Semistructured 36 for men Sexual desire/frequency, Functioning al. 1997 interview 34 for women desire/interest, sexual Questionnaire pleasure, arousal/interest, orgasm/completion Dickson Glazer Dickson et Self-report, 32 for men Sexual desire, arousal, Scale al. 2001 computerized 40 for women frequency of activity, orgasmic function, satisfaction, sexually related problems; questions on perceptions of sexual side effects

Used in schizophrenia or antipsychotic studies? Yes

Yes. Validated, found reliable (Byerly et al. 2006b) Yes

Yes

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Antipsychotics in Sexual Functioning Questionnaire Arizona Sexual Experience Scale

Authors

TABLE 12–2. Rating instruments for sexual function used in schizophrenia (continued) Assessment

Authors

Administration format

Udvalg for Kliniske Undersogelser (sexual items)

15 for men

Lingjaerde Clinician rated 48 items related et al. 1987 to adverse effects; 10 items on sexual/ reproductive issues

UKU=Udvalg for Kliniske Undersogelser.

Used in schizophrenia or antipsychotic studies?

Yes Erectile function, orgasm, desire, intercourse, satisfaction, overall Frequency of sexual thoughts, Yes erections, masturbation over past 2 years and immediate 2 weeks; changes in specific aspects of sexual function 3 components: adverse effects Yes (psychic, neurological, autonomic, other), global assessment of presence/ absence of interference in daily performance due to adverse effects, and indication of consequences of clinician taking action to address side effects

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Note.

15 for men

Domains

Sexual Dysfunction

Rosen et al. Self-report International 1997 Index of Erectile Function Sexual Functioning Burke et al. Structured Questionnaire 1994 interview

Number of items

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Patients who are switched to less sexually adverse medications must be counseled regarding the expected impact on all aspects of sexual and hormonal functioning. Because symptoms may improve, libido and the desire to engage in intimate relationships may increase. Several cases have been reported of patients being switched to an SGA from an FGA with resultant unplanned pregnancies, potentially related to improvements in sexual function as well as the return of fertility (Dickson and Hogg 1998; Neumann and Frasch 2001; Tényi et al. 2002). Patients with schizophrenia often have poor judgment and report fairly frequent sexual activity with people who are known to be injection drug users. Fifty percent of patients with schizophrenia in one study were reported to be involved in sex exchange behavior (sex bought or sold for money, drugs, or goods), and condom use was particularly low, with less than 10% of these individuals using protective measures (Cournos et al. 1994). Moreover, women with schizophrenia not wishing to become pregnant do not commonly use contraception (Miller 1997). Sexual activity also occurs with those known to be infected with human immunodeficiency virus (HIV) or who are at risk, with documented HIV infection rates that are higher in patients with severe mental illness compared with the general population (Blank et al. 2002). Furthermore, rates of HIV infection have been increasing substantially in adults with serious mental illness (Otto-Salaj and Stevenson 2001). (For a more extensive discussion of HIV, see Chapter 10, “HIV and Hepatitis C in Patients With Schizophrenia.”) Women with schizophrenia also have more abortions and are more often victims of violence during pregnancy than those without mental illness (Miller and Finnerty 1996). Therefore, clinicians should be ready to deal with these issues and refer patients for additional counseling if needed. To help with the sexual dysfunction of patients with schizophrenia, clinicians should arrange for family planning, education, and contraceptive counseling as an integral part of the comprehensive treatment plan.

Prolactin Monitoring Despite variations in serum prolactin levels, both within and across individuals, a reasonable consensus exists regarding the upper limit of the normal range. Conservative reports consider >18–20 ng/mL in men and >24 ng/mL in women as the standard for the upper limit (Jung et al. 2005, 2006; Kinon et al. 2003, 2006). Not all prolactin elevations are symptomatic, however, and levels associated with sexual dysfunction and hormonal side effects vary widely. Nevertheless, women have sig-

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nificantly greater elevations from dopamine antagonists than do males, and prolactin levels of 80–150 ng/mL are in most cases correlated with clinically evident hormonal side effects. The recommendations from the 2004 Mt. Sinai Conference on Health Monitoring of Patients With Schizophrenia include directly asking patients about changes in menstruation, libido, erectile or ejaculatory function, and galactorrhea, which may be prolactin-related adverse effects, and if patients are receiving antipsychotics with greater propensity to elevate prolactin, the authors recommend “more frequent“ assessment. With a positive screen for these adverse events, prolactin levels should be drawn and, if possible, other potential causes for these symptoms should be ruled out (Marder et al. 2004). In the Practice Guideline for the Treatment of Patients With Schizophrenia, the American Psychiatric Association (2004) suggests initial or baseline screening for symptoms of hyperprolactinemia, and, if indicated on the basis of clinical history, a baseline serum prolactin level. These guidelines recommend follow-up screening for symptoms of hyperprolactinemia at each visit until stable, then yearly if the patient is taking an antipsychotic known to increase prolactin. Prolactin levels at follow-up are recommended if indicated on the basis of clinical history.

Medication Management No universal guidelines exist for managing sexual dysfunction in schizophrenia. Once sexual symptoms are identified, the degree of discomfort and dissatisfaction associated with the symptoms should be assessed, especially because sexual side effects are often of concern to patients and may affect medication adherence if the patient attributes sexual dysfunction to his or her treatment regimen. Interventions for the management of sexual dysfunction in patients with schizophrenia should be undertaken after careful consideration of all etiologies because sexual disturbances are complex and may arise from various sources. In addition to antipsychotic treatment, symptoms of schizophrenia itself and the psychosocial problems it entails are likely to impact sexuality. Other mental and physical conditions and diseases (e.g., depression, diabetes, nicotine dependence, cardiovascular disease) and medications (e.g., antidepressants, anticholinergic agents, antihypertensives) may contribute to sexual dysfunction. When possible, elucidation of the likely source of sexual dysfunction will assist in preparing a plan for management, beginning with the identification and elimination of potential nonpsychiatric causes. Management of sexual dysfunction related to schizophrenia also depends, in part, on the presenting symp-

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toms. When addressing symptoms thought to be related to hyperprolactinemia, other reasonable clinical alternatives should be discarded prior to focusing on the potential to alleviate the prolactin elevation. Dose Lowering and Antipsychotic Switching. As recognized previously in this chapter, different antipsychotic agents lead to different sexual dysfunction risks, with FGAs as a group contributing greater sexual side effect burden than SGAs. Among the SGAs, risperidone and extended-release paliperidone are more likely to be associated with increases in prolactin and the risk of sexual and neuroendocrine dysfunction. Lowering the dosage of the antipsychotic is a consideration, but clinicians must use caution to avoid decreasing an antipsychotic below its therapeutic threshold for a specific patient; moreover, antipsychotic agents with high levels of dopamine antagonism are associated with prolactin elevation even at low dosages, and no formal studies have been published to support a dosage reduction for sexual side effects (Costa et al. 2006). Switching to another antipsychotic with less propensity to cause sexual side effects entails some risk of psychotic relapse during the switch, but this option may be effective for certain patients (Marder et al. 2004), with some positive data indicating the benefits of successful antipsychotic switching. Kinon et al. (2006) openly switched 27 stable schizophrenia patients with hyperprolactinemia to olanzapine, and found reductions in mean serum prolactin, increased free testosterone levels, and improvements in sexual functioning. Nakajima et al. (2005) examined the effects of openly switching 25 female schizophrenia patients with hyperprolactinemia to quetiapine. Although eight patients dropped out due to psychotic exacerbation, the 17 patients who completed the 8-week study (68%) showed significant decrease in serum prolactin without significant change in illness severity. Byerly et al. (2008) reported the differential effects of switching patients with schizophrenia and sexual dysfunction to quetiapine versus continuing risperidone. Forty-two patients with risperidone-associated sexual dysfunction were randomized to double-blind quetiapine versus risperidone for 6 weeks. This study did not find significant differences in rated levels of sexual dysfunction between the quetiapine and risperidone groups, although total scores were slightly lower in the switch group at endpoint. Mir et al. (2008) reported data from an open-label switch to aripiprazole from other antipsychotics (N= 27), and found reduced prolactin levels, improved libido, reduction of menstrual and ejaculatory difficulties, and reduced menstrual dysfunction, accompanied by overall improvement in satisfaction in sexual functioning. By

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the end of the study, over half of the patients were still taking their original antipsychotic in addition to aripiprazole. Adjunctive Treatment. The use of adjunctive medication for the treatment of sexual dysfunction in patients with schizophrenia has not been as widely studied as the treatment of sexual dysfunction in the general population. The lack of large, well-designed, controlled longitudinal trials for the treatment of sexual dysfunction in patients with schizophrenia gives rise to difficulties in recommending any intervention with a high degree of confidence. Most of the information regarding management of sexual dysfunction in schizophrenia is focused on those symptoms thought to be adverse effects of the antipsychotic agents and consists mainly of small open-label studies and case reports, although a few small, randomized, placebo-controlled studies have been published. Sildenafil, an agent that improves erectile dysfunction via selective inhibition of cyclic guanosine monophosphate–specific phosphodiesterase type 5 (PDE5), has been used in schizophrenia in one doubleblind, placebo-controlled, crossover study (Gopalakrishnan et al. 2006); two open-label trials (Atmaca et al. 2002; Aviv et al. 2004); and several case reports. In the double-blind trial, sildenafil 25–50 mg was given to 32 patients with schizophrenia or delusional disorder and antipsychotic-induced erectile dysfunction. Sildenafil was superior to placebo on all measures, including erections and satisfaction with sexual intercourse. In a subgroup with elevated prolactin (n =22), sildenafil differed from placebo in satisfactory erections, duration of erections, and satisfaction with sexual intercourse. Adverse events were consistent with trials in the population without schizophrenia and included nasal stuffiness and headache (Gopalakrishnan et al. 2006). One open-label study reported that the use of sildenafil 50–100 mg in 10 patients with olanzapine-induced erectile dysfunction resulted in significant differences in erectile dysfunction scores (Atmaca et al. 2002). The second study found that sildenafil 25–75 mg in 12 male patients with schizophrenia taking risperidone resulted in either partial or great improvement in 67% of patients during open-label treatment (Aviv et al. 2004). Vardenafil is another PDE5 inhibitor with data for use in patients with schizophrenia. One open-label 12-week trial of 21 completing outpatients found that vardenafil 10–20 mg was associated with significant improvements in orgasmic function, sexual desire, intercourse satisfaction, and overall satisfaction. Improvements in sexual function were also associated with improvement in quality of life as measured by the Quality of Life Scale (Mitsonis et al. 2008). Adverse events, which were similar to

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those reported with other PDE5 inhibitors, most commonly included headache, flushing, nasal congestion, dyspepsia, and orthostatic hypotension. One subject withdrew from the study due to headache. Bromocriptine is a dopamine agonist that has been reported to improve libido in patients with hyperprolactinemia (Kelly and Conley 2004). Although use of the dopamine agonists has been concerning due to the potential for exacerbating psychotic symptoms, three small studies have investigated bromocriptine for sexual dysfunction. A small, open-label study of bromocriptine 5–10 mg/day resulted in a resumption of normal menstrual cycles in 55% of women and relief of galactorrhea in 33%, but smaller effects were seen with erectile and ejaculatory dysfunction (Beau and Guillard 1980). In an open-label trial of bromocriptine 5–7.5 mg/day, of the 35 patients (24 female, 11 male) studied, improvement in impotence was seen in 66% of male subjects, and return of menstrual cycle and relief of galactorrhea were seen in over 50% of the females with these complaints (Matsouka et al. 1986). A third study compared bromocriptine to the herbal supplement PeonyGlycyrrhiza Decoction (PGD) in the treatment of risperidone-induced hyperprolactinemia. In this randomized study, 20 women with schizophrenia taking risperidone received PGD or bromocriptine 5 mg/day for 4 weeks, and were then crossed over to other treatment after a 4-week washout. Neither treatment was associated with worsening of psychotic symptoms, and similar decreases in serum prolactin were found with both agents; however, 56% of subjects taking PGD but only 17% of subjects taking bromocriptine had improvement in side effects (Yuan et al. 2008). Cabergoline, a dopamine agonist, has been found effective in a few cases for reducing prolactin elevation in patients with antipsychoticassociated hyperprolactinemia without worsening of psychiatric symptoms (Cohen and Biederman 2001; Tollin 2000). One open-label pilot study reported the results of 19 patients with schizophrenia and risperidone-associated hyperprolactinemia who were treated with cabergoline 0.125–0.250 mg/week for 8 weeks. Treatment with cabergoline was associated with a statistically significant decrease in prolactin, and 11 patients reported alleviation of clinical signs of hyperprolactinemia. Cabergoline was not associated with a change in psychopathology (Cavallaro et al. 2004). A black-box warning has been issued, however, due to significant concern regarding cardiopulmonary toxicity with use of cabergoline and, to a lesser extent, bromocriptine. Fifteen cases of valvular heart disease in patients taking cabergoline had been reported to the U.S. Food and Drug Administration by the end of 2002 (Flowers et al. 2003).

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Selegiline, a monoamine oxidase inhibitor, was examined in one randomized trial for its potential use for sexual dysfunction in schizophrenia. Ten men with schizophrenia reporting sexual dysfunction while being treated with an FGA (perphenazine or haloperidol) were randomly assigned to receive selegiline 15 mg/day or placebo for 3 weeks, with a 2-week washout before a crossover to 3 weeks of the other treatment. No significant differences were found between the selegiline and placebo phases on measures of sexual function, although prolactin levels decreased during selegiline exposure (Kodesh et al. 2003). Side effects were not reported in the manuscript. Amantadine has been explored for the treatment of neuroendocrine side effects and/or sexual dysfunction because it purportedly causes dopamine release at neuronal terminals, and therefore may be effective in decreasing prolactin levels that are elevated as a result of antipsychotic use. Two open-label studies have been reported. Correa et al. (1987) found reductions in prolactin, gynecomastia and galactorrhea, breast tenderness, decreased libido, and amenorrhea in 10 patients with schizophrenia who were treated with open-label amantadine 200–300 mg/day in a 7-week study. In the other study, Valevski et al. (1998) reported the effects of amantadine on sexual dysfunction in males with schizophrenia who were treated with antipsychotics. Open-label amantadine 100 mg/day for 6 weeks was shown to improve patient scores on desire, erection, and satisfaction from sexual performance. Amantadine, however, is associated with a theoretical risk of worsening psychosis or other psychiatric side effects due to its effects on dopamine, as well as other dopaminergic adverse effects such as orthostatic hypotension. Aripiprazole has not been systematically studied for its effects on improving sexual dysfunction; however, adjunctive aripiprazole has been shown in a randomized, double-blind, 8-week trial to normalize elevated prolactin levels and improve hormonal side effects. In the aripiprazole group, 88.5% of patients at week 8 had normalized prolactin levels compared with 3.6% of patients in the placebo group. Among the 11 female patients with menstrual disturbances randomized to aripiprazole, seven regained menstruation during the study (63.6%), whereas no female patients did in the placebo group (Shim et al. 2007). A number of other open-label studies (Mir et al. 2008) and case reports of adjunctive aripiprazole with existing antipsychotics have also been published that support the results of larger trials. Several case reports and small studies have been published, mostly in the Japanese literature, describing the use of herbal supplements in the treatment of hyperprolactinemia associated with antipsychotics. One study and a case report using Shakuyaku-kanzo-to, or TJ-68, an

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herbal product, have found significant reductions in prolactin levels and hormonal side effects (Yamada et al. 1997, 1999). In one small, randomized, crossover study, the preparation Peony-Glycyrrhiza Decoction (PGD) was compared to bromocriptine in 20 women with schizophrenia and risperidone-associated hyperprolactinemia experiencing oligomenorrhea or amenorrhea. In this small study, PGD was more beneficial than bromocriptine for improving side effects, although prolactin decreases were similar (Yuan et al. 2008). Little information is available regarding the pharmacology or side effects of these agents.

Conclusion Sexual dysfunction is a frequently occurring problem in patients with schizophrenia, yet its recognition and significance have been overlooked by clinicians. Multiple etiological factors (e.g., schizophrenia itself, vascular disease, diabetes, smoking) are likely to exist beyond the effects of psychotropic medications, and these should not be overlooked. Many antipsychotic medications are associated with sexual dysfunction, and prolactin elevations contribute to a large proportion of sexual complaints, but hyperprolactinemia is not always associated with hormonal and sexual side effects. Anticholinergic and α-adrenergic mechanisms may also be particularly important for certain patients, with males especially vulnerable to erectile problems from the latter. The management of patients with sexual dysfunction involves optimal communication between the patient and clinician, careful exploration of potential causes and contributing factors, and assessment of impact on the patient’s attitude toward treatment and quality of life. Identifying and eliminating nonpsychiatric causes may be helpful in addressing this problem. Treatment changes based on sexual dysfunction should be carefully considered and, when possible, targeted to the specific symptoms. Switching an antipsychotic medication to one less likely to cause sexual dysfunction, or in some cases reducing the dosage, has been proposed but may not always be the practical or recommended approach for certain patients. The best approaches for the treatment of hyperprolactinemia and sexual dysfunction currently appear to be either initiating treatment with prolactin-sparing antipsychotics or decreasing prolactin levels through the use of dopamine agonists or aripiprazole adjunctively, if the side effects are definitely secondary to prolactin elevations. The use of PDE5 inhibitors may be of particular value in cases with a less clear association between sexual dysfunction and elevated prolactin, particularly in males who, for in-

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stance, smoke or have diabetes; however, studies are needed to help guide evidence-based treatment. As clinicians strive to reach recovery in patients, better communication on sexuality and sexual dysfunction will assist greatly in this endeavor.

Key Clinical Points ◗

Sexuality and sexual dysfunction in patients with schizophrenia have received little attention in the past.

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Sexual dysfunction has been difficult to measure accurately in patients with schizophrenia, but its prevalence is generally considered to be higher in these patients than in the general population. Reported prevalence rates vary widely, with most publications citing rates of 50%–75%.

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The types and prevalence of sexual dysfunction are likely to differ between men and women. Males with schizophrenia who have sexual dysfunction typically complain of decreases in libido and erectile, ejaculatory, and orgasmic functions, whereas women may experience disturbances in libido, vaginal lubrication, and orgasm, as well as dyspareunia and menstrual disturbances.

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Sexual dysfunction, especially if it is perceived by the patient to be an effect of antipsychotic medication, may be a factor that impacts treatment adherence.

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Multiple factors may contribute to sexual dysfunction, including lifestyle factors, symptoms of schizophrenia and other comorbidities, medications or substances used, and cigarette smoking.

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The mechanisms by which medications affect sexual function likely differ. Although many neurotransmitter systems (dopaminergic, serotonergic, adrenergic, cholinergic, histaminic) that are affected by antipsychotics may contribute to sexual dysfunction, elevation of serum prolactin is thought to account for a significant proportion of sexual dysfunction seen in patients.

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The effects of prolactin elevation should be considered when screening patients at clinic visits, especially those patients taking prolactin-elevating antipsychotics.

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First- and second-generation antipsychotics have both been associated with sexual dysfunction, although differences exist both within and among the different classes.

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◗

Risperidone, paliperidone, and some FGAs have been associated with the greatest increases in prolactin levels among patients treated with antipsychotics.

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The assessment of sexual dysfunction has not been widely studied. Several instruments exist, but no gold standard has been identified. Because patients may be hesitant to broach the subjects themselves, directly questioning patients about sexual function and dysfunction should be incorporated into the treatment plan and may result in detecting dysfunction.

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The management of sexual dysfunction in patients with schizophrenia is complex. Psychosocial issues should be addressed. Medication management may be necessary, and adjunctive medications have sometimes been reported in the literature. Only limited data exist to evaluate the efficacy of these interventions.

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Wang PS, Walker AM, Tsuang MT, et al: Dopamine antagonists and the development of breast cancer. Arch Gen Psychiatry 59:1147–1154, 2002 Werneke U, Northey S, Bhugra D: Antidepressants and sexual dysfunction. Acta Psychiatr Scand 114:384–397, 2006 Yamada K, Kanba S, Yagi G, et al: Effectiveness of herbal medicine (shakuyakukanzo-to) for neuroleptic-induced hyperprolactinemia. J Clin Psychopharmacol 17:234–235, 1997 Yamada K, Kanba S, Yagi G, et al: Herbal medicine (shakuyaku-kanzo-to) in the treatment of risperidone-induced amenorrhea. J Clin Psychopharmacol 19:380–381, 1999 Yamazawa K, Matsui H, Seki K, et al: A case-control study of endometrial cancer after antipsychotics exposure in premenopausal women. Oncology 64:116–123, 2003 Yuan HN, Wang CY, Sze CW, et al: A randomized, crossover comparison of herbal medicine and bromocriptine against risperidone-induced hyperprolactinemia in patients with schizophrenia. J Clin Psychopharmacol 28:264–270, 2008 Yusufi B, Mukherjee S, Flanagan R, et al: Prevalence and nature of side effects during clozapine maintenance treatment and the relationship with clozapine dose and plasma concentration. Int Clin Psychopharmacol 22:238– 243, 2007 Zyprexa Prescribing Information. Indianapolis, IN, Eli Lilly, 2008

CHAPTER 13 Managing the Health Outcomes of Schizophrenia Treatment in Children and Adolescents Christoph U. Correll, M.D.

In children and adolescents, antipsychotics are used in increasing quantities for schizophrenia, other psychotic disorders, and various nonpsychotic conditions (Olfson et al. 2006). For youth, as for adults, the majority of antipsychotics used are second-generation agents, partly because children and adolescents are especially sensitive to the adverse neuromotor effects of first-generation antipsychotics (Correll et al. 2006). At the time of this writing, the U.S. Food and Drug Administration (FDA) has approved only four antipsychotics—haloperidol and

This work was supported in part by the Zucker Hillside Hospital National Institute of Mental Health Advanced Center for Intervention and Services Research for the Study of Schizophrenia grant MH 074543-01, and the North Shore–Long Island Jewish Health System Research Institute National Institutes of Health General Clinical Research Center grant M01 RR018535.

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thioridazine, which are first-generation antipsychotics (FGAs), and risperidone and aripiprazole, which are second-generation antipsychotics (SGAs)—for use in pediatric schizophrenia, with approval for the two FGAs being based predominantly on adult data and small studies in youths. However, with the increasing use of SGAs, their effects on body weight and metabolic health have become increasing concerns (Correll and Carlson 2006). Weight gain and obesity have known associations with diabetes, dyslipidemia, and hypertension, all of which are leading risk factors for future cardiovascular morbidity and mortality (Ebbeling et al. 2002). Moreover, data suggest that obesity during childhood predicts poor metabolic outcomes for adults even better than obesity during adulthood (Must et al. 1992). In this chapter, I review the available pediatric data on the side effects of antipsychotics with adverse health impact, aiming to inform antipsychotic prescribing and monitoring practices in this vulnerable population. Data from studies of children and adolescents with schizophrenia are highlighted, augmented by pediatric data from studies of other disorders where appropriate. Based on the far-reaching implications of age-inappropriate weight gain and metabolic abnormalities, adequate monitoring, management, and, whenever possible, prevention of adverse health outcomes in youths is crucial to promoting long-term physical and psychological well-being, sustained treatment adherence, and adequate role functioning and attainment of developmental milestones.

Developmental Considerations Childhood through adolescence is a period of unparalleled development, biologically, psychologically, and socially. Although data regarding the bioavailability and bioactivity of medications in pediatric populations are relatively slim, drug uptake, distribution, and metabolism in youth are affected by several factors that differ from those in adults. Some of these factors relevant for medication treatment include active tissue growth, reproductive hormone release beginning in adolescence, a higher ratio of liver organ-to-tissue mass, greater intracellular and extracellular tissue water and glomerular filtration rate, lower protein binding, and reduced fat tissue mass in youths compared with adults (Paxton and Dragunow 1993). Clinically, these differences translate into the general need for higher dosages per kilogram of weight in children and adolescents compared with adults in order to reach comparable serum levels and achieve therapeutic efficacy; also, more fre-

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quent doses during the day may be required in prepubertal children (Woods et al. 2002).

Efficacy of Antipsychotics in Children and Adolescents With Schizophrenia Twelve, mostly recent, randomized, controlled antipsychotic trials (N= 1,014) have shown efficacy as monotherapy in pediatric schizophrenia (Kumra et al. 2008b). Superior efficacy of antipsychotics versus placebo in reducing scores on the Positive and Negative Syndrome Scale (PANSS) and/or the Brief Psychiatric Rating Scale (BPRS) was demonstrated in three randomized, placebo-controlled trials of patients ages 13–17 with schizophrenia. The SGAs used in these studies were aripiprazole (N =294, using fixed dosages of 10 mg/day, mean 9.56 mg/ day, and 30 mg/day, mean 27.8 mg/day) (Robb et al. 2007), olanzapine (N = 107, using flexible dosages of 2.5–20 mg/day, mean 11.1 mg/day) (Kryzhanovskaya et al. 2005), and risperidone (N= 158, using flexible dosage range of 0.5–3 mg/day, mean 2.6 mg/day, and 4–6 mg/day, mean 5.3 mg/day) (Haas et al. 2007). In one additional, currently unpublished study, risperidone (N= 279) was dosed at 1–6 mg/day (mean 4.0 mg/day) and compared to a pseudo-placebo with a dosage range of 0.1–0.6 mg/day (mean 0.5 mg/day) in pediatric patients with schizophrenia (Janssen Pharmaceutica, unpublished data). In all four trials, compared with patients taking the placebo or the pseudo-placebo dose of risperidone, the patients taking the SGA had superior primary outcome, consisting of the total mean score change on the PANSS or BPRS from baseline to endpoint. In an older, 4-week, placebo-controlled trial (Pool et al. 1976), both haloperidol (n= 25, mean 9.8 mg/day) and loxapine (n = 26, mean 87.5 mg/day) were associated with significantly greater reductions in BPRS scores compared with placebo, but there were no differences between the two active medication groups. The remaining antipsychotic studies in pediatric schizophrenia were all active-controlled trials, comparing different antipsychotics and lacking a placebo arm, thereby precluding a conclusive assessment of the efficacy of the tested antipsychotics. In the three studies not involving clozapine that lasted between 4 and 8 weeks, no statistically significant differences in efficacy were found between the tested antipsychotics, including comparisons of thiothixene (mean 16.2 mg/day) and thioridazine (mean 178 mg/day) (N= 21; Realmuto et al. 1984); haloperidol (mean 5.0 mg/day), olanzapine (mean 12.3 mg/day), and risperidone (mean 4.0 mg/day) (N= 50; Sikich et al. 2004); and molindone

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(range 10–140 mg/day, target 65 mg/day), olanzapine (range 2.5–20 mg/day, target 12.5 mg/day), and risperidone (range 0.5–6 mg/day, target 3 mg/day) (N =119; Sikich et al. 2008). On the other hand, in relatively small, active controlled trials, clozapine at mean dosages between 176 mg/day and 403 mg/day was superior on several efficacy measures compared with haloperidol (N=21, mean 16 mg/day; Kumra et al. 1996), olanzapine (N=13, mean 18.1 mg/day; Shaw et al. 2006), and “high”-dose olanzapine (up to 30 mg/day) (N=39, mean 26.2 mg/day; Kumra et al. 2008a). Taken together, findings from these studies show that antipsychotics are superior to placebo in youth with schizophrenia, as in adults, and that the differences between antipsychotics other than clozapine may be relatively small. Therefore, differences in adverse effects, and especially adverse effects that can impair health outcomes and longevity, are to be taken seriously when prescribing this class of medications to pediatric patients, who often suffer from a severe form of the disorder and who are likely to require antipsychotic treatment for long periods of time.

Adverse Effects Associated With Antipsychotics in Children and Adolescents Children and adolescents seem to be more sensitive than adults to most antipsychotic adverse effects, including sedation, extrapyramidal side effects (except akathisia, which occurs at similar rates), withdrawal dyskinesia, prolactin elevation (especially in postpubertal patients), weight gain, and related metabolic abnormalities (Correll et al. 2006). On the other hand, adverse effects that require a longer time to develop physiologically (e.g., diabetes mellitus) and/or that are related to medication dosage and lifetime exposure (e.g., tardive dyskinesia) seem to emerge less frequently in pediatric cohorts, at least during follow-up durations that are relatively short (Correll et al. 2006). Actually, these adverse events may not occur at a reduced frequency in youths, who have a relatively large reserve of pancreatic beta cells and striatal dopamine neurons, but may rather be delayed and show up earlier in adulthood, depending on how early antipsychotic treatment was initiated during childhood and adolescence. Clearly, longer-term follow-up studies of youths in whom antipsychotics are initiated are required to clarify this issue further.

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Weight Gain and Metabolic Adverse Effects Although pediatric data are limited, children and adolescents with psychiatric disorders seem to be at increased risk for being overweight or obese (Patel et al. 2007), especially when exposed to antipsychotics for longer periods of time (Laita et al. 2007). Age-inappropriate weight gain is of particular concern in children and adolescents because weight gain is associated with health and psychosocial issues at a time in human development when self-esteem and body image are being formed and consolidated. Weight gain can be associated with the development of eating disorders and depression, and the medical consequences of weight gain may adversely affect pulmonary, gastrointestinal, renal, musculoskeletal, cardiovascular, and endocrine systems in a manner that is both enduring and detrimental (Ebbeling et al. 2002). These medical comorbidities and complications can impair patients’ quality of life and shorten life expectancy. Antipsychotic-Related Weight Gain. Reasons for weight gain and obesity in patients with psychiatric illness are multifactorial and complex, including effects of the underlying psychiatric illness, consequences of lifestyle behaviors (particularly sedentary lifestyle and unhealthy diet), and direct and indirect effects of psychotropic treatment. A recent review of data suggested that the weight gain potential of SGAs for pediatric patients follows roughly the same rank order as that for adults (American Diabetes Association et al. 2004) but that the magnitude is greater (Correll and Carlson 2006). Exceptions may be a greater relative weight gain propensity of risperidone in youth (Safer 2004), a greater likelihood of aripiprazole and ziprasidone to not be weight neutral in subgroups of pediatric patients, and possibly greater olanzapine-induced weight gain compared with clozapine in treatment-refractory youth, although results differ depending on the studies and patient groups (Correll 2008b; Correll and Carlson 2006). Research studies have not yet resolved whether the greater antipsychotic-related weight gain in pediatric patients than in adults is due to physiological differences between growing children and adults that are related to mechanisms regulating food intake and energy homeostasis, whether the greater weight gain is due to less lifetime antipsychotic exposure, or whether it is due to a combination of both of these factors. The latter is suggested by findings of substantial amounts of weight gain in adults who are antipsychotic naive or in a first episode of schizophrenia (Alvarez-Jiménez et al. 2008). In an 8-week, randomized study of 25 patients ages 7–16 years, clozapine and olanzapine resulted in similar weight gain (3.8 ± 6.0 kg and

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3.6± 4.0 kg, respectively) (Shaw et al. 2006). In an earlier, randomized trial of patients ages 10–18 years with early-onset schizophrenia, clozapine and haloperidol produced similar and quite modest weight gain (0.9 ± 6.5 kg and 0.9 ±2.9 kg, respectively) (Kumra et al. 1996). On the other hand, in a naturalistic study, olanzapine was associated with greater weight gain (4.6 ±1.9 kg) than clozapine (2.5 ±2.9 kg), which had comparable weight gain to that of risperidone (2.8 ± 1.3 kg) (Fleischhaker et al. 2006). However, because clozapine was used in treatmentrefractory patients, weight gain in clozapine-treated children could have been attenuated by prior antipsychotic exposure and resultant weight gain. Similar to the study by Fleischhaker et al. (2006), Sikich et al. (2004) found a higher weight gain in youths ages 5–17 years with psychotic disorders who were randomly assigned to receive olanzapine for 8 weeks (7.1±4.1 kg) than in youths randomized to either risperidone (4.9± 3.6 kg) or haloperidol (3.5 ± 3.7 kg). After only 8 weeks of treatment, all treatment groups had mean observed weight gain that was severe and disproportionate to that expected from normal growth. In a prior open-label study, Ratzoni et al. (2002) reported on weight change in adolescents with schizophrenia treated for 12 weeks using the same three antipsychotics. Both statistically and clinically significant weight gain was observed with olanzapine (7.2 ± 6.3 kg) and risperidone (3.9 ±4.8 kg), but the mean weight change with haloperidol (1.1± 3.3 kg) was not significant. Finding weight gain of ≥7% from baseline to the end of 12 weeks in 90.3% of patients taking olanzapine, 42.9% taking risperidone, and 12.5% taking haloperidol, the authors concluded that the weight gain in their adolescent sample was more extreme than that observed in adult studies. Similarly, high weight gain has been reported in preschool-age children (ages 4–6 years); during only 8 weeks of treatment, children treated with olanzapine and risperidone had a mean increase in weight of 12.9% ±7.1% and 10.1% ±6.1%, respectively (Biederman et al. 2005). In a 6-month naturalistic, unmatched study of 66 patients with fewer than 30 days of antipsychotic exposure and treated with olanzapine (n =20), risperidone (n =22), or quetiapine (n =24), age- and sex-adjusted weight gain, measured as body mass index (BMI) z-scores, was significant in the olanzapine (1.1 ±0.82) and risperidone (0.48 ±0.73) groups, but not in the quetiapine group (0.27 ±0.86) (Fraguas et al. 2008). In this small sample, a transition to an adverse health outcome—that is, >85th BMI percentile plus at least one adverse health outcome related to blood pressure or lipid or glucose metabolism (Correll and Carlson 2006)—occurred significantly compared to baseline in the olanzapine

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group (15.0%–60.0%), but not in the risperidone (22.7%–36.4%) or quetiapine (15.5%–20.8%) groups. Due to the confounding effects of nonrandom assignment and small sample sizes in the studies mentioned previously, larger, placebocontrolled trials are more informative. Because none of the four 6-week, randomized, placebo-controlled studies of SGAs in adolescents with pediatric schizophrenia have been published and only three have been presented at scientific meetings, at this point, data on absolute weight gain are available for only two of these trials. In a study comparing fixed-dosage aripiprazole 10 mg (n =102) and 30 mg (n =100) with placebo (n=100), a slight but significant difference (P<0.05) in weight gain was reported in adolescents taking placebo (−0.8 kg) versus aripiprazole 10 mg (0 kg) and 30 mg (0.2 kg) (Findling et al. 2007), although the weight change with aripiprazole was minimal in this study and comparable to what has been reported in adults. On the other hand, treatment with olanzapine (n= 72) at dosages between 2.5 and 20 mg (mean 11.1 mg) was associated with a 4.3-kg weight gain, which was significantly greater (P<0.0001) than the 0.1-kg weight gain in patients on placebo (n =35) (Kryzhanovskaya et al. 2005). Because mean weight change can easily obscure substantial weight gain in a subset of patients due to weight loss in another subgroup with different past antipsychotic exposure and other characteristics, an important consideration is the proportion of patients who gained at least 7% of weight in the recent placebo-controlled trials with SGAs. Figure 13–1 summarizes the data from the three double-blind, placebocontrolled studies of atypical antipsychotics in adolescents with schizophrenia for which data are available on the proportion of patients who experienced at least 7% of weight gain during 6 weeks of treatment (Correll 2008b). Results suggest that similar to adult studies, the greatest weight gain occurred in patients taking olanzapine (45.8%) versus placebo (1.7%) (Kryzhanovskaya et al. 2005). Risperidone was associated with intermediate risk, with at least 7% weight gain occurring in 15% of the 1- to 3-mg group and 16% of the 4- to 6-mg group, compared with 2% of the placebo group (Haas et al. 2007). Finally, aripiprazole was associated with the lowest risk, with at least 7% weight gain in 4% of patients on 10 mg and 5.2% of patients on 30 mg of aripiprazole, compared with 1% of patients on placebo (Findling et al. 2007). The resulting numbers needed to harm (NNH) in patients with adolescent schizophrenia were 3.2 for olanzapine, 7.1–7.7 for risperidone, and 24.4–33.3 for aripiprazole (Correll 2008b). Data from the completed treatment of early-onset schizophrenia spectrum disorders study (Sikich et al. 2008), which compared risperidone, olanzapine, and

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molindone, will add to this picture, but more randomized head-to-head studies of antipsychotics in youths are needed to directly compare riskbenefit ratios. Of note, currently available data suggest that combined treatment with an SGA plus a stimulant does not seem to substantially attenuate SGA-induced weight gain (Aman et al. 2004; Calarge et al., in press). On the other hand, at least with olanzapine, risperidone, and possibly quetiapine, combined treatment with an SGA plus a mood stabilizer seems to be associated with greater weight gain than monotherapy with a mood stabilizer or even combination treatment with lithium plus valproic acid, as suggested by trials in youths with bipolar disorder (Correll 2007b). Adverse Metabolic Effects. With the widely reported age-inappropriate weight gain in children and adolescents treated with antipsychotics, a worsening of metabolic indices, such as triglycerides, cholesterol, and insulin resistance, is expected to occur. However, methodologically sound, conclusive, and long-term prospective data regarding metabolic effects of antipsychotics in pediatric patients are largely lacking. In a cross-sectional study with metabolic data from 80 to 95 pediatric patients, total cholesterol levels (P< 0.001) and low-density lipoprotein (LDL) cholesterol levels (P=0.018) were significantly higher in youths receiving antipsychotics for 12 months or longer than in similar patients given antipsychotics for less than 1 month (Laita et al. 2007). Despite large differences in BMI (i.e., 24.1 in youth with longer-term exposure vs. 20.4 in youth with shorter-term exposure), triglyceride levels (which correlate with insulin resistance) were not statistically different (94.7 ± 48.3 mg/dL vs. 82.7 ±48.9 mg/dL). Although this lack of a significant difference for triglycerides is somewhat surprising, these results could have been due to any of the following: the sample size was relatively small, groups were not randomized or closely matched, weight changes may have occurred largely within the normal weight range, youths might be able to draw upon intact and effective compensatory mechanisms, and some of the assessments were from nonfasting patients. Although the link between antipsychotic treatment and adverse metabolic consequences such as dyslipidemia, hyperglycemia, diabetes, and metabolic syndrome has been established in adults (American Diabetes Association et al. 2004), the few published retrospective and prospective pediatric studies (Biederman et al. 2005, 2007; Malone et al. 2007; Martin and L’Ecuyer 2002; Sikich et al. 2004) have produced almost exclusively negative results, in that antipsychotic exposure and weight gain were associated with no significant metabolic abnormalities. However, the

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Placebo n =100

Placebo n =54

Placebo n =35

Aripiprazole 10 mg n =102

Risperidone 1–3 mg n =55

Olanzapine 2–20 mg n =72

Aripiprazole 30 mg n =100

Risperidone 4–6 mg n =51

FIGURE 13–1. Proportion of adolescents (ages 13–17 years) with schizophrenia gaining >7% of baseline weight in 6-week, doubleblind, placebo-controlled trials with atypical antipsychotics.

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interpretation of these results is limited by small sample sizes, varying treatment histories, and mostly the inclusion of random glucose assessments. In a pooled analysis of 24 medication trials of antipsychotic-treated youth with bipolar disorder, nonfasting glucose and lipid changes were nonsignificant in the only two atypical antipsychotic trials with available data (N =61) (Correll 2007b). Moreover, as briefly reported (Correll and Carlson 2006), interim results from a large-scale, naturalistic cohort study presented at a scientific meeting suggested the emergence of relevant rates of new-onset dyslipidemia and increases in insulin resistance in several of the SGA groups after only 3 months of exposure in the subgroup of antipsychotic-naive patients. This preliminary report is consistent with another recent study of 66 pediatric patients (67% male, mean age 15.2 years) with psychotic disorders, treated naturalistically with either olanzapine (n= 20), risperidone (n =22), or quetiapine (n =24) (Fraguas et al. 2008). Importantly, as in the preliminary report by Correll et al. (2006), patients had minimal prior antipsychotic use—all had fewer than 30 days lifetime exposure, and 38% were antipsychotic naive. After 6 months of antipsychotic exposure in this nonrandomized and unmatched sample, total cholesterol levels increased significantly in the olanzapine group (P=0.045) and the quetiapine group (P= 0.016), but not in the risperidone group. Although weight gain was significant in all three groups, triglyceride, LDL, high-density lipoprotein (HDL), and glucose levels did not increase significantly compared with baseline levels over the 6-month period in this small group of patients. As recently summarized (Correll 2008b), short-term, placebocontrolled trials with aripiprazole, risperidone, and quetiapine in youths with schizophrenia or bipolar disorder found no significant mean changes in lipid or glucose parameters. The same was true for a recently presented placebo-controlled trial with ziprasidone in pediatric patients with bipolar disorder, who experienced minimal weight gain (DelBello et al. 2008). Conversely, compared with placebo, olanzapine resulted in significant increases in triglycerides in adolescents with schizophrenia (P= 0.029), as well as significant increases in blood glucose (P= 0.002), total cholesterol (P= 0.010), and uric acid (P =0.026) in pediatric patients with bipolar disorder (Tohen et al. 2007). Moreover, in patients with pediatric bipolar disorder, new-onset abnormal metabolic values that occurred at any time during the study were significantly more frequent with olanzapine than with placebo; these values included abnormally elevated total cholesterol (19.1% vs. 2.1%, P = 0.004), low HDL (10.9% vs. 0.0%, P = 0.016), and hypertriglyceridemia (49.1% vs. 14.8%, P=0.003) (Tohen et al. 2007).

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Although individual case reports of diabetes in pediatric patients taking antipsychotics have been published (for specific reports, see Correll and Carlson 2006), methodologically rigorous, prospective studies of metabolic syndrome and diabetes in youths exposed to antipsychotics, especially for longer periods of time, are almost absent. Despite the absence of such long-term studies, long-term prospective data in nonpsychiatric pediatric populations followed into adulthood indicate that ageinappropriate weight gain has particularly deleterious effects when occurring early in life. In follow-up studies, obesity, metabolic abnormalities, and weight gain during childhood have been shown to strongly predict obesity, metabolic syndrome, hypertension, cardiovascular morbidity, sleep apnea, osteoarthritis, and malignancy risk in adulthood (Baker et al. 2007; Dietz and Robinson 2005; Freedman et al. 2004; Must et al. 1992; Srinivasan et al. 2002). Clearly, these data strengthen the concern about the magnitude of the antipsychotic-related weight gain that is observed in short-term studies of pediatric populations.

Prolactin-Related Side Effects As previously summarized (Correll and Carlson 2006), FGAs and several SGAs are associated with clinically relevant prolactin elevations in children and adolescents. Hyperprolactinemia can result in sexual and reproductive system side effects, such as amenorrhea or oligomenorrhea, erectile dysfunction, decreased libido, hirsutism, and breast symptoms, such as enlargement, engorgement, pain, or galactorrhea. However, in open-label (Findling et al. 2003; Masi et al. 2003; Saito et al. 2004) and randomized (Aman et al. 2002) studies with youth, serum prolactin levels are not tightly correlated with these side effects, and not all patients with hyperprolactinemia develop these signs and symptoms (Masi et al. 2003). Like adults, many pediatric patients continue to have normal gonadal function and no overt reproductive-system side effects, despite moderately elevated serum prolactin (Findling et al. 2003). Available data also suggest that hyperprolactinemia is dosage dependent, may normalize over time in some patients, and resolves after antipsychotic discontinuation. Similar to the pattern seen in adults, the relative potency of antipsychotic drugs in inducing hyperprolactinemia in pediatric patients is roughly the following: paliperidone ≥ risperidone > haloperidol > olanzapine > ziprasidone > quetiapine> clozapine >aripiprazole. Due to prepubertal status and less sexual activity and familiarity with their developing sexuality, many pediatric patients exposed to antipsychotics may not experience, notice, or report sexual or reproductive system dysfunction, making it more difficult to determine if hyper-

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prolactinemia is present through history taking or even physical examination (Correll and Carlson 2006). Studies suggesting that levels of hyperprolactinemia that cause hypogonadism (i.e., that suppress gonadotropin-releasing hormone and, thus, sex hormone levels) are associated with osteoporosis and increased risk of bone fractures are especially concerning, because adolescence is the prime time of bone mineralization development (Byerly et al. 2007). Other potential but unconfirmed risks from childhood hyperprolactinemia might include a negative effect on pubertal development (Correll and Carlson 2006) and a risk for breast cancer or pituitary tumors (Byerly et al. 2007). In a review of antipsychotic effects on prolactin levels in youths with schizophrenia spectrum disorders (Kumra et al. 2008b), risperidone and haloperidol were noted to have the greatest effect on prolactin levels; quetiapine, clozapine, and aripiprazole were noted to have the least effect on prolactin levels; and olanzapine and ziprasidone appeared to have intermediate effects. In a 3-week study of 161 children and adolescents, olanzapine treatment was associated with a greater baseline-to-endpoint increase in prolactin levels compared with placebo, as well as with surprisingly high incidence rates of hyperprolactinemia, particularly among boys (in boys, 62.5% with olanzapine vs. 5% with placebo, P<0.001; in girls, 25.7% with olanzapine vs. 0% with placebo, P=0.007) (Tohen et al. 2007). A pooled analysis of several pediatric risperidone studies in children ages 5–15 years treated with mean dosages of 0.02–0.06 mg/kg/day found that the biggest increase in prolactin levels occurred in the first 1– 2 months (N=550) (Findling et al. 2003). However, results of this study have to be interpreted within the limitations that they are based on a sample with an inherently relatively low hyperprolactinemia risk, consisting of prepubertal individuals, predominantly boys, treated with low dosages of risperidone, and cotreatment with stimulants was allowed. One larger study (N =222) examined the effects of risperidone on height and sexual maturation (Dunbar et al. 2004). Boys ages 10–15 years and girls ages 9–15 years were evaluated for sexual maturation by Tanner staging and followed for 11–12 months. Encouragingly, this study found no correlation between prolactin levels and either height or sexual development; however, firm conclusions from this single study are precluded by sample heterogeneity in age and pubertal stage, combined with follow-up of only 1 year.

QTc Prolongation As discussed extensively in Chapter 7, “The Spectrum of Cardiovascular Disease in Patients With Schizophrenia,” antipsychotics can differ-

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entially prolong the heart rate–corrected QT interval (QTc) of the electrocardiogram. QTc prolongation may be associated with torsade de pointes, a potentially fatal arrhythmia (Blair et al. 2004). Concerns in pediatric patients include the notion that the developing cardiac conduction system may be especially vulnerable to these effects. In adults, QTc prolongation is usually minimal with antipsychotics compared to placebo, except with certain medications (e.g., thioridazine), but among the SGAs, ziprasidone has been associated with the greatest QTc prolongation compared to baseline (Glassman and Bigger 2001), although without known incidence of torsade de pointes. Cardiac conduction effects of ziprasidone have been studied in children and adolescents, and QTc prolongation to >430 milliseconds has been described in three of 20 pediatric patients treated prospectively with ziprasidone (mean QTc prolongation of 28 ± 26 milliseconds, P< 0.01) (Blair et al. 2005). Although no relationship to ziprasidone dosage was found in this study, dosages were very low (mean 30±13 mg/ day, range 30–60 mg/day). In a small study in only 12 youths, a statistically significant increase in QTc (14.7±21.0 milliseconds, P= 0.04) was reported at a mean ziprasidone dosage of 98.3 (range 40–160) mg/day (Malone et al. 2007). On the other hand, QTc changes were reported to have been nonsignificant in studies of 12 (McDougle et al. 2002), 16 (Sallee et al. 2000), and 21 patients (Biederman et al. 2007) at ziprasidone dosages of 57.3 (range 20–120) mg/day, 28.2 (range 5–40) mg/day, and 59.2 (range 20–120) mg/day, respectively. Moreover, no patient in any of these studies reported cardiac side effects, such as dizziness, palpitations, or syncope. Thus, the clinical relevance of this degree of QTc prolongation, which did not reach the generally accepted pathological threshold of >500 milliseconds or an increase in QTc over baseline of >60 milliseconds (Glassman and Bigger 2001), is unclear, and theoretical concerns about QTc prolongations with ziprasidone need to be weighed against the more certain benefits regarding the relative risk for weight gain and metabolic abnormalities. (For more discussion, see Chapter 7, “The Spectrum of Cardiovascular Disease in Patients With Schizophrenia.”)

Monitoring and Management of Adverse Effects Pediatric patients taking antipsychotics must be monitored carefully and proactively for adverse effects, particularly medical adverse effects that can shorten life expectancy, decrease quality of life and functioning, or nega-

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tively affect treatment alliance and adherence. If results of monitoring show clinically relevant adverse events, actions should be taken to minimize their impact on patient health and other outcomes. Importantly, these adverse effects may have to be identified and managed by mental health prescribers because young patients are most often seen by pediatricians only once per year for routine checkups. Because physical health is very important and also related to psychiatric treatments and outcomes, the psychiatrist needs to take the initiative to monitor medical effects of psychiatric medications, initiate referrals for a consultation, and actively comanage the patient’s physical health in addition to the patient’s mental health.

Monitoring Strategies Several assessments of adverse effects should be made at baseline and at regular intervals to monitor the impact of antipsychotic treatments on pediatric patients (see Table 13–1). Importantly, as children and adolescents undergo normal developmental changes, the adverse effect assessment and monitoring has to take into consideration developmental norms and thresholds that can differ substantially from those for adults (see Table 13–2). At baseline and annually, personal and family histories of metabolic and endocrine complications should be assessed. At each visit, the clinician should inquire about the status of health lifestyle behaviors related to diet, activity, sleep, and substance use, unless the patient’s weight and metabolic status are healthy and stable. The elicited information should be compared with recommended behaviors in the general pediatric population (American Medical Association 2007) or those that were adapted for youth with psychiatric illness (Correll and Carlson 2006) (see Table 13–3).

Height, Weight, and Body Composition Being dynamic parameters in youths, height and weight should be measured and recorded at each visit. Height measurement can be difficult and requires adequate tools—ideally a wall-mounted stadiometer—and trained personnel who measure height several times and make sure patients stand erect, place their heels against the wall, and keep their head straight. The clinical measures used most often to monitor body weight include absolute weight change (kilograms, pounds), percent weight change (weight change/baseline weigh t), and ch an ge in BMI (BMI=[weight in kilograms]/[height in meters2] or [weight in pounds]/ [height in inches2]×703). Although all measures are easily obtained and valid in adults, these measures are only useful in pediatric patients who are followed for periods of 3 months or less because they do not take into

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account age-appropriate development. Therefore, BMI values need to be adjusted for age- and sex-dependent growth velocities, using freely available growth charts (http://www.cdc.gov/growthcharts) or calculators (http://www.kidsnutrition.org/bodycomp/ bmiz2.html). The adjusted BMI values are the BMI z-score and the BMI percentile, where a z-score (i.e., standard deviations) of zero and the 50th BMI percentile represent the population mean, and where continuation on the same BMI z-score or percentile over time indicates stable age- and sex-adjusted body weight in relationship to height. Because BMI z-scores are not “capped” at the zero or 99th percentile, z-scores are preferably used to track weight change. BMI percentiles, on the other hand, are useful to determine the weight category that a pediatric patients belongs to, where a BMI percentile of <5 is underweight, 5–84.9 is healthy weight, 85–94.9 is overweight, and ≥95 is obese (see Table 13–2). Although waist circumference is preferred over BMI in adults as a metabolic syndrome criterion and is highly predictive of metabolic syndrome (Straker et al. 2005), the American Medical Association Expert Committee did not recommend waist circumference measures in pediatric patients because cutoffs are less well established and assessments are liable to measurement error (Correll 2008c). Despite the importance of age-inappropriate weight gain in pediatric patients, no consensus exists in the general pediatric literature regarding the cutoff for clinically meaningful weight change during development. Rather, a BMI in the 85th percentile is the accepted lower intervention threshold in youths (American Medical Association 2007) (see Table 13–2). However, in psychiatric care, where the underlying disorder together with adverse treatment effects can lead to rapid and often significant weight gain, clinicians require guidance at what point to consider changing therapy or using adjunctive treatments to address clinically relevant weight gain. In patients with psychiatric illness, clinically “significant” weight gain or abnormal weight status that requires a reconsideration of the current treatment plan has recently been operationalized as 1) >5% weight gain during 3 months, or any of the following three conditions at any time during treatment: 2) an increase ≥ 0.5 in BMI z-score; 3) BMI percentile ≥85–94.9 plus one adverse health consequence (hyperglycemia, dyslipidemia, hyperinsulinemia, hypertension, orthopedic, gall bladder, or sleep disorder); or 4) BMI ≥ 95th percentile or abdominal obesity (> 90th percentile) (Correll et al. 2006).

Fasting Blood Glucose and Lipids Although no generally accepted pediatric guidelines regarding fasting glucose and lipid monitoring have been published, one proposed schedule requires monitoring at baseline, after 3 months of treatment,

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TABLE 13–1. Suggested monitoring strategies in children and adolescents treated with antipsychotic agents a

Assessment

✓

✓

✓

✓

✓

During titration and at target dosage

At 3 months

Every 3 months

✓

✓

✓

✓

✓

✓

✓

✓

Every 6 months

Annually

✓ ✓ ✓

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Lifestyle behaviorsb Height, weight (calculate BMI percentile, BMI z-score) Sexual/ reproductive dysfunction Fasting glucose and lipids Blood pressure and pulse Personal and family medical historyc

Baseline

Each visit

TABLE 13–1. Suggested monitoring strategies in children and adolescents treated with antipsychotic agents a (continued)

Electrolytes, full blood count, renal function Electrocardiogram

Prolactin d

Baseline

During titration and at target dosage

At 3 months

Every 3 months

Every 6 months

✓

If on ziprasidone or clozapine Only if symptomatic

Annually If symptomatic, mandatory CBC for clozapine

If on ziprasidone or if symptomatic on clozapine Only if Only if symptomatic symptomatic

Only if symptomatic

Only if symptomatic

Only if symptomatic

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Note. BMI=body mass index; CBC = complete blood cell count. a More frequent assessments of abnormalities occur if patient is at very high risk for specific adverse events by personal or family history. b Lifestyle behaviors include diet, exercise, smoking, substance use, and sleep hygiene. c Medical history includes components of the metabolic syndrome (obesity, arterial hypertension, diabetes, dyslipidemia); past medical history for coronary heart disease or coronary heart disease equivalent disorders (i.e., diabetes mellitus, peripheral arterial disease, abdominal aortic aneurysm, and symptomatic carotid artery disease); history of premature coronary heart disease in first-degree relatives (males <55 years and females <65 years); and past efficacy and adverse effect experiences in patients and/or family members. d In case of abnormal sexual symptoms or signs, prolactin is drawn fasting in the A.M. and approximately 12 hours after the last antipsychotic dose.

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Assessment

Each visit

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TABLE 13–2.

Clinically relevant thresholds for body weight and metabolic parameters in children and adolescents

Variables

Children and adolescents

Body weight category Underweight

*BMI<5th percentile for sex and agea

Normal weight

*BMI 5th–<85th percentile for sex and agea

Overweight (previously “at risk for overweight” in pediatric patients)

*BMI 85th–<95th percentile for sex and agea

Obese (previously “overweight” in pediatric patients)

*BMI ≥95th percentile for sex and agea

Blood lipid abnormalities Total cholesterol

*≥170 mg/dL

LDL cholesterol

*≥130 mg/dL

HDL cholesterol

*<40 mg/dL in males and females

Triglycerides

*≥110 mg/dL

Blood glucose abnormalities Fasting hyperglycemia (“prediabetes”)

100–125 mg/dL

2-hour oral glucose tolerance test result

140–199 mg/dL

Fasting diabetes (needs to be repeated)

≥126 mg/dL

2-hour post–glucose load diabetes

≥200 mg/dL

Insulin abnormalities and insulin resistance Fasting hyperinsulinemia

*>20 μmol/L

Homeostatic model assessmentb

*≥4.4

Triglycerides:HDL cholesterol ratio *? >3.5

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TABLE 13–2.

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Clinically relevant thresholds for body weight and metabolic parameters in children and adolescents (continued)

Variables

Children and adolescents

Metabolic syndrome

≥ three out of five criteria required

Abdominal obesity criterion

*Waist circumference ≥90th percentile, or BMI ≥95th percentile for sex and agec

Fasting triglycerides criterion

*≥110 mg/dL

Fasting HDL cholesterol criterion

*<40 mg/dL in males and females

Blood pressure criterion

*≥90th percentile for sex and aged

Fasting glucose criterion

≥110 mg/dL

Adjusted fasting glucose criterion ≥100 mg/dL Note. BMI=body mass index; HDL =high-density lipoprotein; LDL =lowdensity lipoprotein. *Thresholds specific for children and adolescents. a

BMI=[weight in kilograms]/[height in meters2] or [weight in pounds]/ [height in inches]×703. Sex- and age-adjusted BMIs are expressed in percentiles (population norm: 50th BMI percentile). Alternatively, they can be expressed as BMI z-scores (population norm: 0 BMI z-score). Growth charts are available at http://www.cdc.gov/growthcharts, and Web-based calculators are available at http://www.kidsnutrition.org/bodycomp/bmiz2.html. Stable age- and sex-adjusted weight is indicated by absence of any change in BMI percentile z-score over time. Homeostatic model assessment (HOMA) = fasting insulin (μmol/L)× glucose (mmol/L)/22.5, where glucose mmol/L= glucose m/dL/17.979797, or fasting insulin (mg/dL)×glucose (mg/dL)/405.

b

c

Sex- and age-adjusted waist circumference percentile tables (Fernandez et al. 2004).

d

Sex- and age-adjusted blood pressure percentiles tables (“Fourth Report on the Diagnosis, Evaluation, and Treatment of High Blood Pressure in Children and Adolescents” 2004).

Correll and Carlson’s (2006) recommendations to patients

American Medical Association’s (2007) stage I recommendations for clinicians

Pediatric patients <18 years receiving General pediatric population ages 2–19 years; prevention psychotropic medications associated with and intervention for individuals who are overweight weight gain (≥85th BMI percentile) or obese (≥90th BMI percentile) Parenting style Encourage child to self-regulate meals; encourage authoritative parenting stylea that supports increased physical activity and reduced sedentary behavior, and provides tangible and motivational support; discourage overly restrictive parenting styleb Family involvement Yes Yes

Meal frequency

Breakfast

Replace sugar-containing drinks, including Suggest curtailing sugar-sweetened beverages; assess for “diet” drinks, with water or moderate excessive consumption of 100% fruit juice amounts of unsweetened tea or milk Eat 4 to <6 separate meals per day, with no Assess for meal frequency (including quality) more than 2 meals in the evening or at night Avoid skipping breakfast Encourage daily breakfast

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General Target group

Diet Sugar-containing beverages

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TABLE 13–3. Healthy lifestyle recommendations to treat age-inappropriate weight gain and weight status in children and adolescents with psychiatric disorders and those who are overweight and obese in the general population

TABLE 13–3. Healthy lifestyle recommendations to treat age-inappropriate weight gain and weight status in children and adolescents with psychiatric disorders and those who are overweight and obese in the general population (continued)

Fat content

Fiber content Snacks

Outside meals/fast food

American Medical Association’s (2007) stage I recommendations for clinicians

Have small meal portions Eat slowly and take second helpings only after a delay Preferentially eat food with a low glycemic index (i.e., of 55 or less— http://www.glycemicindex.com) Reduce saturated fat intake, but avoid extensive consumption of processed fatfree food items Eat at least 25–30 g of soluble fiber per day

Assess for consumption of excessive portion sizes for age

Avoid snacking in a satiety state; replace high-fat, high-calorie snacks with fruits and vegetables Limit fast food to no more than once per week

Assess for excessive consumption of foods that are high in energy density Recommend diet with balanced macronutrients (calories from fat, carbohydrate, and protein in proportions for age, as recommended by Dietary Reference Intakes) Promote diet high in fiber, with five or more servings of fruits and vegetables per day Assess for snacking patterns (including quality); limit consumption of energy-dense foods Suggest limiting meals outside the home, especially in fast-food restaurants; encourage family meals at least 5–6 times/week

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Meal portions Pacing of food consumption Sugar content

Correll and Carlson’s (2006) recommendations to patients

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Correll and Carlson’s (2006) recommendations to patients

Exercise

American Medical Association’s (2007) stage I recommendations for clinicians

Limit sedentary behaviors, such as Recommend limiting screen time to 2 or fewer hours per watching TV or playing computer/video day, and not having a television in the room where the games to less than 2 hours per day child sleeps Perform moderate level physical activity Encourage 1 hour or more of daily physical activity for at least 30–60 minutes/day

Note. BMI=body mass index. a Authoritative parents are demanding and responsive. “They monitor and impart clear standards for their children’s conduct. They are assertive, but not intrusive and restrictive. Their disciplinary methods are supportive, rather than punitive. They want their children to be assertive as well as socially responsible, and self-regulated as well as cooperative” (Baumrind 1991, p. 62, as cited in American Medical Association 2007). b Restrictive parents heavily monitor and control a child’s behavior (American Medical Association 2007).

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Exercise Sedentary behavior

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TABLE 13–3. Healthy lifestyle recommendations to treat age-inappropriate weight gain and weight status in children and adolescents with psychiatric disorders and those who are overweight and obese in the general population (continued)

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and then every 6 months (Correll 2008a). Glucose and lipid measurements have been recommended more frequently in children and adolescents than in adults because of the relatively greater proclivity of pediatric patients to gain weight when taking antipsychotics and also because of early indications of a risk, at least, for lipid abnormalities (Correll et al. 2006; Fraguas et al. 2008; Kryzhanovskaya et al. 2005; Laita et al. 2007; Tohen et al. 2007). Importantly, similar to the adjustment of weight and BMI assessment for normal growth, developmentally appropriate thresholds also need to be used for identifying metabolic abnormalities in pediatric patients. Although fasting glucose thresholds for prediabetes (100–125 mg/dL) and diabetes (≥ 126 mg/dL) are similar for pediatric and adult patients, lipid thresholds differ (Correll 2008a) (see Table 13–2). Abnormally high fasting total cholesterol levels and triglyceride levels in youths are 170 mg/dL and 110 mg/dL, respectively, instead of 200 mg/dL and 150 mg/dL in adults. Furthermore, because children and adolescents generally have sufficient pancreatic beta cell reserve, hyperglycemia is an unlikely and rather late adverse event, and it is preceded by insulin resistance, signified by insulin levels that are sufficiently increased to keep the fasting glucose levels within the normal range. Although not used routinely, a relatively easy way to measure insulin resistance is the homeostatic model assessment (HOMA) method: fasting insulin (μmol/L)×glucose (mmol/L)/22.5, where glucose mmol/L = glucose mg/dL/17.979797. Based on the U.S. pediatric general population, HOMA values >4.39 have been defined as being indicative of insulin resistance in adolescents (Lee et al. 2006). Although not validated in youths, a cheaper and simpler alternative would be to use a lipid-based measure of insulin resistance (McLaughlin et al. 2005). This proxy measure consists of the ratio of fasting triglycerides divided by HDL cholesterol, whereby increased values over time indicate decreased insulin sensitivity, with a threshold of >3.5 possibly indicating insulin resistance.

Blood Pressure Blood pressure should be measured with a large enough cuff in pediatric patients that 80% of the upper arm is covered by the cuff bladder. To determine whether a patient has arterial hypertension (i.e., ≥90th percentile for sex and age; see Table 13–2), the patient’s height percentile needs to be calculated (e.g., https://www.nutropin.com/patient/ 3_5_3_growth_charts.jsp) and the measured blood pressure compared with population norms from children of the same age, sex, and height (“The Fourth Report on the Diagnosis, Evaluation, and Treatment of High Blood Pressure in Children and Adolescents” 2004).

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Sexual and Prolactin-Related Side Effects If a patient develops hyperprolactinemia, other reasons than antipsychotic effects need to be ruled out first. These include hormonal contraception or pregnancy, hypothyroidism, and renal failure, all of which can be assessed by taking a detailed history and measuring serum human chorionic gonadotropin, thyroid-stimulating hormone, and/or creatinine, where appropriate. To identify hyperprolactinemia-related hypogonadism, clinicians should inquire at baseline, during drug titration, and quarterly about menstruation patterns, nipple discharge, breast enlargement or pain, sexual functioning, and (if appropriate) pubertal development. Currently, because the extent of physiological effects of subclinical prolactin elevations have not been established in adult or pediatric patients, prolactin measurements are generally recommended only if clinical symptoms or signs are present. Because prolactin undergoes diurnal variations and increases with food intake, exercise, and stress, prolactin should be measured in the morning, after fasting, and 8–12 hours after the last medication dose. Prolactin thresholds are usually laboratory dependent and higher for postpubertal than prepubertal individuals and in females (upper level ∼20–30 ng/ml) than males (upper level: ∼11–15 ng/ml or 0+age).

Management of Antipsychotic-Related Adverse Effects With Adverse Health Outcomes Weight and Metabolic Dysfunction Healthy lifestyle and medical health strategies for pediatric patients treated with antipsychotics were recently summarized (Correll 2007a). Three levels of strategies are included. Primary preventive strategies include 1) educating about and maximizing adherence to healthy lifestyle behaviors (see Table 13–3) and 2) choosing a medication with the lowest likelihood of adverse effects on body weight and metabolic health. Secondary preventive strategies in overweight patients and those with mild baseline metabolic abnormalities, significant weight gain, or beginning metabolic abnormalities (see Table 13–3) during antipsychotic therapy include 1) intensification of healthy lifestyle instructions; 2) consideration of switching to a lower-risk agent; and 3) a nonpharmacological weight loss treatment or adjunctive pharmacological interventions that target normalization or

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reversal of weight abnormalities. Tertiary preventive strategies in patients who are obese or have clinically defined related abnormalities (i.e., hyperglycemia, diabetes, dyslipidemia, or hypertension; see Table 13–3) require intensified weight reduction interventions; attempts at switching to or initiating lower-risk medications for the underlying psychiatric condition; and targeted treatments of these suprathreshold metabolic or endocrine abnormalities, often in conjunction with a subspecialist. The first line of treatment for abnormalities in body weight or metabolic health includes nonpharmacological lifestyle education and modification strategies. (See Chapter 8, “Behavioral Treatments for Weight Management of Patients With Schizophrenia,” for an extensive review of behavioral means to control weight gain.) Although such strategies and programs have been tested and shown to be successful to a certain degree in adults (Faulkner et al. 2007), the effects of healthy lifestyle programs in antipsychotic-treated youths have not been reported. The recent American Medical Association (2007) Stage 1 recommendations for healthy lifestyle behaviors in pediatric patients are summarized in Table 13–3. After 3–6 months of treatment, if no improvement has occurred in a patient’s unhealthy BMI and weight, and if the patient and/or family indicate readiness to change, progression to the Stage 2 structured weight management protocol is indicated. Stage 2 interventions can be implemented by a primary care physician or allied health care provider highly trained in weight management and include the following: 1) dietary and physical activity behaviors—that is, a) plan development for utilization of a balanced macronutrient diet emphasizing low amounts of energy-dense foods, b) increased structured daily meals and snacks, c) supervised active play of ≥60 minutes/day, and d) screen time of ≤1 hour/day; 2) increased monitoring (e.g., dietary intake, restaurant logs, screen time, physical activity) by provider, patient, and/or family; and 3) goal setting of weight maintenance that results in a decreasing BMI as age and height increase. If no improvement in BMI and weight occurs after 3–6 months, the patient should be advanced to Stage 3, consisting of a comprehensive multidisciplinary protocol (American Medical Association 2007). At this stage, the patient should be referred to a multidisciplinary obesity care team. The eating and activity goals are the same as in Stage 2. Additional activities should include 1) a structured behavioral modification program, including food and activity monitoring, as well as development of short-term diet and physical activity goals, and 2) involvement of primary caregivers in behavioral modification for children under age 12 years and training of primary caregivers for all children. The goal at this stage should be weight maintenance or gradual weight loss until the patient’s BMI is lower than the 85th percentile.

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If staged behavioral measures alone provide insufficient results, pharmacological weight loss interventions may be added. Data in obese youths without a primary psychiatric illness support the use of sibutramine (serotonin-norepinephrine reuptake inhibitor), orlistat (enteric lipase inhibitor that blocks absorption of about 30% of dietary fat), and metformin (insulin sensitizer) (Correll 2008c). Sibutramine (e.g., 5–15 mg/day) and orlistat (e.g., 120 mg three times daily) are FDA approved for weight loss in adolescents. Sibutramine, which is approved only for patients ages 16 years and older, may increase blood pressure and should not be given together with other serotonin-enhancing drugs (i.e., antidepressants, stimulants, or lithium) to avoid serotonin syndrome. Therapies that have had some reported success in leading to weight loss in pediatric patients receiving antipsychotics include metformin (e.g., 250 mg/day three times daily if patient’s weight is <50 kg, or 500 mg/day three times daily to 1,000 mg/day twice daily if patient’s weight is ≥50 kg titrated up over 3–4 weeks), topiramate (e.g., 25–400 mg/day), amantadine (e.g., 100 mg twice daily), and orlistat (Correll 2008c). Dyslipidemia should also be treated initially with diet and exercise. If these changes are not sufficient, drug therapy may be given, as in adults, with a fibric acid derivative (e.g., gemfibrozil, fenofibrate), a statin, fish oil, or niacin, if appropriate. Diabetes may be treated with diet, oral hypoglycemic agents, or insulin, as needed, but diabetes induced by atypical antipsychotic agents sometimes disappears when the drug is stopped or changed to a lower-risk agent (Correll and Carlson 2006). Whereas treatment for age-inappropriate weight gain may be managed by the primary psychiatric care provider, treatments for dyslipidemia and hyperglycemia most likely will be initiated by a pediatrician or pediatric endocrinologist.

Hyperprolactinemia and Related Abnormalities If the patient’s serum prolactin is <200 ng/mL, the clinician can attempt reducing the dosage of the antipsychotic or changing the prescription to a prolactin-sparing drug, such as aripiprazole, quetiapine, or, in treatmentresistant patients, clozapine (Correll and Carlson 2006). If serum prolactin is >200 ng/mL or is persistently elevated despite a switch to a prolactinsparing drug, a magnetic resonance imaging (MRI) scan of the sella turcica should be obtained to rule out presence of a pituitary adenoma or parasellar tumor. If the MRI scan is normal, sex steroids (e.g., oral contraceptives for women of menstrual age, testosterone for men) can be replaced to treat the hypogonadism, or drugs such as bisphosphonates (e.g., alendronate, risedronate) can be given to prevent or treat osteoporosis. Prolactin levels can also be lowered by adding a dopamine agonist (e.g., amantadine,

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bromocriptine), or by adding a partial dopamine agonist (e.g., aripiprazole 5–15 mg/day), which has been shown to be effective in adults (Shim et al. 2007). The use of ergot derivatives (e.g., cabergoline) is not recommended due to known risks for valvular heart disease from these agents.

QTc Abnormalities Although a very uncommon complication of antipsychotic treatment, any QTc value of ≥500 milliseconds, confirmed by manual reading, should prompt a discontinuation of the antipsychotic, unless hypomagnesemia or hypokalemia is present that can be corrected or unless other QT-prolonging agents can be discontinued successfully. (See Chapter 7, “The Spectrum of Cardiovascular Disease in Patients With Schizophrenia,” for monitoring recommendations.)

Conclusion Although more data are needed, children and adolescents exposed to antipsychotics appear to be vulnerable to developing hyperprolactinemia and age-inappropriate weight gain, with the related potential for metabolic dysfunction, at least for lipid abnormalities. Determining whether the risk for diabetes in youths is lower than in adults or is simply delayed requires long-term follow-up studies, but data in the general population suggest the latter. Because of the relevant adverse effects of antipsychotics in youths, proactive and routine monitoring of antipsychotic efficacy and risks, as well as timely management of clinically relevant adverse effects with negative impact on health and adherence, should be part of general clinical practice. Clinicians should ideally make measurement-based and shared treatment decisions. They should use age-appropriate sideeffect measures and thresholds and define abnormal values depending on the patient’s developmental status. In addition, safety and efficacy data should inform a carefully weighed antipsychotic selection that takes into account the illness severity, current and past response patterns, side-effect probabilities and occurrences, and each patient’s and family’s preferences. Finally, because adverse effects are generally more readily predicted than therapeutic efficacy, and because antipsychotics’ differences in efficacy are generally smaller than their differences in adverse effects, treatment decisions may need to be guided to a relevant degree by the individual and varying adverse effect profiles across antipsychotic agents.

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Key Clinical Points ◗

Children and adolescents appear to be particularly susceptible to developing prolactin elevation, antipsychotic-induced age-inappropriate weight gain, and, to some degree, lipid abnormalities.

◗

Ranking order of antipsychotic adverse effects on body weight and metabolic health is similar in children and adolescents compared with adults, with a potentially greater effect of risperidone, possibly a lesser effect of clozapine, and greater weight gain liability with medications that are generally considered weight neutral in adults.

◗

Although diabetes and metabolic syndrome have not been researched sufficiently in pediatric patients exposed to antipsychotics, the onset of these longer-term adverse effects may generally be delayed in youths, who more often than adults have less lifetime antipsychotic exposure and who have greater pancreatic beta cell reserve.

◗

Sustained, age-inappropriate weight gain is of great concern due to the known relationship between obesity in childhood and adverse cardiac outcomes in adults in the general population.

◗

Patients and families should be counseled about the probability of specific adverse effects, which should inform the most appropriate medication choice to concurrently achieve sustained symptom benefits, adherence, and physical health.

◗

Education about and proactive assessment of antipsychotic adverse effects on the health status in youths should be routine clinical practice of mental health practitioners prescribing antipsychotics.

◗

Safety assessments must utilize developmentally adjusted measures and thresholds for growing children and adolescents.

◗

Although adverse effects need to be balanced against efficacy gains, clinicians should be prepared to change antipsychotic treatment or initiate interventions to reduce bothersome as well as physically problematic adverse effects to improve overall outcomes.

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McDougle CJ, Kem DL, Posey DJ: Case series: use of ziprasidone for maladaptive symptoms in youths with autism. J Am Acad Child Adolesc Psychiatry 41:921–927, 2002 McLaughlin T, Reaven G, Abbasi F, et al: Is there a simple way to identify insulin resistant individuals at increased risk of cardiovascular disease? Am J Cardiol 96:399–404, 2005 Must A, Jacques PF, Dallal GE, et al: Long-term morbidity and mortality of overweight adolescents: a follow-up of the Harvard Growth Study of 1922 to 1935. N Engl J Med 327:1350–1355, 1992 Olfson M, Blanco C, Liu L, et al: National trends in the outpatient treatment of children and adolescents with antipsychotic drugs. Arch Gen Psychiatry 63:679–685, 2006 Patel NC, Hariparsad M, Matias-Akthar M, et al: Body mass indexes and lipid profiles in hospitalized children and adolescents exposed to atypical antipsychotics. J Child Adolesc Psychopharmacol 17:303–311, 2007 Paxton JW, Dragunow M: Pharmacology, in Practitioner’s Guide to Psychoactive Drugs for Children and Adolescents. Edited by Werry JS, Aman MG. New York, Plenum Medical, 1993, pp 23–55 Pool D, Bloom W, Mielke DH, et al: A controlled evaluation of Loxitane in seventy-five adolescent schizophrenic patients. Curr Ther Res Clin Exp 19:99– 104, 1976 Ratzoni G, Gothelf D, Brand-Gothelf A, et al: Weight gain associated with olanzapine and risperidone in adolescent patients: a comparative prospective study. J Am Acad Child Adolesc Psychiatry 41:337–343, 2002 Realmuto GM, Erickson WD, Yellin AM, et al: Clinical comparison of thiothixene and thioridazine in schizophrenic adolescents. Am J Psychiatry 141:440–442, 1984 Robb AJ, Findling RL, Nyilas M, et al: Efficacy of aripiprazole in the treatment of adolescents with schizophrenia. Poster presented at the annual meeting of the American Psychiatric Association, San Diego, CA, May 2007 Safer DJ: A comparison of risperidone-induced weight gain across the age span. J Clin Psychopharmacol 24:429–436, 2004 Saito E, Correll CU, Gallelli K, et al: A prospective study of hyperprolactinemia in children and adolescents treated with atypical antipsychotic agents. J Child Adolesc Psychopharmacol 14:350–358, 2004 Sallee FR, Kurlan R, Goetz CG, et al: Ziprasidone treatment of children and adolescents with Tourette’s syndrome: a pilot study. J Am Acad Child Adolesc Psychiatry 39:292–299, 2000 Shaw P, Sporn A, Gogtay N, et al: Childhood-onset schizophrenia: a doubleblind, randomized clozapine-olanzapine comparison. Arch Gen Psychiatry 63:721–730, 2006 Shim JC, Shin JG, Kelly DL, et al: Adjunctive treatment with a dopamine partial agonist, aripiprazole, for antipsychotic-induced hyperprolactinemia: a placebo-controlled trial. Am J Psychiatry 164:1404–1410, 2007

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CHAPTER 14 Medical Health in Aging Persons With Schizophrenia Samantha Brenner, M.P.H. Carl I. Cohen, M.D.

A potential health crisis is emerging in mental health care. Approximately 1% of the population ages 55 and older—more than onehalf million persons—has schizophrenia (Cohen et al. 2008). Over the next two decades, this number will double as postwar baby boomers reach old age. Moreover, these individuals will be at increased risk for physical illness as they age. More than four-fifths of the general older population have one or more chronic medical conditions (Kovar 2001), and these disease combinations can act synergistically to produce much higher levels of functional disability than associated with either disease alone (Verbrugge et al. 1991). Thus, physical diseases co-occurring with schizophrenia may have greater impact on adaptive functioning than they might in persons without mental disease. Unlike the previous generations of older persons with schizophrenia who spent much of their

This work was supported in part by grant S06 GM74923 from the National Institute of General Medical Sciences.

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later years in mental institutions, approximately 85% of older persons with schizophrenia now live in the community, in settings other than nursing homes or hospitals (McAlpine 2003). A critical issue for the new generation of older persons with schizophrenia is whether they will be able to negotiate a health and social service system that may be ill prepared to deal with them. The aim of this chapter is to provide an overview of medical health issues of the aging schizophrenia population. In so doing, we focus first on the epidemiology of physical disorders, both general physical health and specific medical disorders, then examine treatment issues, including medication-related issues, barriers to health care, and concerns about competency.

Background Only 1% of the literature on schizophrenia has been devoted to issues of aging (Cohen et al. 2008), and few papers have specifically addressed issues of health among aging individuals with schizophrenia. Research in this area has been limited by the fact that the majority of schizophrenia studies cover a wide age range, with the predominant focus on younger patients. Comparisons between studies are also hampered by the differences in types of patients (inpatients, outpatients, Veterans Affairs [VA] hospital patients), use of disease prevalence versus incidence in populations, and diverse geographical locations for the study populations. Despite these limitations, we have tried in this chapter, wherever possible, to make comparisons between older schizophrenia patients and their age peers in the general population or with other psychiatric populations, and to make comparisons between older and younger patients with schizophrenia. To expand our data sources, we have also extrapolated from studies of schizophrenia patients in general by using mean values and standard deviations and by incorporating any findings in which there was a breakdown by age.

General Physical Health Persons with schizophrenia are generally believed to have worse health than their age-matched peers in the general population, and their conditions often go undiagnosed and untreated (Dixon et al. 1999). For example, increased rates of comorbid physical illness in patients with schizophrenia have been reported to occur primarily in the categories of non-insulin-dependent diabetes mellitus, cardiovascular disease, in-

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fectious diseases, respiratory diseases, some forms of cancer, and a variety of other illnesses (Dixon et al. 1999). Also, persons with schizophrenia may have more severe forms of disorders (Jeste et al. 1996), which may be exacerbated by the side effects of antipsychotic medications (e.g., anticholinergic, cardiovascular, metabolic effects) and by the psychotic illness itself, and significant correlations have been found between positive symptoms and the number of medical conditions (Dixon et al. 1999; Jeste et al. 1996). Moreover, other clinical symptoms commonly found in schizophrenia, such as levels of depression and neurocognitive impairment, also may be associated with increased rates of comorbid medical conditions (Chwastiak et al. 2006a, 2006b). Because older persons with schizophrenia are survivors compared with their younger counterparts, an important consideration is whether the older group has more medical comorbidities than the younger group. In a large study of 8,083 patients using the National Patient Care Database of the Veterans Health Administration, Kilbourne et al. (2005) found that schizophrenia patients ages 60 years and older were indeed more likely to have medical comorbidities compared with younger schizophrenia patients. They also found that older patients were less likely to have substance abuse or hepatic diagnoses. Although those findings may have been expected, they had not been confirmed previously using a large population. Because results of investigations such as the Patient Outcomes Research Team (PORT) study (Dixon et al. 1999) have suggested that the diagnosis of schizophrenia in general confers greater risk for physical illness, one might assume that older persons with schizophrenia would be more medically ill versus age-matched peers. Nevertheless, studies have yet to determine whether aging interacts with schizophrenia such that the older cohort is disproportionately more ill than age peers compared with a younger cohort of patients with schizophrenia. To this end, researchers in San Diego, California (Jeste et al. 1996; Lacro and Jeste 1994), found that middle-aged and older persons with schizophrenia had fewer medical illnesses (mean = 1.0) than persons with Alzheimer’s disease (mean = 1.4) and major depression (mean =2.4), and their severity index on the Cumulative Illness Rating Scale for Geriatrics was comparable to that of an older normal comparison group. Similarly, a study in New York City of 198 patients with schizophrenia ages 55 years and older (mean 61.5 years) and an age-, gender-, and racematched comparison group found no significant differences in the number of physical disorders, 1.3 and 1.1, for the schizophrenia and community groups, respectively (C.I. Cohen, unpublished data). One confounding issue for the San Diego investigations was that the normal

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comparison group was 12 years older; however, in the New York City study, the comparison group was only 1.5 years older. Interestingly, the San Diego study found a significant correlation between physical symptom severity and positive symptoms of schizophrenia, depression, and overall psychopathology, whereas the New York City study found a correlation only between symptom severity and depressive symptoms, which is consistent with the geriatric literature on depression and health (Diwan et al. 2007). Results from the studies in New York City and San Diego do not suggest that older outpatients with schizophrenia have more physical disorders or that their disorders are necessarily more severe than their age peers from comparable backgrounds, although results of the San Diego studies were more equivocal due to age differences between comparison groups. One possible explanation for these findings is that persons in the schizophrenia samples were all involved to some extent in clinical programs, most of which encouraged or provided physical examinations. Moreover, because psychopathology tends to diminish with age, older persons may be more apt to attend to medical problems and be better received by other health professionals. The San Diego researchers interpreted the significant correlation between positive symptoms and physical health as reflecting the fact that physical symptoms may seem less important or be overlooked in the presence of florid psychosis and, conversely, more apt to be addressed when the patient has fewer schizophrenia symptoms. A “survivor effect” may be another plausible explanation for the lack of differences between the older patients with schizophrenia and community persons. That is, because mortality rates among patients with schizophrenia substantially exceed those of the general population throughout their lifetime, those with schizophrenia who are oldest are presumably the heartiest, both physically and emotionally. For example, with respect to the latter, Rockett et al. (2007) found that the percentage of suicides due to schizophrenia declined in patients ages 65 and older, whereas suicide rates for other mental illnesses such as depression remained constant.

Specific Medical Disorders Diabetes The association between diabetes and schizophrenia is discussed at length in Chapter 5, “Glucose Intolerance and Diabetes in Patients With Schizophrenia.” Nonetheless, it bears noting that although diabetes increases with age and affects about 20% of the geriatric population

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(Marsh 1997), the prevalence rates of diabetes among persons with schizophrenia seem to be consistently higher versus their nonpsychiatric age peers only in the younger and middle-aged groups, whereas differences in the geriatric population may be minimal. Researchers have found that disordered glucose homeostasis is significantly worse in older patients with schizophrenia than in younger persons with schizophrenia (Subramaniam et al. 2003), although similar age differences exist in the general population. When compared with patients with other psychiatric disorders, middle-aged and elderly patients with schizophrenia were found by Jeste et al. (1996) to have no significant difference in prevalence of diabetes. Similar results were found in a study of older patients with schizophrenia in New York City; self-reported rates of diabetes were not significantly greater among schizophrenia patients (25%) than among the comparison community group (19%) (C.I. Cohen, unpublished data). Two studies (Mukherjee 1995) of VA inpatients and outpatients have confirmed the increasing prevalence of diabetes among patients with schizophrenia as they age, with rates of 0% and 1.6% among those under age 40 years, and 25% and 50% in those ages 70 and older, for inpatients and outpatients, respectively. In another study, conducted in Italy, Mukherjee et al. (1996) studied a sample of 95 patients with schizophrenia and found that the prevalence of diabetes increased from 0% in those younger than age 50 years, to 12.9% in those ages 50–59 years, 18.9% in those ages 60–69 years, and 16.7% in those ages 70–74 years. Although antipsychotic medication, particularly the atypical agents olanzapine and clozapine, may have an impact on glucose tolerance, the PORT study concluded that people with schizophrenia had a greater risk of developing diabetes than the general population even before the widespread use of the newer agents (Dixon et al. 2000). Similarly, Murkherjee et al. (1996) observed, “It bears emphasizing that high rates of insulin resistance and impaired glucose tolerance had been noted in schizophrenia patients before the introduction of neuroleptics” (p. 71). Several recent studies, some of which provide strong evidence because they are longitudinal, have found that the use of atypical antipsychotics is the principal cause of the rise in the prevalence of diabetes in persons with schizophrenia, although the evidence is less convincing among older adults. From 1988 to 2002, after the introduction of atypical antipsychotics to the U.S. market, a net increase occurred in the prevalence of obesity and diabetes mellitus among inpatients with schizophrenia of all ages (Reist et al. 2007). Likewise, a study conducted from 1979 to 2001 found that trends in diabetes mellitus prevalence

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were comparable among inpatients with schizophrenia and inpatients without mental illness during the years before the introduction of atypical antipsychotics, whereas from 1996 to 2001, the net difference in the prevalence of diabetes between inpatients with schizophrenia and inpatients without mental illness grew at an increasing rate of 0.7% per year (Basu and Meltzer 2006). Studying a large group of VA outpatients with schizophrenia, Sernyak et al. (2002) found that when effects of age were controlled, patients who received atypical neuroleptics were 9% more likely to have diabetes than patients who received typical antipsychotic medications. By contrast, Barak and Aizenberg (2003) found that in a small sample of older patients (mean age 72 years), the association between atypical antipsychotics and lipid abnormalities did not hold true. With respect to treatment, the PORT study, based on data from 719 schizophrenia outpatients (mean age 43 and approximately 17% above age 55), found that 86% of patients with schizophrenia who reported having diabetes mellitus said they were receiving treatment for it (Dixon et al. 1999). This is consistent with data from the study of older patients with schizophrenia in New York City, which was cited earlier, in which 86% of persons with diabetes reported receiving treatment (Vahia et al. 2008). However, although treatment rates may not differ with respect to diabetes, outcomes may differ. For example, Weiss et al. (2006) found that older diabetic patients with schizophrenia did not differ significantly from diabetic controls in the appropriateness of their treatment regimens; however, there was a significant difference in the clinical quality benchmarks for cholesterol and low-density lipoprotein levels in the schizophrenia group. As such, persons with schizophrenia were more likely to have prescriptions for the older lipid-lowering agents, as well as a higher rate of missed appointments. In a study of middle-aged and elderly VA outpatients with schizophrenia, Dolder et al. (2003) found that the 12-month mean compliant fill rates for antipsychotic, antihypertensive, dyslipidemic, and glucose control medications ranged from 52% to 64%, regardless of whether patients were on atypical or typical antipsychotics. On the positive side, a recent study of a broad age range of patients in the VA health care system found that both quality of care and intermediate diabetic health outcomes were the same for age-matched diabetic patients with and without serious mental illness, suggesting that comparable care and access are achievable for patients in the VA system (Krein et al. 2006). However, outside of the VA system, researchers have questioned the ability of health care workers to successfully communicate appropriate diabetic care to elderly patients with schizophrenia. In a

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small study with 100 patients, Dickerson et al. (2005) found that patients with schizophrenia scored significantly lower on a standardized diabetes knowledge test than did psychiatrically healthy diabetic controls.

Cardiovascular Disease Cardiovascular diseases are among the most common disorders found among persons with schizophrenia. They are reported to occur more frequently and to be responsible for increasing mortality rates among individuals with schizophrenia than among those in the general population (Dixon et al. 1999; Fors et al. 2007; Goff et al. 2005; Ösby et al. 2000; Tsuang et al. 1983). Mortality from increased cardiovascular morbidity is most likely a result of increased rates of smoking, obesity, diabetes, and hypertriglyceridemia in the population with schizophrenia, whereas the relationship of mortality to antipsychotic drug usage is less clear (Enger et al. 2004; Goff 2005; Jerrell and McIntyre 2007; Seeman 2007). Some controversy is apparent in the literature as to the effect of antipsychotic usage on cardiovascular disease. Straus et al. (2004) found that current use of antipsychotic medications, even in low dosages, is associated with an increased risk of sudden cardiac death. The Oxford Record Linkage Study, using data derived from hospital activity analyses and mental health inquiry systems, amassed information on 2,314 persons with schizophrenia across all age groups, of whom one-third were ages 55 and older. The authors found that this patient cohort had a significant increase in relative risk for atherosclerotic heart disease, but not for other forms of cardiac, hypertensive, or circulatory diseases (Baldwin 1979). More recent data from a study with 240 subjects (mean age 42± 11.5 years) showed that compared with U.S. adult population rates, male patients with schizophrenia had a greater 10-year risk of myocardial infarction, whereas female patients with schizophrenia did not show increased risk (Cohn et al. 2004). Similarly, Enger et al. (2004) found that those schizophrenia patients being treated with typical antipsychotics (mean age 38 ±14 years) had a fivefold increased risk of myocardial infarction compared with psychiatrically healthy controls. However, cardiovascular mortality risk was inversely associated with “intensity” of use of antipsychotic drugs (i.e., proportion of follow-up days taking medication), suggesting that the observed risks may not be due to a simple or direct effect of drugs. The limited data on older samples have tended in some instances to contravene the findings for schizophrenia in general. Sajatovic et al. (1996) studied 49 patients with schizophrenia (96% male) ranging in age from 65 to 85 years (mean age 72 years), at the Cleveland Veterans Affairs Medical Center. The authors reported that the most frequent rea-

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sons for medical hospitalization of the patients with schizophrenia were cardiovascular or pulmonary disease, but they did not provide a comparison with nonpsychiatric patients. Sheline (1990) reported that cardiovascular disease was the most prevalent physical illness seen in geriatric psychiatric inpatients (age range 60–85 years). Although persons with schizophrenia accounted for 20% of the study population, the authors did not report medical diagnoses specific to the individuals with schizophrenia. In a study by Lacro and Jeste (1994), elderly patients with schizophrenia had the lowest prevalence of hypertension, coronary artery disease, and congestive heart failure when compared with other elderly psychiatric patients. Finally, in the New York City study of older outpatients with schizophrenia cited previously, no significant differences were apparent between the schizophrenia group and the community comparison group on self-reported rates of heart disease (22% vs. 14%) and hypertension (38% vs. 38%) (C.I. Cohen, unpublished data). Results from several recent studies suggest that older adults with schizophrenia and comorbid cardiovascular disease are receiving suboptimal care. For example, Piette et al. (2007) found that schizophrenia patients with both diabetes and cardiovascular disease were selective about their medication adherence, favoring antipsychotic medications over medications for their comorbid conditions. Moreover, in studies in which older patients with both schizophrenia and hypertension had similar levels of antihypertensive medication adherence versus their age peers, persons with schizophrenia were still significantly less likely to have their blood pressure controlled, have their lipids assessed regularly, or have their body weight monitored (Dolder et al. 2005; Hippisley-Cox et al. 2007a; Paton et al. 2004). Druss et al. (2000) found that after an acute myocardial infarction, patients with schizophrenia were 59% less likely to undergo cardiac catheterization than were those individuals without mental disorders. These researchers also found a 19% increase in 1-year mortality risk among persons with schizophrenia that disappeared after adjusting for five quality measures, which included the timely prescription of betablockers, angiotensin-converting enzyme inhibitors, and smoking cessation counseling. Their findings, corroborated by further research (Druss et al. 2001), lend support to the notion that much of the mortality difference seen between patients with schizophrenia and their age peers is a direct result of deficits in the quality of the medical care received.

Respiratory Disorders Until 50 years ago, respiratory diseases such as pneumonia and tuberculosis accounted for much of the excessive mortality rates among in-

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stitutionalized patients with schizophrenia (Alstrom 1942; Baldwin 1979; Odegard 1951). These findings were not specific to patients with schizophrenia, but rather were observed in institutionalized psychiatric patients as a whole. Recent studies continue to point to disproportionately higher rates of respiratory morbidity and mortality in schizophrenia populations, although the usual proviso about lack of data among older patients with schizophrenia applies for respiratory disorders as well (Joukamaa et al. 2001). In a 10-year study by Sajatovic et al. (1996) of hospital utilization of elderly veterans with bipolar disorder (n = 23) and schizophrenia (n= 49), respiratory disease was found to be one of the most frequent causes of medical hospitalization (18%) (cf. 22% for cardiovascular disease). Hussar (1966) examined the autopsy reports, collected from 29 VA hospitals, of 1,275 white male patients with chronic schizophrenia with a mean age at the time of death of 63 years; they found an increased number of deaths due to pneumonia in comparison to the rate in the age-matched general population. Weiner and Marvit (1977) found increased morbidity from respiratory disease in their middleaged schizophrenia population, whereas Dynes (1969) and Saku et al. (1995) found respiratory disease to be a leading cause of death in their schizophrenia population of all ages. Finally, Daumit et al. (2006) found that versus hospitalized patients without schizophrenia, patients with schizophrenia (mean age 55) had at least twice the adjusted odds ratio for intensive care unit admission and death secondary to respiratory failure or sepsis.

Immune Function Hypotheses about the link between immune dysfunction and schizophrenia date back to the early 20th century, and in the 1960s an autoimmu ne-mediated process was implicated in the etiology of schizophrenia (Rappaport and Delrahim 2001). Paradoxically, studies of specific immunological disorders have generally supported lower prevalence rates among schizophrenia populations. For example, Ehrentheil (1957) and Lipper and Werman (1977) noted a decreased incidence of asthma, hay fever, and other allergic reactions in patients with schizophrenia. Other studies, such as that of Sabbath and Luce (1952), have shown an alternating pattern of coexisting psychosis and allergies. The strongest evidence for a negative association between schizophrenia and a disease exists with rheumatoid arthritis. Nissen and Spencer (1936) may have been the first to point out that rheumatoid

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arthritis and schizophrenia do not appear to exist together. Eaton et al. (1992) reviewed 14 epidemiological studies conducted between 1934 and 1985 and concluded that ample evidence supported the negative association between these two disorders. A more recent study by Gorwood et al. (2004) continued to confirm earlier studies finding a low relative risk between the two disorders. Underdiagnosis also has been proposed as an alternative explanation for the negative association observed between the two disorders (Mors et al. 1999). Although rheumatoid arthritis has been the most widely studied disorder, Juvonen et al. (2007) found a significantly lower incidence rate of schizophrenia in a Finnish cohort of individuals with type 1 diabetes. Several mechanisms have been postulated to explain this phenomenon, including immunological, biochemical, and genetic mechanisms. On the other hand, evidence also indicates that persons with schizophrenia may be more prone to certain infectious agents such as Toxoplasma gondii and are more likely to have increased serointensity (parasitic load found in blood) compared to psychiatrically healthy controls. Given that serointensity was significantly associated with C-reactive protein levels and leukocyte counts, researchers hypothesize that the increased serointensity in persons with schizophrenia is a result of the shifted Thelper cell balance between Th1 and Th2 cell types found in schizophrenia (Hinze-Selch et al. 2007). Moreover, patients with schizophrenia have been found to have down-regulated levels of cytokines in situations where activation of the immune system would be appropriate and beneficial (Na and Kim 2007). Although the exact mechanisms have yet to be determined, both immunoprotective and immunologically harmful immune states have been correlated with schizophrenia. The latter may be especially pernicious in older adults.

Cancer Relative prevalence rates of the different types of cancers vary between the schizophrenia population and the general population. Comparisons across studies are difficult because some studies focus on mortality rates and others focus on disease incidence or prevalence rates. In Israel, the incidence for all cancers over a 10-year period was 42% lower in the schizophrenia population than in age- and gender-matched controls (Barak et al. 2005; Grinshpoon et al. 2005). Some studies indicate that compared with the overall population, the schizophrenia population seems to have a lower rate of lung cancer and higher rates of digestive and breast cancers (Catts et al. 2008; Hippisley-Cox et al. 2007b; Schoos and Cohen 2003). The apparent lower prevalence of lung cancer in patients with schizophrenia is surprising in light of the high number

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of smokers in this population (Jeste et al. 1996). However, a British study of 370 patients with schizophrenia ages 16–66 years (Brown et al. 2000) found mortality rates for lung cancer in patients with schizophrenia to be twice the expected values. Because the majority of these patients were also heavy smokers, cigarette smoking likely accounts for the higher mortality rate. However, in a large study, Hippisley-Cox et al. (2007b) found no differences in lung cancer incidence in patients with schizophrenia versus their age peers; in fact, after controlling for smoking exposure, they noted that the subjects with schizophrenia had lower rates. A meta-analysis by Catts et al. (2008) found that much like decreased respiratory cancer rates in patients with schizophrenia, pooled overall cancer incidence in their siblings and parents is significantly reduced, supporting the hypothesis that schizophrenia may provide a protective effect against certain neoplasms. In Denmark, researchers examined a cohort of 1.3 million women of whom 7,541 had been hospitalized for schizophrenia between 1970 and 1997. Within this group, researchers found that after adjusting for age, menstrual period, age at first birth, and number of births, the prevalence of breast cancer was not different between women with schizophrenia and controls. The authors postulated that previous studies may not have accounted properly for parity and other environmental risk factors for breast cancer (Dalton et al. 2003). However, by contrast, an Israeli group of researchers found, in a cohort of 3,226 persons with schizophrenia, that breast cancer rates were reduced by 10%–63% when compared with those of age-matched controls (Barak et al. 2005). Looking at age-specific trends, Mortensen and Juel (1993) concluded that no significant increase in cancer mortality exists in any age group of patients with schizophrenia, but there is a trend toward decreased cancer mortality in older patients. Based on a schizophrenia study population consisting of 555 females (65% ≥60 years) and 389 males (81% ≥60 years), Malzberg (1950) found increased cancer mortality in young patients but significantly decreased rates in elderly patients, which was further broken down to show lower rates in males than in females. Baldwin (1979) also reported that long-term hospitalized elderly patients with schizophrenia had significant reductions in lung cancer, gastrointestinal cancer, and prostate or bladder cancer. Compared with the general population, mental patients as a whole appear to have excess cancer mortality rates when hospital stays are short but diminished cancer mortality rates when hospital stays are long, especially among those ages 65 and older (Baldwin 1979; Fox and Howell 1974). Although these studies included patients with schizophrenia, they were not specific to schizophrenia. Baldwin (1979) posits two possible explanations for the increased mortality rates

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among short-stay patients, including greater age or reasons for the admission (i.e., selection biases). Lower cancer mortality rates among longer-stay older persons has led some authors to propose that the environment of the hospital, rather than schizophrenia per se, could be a factor in protecting elderly patients from some cancers (Tsuang et al. 1983). Controversial data exist with respect to neuroleptic use and cancer morbidity and mortality. Mortensen (1986) proposed that phenothiazine treatment may be an environmental factor that protects against malignant neoplasia. Studies have shown an association between high-dosage neuroleptics and reduced incidence of bladder and prostate cancer and between nonphenothiazine neuroleptics and a decrease in lung and breast cancer (Mortensen 1989, 1992; Mortensen and Juel 1990). However, Ettigi et al. (1973) observed that breast cancer may be more common with phenothiazine treatment. Goode et al. (1981) suggested that neuroleptics may potentially cause an increased incidence of breast cancer by elevating the prolactin level, although their study in a large psychiatric hospital over a decade noted that breast cancer rates were not higher among these psychiatric patients despite their use of antipsychotic drugs. More recent research on neuroleptic usage from a large study in Denmark indicated that after controlling for a significant number of potential confounders, including age, menstruation, pulmonary disease, liver cirrhosis, alcoholism, chronic nonsteroidal anti-inflammatory drug usage, hormone therapy, age at first birth, and number of children, the use of neuroleptic medications was not related to a reduced risk of cancer, except for suggestive decreases in cancers of the rectum, colon, and prostate (Dalton et al. 2006).

Hyponatremia Older persons in general are at greater risk for developing hyponatremia, with data indicating that older persons with schizophrenia have an even greater susceptibility. Results from studies by de Leon’s group (de Leon 2003; de Leon et al. 1994) indicate that 10% of chronic psychiatric inpatients have hyponatremia, and up to 20% of chronically institutionalized patients with schizophrenia may have polydipsia. Jos et al. (1986) found that polydipsia was seen most frequently in white male inpatients with schizophrenia. The pathophysiology of hyponatremia in patients with schizophrenia is still under investigation in the literature, but studies indicate that 1) persons with schizophrenia may have increased antidiuretic hormone (ADH) release and abnormal osmotic regulation (Kawai et al. 2001); 2) effects of antipsychotic medications on ADH release result in hyponatremia; 3) susceptibility to polydipsia is genetic (Fukunaka et al.

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2007; Meerabux et al. 2005); 4) polydipsic hyponatremic patients with schizophrenia have anterior hippocampal pathology that contributes to their syndrome (Goldman et al. 2007b, 2008); and 5) polydipsic hyponatremic patients with schizophrenia have a differential response to psychological stressors, resulting in prolonged rises in plasma adrenocorticotropin (ACTH) and cortisol levels relative to polydipsic normonatremic patients with schizophrenia, implicating dysregulation in the cortisol-ACTH-hippocampal axis either independent of or secondary to antipsychotic medications (Goldman 2000; Goldman et al. 2007a, 2007b; Madhusoodanan et al. 2002, 2003). In one earlier study, 70% of hyponatremic patients with schizophrenia were taking anticholinergic drugs versus 8% of the normonatremic patients with schizophrenia, leading to a conclusion that dry mucous membranes induced thirst and increased water consumption (Gleadhill et al. 1982). However, recent studies in which patients were taking both different classes and dosages of antipsychotic medications demonstrated that antipsychotic medication was not correlated with serum sodium levels or changes in neurosecretory activity of vasopressin (Jessani et al. 2006; Malidelis et al. 2005). Because most patients with schizophrenia are heavy smokers, the stimulating effects of nicotine on ADH release may also play a role.

Musculoskeletal Disease Limited research interest has been shown in musculoskeletal disease in patients with schizophrenia despite its importance among aging patients with schizophrenia. The literature is somewhat divided regarding the epidemiology of decreased bone mineral density in the schizophrenia population. In one of the larger studies, Howard et al. (2007) found that taking prolactin-raising antipsychotics was independently associated with hip fracture, but schizophrenia per se was not a risk factor in either men or women. However, some studies have found decreases in bone mineral density in patients with schizophrenia compared with controls for either men or women, but not both (Bilici et al. 2002; Halbreich et al. 1995; Jung et al. 2006; Lehman and Meyer 2005). The accelerated rates of osteoporosis in patients with schizophrenia have been attributed to at least six different pathophysiological mechanisms: 1) nutritional alterations, 2) reduced calcium levels due to smoking, 3) hypogonadotropic hypogonadism, 4) hyperprolactinemia associated with decreased estrogen and testosterone secondary to antipsychotic medication, 5) alcoholism, and 6) polydipsia (Lambert et al. 2003; Misra et al. 2004). With regard to the hyperprolactinemia induced by antipsychotic medications, individuals being treated for schizophrenia have been found to

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have lower bone mineral density compared with controls irrespective of their exercise or vitamin D intake levels, which suggests that the duration of hyperprolactinemia that a patient sustains creates lower bone mineral density as a result of the inhibition of the hypothalamo-pituitary-gonadal axis (Kishimoto et al. 2008). Thus, researchers have postulated that clinicians treating older persons with schizophrenia should be aware of these potential side effects and screen for loss in bone mineral density, so that decreases can be treated early by reducing patients’ antipsychotic dosages or switching to a prolactin-sparing agent, or by prescribing estrogen replacement in hypoestrogenic female patients (Haddad and Wieck 2004; Meaney and O’Keane 2007). Given the increase in bone demineralization, the finding that elderly patients with schizophrenia who fall are approximately 1.5 times more likely to sustain injury than psychiatrically healthy controls is not unexpected (Finkelstein et al. 2007).

Visual Impairment Visual impairment is another medical comorbidity that is commonly overlooked in patients with schizophrenia. In a national study conducted in Finland in adults ages 30 years and older (mean age 53 years), persons with schizophrenia were five times as likely as controls to have visual impairment for distance and six times as likely for near vision. Thus, their visual acuity was significantly more likely to be impaired (Viertiö et al. 2007). These researchers contend that although some antipsychotic medications are associated with increased risk of cataracts, retinopathy, and visual impairment secondary to comorbidity with diabetes, the most significant cause of visual impairment in patients with schizophrenia is insufficiently corrected refractive errors. Unfortunately, as the authors pointed out, visual impairment can lead to many negative consequences for this patient population, including greater difficulties performing daily activities, increased risk of injuries and falls, worsened visual perception and memory, and increased social isolation, all of which exacerbate conditions for which patients with schizophrenia are already predisposed.

Mortality Rates Seeman (2007) pointed out that whereas the mean life expectancy of the general U.S. population is 76 years, the corresponding figure for the population with schizophrenia is 61 years. Thus, compared with the general population, persons with schizophrenia have a 20% reduced life expectancy. (For an extensive discussion of mortality in patients with schizophrenia, see Chapter 2, “Excessive Mortality and Morbidity Associated With

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Schizophrenia.”) Death rates from all causes remain higher among persons with schizophrenia across the lifespan (Capasso et al. 2008; Laursen et al. 2007; Seeman 2007). Enger et al. (2004) found that the all-cause mortality rate among patients with schizophrenia across age groups was four times higher than among age- and gender-matched controls in the same health plan. Furthermore, this elevated risk remained constant regardless of treatment with typical or atypical antipsychotic drugs. However, some environmental and lifestyle factors do account for the excess mortality rate in persons with schizophrenia, such as their high prevalence of smoking (Brown et al. 2000) or living in urban versus rural areas (Fors et al. 2007). Older persons with schizophrenia are also likely to face higher mortality rates as inpatients. Among all inpatients who died in VA hospitals during 2002, patients with schizophrenia had a twofold increased risk of unforeseen deaths compared with controls without schizophrenia (Copeland et al. 2006). Likewise, in a study of long-stay psychiatric patients (i.e., those with greater than 6 months of continuous hospitalization), of which 80% were persons with schizophrenia, researchers found an increased mortality risk among these patients versus the standardized mortality rates in the general population (Rasanen et al. 2003). Interestingly, despite maintaining higher mortality rates than the general population, older patients with schizophrenia have been found to have lower than expected mortality in relation to other older psychiatric patients (Wood et al. 1985). Explanations may include 1) a different sort of lifestyle (environment) for patients with schizophrenia, 2) a possible protective mechanism of neuroleptics on cardiovascular function, and 3) the possibility that elderly patients with schizophrenia are hearty survivors in that they have survived a weeding-out process in which disproportionately more physically ill patients with schizophrenia have already died. Indeed, Heila et al. (2005) reported that the highest age-adjusted rates of increased mortality occur within the first 5 years of diagnosis with schizophrenia. The lower mortality rates in older patients with schizophrenia are observed for nearly all causes, with the exceptions being heart disease and cancer. Cancer mortality in patients with schizophrenia is higher than in other psychiatric patients but lower than in the general population (Wood et al. 1985).

Subjective Health Status Self-rated health status is an important measure of subjective wellbeing. Although it tends to correlate with more objective measures of health, it is based on personal perception and judgments, which in turn may be influenced by health problems in the past, the level of health of

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other persons in the subject’s social sphere, and the subject’s aspirations for the future. Therefore, individuals may underestimate the severity of their illnesses and postpone seeking treatment. Only a few studies have examined subjective health status in aging schizophrenia populations. One study by Krach (1993) used the Older Americans Resources Survey to obtain information on physical health from 20 older patients with schizophrenia (mean age 61 years). Ratings of excellent/good and fair/poor physical health were reported by 60% and 40% of the sample, respectively. Mental health ratings were similar, with 70% and 30% reporting excellent/good and fair/poor mental health, respectively. Based on the level of physical disorders and reports of impairment in activities of daily living (e.g., 35% had moderate or severe impairment in activities of daily living), Krach concluded that these patients overrated their physical health status and underreported medical symptoms, although the author provided no objective measures of physical health. Indeed, in contradistinction to Krach’s conclusions, the authors of the PORT study (Dixon et al. 1999) maintained that “persons with schizophrenia have the capacity for reasonable appraisal of their medical conditions that can be a useful tool to promote positive health behaviors” (p. 501). This conclusion was based on the finding of a significant association between the number of medical conditions and self-rated health. In the PORT survey, lower educational level and number of comorbid medical disorders were the only variables associated with poorer self-rated physical health. Other variables such as gender, race, age, comorbid alcohol or drug disorder, geographic location, or patient setting were not associated with self-health ratings, although older subjects tended to perceive their health as better. Self-health assessments conducted in the previously cited study of older patients with schizophrenia in New York City supported the conclusions of the PORT study. Identical percentages of persons in the schizophrenia sample and the community comparison sample rated themselves in poor/ fair health (33%) or good/excellent health (67%), which was consistent with the findings that they had a similar number of physical disorders (C.I. Cohen, unpublished data). Thus, older patients with schizophrenia seem able to provide reasonable assessments of their overall health.

Treatment Issues Pharmacokinetic Factors Because older patients with schizophrenia are usually taking antipsychotic medications, the addition of drugs for physical disorders or other

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psychotropic drugs requires a sophisticated understanding of the potential risks for adverse effects. In this section, we summarize some basic concepts of pharmacokinetics and pharmacodynamics as they affect older persons in general. Pharmacokinetics, or how a drug moves through the body, becomes increasingly important as people age. Age affects the absorption, distribution, metabolism, and elimination of medications to varying degrees (Jacobson et al. 2002). Absorption may be affected by physiological changes associated with aging, which include decreased gastric acidity, a decline in small bowel surface area, and diminished blood flow to the small bowel, although no clinically significant decreases in drug absorption attributable to aging have been reported. However, use of antacids, fiber supplements, or anticholinergic agents may slow drug absorption and the onset of medication action. The distribution of drugs to peripheral sites is substantially affected by aging, because adipose tissue increases and lean body mass decreases. Thus, older bodies have a larger volume of distribution for fat-soluble drugs, which includes nearly all psychotropic medications. Several consequences result from this age-related change. The half-life of lipophilic drugs increases, leading to accumulation of drugs taken chronically and greater potential for toxicity, and increased uptake in the peripheral sites (e.g., fat tissues) may result in less of the drug reaching the brain and potentially a shorter duration of drug action after a single dose than seen in younger persons. Conversely, total body water decreases with age so that the volume of distribution of water-soluble drugs decreases and more of the drug is present in the circulation and proportionately more reaches the brain. Thus, water-soluble drugs (e.g., ethanol and lithium) may have increased effects in older persons. Elderly persons also have a diminished lean body mass so drugs (e.g., digoxin) that bind to muscle may show increased concentrations at any given strength. Finally, the concentration of plasma proteins such as albumin tends to decrease in older persons, and this decline may be further exacerbated by physical illness and poor nutrition. For proteinbound drugs, lower albumin concentrations affect the free fraction (percent bound vs. unbound) but do not affect the measured total drug concentration. The principal concern is that laboratory measurement of drug concentration is based on total drug concentrations; therefore, where the free fraction is high because of lower albumin levels, the measured concentration of the drug will underestimate the amount of active drug at the target organ. This is important in assessing blood levels of highly protein-bound drugs (e.g., digoxin, warfarin, theophylline, and phenytoin) with narrow therapeutic indices.

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The rate of drug metabolism by the liver is determined by hepatic function and blood flow. Hepatic mass and functioning hepatocytes decrease with age, and hepatic blood flow is reduced by 0.3%–1.5% per year after age 25 (Chutka et al. 1995). This results in a substantial reduction in the first-pass metabolism of a drug through the liver, so more of the active drug remains available. Phase I hepatic metabolism is performed by the microsomal oxidase cytochrome P450 (CYP450) system. Initially, these oxidative conversions may produce pharmacologically active metabolites, and subsequent oxidations produce progressively more water-soluble compounds that can be excreted by the kidneys and gut. Some of the cytochrome enzymes are affected by aging, most notably CYP1A2 and CYP3A4 (Jacobson et al. 2002). The latter is one of the most abundant of the CYP enzymes and is important in the metabolism of a wide variety of drugs (e.g., retroviral agents, antibiotics, antifungals, quinidine, calcium channel blockers, statin drugs, various serotonin reuptake inhibitors, and several antipsychotics including haloperidol, quetiapine, clozapine, ziprasidone). The CYP1A2 enzyme is involved in the metabolism of clozapine, olanzapine, theophylline, and caffeine, whereas CYP2D6 is involved in the metabolism of many antipsychotics (e.g., risperidone), antidepressants, mood stabilizers, analgesics, and beta blockers, and does not seem to be affected by age. Phase II hepatic metabolism involves the conjugation of drugs or their metabolites with glucuronide, sulfate, or acetyl moieties to produce polar, pharmacologically inactive, hydrophilic compounds that can be excreted. These processes are typically not affected by normal aging, although they may be slowed by malnutrition and extreme old age. Clearance depends on the removal of a drug from systemic circulation by the liver and kidney. As noted above, age-associated declines in hepatic function and blood flow affect liver clearance, whereas ageassociated reductions in renal blood flow and glomerular filtration rate affect kidney clearance. Renal blood flow and glomerular filtration rate are reduced about 35%–40% in the elderly compared with normal younger persons. Thus, clearance of various drugs that undergo renal eliminations such as digoxin, gentamicin, procainamide, gabapentin, or lithiums will be affected by aging.

Pharmacodynamic Factors Pharmacodynamics, which is the end-organ responsiveness to medications, is also affected by aging, although it has been much less studied than pharmacokinetic changes. Some of the pharmacodynamic changes noted with aging, depending on the type of medication, include

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reduced density of muscarinic, opioid, and D 2 dopamine receptors; impaired ability to up-regulate and down-regulate postsynaptic receptors; reduction in most enzyme activities affecting neurotransmitters; and increased or decreased receptor sensitivity (Jacobson et al. 2002). The clinical conclusion is that older persons are more susceptible to the adverse effects of medications, particularly of psychotropic drugs. Among the principal effects are the following (Zubenko and Sunderland 2000): • Peripheral anticholinergic effects, such as memory impairment, dry mouth, constipation, blurred vision, and urinary retention • Central nervous system effects (anticholinergic and antihistaminic), such as confusion, sedation, and memory impairment • Motor effects, such as tremor, impaired gait, extrapyramidal symptoms, falling, and postural instability • Cardiovascular effects, such as orthostatic hypotension, cardiac conduction delays, and tachycardia • Miscellaneous effects, which include gastrointestinal disturbances, headache, agitation, sexual dysfunction, hyponatremia, and impaired insulin response

Pharmacogenetic Factors The newest genetic research regarding both schizophrenia and its treatment has adumbrated several promising avenues for clinical care. Genetic single-nucleotide polymorphisms have been discovered at every level of the pathophysiological pathway of schizophrenia, from the genes that predispose patients to the disease and particular manifestations and symptomatology, to the genes that are involved with the patient’s ability to respond to medication, to the genes that predispose certain patients to particular side-effect profiles. Thus, the pharmacogenetic considerations may eventually shape clinicians’ understanding of both the pharmacokinetic and pharmacodynamic aspects of psychopharmacology in the elderly schizophrenia population. Some experimental techniques have been reported in the literature as methods of evaluating the consistency of pharmacotherapy exposure by measuring population pharmacokinetics. Determination of expected antipsychotic levels is useful for a clinician in deciding whether a patient has been adherent to medication or has an atypical pharmacokinetic profile (Bies et al. 2002). By elucidating polymorphisms in CYP450 genes that affect the metabolism of antipsychotic drugs (Dahl 2002), researchers have been able to clinically characterize CYP polymorphisms,

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resulting in the status of patients as poor metabolizers, slow metabolizers, or ultrarapid metabolizers (Arranz and de Leon 2007; Fang and Gorrod 1999). Patients who are poor or slow metabolizers will require lower antipsychotic dosages, whereas patients who are ultrarapid metabolizers will require increased drug dosages (Arranz and de Leon 2007; de Leon et al. 2005; Ozaki 2004). Although some centers are beginning to use such markers, it remains to be seen whether these markers will be used routinely for determining dosing levels in those patients who might be particularly sensitive or unresponsive to an atypical antipsychotic medication. Research concerning the relationship between genetic polymorphisms for receptor types and patients’ responsiveness to medications is also in its infancy; however, investigators continue to identify promising candidates for clinically relevant genetic testing. A variety of receptor types, especially dopamine receptors, have been found to be correlated with antipsychotic response (Potkin et al. 2003; Reynolds et al. 2005; Xing et al. 2007; Zhao et al. 2005); moreover, proteins that interact with dopamine receptors (e.g., dopamine receptor–interacting protein, molecular transporters at the blood-brain barrier) have been elucidated (Lin et al. 2006; Strous et al 2007; Yasui-Furukori et al. 2006). Finally, certain genetic markers have been linked to enhanced drug efficacy and side effects (Arranz and de Leon 2007; Campbell et al. 2008; Malhotra et al. 2007). All these discoveries need to be assessed with respect to age; however, they may provide additional tools in navigating the narrow pathway between therapeutic efficacy and adverse effects in geriatric pharmacotherapy.

Drug Interactions Because at least 90% of persons ages 65 years and older take at least one medication daily, and most take two or more (Chutka et al. 1995), clinicians need to be aware of various mechanisms underlying drug interactions. Potential kinetic interactions may be due to 1) effects of one drug on the metabolism of the other so that blood levels of one or both drugs may be raised or lowered, thereby producing a transient increase in the free concentrations of one or both drugs through competition for protein binding sites, or 2) concomitant administration of two drugs with similar side-effect profiles, which could exacerbate the level of adverse effects (pharmacodynamic effects). Thus, several key points emerge with respect to the use of medications, particularly the coadministration of antipsychotic agents with other medications, in older persons with schizophrenia:

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1. Determine whether the patient has any hepatic, renal, neurological, nutritional, or other medical disorders that are likely to enhance medication side effects. 2. Determine whether any newly prescribed drug is an inhibitor or inducer of CYP enzymes that are involved with the clearance of the patient’s antipsychotic medication. 3. Review the side-effect profile of any new medication to be sure that it does not add to the side effects of the patient’s antipsychotic medication. For example, the anticholinergic effects of tolterodine (Detrol) may enhance the anticholinergic effects of olanzapine or clozapine. 4. Obtain baseline measures and periodically monitor electrocardiograms; white cell counts; serum sodium; fasting glucose, triglycerides, and cholesterol; weight; and vital signs including blood pressure sitting and standing—values that should be watched due to an increased propensity of various antipsychotic agents to affect cardiac conduction, induce leukopenia, create insulin resistance and glucose intolerance, cause hyponatremia, induce hyperlipidemia, and produce orthostatic hypotension. Other drugs that can also affect these indices should be used cautiously and may require even more frequent monitoring. 5. Monitor medication blood levels, taking into account low levels of albumin or competition between highly bound drugs. If one of these situations is present, the total concentration of the drug (which is the result reported by the laboratory) may remain the same, although the free drug concentration has increased. This could result in toxicity at seemingly therapeutic dosages of the medication. 6. Be aware that the increasingly complicated medication regimens of older adults result in decreased patient medication adherence. Work with primary care physicians to coordinate and simplify the treatment regimens of older adults with schizophrenia (Piette et al. 2007).

Health Care Issues Because of the psychiatric and medical requirements of older individuals with schizophrenia, their health care costs are among the highest for any disorder that affects the geriatric population. Bartels et al. (2003) found that Medicaid and Medicare expenditures for patients with schizophrenia ages 65 and older exceeded those of persons with

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dementia, depression, or “medical disorders only.” According to findings from the PORT study, in which one-sixth of the patients with schizophrenia were ages 55 and older, more than 30% of the patients who reported current physical problems, with the exception of diabetes and hypertension, were not receiving treatment for those problems (Dixon et al. 1999). A variety of patient, physician, and systemic factors have been identified as potential impediments to health care for persons with schizophrenia in general. For example, patients may lack insight into a physical condition, have impaired ability to communicate with a physician, or have emotional or behavioral problems that interfere with an evaluation. Also, physicians may be more apt to conduct inadequate physical examinations, take a poor history, fail to repeat labs or other tests as needed, misinterpret physical symptoms as manifestations of psychosis, or passively accept consultative recommendations (Felker et al. 1996). Systemic factors may also affect health care, especially among older patients with schizophrenia. Many older persons with schizophrenia receive Medicaid, either alone or with Medicare. However, Medicaid reimbursement, eligibility requirements, and coverage vary widely across the nation, and Medicaid generally lacks the flexibility in choice of provider that may be available with Medicare alone. Medicaid patients are often relegated to public sector health programs that are overcrowded and not well equipped to deal with older persons with psychiatric problems. On the other hand, persons who receive only Medicare have virtually no coverage for psychiatric day programs, prescription medications, home attendants, case management, home visits, transportation, and other essential outpatient services. Slade et al. (2005) reported that patients who received only Medicare were 25%–45% less likely to have utilized case management, rehabilitation services, and individual therapy with nonpsychiatrist mental health providers than were patients with schizophrenia in private mental health treatment organizations. The authors concluded that the discrepancy in patient cost sharing and gaps in Medicare coverage account for the different patterns of patient utilization of services. Moreover, outpatient psychiatric treatment by Medicare patients requires a 50% copayment. Thus, Medicare copayments for outpatient psychiatric treatment continue to be 2.5 times those for other medical specialties, and reimbursable services are heavily weighted toward inpatient care. Differential treatment also occurs regarding the types of medications that are prescribed to patients with schizophrenia who have public versus private insurance. Sankaranarayanan and Puumala (2007) found

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that patients with schizophrenia who were older (ages 41–64 years) versus younger (ages 18–40 years) and those with public as opposed to private insurance were, respectively, 39% and 41% less likely to receive atypical versus typical antipsychotic medications. The impact of the new Medicare drug benefit on persons with schizophrenia has not yet been fully assessed. Studies prior to the introduction of the new Medicare drug benefit found that beneficiaries with both Medicare and Medicaid were significantly more likely to receive their requisite antipsychotic medication than their Medicare-only peers (Yanos et al. 2001). Despite the concerns about inadequate health care for persons with schizophrenia, data from the previously cited New York City study of older persons with this diagnosis suggested a more nuanced picture. Eighty-nine percent of the sample had seen a physician other than a psychiatrist in the previous year, and roughly one-third visited a physician on a monthly basis (C.I. Cohen, unpublished data). Visits to nonpsychiatric health care providers by patients with schizophrenia were actually somewhat greater than similar visits by individuals in the community comparison group. Only 11% of the patients with schizophrenia felt that they required more frequent medical services. In addition, 48% of this sample had seen a dentist in the past year. On the other hand, among persons with at least one of four common medical problems (heart disease, diabetes, hypertension, gastrointestinal ulcers), the patients with schizophrenia were significantly less likely than their age peers to receive medication treatment for two of these conditions (i.e., hypertension and heart disease) (Vahia et al. 2008). Thus, older urban outpatients with schizophrenia have access to treatment but not necessarily adequate care. Access to treatment was facilitated by the availability of health insurance (Medicare and Medicaid in most instances), easier access to public transportation and ambulette services, wider availability of home attendant services to assist patients and to accompany them to medical visits, and their participation in programs that encouraged physical assessments. Notably, a lack of adequate treatment was found to be associated with more positive symptoms and more depression. Thus, clinical symptoms may play a role in affecting treatment (Vahia et al. 2008). Because distance to health care may affect use of services among persons with serious mental illness (McCarthy and Blow 2004), the aforementioned findings regarding accessibility may be applicable only to those older patients living in urban settings. In an exploratory study in New York City, Jones et al. (2008) found that primary care physicians’ anticipated behavior toward older adults with schizophrenia was favorable, although some mild negative stereo-

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typing and attitudes were present. More important, communication of information about the patient, especially from psychiatrist to primary care provider, was identified as a problem and may account for some of the problems in adequacy of care. The authors recommended a doublepronged approach to facilitate interdisciplinary communication along with an expansion of medical education programs regarding the care of aging adults with schizophrenia. With the expansion of managed care programs for Medicaid and Medicare recipients, a critical issue will be whether persons with schizophrenia will be better off in so-called carved-in or carved-out programs (Cohen et al. 2000). The former provides mental health coverage as part of an overall package. The potential advantage is better integration of medical and psychiatric care, and older persons in these programs might have greater access to preventive as well as ongoing medical care. The disadvantage is that such programs may underfund psychiatric treatment and attempt to exclude those persons with more severe and persistent mental disorders. The carved-out programs allow for separate coverage for physical health and psychiatric care. The advantage is that such programs, if adequately funded, may allow for more appropriate services for older patients with chronic psychiatric illness. The disadvantage is that the potential integration of health and psychiatric services is lost. At the practical level, psychiatric clinicians may have to employ a variety of strategies to enhance medical care of older persons with schizophrenia. First, they should try to ensure that all persons eligible for Medicaid apply for such services because it can fill many of the gaps in services not provided by Medicare, such as prescription medication, home care services, day treatment, psychosocial rehabilitation, and so forth. In many instances, persons may be eligible for “buy-ins” for Medicaid based on their monthly medical expenditures. Second, clinicians should ensure that all patients obtain the optimal Medicare Part D drug plan. Because plans vary with respect to which drugs are covered, patients and clinicians must work together to select the optimal plan for each patient. For those not on Medicare, or for patients entering the Medicare “doughnut hole” where drug reimbursement is reduced, clinicians can work with patients to obtain free medications through patient assistance programs offered by most pharmaceutical companies or through enrollment in state-operated prescription programs for seniors (e.g., the Elderly Pharmaceutical Insurance Coverage program in New York). Some of these programs allow eligible persons to have annual incomes as high as $35,000 and, unlike Medicaid, do not count personal assets. In many communities, public and voluntary health facilities may

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offer care with sliding scales that may include prescription medications, and the VA is an excellent, low-cost option for eligible veterans. For older patients who are resistant to seeking formal medical care, clinicians can use a number of potential strategies. First, an arrangement might be made for a primary care doctor, physician’s assistant, nurse practitioner, or phlebotomist to provide services at a mental health facility, particularly if the professional can see multiple patients during a single time block. Some health services can be arranged at patients’ homes through mobile health units, local medical laboratories, and the visiting nurse services; the latter can arrange for physical therapy in the home, medication monitoring, and home health aides for physical health problems of limited duration. In general, these home health services are covered by Medicare. Finally, psychiatrists may need to serve temporarily as primary care doctors for their older patients until suitable ongoing health care services can be arranged. The extent to which a psychiatrist should serve as a primary care physician remains controversial, although many geropsychiatrists routinely conduct periodic physical assessments of their patients, and it is not difficult to oversee the management of uncomplicated common medical problems such as hypertension, gastritis, osteoarthritis, or non-insulindependent diabetes. Finally, capacity and competency can be thorny problems in the case of older persons with schizophrenia. A judgment about a person’s capacity is made by a clinical evaluator concerning the person’s functional ability to make independent, authentic decisions about his or her life, whereas a judgment about competency is made by the court about such abilities (Grossberg and Zimny 1996). When the person is competent, he or she may create a legal document (power of attorney) designating someone to act on his or her behalf if the person becomes incompetent to do so. Alternatively, the older person may sign a health care proxy, designating someone to act on his or her behalf regarding medical matters and end-of-life decisions. If prior arrangements have not been made, surrogate management arrangements can be established through the use of a representative payee, guardian, or conservator. Issues of competency are more problematic for older individuals with schizophrenia because the demarcation of incapacity becomes murkier. In younger patients with schizophrenia, incapacity is typically due to psychotic processes, although substance abuse can confound the etiology of the disturbance. In older patients with schizophrenia, in addition to the effects of psychoses, the effects of neuropsychological deficits and medical disorders must be carefully considered. Although as many as three-fourths of patients with schizophrenia evince some

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neuropsychological deficits within the first few years of their illness, roughly one-fifth of persons with schizophrenia have a very poor longterm outcome with respect to psychopathology and cognition (Davis 2002). In their 7th and 8th decades of life, such persons reach levels of cognitive deficits comparable to persons with moderate to severe Alzheimer’s disease, although no neuropathology of the latter is present (Davis 2002). In a larger group of patients with schizophrenia, as part of the normal aging process, some modest decline in cognitive functioning occurs (Cohen and Talavera 2000). Because many of these persons also had some mild cognitive deficits at the onset of their illness, this further decline in cognitive functioning with age places many older patients with schizophrenia into a level comparable with mild to moderate dementia. Researchers have shown that the strongest correlates of capacity, particularly of understanding and appreciation of information, are cognitive test scores. However, negative symptoms are also correlated with diminished capacity, such that clinicians should be aware of their potential impact (Palmer and Jeste 2006). Moreover, in patients with schizophrenia who have mild and severe cognitive impairments, cognitive status can be worsened by undiagnosed or poorly treated medical conditions, increased sensitivity to psychotropic and other medications, adverse drug interactions, small vessel disease in the brain, sensory impairments, or lack of environmental stimulation and isolation. Although older patients with schizophrenia often show considerable improvement in their psychopathology, especially positive symptoms, they remain functionally impaired because of cognitive deficits. Moreover, unlike Alzheimer’s disease in which cognitive decline is more apparent over a few years, cognitive decline in schizophrenia is insidious, and clinicians may not be aware that a patient’s cognitive functioning has become grossly abnormal. Thus, apart from their risk of developing a primary dementia such as Alzheimer’s disease or vascular dementia, a risk that is no higher than that of their age peers, older patients with schizophrenia may develop diminished capacity due to the following: psychoses, cognitive decline, and medical or environmental factors. Although any of these factors alone may not be sufficiently severe to reach levels to affect competency, several factors occurring in concert may result in more pronounced deficits. Therefore, the practicing clinician should regularly monitor the cognitive status of older patients with schizophrenia (e.g., using Folstein et al.’s [1975] Mini-Mental State Examination); carefully review laboratory results, especially those that may be more likely to affect cognition (e.g., B12, folate, thyroid indices, sodium, glucose, blood

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levels of lithium and other mood stabilizers); and be vigilant for any drug interactions that might affect cognition. Some researchers have suggested that as an alternative to the Mini-Mental State Examination, a targeted brief questionnaire can be used as a screening tool for capacity (Palmer et al. 2005). Because they are at increased risk for diminished capacity, middle-aged and elderly patients with schizophrenia who are currently competent should be encouraged to complete a health care proxy or to establish a power of attorney.

Conclusion Although patients with schizophrenia in general are thought to have worse physical health than their age peers, available data suggest that compared to their age peers, older persons with schizophrenia in treatment programs do not have more physical problems, whereas the severity of their medical conditions may be slightly worse. Although older adults with schizophrenia consider health a top priority (Lester et al. 2003), their ability to receive optimal health care is often caught between the Scylla of psychiatrists who may disregard physical problems because they believe that the primary care physician is addressing them, and the Charybdis of primary care physicians who may find that their physical assessments are confounded by patients’ mental disorders (Lambert et al. 2003).

Key Clinical Points ◗

Clinicians must ensure that older patients with schizophrenia are appropriately and regularly screened for medical conditions and diseases.

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Frequent communication between medical and psychiatric treatment teams caring for older persons with schizophrenia must become an essential part of an adequate standard of care. Some pilot studies have used health care managers to facilitate communication among health providers as well as to enhance patient adherence to medical and psychiatric regimens (Bartels et al. 2004).

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Clinicians must be cognizant of the pharmacokinetic changes associated with aging, especially decreased clearance and potential drug-drug interactions, and the pharmacodynamic changes associated with aging, particularly heightened sensitivity to certain medication side effects.

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Although a high proportion of older patients with schizophrenia may see a nonpsychiatric physician (perhaps due to the availability of Medicare and Medicaid), psychiatrists need to develop alternative approaches to ensuring health care for these patients, including use of mobile health teams, home phlebotomy, visiting nurse services, and the adoption of a primary care role.

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Although positive symptoms tend to decline with age, many older patients with schizophrenia have appreciable levels of cognitive impairment that can be exacerbated by medical illness, medication side effects, environmental understimulation, and psychosis. To avoid future problems related to competency, clinicians are advised to encourage currently competent middle-aged and elderly patients with schizophrenia to complete a health care proxy or to establish a power of attorney.

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In tandem with the changes in the number and ethnic diversity of older persons with schizophrenia that will occur over the next two decades (Cohen et al. 2008), a dramatic increase in research is needed to address the huge gaps in knowledge concerning the health needs and treatment of aging persons with schizophrenia.

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CHAPTER 15 Managing Health Outcomes of Women With Schizophrenia During Pregnancy and Breastfeeding Adele C. Viguera, M.D., M.P.H. Mackenzie Varkula, D.O. Katherine Donovan, B.A. Ross J. Baldessarini, M.D.

Schizophrenia occurs in approximately 1% of women in the general population, and the disorder most commonly begins or is present during the childbearing years (Seeman 2008). Its prevention and treatment are particularly important and can be complicated for women who are pregnant or nursing. However, remarkably little is known about the impact of the female reproductive life cycle—the menstrual cycle, pregnancy, postpartum period, nursing, and menopause—on the course of schizophrenia (Miller 1997; Miller and Finnerty 1998; Seeman 2008). Physicians caring for pregnant women with schizophrenia face a complex clinical challenge in trying to minimize risk to the fetus while limiting the 415

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impact that maternal morbidity, which might result from potentially severe untreated psychiatric illness, would have on the mother, her unborn offspring, and her family. Effective care of women with schizophrenia or other psychotic disorders has the potential to improve outcomes of pregnancy and delivery, and to limit adverse effects on the fetus and newborn (Seeman 2008). In this chapter, we consider information about the course of schizophrenia during pregnancy and the postpartum period, the reproductive safety data of antipsychotic drugs, and the safety of their use during breastfeeding. We also consider treatment guidelines for improved clinical care of pregnant women with schizophrenia.

Outcomes of Sexuality, Reproduction, and Family Planning Among Women With Schizophrenia The reproductive and family planning needs of women with schizophrenia appear to be poorly met by most contemporary health care delivery systems (Miller and Finnerty 1998; Seeman 2008). Although fertility rates in women with schizophrenia are lower than in the general population, the majority of women with schizophrenia have children (Howard 2005; Howard et al. 2001; Svensson et al. 2008). This trend may be due to deinstitutionalization and greater prescribing of the atypical antipsychotics that do not suppress the hypothalamic gonadal axis. Also, compared with women without mental illness, women with schizophrenia experience higher rates of unplanned and unwanted pregnancies, and are more likely to be victims of sexual abuse, exploitation, and violence during pregnancy (Miller 1997; Miller and Finnerty 1998). Moreover, women with schizophrenia tend to be less knowledgeable about or attentive to use of contraception, and they encounter more obstacles in using and obtaining birth control (Miller and Finnerty 1998). They are also less likely to receive prenatal care and more likely to abuse alcohol or drugs or to smoke heavily (Bennedsen et al. 1999; Howard 2005; Miller 1997; Sacker et al. 1996). Studies also indicate that the majority of women with schizophrenia lose custody of their children because they have difficulty meeting their children’s basic needs (Miller and Finnerty 1998; Seeman 2008). In addition, they are less likely to have another caregiver or partner helping to raise their children (Miller and Finnerty 1998). Women with psychiatric illness generally, and schizophrenia in particular, may encounter significant obstacles from the professional com-

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munity in planning for pregnancy, and are often counseled to avoid becoming pregnant or to terminate an established pregnancy so as to prevent fetal exposure to potentially teratogenic medications or to avoid the risk of recurrent illness or symptom exacerbation (Einarson et al. 2001; Viguera et al. 2002). Women with schizophrenia who pursue pregnancy, even those with frequently exacerbated or chronic illnesses, may risk illness by discontinuing treatment after conception and are likely to perceive psychotropic drugs as more dangerous or less necessary than other medications during pregnancy (Bonari et al. 2005; Cohen et al. 2006; Coverdale et al. 2002; Einarson et al. 2001). In addition, women with chronic mental illness are often treated with multiple medications in contemporary U.S. psychiatric practice (Centorrino et al. 2008; Peindl et al. 2007). Despite the high rates of polypharmacy, many patients receive suboptimal treatment for psychiatric illnesses (Howard 2005; Peindl et al. 2007).

Maternal Outcomes During Pregnancy and the Postpartum Period Whether pregnancy favorably or unfavorably affects the risk of psychiatric decompensation in women with schizophrenia is surprisingly uncertain (Howard et al. 2004; McNeil et al. 1984). Some clinical observations suggest that pregnancy may reduce the risk of acute psychiatric illness and specifically protect against exacerbation of psychotic disorders and suicide (Marzuk et al. 1997; Nott 1982; Pugh et al. 1963; Terp and Mortensen 1998). Other studies have found rates of psychiatric hospitalization to be either somewhat lower or unchanged during pregnancy (Kendell et al. 1987; Lier et al. 1989). A few reports suggest that some women with schizophrenia are less likely to decompensate during pregnancy than during the postpartum period, whereas other reports indicate improvement in psychotic symptoms during pregnancy (Lier et al. 1989; Trixler et al. 1995). Nevertheless, several reports have noted that the majority of women with schizophrenia (over 60%) experienced symptom exacerbation during pregnancy, especially when maintenance medication was discontinued (Casiano and Hawkins 1987; McNeil et al. 1984; Nishizawa et al. 2007). Previous studies have suggested that women with schizophrenia do not experience an increased risk for symptom exacerbation in the postpartum period, somewhat contrary to the findings of high rates of symptom exacerbation during the postpartum period in women with mood and anxiety disorders (Davies et al. 1995; Kendell et al. 1987; McNeil 1986;

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Terp and Mortensen 1998). However, other findings suggest that the postpartum period is indeed a period of high risk for psychotic relapse in women with schizophrenia. Findings from one study indicated that at least 50% of women with schizophrenia experienced an exacerbation of their psychotic illness (Howard et al. 2004). In a prospective study of women with psychotic disorders, 24% of women with schizophrenia became acutely psychotic within 6 months postpartum (McNeil 1986, 1987). Other researchers have noted that women with schizophrenia who present with an affective component are at especially high risk of postpartum relapse (Davies et al. 1995). When relapse or exacerbation occurs, women with schizophrenia tend to experience these episodes much later in the postpartum period and to have significantly longer hospitalizations compared with women who have mood disorders (McNeil 1987). Despite the potential increased risk for recurrence during the postpartum period, no studies have specifically examined the role of postpartum prophylaxis with antipsychotics. Another important finding regarding postpartum illness course is that women with schizophrenia appear to be at a twofold increased risk for developing postpartum depression compared with controls (Howard 2005). This observation has important clinical implications for women with schizophrenia, because maternal depression itself may adversely affect child development (Murray and Cooper 1997; Newport et al. 2002). In contrast, compared with women with affective disorders, women with schizophrenia are at lower risk of developing postpartum psychosis, a rare but potentially dangerous condition for the mother and her infant (Howard 2005). Given that little evidence supports a protective effect of pregnancy against exacerbations of schizophrenia, it is important to consider the growing findings in nongravid women that indicate a high risk of relapse associated with discontinuation of maintenance antipsychotics (Baldessarini et al. 1999; Suppes et al. 1997; Viguera et al. 1997, 1998). For example, among patients with schizophrenia, approximately half experience clinically important exacerbations of symptoms within 6 months of discontinuing antipsychotic treatment (Viguera et al. 1997). This risk is much higher and earlier following abrupt rather than gradually tapered discontinuation of antipsychotic drugs (Baldessarini et al. 1999; Viguera et al. 1997). Similar findings have been noted in patients diagnosed with unipolar major depression, bipolar disorder, and anxiety disorders who are withdrawn from maintenance medications, especially when discontinuation occurs rapidly or abruptly, as is common early in pregnancy due to the desire to avoid adverse drug effects on fetal development (Suppes et al. 1997; L.Tondo et al., unpublished data, 2008; Viguera et al. 1997, 1998).

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In light of these findings, the cessation during pregnancy of ongoing pharmacotherapy used to treat schizophrenia must be viewed as potentially dangerous. Inadequately treated maternal psychiatric illness may result in poor prenatal care and nutrition, exposure to additional drugs or herbal remedies, increased use of alcohol and tobacco, deficits in mother-infant bonding, and disruption within the family environment (ACOG Committee on Practice Bulletins—Obstetrics [ACOG] 2008). Accordingly, decisions to discontinue maintenance treatment should be made only after careful consideration of the potential negative impact of untreated illness on maternal and fetal outcomes (Newport et al. 2002; Weissman et al. 2006).

Risk of Obstetric Complications Compared to women in the general population, those with schizophrenia, especially if the illness is acutely symptomatic, are at increased risk for obstetrical complications (Nilsson et al. 2002; Sacker et al. 1996; Wrede et al. 1980). These complications include a broad spectrum of adverse pregnancy outcomes, including fetuses that are small for gestational age, preterm delivery, low-birth-weight infants, placental abnormalities and antenatal hemorrhage, increased rates of congenital malformations (especially cardiovascular system), and higher incidences of stillbirth or neonatal death and sudden infant death syndrome (Bennedsen et al. 1999, 2001; Jablensky et al. 2005; Nilsson et al. 2002; Wrede et al. 1980). Women with schizophrenia are also at increased risk for labor induction, assisted vaginal delivery, and cesarean section (Bennedsen et al. 2001; Reis and Kallen 2008). Causes of such obstetrical outcomes are complex and may include effects of compromised socioeconomic circumstances and inferior clinical and self-care during pregnancy, in addition to possible effects of abused substances or psychotropic drugs (Howard 2005; Miller 1997). Given an association between a history of obstetrical complications and greater lifetime risk of schizophrenia, prevention of obstetrical complications through improved prenatal care might also limit future risks of mental illness in the offspring of women with schizophrenia (Howard 2005; Seeman 2008).

Potential Risks of Pharmacotherapy All psychotropic medications diffuse readily across the placenta and the blood-brain barrier, and no psychotropic drug has been approved

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by the U.S. Food and Drug Administration (FDA) for use during pregnancy. For ethical reasons, conducting randomized placebo-controlled studies on medication safety in pregnant women is virtually impossible. Accordingly, most information about the reproductive safety of drugs derives from case reports, case series, and retrospective studies, and few reports involve prospective designs (ACOG 2008; Altshuler at al. 1996). To guide physicians seeking information about the reproductive safety of various prescription drugs, the FDA has established a system that classifies medications into five risk categories (A, B, C, D, and X) based on data derived from human and animal studies (Table 15–1). Category A medications are designated as safe for use during pregnancy (no psychotropic drugs currently have this rating), whereas category X drugs are contraindicated by having demonstrated fetal risks that outweigh any benefit to the patient. Drugs in Categories B, C, and D are considered to have intermediate risks, which increase from B to D. Most psychotropic drugs are classified as category C, agents for which adequate human studies are lacking and for which risk cannot be ruled out and clinical judgment is required to balance potential risks and benefits. Experience has shown, however, that the FDA’s pregnancy categories for drugs do not correlate well with information on teratogenicity from other sources and are not informative in clinical practice (Holmes et al. 2004; U.S. Food and Drug Administration 2001). Recently, the FDA proposed major revisions to prescription drug labeling to provide more accurate and helpful information on the effects of medications used during pregnancy and breastfeeding (U.S. Food and Drug Administration 2008). At present, prescribers and patients are left to rely on limited peer-reviewed studies and treatment consensus guidelines sponsored by professional organizations as sources of information when recommending the use of psychotropic medications during pregnancy (ACOG 2008). An important realization is that random fetal anomalies are remarkably common in the general population and represent a high background rate against which to compare teratogenic effects suspected as being related to exposure to psychotropic agents. The baseline incidence of major congenital malformations in newborns in the United States is approximately 2%–4% (Holmes et al. 2002). Basic formation of major organ systems takes place early in pregnancy and is virtually complete within the first 12 weeks after conception. However, pregnancy is often not diagnosed for 6–8 weeks, during which time critical steps in major organ development have already occurred. Teratogens are chemical agents, including drugs, that interfere with organ development to produce malformations of varying severity. Each organ system

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TABLE 15–1. FDA classification of teratogenic drug risk Category Description of risk A

No fetal risk shown in controlled human studies

B

No human data available, and animal studies show no fetal risk, or animal studies, but not human studies, show fetal risk

C

No controlled studies on fetal risk available for humans or animals, or fetal risk is found in controlled animal studies with no human data (benefit of drug use must clearly justify potential fetal risk in this category)

D

Studies show fetal risk in humans (use may be acceptable even with risks, such as in life-threatening illness or where safer drugs are ineffective)

X

Risk to fetus clearly outweighs any benefits from these drugs

Source.

U.S. Food and Drug Administration 2001.

appears to be vulnerable to teratogenic effects during relatively specific and limited time periods during the first trimester.

Fetal Risks Associated With Medications Used to Treat Schizophrenia Reproductive safety of typical or first-generation neuroleptics, such as chlorpromazine, fluphenazine, haloperidol, perphenazine, thioridazine, and trifluoperazine, is supported by extensive data accumulated over the past 50 years, especially from experience in using such agents to treat hyperemesis gravidarum (Altshuler et al. 1996; Einarson 2005; Trixler et al. 2005). No significant teratogenic effect has been documented with chlorpromazine, haloperidol, and perphenazine, in particular (ACOG 2008). However, one meta-analysis found a small increase in the relative risk of congenital malformations in offspring exposed to low-potency typical antipsychotics compared with high-potency antipsychotics (Altshuler et al. 1996). In general, the higher- and mid-potency typical antipsychotics (e.g., haloperidol, perphenazine) tend to be recommended because they are less likely than lower-potency antipsychotics to have associated sedative or hypotensive effects (Altshuler et al. 1996; DiavCitrin et al. 2005).

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A report from the Swedish Medical Birth Register examined malformation rates among 576 infants exposed to antipsychotics, including typical and atypical agents (Reis and Kallen 2008). The overall odds ratio for clinically significant malformations among exposed infants was 1.52 (95% CI 1.05–2.19). Specifically, among the first-generation antipsychotics, this risk was 4.8% overall (by class: butyrophenones, 2.50%; phenothiazines, 2.75%; thioxanthenes, 7.20%), with somewhat lower risks with second-generation antipsychotics and no statistically increased risk with any particular drug. These findings suggest a modest increase above the baseline malformation rate. However, these findings are limited by the relatively small study sample, as well as unidentified confounding factors, such as maternal alcohol use (Altshuler et al. 1996; Reis and Kallen 2008). Although atypical antipsychotics have been available since the mid1990s and are used widely by women of reproductive age, reliable data regarding the reproductive safety of these compounds remain limited (ACOG 2008; Gentile 2008a, 2008b; Yaeger et al. 2006). Of the six atypical antipsychotics prescribed by physicians in the United States (i.e., aripiprazole, clozapine, olanzapine, quetiapine, risperidone, and ziprasidone), the FDA has categorized clozapine as pregnancy category B and the remaining five compounds as category C, alerting women and their clinicians that although animal studies have been conducted, no adequate and well-controlled trials have been conducted in pregnant females. Most of the information on the reproductive safety of these agents derives from published case reports and manufacturers’ postmarketing data. Thus far, the available evidence does not demonstrate a “signal” for an increased risk for major malformations or for any specific pattern of abnormalities among atypical antipsychotic–exposed infants. However, such spontaneous reports have an inherent bias and cannot provide definitive information about reproductive safety. In one of the only prospective studies completed on the reproductive safety of the atypical antipsychotics, investigators observed no increased risk in children exposed to atypical antipsychotics (N =151), including olanzapine (n= 60), risperidone (n =49), quetiapine (n= 36), and clozapine (n=6), compared with a nonexposed control group (McKenna et al. 2005). The investigators observed one malformation in an infant exposed to olanzapine and two malformations in the nonexposed group. The investigators also observed higher proportions of low-birthweight babies and of mothers with greater body mass index among the exposed group than the control group. In addition, a recent report from the Swedish Medical Birth Register examined malformation rates among 147 infants exposed to atypical antipsychotics (Reis and Kallen

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2008). The major malformation rate was 4.1% overall (clozapine, 5.60%; olanzapine, 3.80%; quetiapine, 0.00%; and risperidone, 3.90%). Interpretation of these findings is limited by the small sample size for each individual drug and other potential confounding variables. For olanzapine, data from the manufacturer’s case registry, which included approximately 37 prospective pregnancy outcomes, demonstrated no cases of malformations, but among 11 retrospective cases, one infant had a dysplastic kidney (Goldstein et al. 2000). Other individual reports and case series involving over 60 cases demonstrated no recurrent pattern in the two reported major malformations (Gentile 2008a; Yaeger et al. 2006). For clozapine, retrospective data include 102 pregnancies with 59 deliveries resulting in 61 births. Data for 22 pregnancies were unavailable. Five infants had major malformations, and five had perinatal difficulties that were not specified, but no data were reported on developmental outcomes (Dev and Krupp 1995; Gentile 2008a; Yaeger et al. 2006). Prospective data are limited to about 19 cases with two reports of perinatal/neonatal seizures and one child born prematurely with several anomalies and delayed development at 7 months. However, normal development was reported in seven subjects evaluated up to 5 years of age. Of note, gestational diabetes and/or pregnancy-induced hypertension complicated five pregnancies (Gentile 2008a; Yaeger et al. 2006). The manufacturers of risperidone recently reported pregnancy and neonatal outcomes from a postmarketing database including 713 pregnancies. Among the 68 prospectively reported pregnancies, organ malformations occurred in 3.8%, a finding consistent with background rates in the general population. Among the 197 retrospective cases, the rate of malformations was substantially higher at 6%, with the most frequently reported malformations involving the heart, brain, lip, and/or palate. Moreover, 37 retrospectively reported pregnancies involved perinatal syndromes, of which 21 cases involved behavioral or motor disorders, including tremor, jitteriness, irritability, feeding problems, and somnolence (Coppola et al. 2007). Among the approximately 60 prospectively identified cases of fetal exposure to risperidone, no congenital malformations were reported and two cases of normal development up to 1 year postpartum were reported (Gentile 2008a; Yaeger et al. 2006). The manufacturer of quetiapine reported 446 prospective and retrospective cases of pregnancy exposure in an international database (P. Fontana, written communication, March 2005). Of these, outcomes were reported for 151 (34%), including eight reports of congenital anomalies. No specific pattern of major malformation was noted. In

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addition, another 39 prospectively identified cases of fetal exposure to quetiapine (including 36 in the study by McKenna et al. 2005) resulted in no reports of congenital malformations, and one case demonstrated normal development at 6 months (Gentile 2008a; Yaeger et al. 2006). Thus far, the safety of aripiprazole in human pregnancy has been investigated in only three case studies (Gentile 2008a). In one of the cases, the baby had no structural anomalies or neurodevelopmental impairment; however, at delivery, symptoms attributable to poor neonatal adaptation (e.g., neonatal tachycardia) were observed. In the other two cases, the outcome was a healthy term infant. Finally, to our knowledge, no reports have been published on human fetal exposure to ziprasidone. Another report, based on prospective data collected from the United Kingdom National Teratology Information Service, similarly found that infants exposed to atypical antipsychotics (i.e., either clozapine or olanzapine) had a significantly higher incidence of being large for gestational age and having a heavier mean birth weight compared with nonexposed controls (Newham et al. 2008). In addition, data from the Swedish Medical Birth Register suggested that compared with controls, antipsychotic-exposed pregnant women had almost a twofold increased risk for gestational diabetes and for cesarean delivery (Reis and Kallen 2008). Unfortunately, the investigators did not examine differences in risk between typical and atypical antipsychotics. Based on these data, patients taking an atypical antipsychotic may choose to discontinue their medication or replace treatment with a better characterized typical antipsychotic agent, such as haloperidol; however, many women do not respond well to typical agents or have such a severe illness that changes to their existing regimen may place them at significant risk for relapse. Although the available manufacturers’ information and existing prospective data are not a guarantee of reproductive safety, they are somewhat reassuring. Further studies are clearly needed, however, to make more definitive conclusions about teratogenic risks for the newer compounds. Pregnancy registries have emerged as an effective and systematic method for assessing fetal risks from exposures in pregnancy. The National Pregnancy Registry for Atypical Antipsychotics was established in 2008 at Massachusetts General Hospital and is the first hospital-based pregnancy registry in the United States to systematically and prospectively collect data on pregnancy outcomes following exposure to atypical antipsychotics (http://www.womensmentalhealth.org). Another registry has been established in Australia for assessing a variety of psychiatric and health outcomes for pregnant women with a history of

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psychosis, including neonatal outcomes following exposure to first- and second-generation antipsychotics (Kulkarni et al. 2008). Such registries will provide a rapid and efficient means of collecting important prospective data on the reproductive safety of the newer antipsychotics.

Risk for Neonatal Symptoms Several studies have reported obstetrical and neonatal complications from exposure to both atypical and typical neuroleptics. Recently, a prospective study examined the placental passage ratios and obstetrical outcomes for infants exposed to antipsychotics, including olanzapine, haloperidol, risperidone, and quetiapine (Newport et al. 2007). Placental passage ratios were estimated to be highest for olanzapine (72%), followed by risperidone (49%), haloperidol (42%), and quetiapine (24%). In addition, investigators found tendencies toward higher rates of low birth weight and neonatal intensive care unit admission among neonates exposed to olanzapine. Other reports have documented symptoms of poor neonatal adaptation in neonates exposed to typical neuroleptics in utero. These symptoms, which include motor restlessness, tremor, hypertonicity, dystonia, and parkinsonism, are typically transient, followed by apparently normal motor development (ACOG 2008). Little information is available regarding the reproductive safety of medications, including amantadine, diphenhydramine, benztropine, or trihexyphenidyl, that are used to manage extrapyramidal side effects. In a case-control study, oral clefts were more common in infants with a significantly higher rate of prenatal exposure to diphenhydramine than in controls (Saxen 1974). A possible association between exposure to benztropine or trihexyphenidyl and increased risk for congenital anomaly has also been described (Heinonen et al. 1977). In contrast, several other studies evaluating the use of diphenhydramine during pregnancy failed to reveal a heightened risk of organ malformation (ACOG 2008). Moreover, studies of beta-blockers, including propranolol and atenolol, during pregnancy (sometimes used to manage akathisia with both first- and second-generation antipsychotic agents) have revealed no teratogenic risk (Altshuler et al. 1996; Reiter et al. 1987).

Approach to Treatment of Schizophrenia During Pregnancy Women of childbearing age who have schizophrenia, especially those with severe or chronic illness or major disability, should be counseled about family planning. They should also be made aware of the atten-

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dant risks of antipsychotic medications and encouraged to consider contraception. Planning for pregnancy while the patient is relatively clinically stable provides opportunities for thoughtful treatment selection and avoids the risk of precipitous treatment changes in response to an unplanned pregnancy (Cohen and Nonacs 2005). An important consideration is that switching from a prolactin-elevating antipsychotic agent, such as risperidone, paliperidone, or a high-potency older neuroleptic, to an agent lacking such effects can increase the risk of becoming pregnant (Volavka et al. 2004). Pregnant women with schizophrenia should be considered potential high-risk obstetrical patients, given their increased risk for obstetrical complications as well as for exacerbations of psychotic illness. Additional clinical monitoring during pregnancy, ideally with close psychiatric and obstetrical collaboration, is imperative to support early detection of impending psychotic relapse with rapid and anticipated intervention. Decisions regarding whether to continue, change, or discontinue treatment during pregnancy must reflect an assessment of the following factors: 1) the highly variable but often poorly quantified risks of fetal exposure to maternal psychotropic drugs commonly used to treat schizophrenia; 2) substantial risks to the patient, fetus, and family from untreated maternal psychotic illness; and 3) typically high risk of early and potentially severe relapse or exacerbation associated with discontinuation of maintenance treatment, particularly if it is abrupt (Baldessarini and Viguera 1995). The psychiatrist who treats women with schizophrenia should discuss with patients the risks associated with continuing or discontinuing treatments during pregnancy. Our own research and clinical experience suggests that patients given similar information, including women with comparable clinical illness histories, make very different decisions about medication use during pregnancy (Cohen et al. 2006; Viguera et al. 2002). These risks should be discussed frankly and repeatedly, both before and after conception, and the patient’s psychiatrist, obstetrician, and other clinicians should have collaborative and effective communication. These discussions should be documented in the clinical record, for both clinical and legal purposes. Evidence-based guidelines are lacking for the treatment of schizophrenia during pregnancy. Given the severity and chronicity of schizophrenia, maintenance treatment with an antipsychotic before and during pregnancy may be the safest option for the mother and fetus. In certain cases of refractory illness, a clinician may decide to use a medication for which information regarding reproductive safety is sparse. For instance, a woman with severe schizophrenia who has responded only to a newer atypical antipsychotic for which reproductive safety

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data are unknown may choose to continue this medication during pregnancy rather than risk relapse by discontinuing or switching to another agent. In another scenario, patients with schizophrenia who present clinically late in the first trimester or early second trimester and who are already stable on a newer neuroleptic may also choose to continue their current treatment, given that fetal exposure has occurred and switching medications may jeopardize maternal stability. For patients presenting with active psychosis, hospitalization may be required, and electroconvulsive therapy can be considered if additional doses of antipsychotic medication are not sufficient (Miller 1994). Electroconvulsive therapy may also be helpful in the clinical management of postpartum psychotic illnesses that arise spontaneously without a history of chronic or recurrent psychotic illness (Greenhalgh et al. 2005; Sit et al. 2006). Antipsychotic dosing should be cautious and conservative throughout pregnancy but kept at an effective dose. Clinicians sometimes risk undertreating psychiatric illness in an attempt to minimize fetal exposure. Drug dosage can be increased following delivery, if required clinically, but such changes should be balanced against consideration of decisions about breastfeeding. Pregnancy and the postpartum period require flexible and responsive treatment, and both the patient and physician should be prepared to reevaluate treatment decisions over the course of pregnancy and the puerperium as clinical conditions may change.

Breastfeeding The inherent benefits of breastfeeding for a mother with schizophrenia and her infant need to be weighed against the risks of neonatal exposure to antipsychotics through breast milk. Women are often encouraged to continue their antipsychotic regimen following delivery, because the postpartum period can be particularly difficult and stressful for women with schizophrenia (Seeman 2008; Sit et al. 2006). If a particular medication was effective during pregnancy, the recommended practice is to avoid switching to an alternative antipsychotic for breastfeeding, if only to avoid exposing the infant to multiple medications. Considerable uncertainty exists regarding the relative safety of particular psychotropic drugs during lactation and the degree to which nursing infants are exposed to these medications (ACOG 2008; Gentile 2008b; Stowe 2007). Data regarding drug excretion into human breast milk and infant exposures are rare and usually limited to small studies of particular agents. All psychotropic medications are secreted in breast

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milk, although medication exposure for the nursing infant is considerably less than in utero placental transfer for the atypical antipsychotics (Newport et al. 2007; Stowe 2007). Olanzapine, in particular, was found in low serum concentrations in nursing infants and did have adverse effects (Gardiner et al. 2003; Goldstein et al. 2000). Among older agents, chlorpromazine was studied in only seven nursing infants, none of whom exhibited developmental deficits at 16-month and 5-year followup evaluations (Kris and Carmichael 1957), but three breastfeeding infants exposed to maternal treatment with chlorpromazine and haloperidol exhibited suggestive developmental delays at 12–18 months (Yoshida et al. 1998). The limited available data preclude firm conclusions regarding safety of antipsychotics to nursing infants (Burt et al. 2001; Stowe 2007; Viguera et al. 2007).

Conclusion Clinicians caring for women with schizophrenia should be aware of the myriad challenges these women face, including high rates of victimization, substance abuse, perinatal complications, poor psychosocial support, difficulties in parenting, and barriers to family planning and medical and prenatal care. Although robust data on the course of schizophrenia during pregnancy are lacking, any potential protective effects of pregnancy are unlikely. Risks for morbidity associated with discontinuation of ongoing maintenance antipsychotic treatment, particularly abruptly or rapidly, are likely to be high for both the mothers and their babies. Therefore, maintenance pharmacotherapy is recommended, in addition to appropriate psychosocial intervention. Conceptualizing pregnant women with schizophrenia as high risk emphasizes the importance of close clinical monitoring and the need for coordinated care among a multidisciplinary team.

Key Clinical Points ◗

Pregnant women with schizophrenia should take a single medication at a higher, possibly divided, dose instead of multiple drugs at low doses.

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Data are lacking regarding long-term outcomes for the offspring of women treated with antipsychotics during pregnancy.

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The postpartum period may be a time of particular risk of recurrences or new psychotic illness.

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◗

Strong social and collaborative clinical supports for women with schizophrenia benefit pregnancy outcomes.

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Medications should be maintained during pregnancy for women diagnosed with schizophrenia, particularly those with a history of repeated decompensations, chronic illness, or substantial disabilities.

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Maintenance antipsychotic treatment during pregnancy may actually limit total drug exposure if the maintenance treatment prevents acute illness and the associated need for higher doses.

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Little evidence is available to support the practice of completely stopping medications (vs. gradually reducing doses), either early in pregnancy or before delivery, in efforts to avoid clinical or legal responsibilities for adverse neonatal outcomes. Doing so probably increases the risk of relapses, with distress to the mother, infant, and family.

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No scientific support indicates the value of monitoring neonatal serum drug levels during breastfeeding.

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Nursing should be stopped if an infant develops symptoms of adverse effects from antipsychotic or other psychotropic treatment; these symptoms are likely to resolve when the child is bottle fed.

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Index Page numbers printed in boldface type refer to tables or figures cancer in, 378–379, 386–388 cardiovascular disease in, 378– 379, 383–384 comparison with nonschizophrenic peers, 379– 380, 391 deficiencies in health care for, 384 depression in, 379, 380 diabetes mellitus in, 378–379, 380–383 general physical health of, 378– 380 health care issues affecting, 397– 403 hyponatremia in, 388–389 immune dysfunction in, 385–386 mortality rates of, 390–391 musculoskeletal disorders in, 389–390 neurocognitive impairment in, 379 prevalence of medical disorders in, 377–380 respiratory disorders in, 378–379, 384–385 schizophrenia prevalence in, 377, 378 subjective health status of, 391– 392 “survivor effect” in, 380, 391 treatment issues affecting, 392–397

Abilify. See Aripiprazole Accidents, as mortality cause, 17–18, 19, 20 Acoustic startle response, prepulse inhibition of, 229–230 Acquired immunodeficiency syndrome (AIDS), 250–251, 254, 266. See also Human immunodeficiency virus (HIV) infection treatment for 258–259 Addictive behavior, 282. See also Substance abuse disorders Adipokines, 62 Adolescents. See Children and adolescents Adrenocorticotropin (ACTH), 389 Aging persons. See also Aging persons with schizophrenia adverse drug effects in, 394–395 body fat in, 63 drug interactions in, 396–397 health care proxy for, 401 pharmacodynamics in, 394–395 pharmacogenetics in, 395–396 pharmacokinetics in, 392–394 Aging persons with schizophrenia, 377–413 antipsychotic medicationexacerbated disorders in, 378, 379 as baby-boomer generation, 377

435

436

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Aging persons with schizophrenia (continued) visual impairment in, 390 Air Force/Texas Coronary Atherosclerosis Prevention Study, 120 Akathisia, 278–279, 281–282, 346 subtle, 67 Alcohol abuse, 281–282, 284–285 and breast cancer, 26 central nervous system effects of, 284, 287–288 demographics of, 275–279 medical consequences of, 29, 287– 288 and mortality, 29 and osteoporosis, 389 during pregnancy, 416 prevalence of, 171 and sexual dysfunction, 309 Alcohol withdrawal, 288 Allergies, 385 Alzheimer’s disease, 28, 379, 402 Amantadine, as weight loss medication, 80–81, 331 Amenorrhea, 312–313, 314 American Association of Clinical Endocrinologists, 39 American Diabetes Association, 39, 92, 105–106, 108 American Heart Association, criteria for metabolic syndrome, 42 American Psychiatric Association, 39 Amiodarone, 176 Amisulpride, effect on weight, 70 Amphetamines, 277, 288, 289 Anhedonia, 281 Anticholinergic effects, of antipsychotic medications, 395, 397 Anticonvulsants, effect on sexual function, 310–311 Antidepressants effect on sexual function, 321 effect on weight, 61, 76

Antidiabetic drugs, 65 Antidiuretic hormone, release of, 388–389 Antihypertensives, 65, 382 effect on sexual function, 310–311 Antipsychotics, 394–395. See also Atypical antipsychotics; Neuroleptics; names of specific antipsychotics and cancer risk, 387–388 and cardiovascular disease risk, 383 choice of, 196 comparative metabolic profiles of. See Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) compliance with, 21–22 dosage in pediatric schizophrenia patients, 344–345 effect on serum lipids, 125–159 effect on weight, 204 fetal/neonatal risks associated with, 421–425 first-generation, 343–344 and galactorrhea, 306 and gynecomastia, 306 health insurance coverage for, 398–399 and mortality, 29–30 nonadherence to, 307–308 and obesity risk, 61–62, 69–72 overdose, as suicide method, 21 proarrhythmic effects of, 175–176 prolactin-elevating, 306, 312–314, 389–390. See also Hyperprolactinemia second-generation, 343–344 sexual side effects of. See Sexual dysfunction smoking and, 282 as substance abuse treatment, 294–295 teratogenicity of, 421 use during pregnancy, 415–416, 418–419, 425–427

Index use in aging patients with schizophrenia, 382 Antipsychotic switching, 76–78, 107– 108, 156, 157, 328–329 Antiretroviral therapy, 255, 258–259, 260, 264, 267–268, 269 Anxiety, in cocaine users, 289 Apolipoprotein B100, 121–122 Aripiprazole adverse health effects of, 3–4 effect on fasting glucose levels, 53, 56 effect on prolactin levels, 319 effect on serum lipids, 130, 131, 138, 146, 148, 159 effect on weight, 78, 104, 107, 349, 351 metabolic profile of, 53, 56 as sexual dysfunction treatment, 331 sexual function effects of, 319, 328–329 as substance abuse treatment, 294 use in pediatric schizophrenia patients, 343–344, 345, 349, 351 Arousal disorders, 305, 306 Arrhythmias, 169–181, 170, 171 surrogate risk markers for, 175– 176, 179–180 Aspirin, cardioprotective effects of, 193, 196 Atherosclerosis, 94, 122 Atypical antipsychotics, 91. See also names of specific atypical antipsychotics adverse effects of, 3–4, 5 cardiovascular effects of, 180–190 choice of, 109 and diabetes mellitus risk, 98–103, 109 efficacy in pediatric schizophrenia patients, 345– 346 extrapyramidal side effects of, 91

437

fetal/neonatal risks associated with, 422–425 and metabolic disorder risk, 108– 109 and obesity risk, 6, 66, 109 Auditory information processing defects, 228–229 Baby-boomer generation, 377 Bariatric surgery, 82 Basal metabolism, 66–67 Behavioral treatment for obesity, 203–222, 206, 209–212 in pediatric schizophrenia patients, 367–368 principles of, 204–206 for substance abuse, 292, 293 Behavioral Treatment for Substance Abuse in Schizophrenia (BTSAS) model, 293 Benzodiazepines in combination with clozapine, 184–185 sexual function effects of, 321 Betahistine, 79 Bipolar disorder, 248, 281, 352, 385 Birth control. See Contraceptives Bladder cancer, 387 Blood-brain barrier, 419–420 Blood pressure. See also Hypertension; Hypotension measurement of, 72–73, 193, 365 weight loss–related reduction in, 215 Body mass index (BMI), 62–63, 64, 66, 72–73 in metabolic syndrome, 42–43 in pediatric schizophrenia patients, 350, 356–357, 360– 361 Breast cancer in aging persons with schizophrenia, 386, 387 dopamine receptor antagonists and, 313

438

Medical Illness and Schizophrenia

Breast cancer (continued) hyperprolactinemia and, 354 and mortality, 25, 31 prevalence in schizophrenia, 24, 26 Breastfeeding, 420, 427–428 Brief Psychiatric Rating Scale (BPRS), 227, 278, 285–286, 345 Bupropion sexual function effects of, 321 use in smoking cessation, 233, 234–236, 237 Butyrophenones and congenital malformation risk, 422 effect on serum lipids, 123, 124, 125–126, 133, 159 Cabergoline, 330 Calcium channel blockers, effect on sexual function, 311 Calcium deficiency, 389 Cancer. See also specific types of cancer in aging persons with schizophrenia, 378–379, 386– 388 alcohol abuse and, 287 human immunodeficiency virus (HIV) infection and, 254 hyperprolactinemia and, 312–314 and mortality, 23, 24, 25, 25, 387– 388 negative correlation with schizophrenia, 387 smoking and, 224 Cannabis (marijuana), 277 demographics of use of, 279 depression and, 381 medical consequences of, 289–290 psychosis-exacerbating effect of, 285–286 Cannabis receptors, 289–290 Capacity, 401, 402 Cardiomyopathy, 4–5, 187–188, 189

Cardiovascular disease, 98, 169–202, 395 in aging persons with schizophrenia, 378–379, 383– 384 alcohol abuse and, 287, 288 clozapine and, 100 comorbidity with diabetes mellitus, 94, 384 definition of, 190 diabetes mellitus and risk of, 94, 117–118 hospitalization for, 383–384 and mortality, 18, 23, 24, 25, 25, 26–27, 100, 118–119, 169, 181, 190, 384 prevalence of, 27–28 prevention of, 103 risk estimation for, 118, 192–193, 194–195 schizophrenia and risk of, 203–204 and sexual dysfunction, 309 smoking and, 224, 312 Care. See Health care Carved-in/carved-out programs, in mental health insurance coverage, 400 Cataracts, 45 CATIE. See Clinical Antipsychotic Trials of Intervention Effectiveness Central nervous system disorders, 24, 25 alcohol abuse and, 284, 287–288 human immunodeficiency virus (HIV) infection and, 255–258 Child custody, 416 Children and adolescents, schizophrenia treatment in, 343– 375 adverse effects of, 346–369, 351, 370 management of, 355–361, 365– 369, 370

Index antipsychotic medication dosage, 344–345 antipsychotic medication efficacy, 345–346 developmental considerations in, 344–345 dyslipidemia and, 155 lifestyle interventions, 356, 362– 364, 366–368 QTc interval prolongation in, 354–355 weight and metabolic parameters for, 355–366, 358–359, 360–361 Chlorpromazine effect on glucose levels, 97 effect on serum lipids, 123 reproductive safety of, 421 secretion in breast milk, 428 and sexual dysfunction, 315 typical antipsychotics and, 123– 125 Cholesterol, total, 51, 58, 119. See also Hypercholesterolemia; National Cholesterol Education Program Cholinergic receptor antagonists, 311 Cirrhosis, 262, 287, 288 Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE), 37–57, 41, 42–43, 66, 95, 98, 99, 118, 124, 129, 130, 190, 277, 278, 279, 295 baseline data, 40–44 buildup to, 38–40 cardiovascular risk estimates of, 41 demographics of, 40 health care access data of, 41, 44 hyperprolactinemia data, 315, 317 inflammatory marker data, 49, 55 phase 1, 38, 44–53, 46, 47, 48, 50, 51, 52 phase 2 , 38, 39, 47, 50, 51, 52, 53, 54 phase 3, 39, 53 purpose of, 37

439

sexual dysfunction data, 316, 317, 318 Clinics, integrated-care, 8–10 Clozapine cardiovascular effects of, 100, 184–189 in combination with benzodiazepines, 184–185 and diabetes mellitus risk, 99–100, 106–107, 109 and diabetic ketoacidosis, 99, 101–102 effect on cognitive function, 98 effect on heart rate variability, 180 effect on serum lipids, 46, 53, 125– 127, 137, 139–143, 148, 149, 153, 159 effect on sexual function, 320–321 effect on sugar intake, 95–96 effect on weight, 39, 46, 47, 70, 71, 80–81, 100, 104, 156, 181, 204, 212, 347–348, 351 fetal/neonatal risks associated with, 423 and glucose intolerance, 99, 381 and hypertension, 192 and insulin resistance, 157 metabolic disorder treatment and, 196 metabolic profile of, 39 as resistant schizophrenia treatment, 107 smoking cessation and, 227, 236 as substance abuse treatment, 294 and sudden cardiac death risk, 184–185 treatment resistance and, 91 use in pediatric schizophrenia patients, 345–346, 347–348, 351, 359 Cocaine, 277 medical consequences of, 288–289 prevalence of abuse of, 171 schizophrenia and, 283–284

440

Medical Illness and Schizophrenia

Cognition, nicotine and enhancement of, 229–230 Cognitive-behavioral therapy, for weight loss, 206, 208, 211, 215 Cognitive deficits, 401–402 alcohol abuse and, 288 effect of atypical antipsychotics on, 98 hepatitis C and, 262 human immunodeficiency virus (HIV) infection and, 255–258, 256–258 nicotinic acetylcholine receptor treatment for, 226 Cognitive status monitoring, 402– 403 Comorbidity, health care access and, 4–5 Competency, 401–403 Condoms, 248–249, 252, 264, 326 Congenital malformations antipsychotics and, 422–425 prevalence of, 420 Congestive heart failure, 384 Contraceptives, 311, 326, 416, 425– 426 condoms, 248–249, 252, 264, 326 Coronary artery disease (CAD), 94 in aging persons with schizophrenia, 384 cannabis and, 290 Coronary heart disease (CHD), 103, 169 antipsychotics and, 190–191 hyperlipidemia and risk of, 119– 123 management of, 192–197 obesity and risk of, 64, 65 risk estimation for, 41 Cortisol, 389 C-reactive protein, 49, 53, 55 Cumulative Illness Rating Scale for Geriatrics, 379 Cytochrome P450 (CYP) enzymes CYP1A2, 226–227, 394

CYP3A4, 394 CYP2D6, 394 drug interactions of, 397 genetic polymorphisms of, 395– 396 Cytokines, 386 Death, sudden cardiac, 169, 170–171, 175–176, 173, 182, 184–186, 383. See also Mortality Delirium tremens (DTs), 287–288 Dementia, 398, 402 human immunodeficiency virus (HIV) infection and, 255–258 Dementia praecox, 17 Dental care, 399 Depression, 28 in cocaine users, 289 lack of health care and, 399 metabolic disorders and, 44 and sexual dysfunction, 309 substance abuse and, 281 in suicidal persons, 21 Diabetes awareness and rehabilitation training (DART) program, 5–6 Diabetes mellitus. See also Diabetic ketoacidosis; Glucose intolerance; Hyperglycemia; Insulin resistance in aging patients with schizophrenia, 378–379, 380– 383 antipsychotics and, 39, 70, 99–100, 107–108, 381–382 atypical antipsychotics and, 3, 91– 92, 98–103 behavioral management of, 214 cancer associated with, 378–379 cardiovascular complications of, 94, 117–118, 383, 384 CATIE data on, 40 diagnostic criteria for, 92–93 monitoring and screening of, 105– 108

Index and mortality, 18, 25, 25, 26, 27, 29 neurological complications of, 94 obesity and risk of, 64, 65, 205, 215 ophthalmic complications of, 94 pathophysiology of, 9–93 in pediatric schizophrenia patients, 346, 367 prevalence of, 27–28, 41, 118, 170– 171, 380–381 prevention of, 215 renal complications of, 94 respiratory disease associated with, 378–379 schizophrenia and risk of, 203– 204 and sexual dysfunction, 309 treatment for, 382 in pediatric schizophrenia patients, 368 pharmacological treatment, 65 type 1, 92, 93 negative correlation with schizophrenia, 386 in unmedicated schizophrenic persons, 96 Diabetes Prevention Trial, 205 “Diabetic foot,” 94 Diabetic ketoacidosis, 92, 93–94, 99, 100, 101–102, 103, 107 definition of, 94 screening for, 106 Diet American Heart Association Step II, 214–215 and diabetes mellitus risk, 95–96 effect of antipsychotics on, 95–96 evaluation of, 74 high-fat, low-fiber, 30 and mortality risk, 17 in obesity treatment, 206, 208, 209–212, 213–215 for pediatric schizophrenia patients, 362–364, 367 role in obesity, 68–69, 74, 205, 206, 367

441

Digoxin effect on sexual function, 311 renal clearance of, 396 methoxybenzylidene anabaseine, 226 Diuretics effect on serum lipids, 155 effect on sexual function, 311 Dopamine cocaine abuse and, 288–289 role in sexual function, 309 substance abuse and, 284, 285 Dopamine agonists, 330, 368–369 Dopamine D2 receptor(s), 315 Dopamine D2 receptor agonists, 319, 320 Dopamine D2 receptor antagonism, 316 Dopamine receptor(s), 396 Dopamine receptor antagonism, role in sexual function, 309 Dopamine receptor antagonists and breast cancer risk, 313 and hyperprolactinemia risk, 315, 326–327 Dopaminergic neurons, 225 Down syndrome patients, 207 Drug(s), therapeutic. See also Pharmacodynamics; Pharmacogenetics; Pharmacokinetics; names of specific drugs and drug classes absorption, 393 clearance, 394 distribution to peripheral sites, in elderly, 393 effect on sexual function, 311 metabolism, 394 teratogenic, 419–425, 421 Drug abuse. See also Substance abuse disorders; specific drugs of abuse central nervous system effects of, 284 during pregnancy, 416 Drug interactions, 396–397

442

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Drug interactions (continued) effect on cognition, 402–403 Drug-seeking behavior, 281 Dual diagnoses. See Substance abuse disorders, in patients with schizophrenia Duloxetine, effect on sexual function, 321 Dyslipidemia, 94–95. See also Hyperlipidemia and cardiovascular disease risk, 191 in pediatric schizophrenia patients, 352, 360–361, 367, 368 prevalence of, 41, 170–171 undertreatment of, 118 Edema, pulmonary, 4–5 Efavirenz, neuropsychiatric side effects of, 267 Ejaculatory disorders, 306, 309, 310– 311, 312–313, 314, 320–321, 328– 329 Elderly. See Aging persons; Aging persons with schizophrenia Electrocardiography (ECG), 177, 183–184 Endocrine disorders, and mortality, 24, 26 Endocrine system, role in sexual function, 309 Endometrial cancer, 313–314 Energy balance, 66–67, 68 Environment, “obesogenic,” 69 Epidemiologic Catchment Area (ECA) study, 276, 277 Erectile dysfunction, 305, 306, 309, 312–313, 314, 315, 318, 332 smoking and, 312 treatment for, 329–330, 332–333 Estrogen, 389 Exercise, 69 health benefits of, 215–216 in pediatric schizophrenia patients, 364

role in weight management, 205, 206, 209–212, 214–216 Extrapyramidal side effects, of antipsychotics, 29, 91, 309 in pediatric schizophrenia patients, 346 Family medicine, psychiatrists’ training in, 9–10 Family planning, 416–417, 425. See also Contraceptives Famotidine, as weight loss medication, 80–81 D-Fenfluramine, as weight loss medication, 80–81 Fetus, antipsychotic drug exposure in, 419–425, 421 Fluoxetine, as weight loss medication, 80–81 Fluperlapine, 125, 132 Fluphenazine effect on serum lipids, 133, 140 reproductive safety of, 421 sexual function effects of, 318 Fluphenazine decanoate, 278 Follicle-stimulating hormone (FSH), 312 Food and Drug Administration, U.S., (FDA), 38–39, 39, 420, 421 Food aspiration, as mortality cause, 23 Framingham Heart Study, 121, 196– 197 cardiovascular disease risk algorithm of, 118, 192–193, 194–195 Fusion inhibitors, 260 Gabapentin, renal clearance of, 396 Galactorrhea, 306, 312–313, 314, 316, 330 Galantamine hydrobromide, 226 Gallbladder cancer, 25 Gastrointestinal cancer, in aging persons with schizophrenia, 386, 387

Index Gastrointestinal disorders, as mortality cause, 24, 25 Genetic factors. See also Pharmacogenetics in diabetes mellitus, 93 in schizophrenia, 284, 395 Genitourinary diseases, 28 as mortality cause, 24, 25 Genotyping, 253 Gentamicin, renal clearance of, 396 Geodon. See Ziprasidone Glucose, plasma levels of fasting, 42–43, 53, 56, 63, 92, 357, 358–359, 365 monitoring of, 107 Glucose intolerance, 91–115, 108 in aging persons with schizophrenia, 381 antipsychotics and, 99, 381 atypical antipsychotics and, 91– 92, 98, 99 conventional antipsychotics and, 96–97 definition of, 92 medical complications of, 93–96 in unmedicated schizophrenic persons, 96 Glucose metabolism, pharmacological improvement of, 104 Glucose monitoring, in pediatric schizophrenia patients, 358–359, 360–361, 365 Glycohemoglobin, 48, 107 Gonadotropin-releasing hormone (GRH), 312, 354 Gynecomastia, 306, 312–313, 314, 316, 318–319 Hallucinations, 21, 282–283, 286, 287 Hallucinogens, 277 Haloperidol cardiac effects of, 182 and diabetes mellitus, 97 effect on bone mass density, 313

443

effect on prolactin levels, 354 effect on serum lipids, 123, 132, 133, 135, 137, 138, 140, 141 effect on sexual function, 315, 331 effect on weight, 71, 210, 348 fetal/neonatal risks associated with, 425 and hyperprolactinemia, 314–315, 316–317 reproductive safety of, 421 use in pediatric schizophrenia patients, 343–346, 348, 354 Health care compliance with, 30, 397 for the geriatric population, 384, 397–403 integration with psychiatric care, 2–12 patients’ utilization of. See Health care access Health care access effect of health insurance coverage on, 399 of homeless persons, 31–32 lack of, 4–5, 10–11, 31–32, 41, 44, 196, 397–403, 398 models for improvement of, 5–10 obstacles to, 398 Health care costs of the geriatric population, 397– 398, 400 obesity and, 65 Health care insurance coverage. See also Medicaid; Medicare for antipsychotic medication, 398–399 carved-in/carved-out programs of, 400 effect on health care access, 399 lack of, 11 for psychiatric care, 398 Health care proxy, 401 Health care skills training, 5–6, 12 Health habits, 30 Health maintenance, 29–32

444

Medical Illness and Schizophrenia

Health status, self-reported, 391–392 Heart. See also Cardiovascular disease electrophysiology of, 171–173, 172 Heart rate variability, 180 Height measurement, 356, 358–359 Hemoglobin, glycosylated, 48 Hepatitis B, substance abuse and, 279, 288 Hepatitis C, 259, 261–264 alcohol abuse and, 288 comorbidity with human immunodeficiency virus (HIV) infection, 261, 269 course of, 259 natural history of, 261 neuropsychiatric manifestations of, 262 prevalence of, 248 psychiatric patients’ knowledge about, 250 psychopharmacology for, 267, 268, 269 risk assessment for, 265–266 risk reduction strategies for, 264, 265 substance abuse and risk of, 250, 279 testing for, 261, 267, 270 transmission of, 259 treatment for, 262–264, 263 Herbal preparations as hyperprolactinemia treatment, 331–332 interaction with antiretroviral therapy, 268 Heroin, 283–284 High-density lipoprotein (HDL), 41, 43, 119, 154 Histamine receptor(s), 71–72 Histamine receptor agonists, as weight loss medication, 79 Histamine receptor antagonists and sexual dysfunction, 312

as weight loss medications, 79, 80–81 Homeless persons, with schizophrenia, 4 mortality rates in, 31–32 substance abuse among, 278, 286 substance abuse treatment for, 292, 293–294 Hospitalization effect on cancer mortality rate, 388 during pregnancy, 417, 427 rate of, 28 for respiratory disease, 385 of schizophrenia patients, 383– 384 of substance-abusing patients, 285 Human immunodeficiency virus (HIV) infection, 247–274, 289 access to patient services for, 265– 266, 267 antiretroviral therapy for, 255, 258– 259, 260, 264, 267–268, 269 CD4 T-cell count in, 251, 253, 254 comorbidity with hepatitis C, 261, 269 confidentiality regarding, 266 counseling for, 266 course of, 250–251 infection rates of, 326 natural history of, 253–254 neuropsychiatric manifestations of, 255–259 opportunistic infections associated with, 254, 255 perinatal transmission of, 264 prevalence of, 248 psychiatric patients’ knowledge about, 250 risk assessment for, 265–266 risk reduction strategies for, 264– 265 sexual risk behaviors and, 248– 249, 250

Index substance abuse and risk of, 249– 250, 279–280 support group-based interventions for, 266 symptoms of, 254 testing for, 252–253, 266, 270 transmission of, 251–252, 264 treatment for, 255, 258–259, 260, 261, 264, 267–268, 269 viral load in, 253 Human immunodeficiency virus (HIV) vaccine, 251 Hypercholesterolemia, statin therapy for, 120 Hyperglycemia, 92, 93, 96, 97, 101, 105, 109 atypical antipsychotics and, 3–4 in pediatric schizophrenia patients, 360–361, 365, 367, 368 screening for, 106 Hyperinsulinemia, 93 Hyperlipidemia, 117–167 and coronary heart disease risk, 119–123 mechanisms of, 155–157, 159 monitoring of, 157–158, 159 obesity and, 64 patient variables in, 155–157, 159 in pediatric schizophrenia patients, 360–361 second-generation antipsychotics and, 39 typical antipsychotics and, 125– 159 Hyperprolactinemia, 389–390 and cancer risk, 312–314 first-generation antipsychotics and, 314–315 monitoring for, 326–327 and osteoporosis risk, 313 in pediatric schizophrenia patients, 346, 353–354, 368– 369, 370

445

second-generation antipsychotics and, 315 and sexual dysfunction, 312–313 treatment for, 328–332, 368–369 Hypertension, 365 in aging patients with schizophrenia, 384 alcohol abuse and, 288 antipsychotics and, 192 and cardiovascular disease risk, 94–95, 120–121 complications of, 4–5 definition of, 192 as metabolic syndrome component, 63 obesity and risk of, 64, 65, 95 in pediatric schizophrenia patients, 358–359, 367 prevalence of, 27–28, 41, 43, 118 and sexual dysfunction, 309 treatment for, 65, 193, 382 effect on sexual function, 310– 311 undertreatment for, 118 untreated, 399 Hyperthermia, benign, 186 Hypertriglyceridemia, 50, 63, 64, 102 alcohol abuse and, 288 atypical antipsychotics and, 125– 129, 155 and cardiovascular disease risk, 383 fasting versus nonfasting, 122–123 insulin resistance and, 121–122, 156–157 in pediatric schizophrenia patients, 350 prevalence of, 118 typical antipsychotic medication and, 124–125 Hypogonadism, 354 hypogonadotropic, 389 Hyponatremia, 388–389 Hypotension, orthostatic, 189–190

446

Medical Illness and Schizophrenia

Immune dysfunction in aging patients with schizophrenia, 385–386 human immunodeficiency virus (HIV) infection and, 253–254 Immunosuppression, 254, 261 Impulsivity, 281 Infectious diseases, 17, 24, 25, 25, 386 Inflammatory markers, of cardiometabolic risk, 49 Insulin resistance, 92–93, 94–95, 97, 100, 102–103, 105, 204 homeostatic model assessment (HOMA) of, 360–361, 365 hypertriglyceridemia and, 121– 122, 156–157 obesity and risk of, 64 in pediatric schizophrenia patients, 350, 352, 360–361, 365 Integrated-care clinics, 8–10 Intercontinental Schizophrenia Outpatient Health Outcomes, 316 Interferon, neuropsychiatric side effects of, 262–263 Internal medicine, psychiatrists’ training in, 9–10 International Physical Activity Questionnaire, 74 Intravenous drug abuse, 44, 250, 252, 259, 264, 279–280 Ion channels, 172 “Is There a Stethoscope in the House (and Is It Used?)” (McIntyre and Romano), 6–7 Kraepelin, Emil, 17 Leptin, 67, 72, 102–103 Libido, decrease in, 305, 306, 309, 312–313, 314, 316, 317 Life expectancy, 18, 44, 64, 169, 203, 355–356, 390 Lifestyle

and obesity, 68–69 sedentary, 30, 68, 69, 93, 169 unhealthful, 30 Lifestyle interventions for coronary heart disease management, 192–193 for obesity management, 6, 74, 208–215 with pediatric schizophrenia patients, 356, 362–364, 366–368 Limbic system, role in sexual function, 309 Lipid-lowering drugs, 65, 382 See also Statins Lipid monitoring, in pediatric schizophrenia patients, 357, 358–359, 365 Lipoproteins, 63, 122, 352, 361 Lithium, renal clearance of, 396 Lithium carbonate, effect on weight, 76 Liver, as drug metabolism site, 268, 394 Liver disease, alcohol abuse and, 287, 288 Lovastatin, 120 Low-density lipoprotein (LDL), 119, 120–121 Lung cancer, 24, 25 in aging persons with schizophrenia, 386–387 smoking and, 233 Luteinizing hormone (LH), 312 Marijuana. See Cannabis (marijuana) Maudsley Prescribing Guidelines, 183 Medicaid, 397–398, 400 Medical care. See Health care Medical conditions, untreated, 398 Medicare, 397–398, 399, 400 drug coverage benefits of, 399, 400–401 Menstrual irregularities, 306–307, 312–313, 316–317, 318–319, 328– 329

Index treatment for, 330, 331–332 Mental health care. See Psychiatric care Metabolic disorders. See also Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE); specific metabolic disorders atypical antipsychotics and, 29 and cardiovascular disease, 169, 170 and depression, 44 in pediatric schizophrenia patients, 346, 350, 352, 353, 366–367 prevention and management of, 77 Metabolic monitoring, 171 in obese patients, 73–74, 75 Metabolic syndrome, 63–64, 66, 94– 95, 98 CATIE data on, 40, 41, 42–43, 48– 49 diagnostic criteria for, 37–38 in pediatric schizophrenia patients, 353, 357, 360–361, 370 prevalence of, 40, 42–43 Metformin in combination with quetiapine, 138 as weight loss medication, 6, 79, 80–81, 212, 214–215, 368 Methadone, 268 Methamphetamine(s), 283–284 d-Methamphetamine, 288 3,4-Methylenedioxymethamphetamine (“ecstasy”), 283– 284 Mirtazapine effect on sexual function, 321 effect on weight, 76 Molindone, 345–346, 349–350 Mood-stabilizing agents effect on sexual function, 321

447

effect on weight, 61, 76 Morbidity, in persons with schizophrenia, 27–29 cardiovascular, 118–119 substance abuse and, 28–29 Mortality/mortality rates, in persons with schizophrenia, 17–20, 23, 25 in aging persons with schizophrenia, 390–391 antipsychotics and, 29–30 cancer and, 3, 23, 24, 25, 25, 387– 388 cardiovascular disease and, 18, 23, 24, 25, 25, 26–27, 100, 118– 119, 169, 181, 190, 269, 384 causes of, 391 historical background to, 17–18 natural causes of, 19, 22, 23, 23– 27, 25 premature, 17 relationship to health care quality, 384 substance abuse and, 28–29 unnatural causes of, 19, 20–22, 23 Motor effects, of antipsychotic medications, 395 Multiple Risk Factor Intervention Trial (MRFIT), 119–120 Musculoskeletal disorders, 28, 389–390 Myocardial infarction antipsychotics and, 5, 191, 383 cannabis and, 290 diabetes mellitus and risk of, 94 inadequacy of care for, 31, 384 as mortality cause, 4, 170, 180 painless, 196–197 statins and, 120 Myocarditis, 185–186, 189 National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (ATPIII), 43, 95, 120–121

448

Medical Illness and Schizophrenia

National Comorbidity Survey, 276 National Health and Nutrition Examination Survey (NHANES) III, 40, 41, 41, 43, 66 National Health Interview Schedule, 66 National Health Interview Survey, 27–28 National Heart, Lung, and Blood Institute, 63 National Institute of Mental Health (NIMH), 6, 8, 37 National Institutes of Health, 204 National Patient Care Database, 379 Negativism, 17 Nephropathy, diabetic, 94 Neurocognitive deficits. See Cognitive deficits Neuroleptics. See also Antipsychotics; Atypical antipsychotics; names of specific antipsychotics anticarcinogenic activity of, 387– 388 atypical, 382 overdose, as suicide method, 21 smoking and, 282 teratogenicity of, 421 Neurological disorders diabetes mellitus and, 94 as mortality cause, 24, 25 Neuropathy, as sexual dysfunction cause, 309 Neuropeptide Y, 67 Neurotransmitters, effect of nicotine on, 224–226 Nevirapine, neuropsychiatric side effects of, 267 NHANES. See National Health and Nutrition Examination Survey Nicotine. See also Smoking cognition-enhancing effects of, 229–230 pharmacological effects of, 224– 226

use by persons with schizophrenia, 277 Nicotine addiction/dependence comorbidity with schizophrenia, 224 treatment for, 295 Nicotine replacement therapy, 234– 236 Nicotine transdermal patch (NTP), 228, 230, 233, 234–236, 237 Nicotinic acetylcholine receptors, 224–226, 228, 229 Nizatidine, as weight loss medication, 80–81 Non-nucleoside reverse transcriptase inhibitors, 260 North American Association for the Study of Obesity, 39 Nucleoside/nucleotide reverse transcriptase inhibitors, 260 Obesity, 61–90 antipsychotics and, 61–62, 69–72, 74–78, 309 atypical antipsychotics and, 3 and cardiovascular disease risk, 383 during childhood, 344 definition of, 62 determinants and mechanisms of, 66–72 and diabetes mellitus risk, 93, 95, 96, 103 duration of, 96 economic cost of, 65 epidemiology of, 65–66 general and evolutionary factors in, 66–67 genetic factors in, 68, 72 health consequences of, 64–65 and hypertension risk, 95 lifestyle factors in, 68–69 measurement of, 62–64, 72–73 metabolic monitoring in, 73–74, 75

Index neurophysiological factors in, 68 “obesogenic” environment and, 69 in pediatric schizophrenia patients, 347, 360–361, 366–368 prevalence of, 30, 61, 65–66, 118, 170–171 prevention and management of, 72–73, 76–83, 206 behavioral treatment, 203–222, 206, 209–212 combined behavioral/ pharmacological treatment, 216 diet, 206, 208, 209–212, 213–215 exercise, 205, 206, 209–212 lifestyle interventions, 74 pharmacological treatment, 76–82, 216, 368 surgical treatment, 82 “thrifty phenotype hypothesis” of, 67 Olanzapine and cardiovascular disease risk, 98 CATIE data on, 44–53 and diabetes mellitus risk, 3–4, 39, 101, 109 as diabetes monitoring indication, 106–107 and diabetic ketoacidosis, 99, 101–102 effect on cholesterol levels, 46, 51, 53 effect on cognitive function, 98 effect on C-reactive protein levels, 49, 53, 55 effect on diet, 95–96 effect on heart rate variability, 180 effect on metabolic syndrome status, 48, 49 effect on prolactin levels, 328, 354 effect on QTc interval, 45, 52 effect on serum lipids, 101, 124, 127–129, 131, 135–151, 153, 154, 155, 159

449

effect on smoking cessation, 230, 236 effect on triglyceride levels, 48– 49, 50 effect on weight, 44–45, 46, 47, 54, 76–78, 79, 80–81, 98, 101, 102– 103, 104, 105, 156, 204, 209– 212, 213 fetal/neonatal risks associated with, 422–423, 425 and glucose intolerance, 381 and hyperprolactinemia, 316 and hypertension, 192 and insulin resistance, 102–103, 157 metabolic profile of, 39, 44–53 secretion in breast milk, 428 sexual function effects of, 316–317 as substance abuse treatment, 294, 295 use in aging schizophrenia patients, 3–4 use in pediatric schizophrenia patients, 345–346, 354 Older adults. See Aging persons; Aging persons with schizophrenia Older Americans Resources Survey, 392 Oligomenorrhea, 312–313 Ophthalmic disorders, diabetes mellitus and, 94 Opiates, 277 Oregon Health and Science University, 7 Orlistat, as weight loss medication, 78 Osteoporosis, 313, 354 Overdose, as suicide method, 21 Oxford Record Linkage Study, 383 Pain sensitivity, 196–197 Paliperidone, 294–295 and hyperprolactinemia, 319–320 sexual function effects of, 320

450

Medical Illness and Schizophrenia

Parkinsonism, 28, 29, 278–279 Patient Outcomes Research Team (PORT) program, 27–28, 379, 381, 382, 392 Peony-Glycyrrhiza Decoction (PGD), 330, 332 Peptic ulcers, 19 Pericarditis, 185–186 Peripheral nervous system, role in sexual function, 309, 311–312 Perphenazine CATIE data on, 44–53, 98 effect on cholesterol levels, 51 effect on C-reactive protein levels, 49, 53, 55 effect on metabolic syndrome status, 48, 49 effect on QTc interval, 45, 52 effect on serum lipids, 124, 153, 154 effect on total cholesterol levels, 46, 51, 53 effect on triglyceride levels, 48– 49, 50 effect on weight, 44–45, 46, 47, 78 metabolic profile of, 44–53, 98 reproductive safety of, 421 sexual function effects of, 331 Pharmacodynamics in aging persons, 394–395 in pediatric schizophrenia patients, 344 Pharmacogenetics, 395–396 Pharmacokinetics in aging persons, 392–394 effect of smoking cessation on, 226–227 Phenothiazines, 23 anticarcinogenic activity of, 25, 388 and diabetes mellitus risk, 97 effect on serum lipids, 123, 132, 133, 155, 159 effect on sexual function, 315 teratogenicity of, 422

Phenotyping, 253 Phenylpropanolamine, as weight loss medication, 81 Phosphodiesterase type 5 inhibitors, 329–330, 332–333 Physical activity, 74. See also Exercise for weight loss, 367 Physical health care, for patients with mental illness, 3–15 Physical inactivity. See Sedentary lifestyle Pimozide, 184 Pituitary tumors, 313, 354 Placenta, drug diffusion across, 419– 420 Pneumonia, 19, 384–385 Polycystic ovarian disease, 64 Polydipsia, 92, 109, 388–389 Polypharmacy, 29, 417 Polyuria, 92, 109 Positive and Negative Syndrome Scale (PANSS), 281, 345 Postpartum period, 415, 417–418, 427 Pravastatin, 120 Prediabetes, 365 Pregnancy, in women with schizophrenia, 415–427 antipsychotic therapy discontinuation during, 415– 416, 418–419, 415–427 maternal outcomes in, 417–419 obstetric complications risk in, 419 treatment for schizophrenia during, 415–416, 418–419, 425–427 unplanned/unwanted, 326, 416 Priapism, 306, 311, 315, 318–319 Primary care integration with mental health treatment, 1, 3, 8<150>10, 12 referrals to, 7, 8, 12 Primary care physicians behavior toward older patients, 399–400 psychiatrists as, 401

Index Primary care training, for psychiatrists, 6–7, 8–10, 12 Procainamide, renal clearance of, 396 Prolactin. See also Hyperprolactinemia function of, 312 Prostate cancer, 24, 387 Protease inhibitors, 155, 260 Proxy, for health care, 401 Psychiatric care integration with primary care, 8–10, 12 lack of health insurance coverage for, 398 Psychiatrists, as primary care physicians, 6–7, 8–10, 12, 401 Psychological Well-Being Index, 64 Psychomimetic agents, 283 Psychosis cannabis and exacerbation of, 285–286 cocaine and, 289 drug and, 282–283, 284 postpartum, 418, 427 substance abuse and, 285 in suicidal persons, 21 Psychotropic medications, teratogenicity of, 419–421 QRS complex, 171–172 QTc interval, estimation of, 179–180 QTc interval prolongation, 169–170, 173, 175–179 antipsychotics and, 45, 52, 55, 180–184, 181, 189 CATIE data on, 45, 52, 55 clozapine and, 189 estimation of, 176–179, 178, 183– 184 nonclozapine antipsychotic medication and, 189–190 in pediatric schizophrenia patients, 354–355, 369 QT dispersion, 179 Quality of life, 64, 95, 308

451

Quetiapine and cataract risk, 45 CATIE data on, 44–53 and diabetes mellitus risk, 3–4, 101 effect on cholesterol levels, 46, 51, 53 effect on cognitive function, 98 effect on C-reactive protein levels, 49, 53, 55 effect on metabolic syndrome status, 48, 49 effect on prolactin levels, 317, 328 effect on QTc interval, 45, 52 effect on serum lipids, 129–131, 137–141, 153, 154, 156–157, 159 effect on sexual function, 317–318, 328 effect on triglyceride levels, 48– 49, 50 effect on weight, 44–45, 46, 47, 54, 70, 78, 98, 105, 348–349, 352 fetal/neonatal risks associated with, 422–423, 425 and glucose intolerance risk, 101 metabolic profile of, 39, 40, 44–53 as substance abuse treatment, 294 use in pediatric schizophrenia patients, 348–349, 350 Quinidine, 172 Reboxetine, as weight loss medication, 78–79, 81 Rectal cancer, 24 Referrals, to primary care, 7, 8, 12 Relapse, during postpartum period, 417–418 Renal disorders, diabetes mellitus and, 94 Residency programs, 7, 10 Respiratory disorders in aging patients with schizophrenia, 378–379, 384– 385

452

Medical Illness and Schizophrenia

Respiratory disorders (continued) cannabis and, 290 cocaine and, 289 hospitalization for, 383–384 as mortality cause, 24, 25 “Reward pathway,” 225, 289 Rheumatoid arthritis, 28, 385–386 Ribavarin, neuropsychiatric side effects of, 262–263 Rimonabant, as weight loss medication, 79 Risperidone and cancer risk, 313 CATIE data on, 44–53 and diabetes mellitus risk, 3–4, 101 effect on cholesterol levels, 46, 51, 53 effect on cognitive function, 98 effect on C-reactive protein levels, 49, 53, 55 effect on metabolic syndrome status, 48, 49 effect on prolactin levels, 315, 330, 354 effect on QTc interval, 45, 52 effect on serum lipids, 98, 128, 129, 130, 136–150, 151, 153, 154, 156, 157, 159 effect on smoking cessation, 230 effect on triglyceride levels, 48– 49,50 effect on weight, 44–45, 46, 47, 54, 70, 76, 77, 78, 98, 101, 105, 210, 213, 348–350, 351, 352 fetal/neonatal risks associated with, 422–423, 425 and glucose intolerance risk, 101 metabolic profile of, 39, 40, 44–53 and pituitary tumor, 313 sexual function effects of, 315– 316, 317–318, 328 as substance abuse treatment, 294 use in pediatric schizophrenia patients, 343–344, 345–346, 348–350, 351, 354

Scandinavian Simvastatin Survival Study, 120 Schizophrenia. See also specific disorders and conditions associated with schizophrenia prevalence of, 377, 378 Sedation, 309, 312 Sedatives/hypnotics, 277 Sedentary lifestyle, 30, 68, 69, 93, 169 Selective serotonin reuptake inhibitors (SSRIs) effect on sexual function, 311–312, 321 effect on weight, 76, 80–81 Selegiline, 331 “Self-medication” hypothesis of smoking, 229 of substance abuse, 280–281, 282, 296 Seroquel. See Quetiapine Serotonin (5-HT), 289 Serotonin agonists, and sexual dysfunction, 311–312 Serotonin antagonism, 125 Serotonin receptors, 102, 103 Serotonin syndrome, 368 Sertindole, cardiac effects of, 176, 182, 184 Sex exchange behaviors, 248–249, 326 Sexual development, 353–354 Sexual dysfunction, 303–342 adjunctive treatment for, 329–332 in adolescent schizophrenia patients, 353–354 antipsychotics and, 304–305, 306– 309, 310–311, 311–323 assessment of, 322–323, 324–325 effect on patient outcomes, 307– 308 etiology of, 308–313 first-generation antipsychotics and, 314–315 gender differences in, 306–308, 333 management of, 326–333 neurobiology of, 309, 311, 312

Index patient-physician discussions of, 304 prevalence of, 303–305, 333 risk factors for, 333 second-generation antipsychotics and, 315–321 types of, 305–306 underestimation of, 303–304, 305 Sexual function, physiology of, 309, 311–312 Sexually transmitted diseases (STDs), 249, 252 Sexual risk behaviors, 248–249, 264– 265 Sibutramine, 104, 105 use in pediatric schizophrenia patients, 368 as weight loss medication, 78, 79, 80–81, 104 Sildenafil (Viagra), 329 Sinus tachycardia, 188 Skin cancer, 24 Smoking, 223–243, 277 and calcium deficiency risk, 389 of cannabis, 290 and cardiovascular disease risk, 120–121, 169, 190–191, 312, 383 of cocaine, 288, 289 cognitive function effects of, 229– 230 effect on antidiuretic hormone release, 389 effect on auditory information processing defects, 228–229 effect on mortality rate, 391 effect on schizophrenia symptoms, 227–230 and erectile dysfunction risk, 312 harm reduction approach to, 232 and lung cancer risk, 24, 387 neuroleptic medication and, 282 during pregnancy, 416 prevalence of, 30, 41, 118, 170– 171, 223–243, 312 as “self-medication,” 229

453

Smoking cessation, 223–224, 227 effect of typical versus atypical antipsychotics on, 230–231 effect on schizophrenia symptoms, 228 pharmacokinetic effects of, 226–227 pharmacotherapy for, 233–237, 235, 236 strategies for, 231–237, 234–236 Statins, 119 cardioprotective effects of, 120 Stimulant abuse, 283, 285–286, 289 Stroke, 94 Substance abuse disorders, in persons with schizophrenia, 275–302. See also Alcohol abuse; Drug abuse biological basis for, 280–281, 296 comorbidity with human immunodeficiency virus (HIV) infection, 249–250, 252 demographics of, 275–280, 285 effect on course of schizophrenia, 283–287 effect on development of schizophrenia, 282–287 in homeless persons, 287 medical consequences of, 29, 287– 290 and mortality, 29 patterns of, 280–283 prevalence of, 44, 171, 296 screening for, 290–291, 296 “self-medication” hypothesis of, 280–281, 282, 296 social functioning and, 275 suicide and, 22 treatment for, 291–296 in urban versus rural populations, 275–280 Sudden cardiac death, 169, 170–171, 175–176, 173, 182, 184–186, 383. See also Mortality Suicide, 17–18, 19, 20–22, 23, 32, 287, 289, 417

454

Medical Illness and Schizophrenia

Survival curve, 20 Sympathetic nervous system, role in obesity, 68 Syndrome X. See Metabolic syndrome Tardive dyskinesia, 44, 278–279, 281, 309 in pediatric schizophrenia patients, 346 Testosterone, 309, 312, 389 Tetratogenicity, of psychotropic medications, 419–425, 421 Thioridazine effect on heart rate variability, 180 effect on serum lipids, 133 effect on sexual function, 315 and QTc interval prolongation, 184 quinidine-like properties of, 172 reproductive safety of, 421 use in pediatric schizophrenia patients, 343–344 Thiorixene, use in pediatric schizophrenia patients, 345–346 Thioxanthenes, teratogenicity of, 422 Topiramate, as weight loss medication, 79, 81 Torsade de pointes, 171, 173–175, 174, 182 QTc interval prolongation and, 169–170, 174, 175–176, 178 risk factors for, 175 surrogate risk markers for, 175– 176, 179–180 Trazodone, effect on sexual function, 321 Treatment. See Health care Tricyclic antidepressants, effect on sexual function, 321 Trifluoperazine, reproductive safety of, 421 Triglyceride to high-density lipoprotein ratio, 121–122 Triglycerides, 43, 50, 63. See also Hypertriglyceridemia

fasting versus nonfasting levels of, 48–49 Tuberculosis, 17 Tumors. See also Cancer prevalence of, 28 T-waves clozapine and changes in, 188–189 measurement of, 177, 179–180 Ulcers, diabetic foot, 94 Unemployment, 285 University of California at San Diego, 7 Valproate/valproic acid effect on weight, 76, 105 sexual function effects of, 321 Vardenafil, 329–330 Varenicline, 226, 235, 236, 237 Venlafaxine, 321 Verapamil, 176 Veterans Affairs (VA), 7, 9, 382 National Patient Care Database, 379 Viagra (sildenafil), 329 Violence as mortality cause, 19 toward pregnant women, 416 Virtual phenotyping, 253 Visual impairment, in aging persons with schizophrenia, 390 Waist circumference, as obesity measure, 43, 62–63, 64, 72–73 in pediatric schizophrenia patients, 357, 360–361, Weight gain. See also Obesity antipsychotics and, 61–62, 95, 100, 101, 102–103 atypical antipsychotics and, 3, 66, 98, 196 CATIE data on, 38–39, 44–47, 46, 47, 53, 54 determinants and mechanisms of, 66–67

Index effect on QTc interval, 178–179 in pediatric schizophrenia patients, 347–350, 362–364 Weight loss, 6 cocaine and, 289 unexplained, 92 Weight loss medications, 78–83, 80– 81 Weight measurement, 218 in pediatric schizophrenia patients, 356–357, 358–359 West of Scotland Coronary Prevention Study, 120 Women. See also Breastfeeding; Pregnancy body fat in, 63 metabolic syndrome in, 66 obesity in, 66 schizophrenia prevalence in, 415 sexual dysfunction prevalence in, 304, 305 substance abuse in, 277–278 Women’s Health Study, 122 World Health Organization (WHO), 63, 170 Ziprasidone, 3–4 cardiac effects of, 183, 184, 355 CATIE data on, 38–39, 44–53 effect on cholesterol levels, 46, 51, 53 effect on cognitive function, 98 effect on C-reactive protein levels, 49, 53, 55 effect on metabolic syndrome status, 48, 49 effect on prolactin levels, 318, 320, 354 effect on QTc interval, 45, 52, 176 effect on serum lipids, 101, 124, 130, 131, 144, 147–149, 151, 153, 154, 159 effect on sexual function, 318–319 effect on triglyceride levels, 48– 49, 50

455

effect on weight, 44–45, 46, 47, 54, 76, 101, 107 metabolic profile of, 38–39, 44–53 as substance abuse treatment, 295 use in pediatric schizophrenia patients, 354, 355, 359 Zotepine effect on serum lipids, 129, 130 effect on weight, 70, 130 Zyprexa. See Olanzapine