National Institute on Drug Abuse RESEARCH MONOGRAPH SERIES Statistical Issues in Clinical Trials for Treatment of Opiate Dependance U.S. Department of Health and Human Services1 • Public2 Health Service8 • National Institutes of Health Statistical Issues in Clinical Trials for Treatment of Opiate Dependence Editor: Ram B. Jain, Ph.D. NIDA Research Monograph 128 1992 U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES Public Health Service Alcohol, Drug Abuse, and Mental Health Administration National Institute on Drug Abuse 5600 Fishers Lane Rockville, MD 20857 ACKNOWLEDGMENT This monograph is based on the papers and discussions from a technical review on “Statistical Issues in Clinical Trials for Treatment of Opiate Dependence” held on December 2-3, 1991, in Bethesda, MD. The technical review was sponsored by the National Institute on Drug Abuse (NIDA). COPYRIGHT STATUS NIDA has obtained permission from the copyright holders to reproduce certain previously published material as noted in the text. Further reproduction of this copyrighted material is permitted only as part of a reprinting of the entire publication or chapter. For any other use, the copyright holder’s permission is required. All other material in this volume except quoted passages from copyrighted sources is in the public domain and may be used or reproduced without permission from the Institute or the authors. Citation of the source is appreciated. Opinions expressed in this volume are those of the authors and do not necessarily reflect the opinions or official policy of the National Institute on Drug Abuse or any other part of the US. Department of Health and Human Services. The U.S. Government does not endorse or favor any specific commercial product or company. Trade, proprietary, or company names appearing in this publication are used only because they are considered essential in the context of the studies reported herein. NIDA Research Monographs are indexed in the “Index Medicus.” They are selectively included in the coverage of “American Statistics Index,” “BioSciences Information Service,” “Chemical Abstracts,” “Current Contents,” “Psychological Abstracts,” and “Psychopharmacology Abstracts.” DHHS publication number (ADM)92-1947 Printed 1992 ii Contents Page Introduction 1 Ram B. Jain Drug Dependence (Addiction) and Its Treatment 6 Frank J. Vocci, Jerome H. Jaffe, and Ram B. Jain Background and Design of a Controlled Clinical Trial (ARC 090) for the Treatment of Opioid Dependence 14 Rolley E. Johnson and Paul J. Fudala Clinical Endpoints: Discussion Session 25 Ram B. Jain Design of Clinical Trials for Treatment of Opiate Dependence: What Is Missing? 29 Ram B. Jain Comments 37 Sudhir C. Gupta Rejoinder 42 Ram B. Jain Summary of Discussion 44 Ram B. Jain iii Efficacy of Urinalysis in Monitoring Heroin and Cocaine Abuse Patterns: Implications in Clinical Trials for Treatment of Drug Dependence 46 Edward J. Cone and Sandra L. Dickerson Comments 59 Nancy L. Geller Summary of Discussion 62 Ram B. Jain Open/Panel Discussion: Design Issues 64 Ram B. Jain A Bayesian Nonparametric Approach to Analysis of Treatment for Drug Dependence Data 70 Ram C. Tiwari Three Estimators of the Probability of Opiate Use From Incomplete Data 82 Alan J. Gross Summary of Discussion 95 Ram B. Jain Issues in the Analysis of Clinical Trials for Opiate Dependence 97 Dean Follmann, Margaret Wu, and Nancy Geller Summary of Discussion 114 Ram B. Jain Analysis of Clinical Trials for Treatment of Opiate Dependence: What Are the Possibilities? 116 Ram B. Jain Summary of Discussion 135 Ram B. Jain Toward a Dynamic Analysis of Disease-State Transition Monitored by Serial Clinical Laboratory Tests 137 T.S. Weng iv Summary of Discussion 158 Alan J. Gross A Markov Model for NIDA Data on Treatment of Opiate Dependence 160 Mei-Ling Ting Lee Summary of Discussion 168 Alan J. Gross Open/Panel Discussion: Analysis Issues 170 Ram B. Jain Open/Panel Discussion: General Issues 176 Ram B. Jain List of Participants 182 List of NIDA Research Monographs 186 v Introduction Ram B. Jain The Medications Development Division (MDD) of the National Institute on Drug Abuse (NIDA) came into existence in August 1990. Its mandate from the U.S. Congress is to develop medications for the treatment of drug dependence, primarily heroin and cocaine dependence. The organizational structure of MDD allows for five branches, one of which is the Biometrics Branch. I happened to be the first one to join the Biometrics Branch, and it was and still is a great learning opportunity for me. I found: Drug dependence is not a disease in the traditional sense that cancer or heart disease is; its treatment is not a treatment in the traditional sense-drug dependence is not treated the way a cancer or an infection is treated; and the characteristics of the data generated by clinical studies in drug abuse area are unique, not seen in other branches of medicine-a more than 50- percent dropout rate! The data generated by these studies are the product of a continuous dynamic interaction between the pharmacological effect of the therapeutic agent, the effect of nonpharmacological services provided as part of the total treatment, and most importantly, the drug-seeking behavior of the addict, which is shaped and influenced by the environmental stimuli around him or her. How does one statistically adjust for this multidimensional “noise”? What is being treated here is not quite obvious-Is it a medical condition, a mental disorder, a behavioral abnormality, or all of them at the same time? Between September 1988 and May 1990, Drs. Rolley E. Johnson and Paul J. Fudala conducted a randomized double blind, “double dummy” clinical trial (ARC 090) to evaluate the efficacy of 8 mg sublingual doses of buprenorphine compared with 20 mg and 60 mg oral doses of methadone in 162 patients. This study was conducted at NIDA’s Addiction Research Center (ARC). These data were provided to me for analysis. The primary data consisted of binary (positive vs. negative) data points obtained by assaying the urine samples for the presence of opiates. Since the urine samples were obtained three times a week from each patient in this 25-week study, each patient could provide up to 75 data points. Many endpoints could be defined and clinically defended using these data (e.g., percent-positive samples; a drug-free period of, say, 28 days or more), and several different statistical methods could be used to analyze them. After spending several months with these data, finding 1 myself more informed every day than the day before, I determined that more could be learned—I could use expert opinion from outside. During the summer of 1991, I began planning for a workshop (a NIDA technical review) in design and analysis of clinical trials in the treatment of opiate dependence. Many well-known statisticians, including those who had many years of experience in managing and analyzing clinical trials, were contacted and asked if they would like to write and present research papers on the design and analysis of clinical trials in the treatment of opiate dependence and/or participate in this workshop. Commitments were obtained for five research papers. Each paper was to present the results of analyzing a part of the ARC 090 data. I also decided to present two papers-one on design, one on analysis. The statisticians who agreed to write research papers and/or participate (and finally came to the workshop) included Drs. Joseph Collins (Veterans’ Administration Medical Center), Lloyd D. Fisher (University of Washington), Dean Follmann (National Heart, Lung, and Blood Institute [NHLBI]), Nancy L. Geller (NHLBI), Albert J. Getson (Merck Sharp & Dohme), Joel B. Greenhouse (Carnegie-Mellon University), Alan J. Gross (Medical University of South Carolina), Sudhir C. Gupta (Northern Illinois University), A.S. Hedayat (University of Illinois), Nicholas P. Jewell (University of California at Berkeley), Peter A. Lachenbruch (University of California, Los Angeles), Jack C. Lee (National Institute of Child Health and Human Development [NICHD]), Mei-Ling Ting Lee (Boston University), Shou-Hua Li (National Institute of Dental Research), Taesung Park (NICHD), Carol K. Redmond (University of Pittsburgh), Saul Rosenberg (NIDA), Vincent Shu (Abbott Laboratories), Richard Stein (Food and Drug Administration [FDA]), Ram C. Tiwari (University of North Carolina), L.J. Wei (Harvard School of Public Health), T.S. Weng (FDA), and Margaret Wu (NHLBI). Without the presence, interaction, guidance, and advice of clinicians working in the drug abuse area, talking about designing and analyzing clinical trials for treatment of drug dependence would have been an exercise in futility, and therefore we requested participation from well-known clinicians in government, industry, and academia. Those who agreed to participate (and came to the workshop) included Jack D. Blaine (NIDA), Robert J. Chiarello (NIDA), Edward J. Cone (ARC), Paul J. Fudala (University of Pennsylvania), Harold Gordon (NIDA), David A. Gorelick (ARC), Charles W. Gorodetzky (CIBA-Geigy Corporation), Charles V. Grudzinskas (NIDA), John Hyde (FDA), Donald R. Jasinski (Johns Hopkins University), Rolley E. Johnson (Johns Hopkins University), Michael Murphy (Hoechst Roussel Pharmaceutical, Inc.), Frank J. Vocci (NIDA), and Curtis Wright (FDA). 2 The NIDA technical review on “Statistical Issues in Clinical Trials for Treatment of Opiate Dependence” took place on December 2-3, 1991, at the Bethesda Marriott, Bethesda, MD. It consisted of four sessions: a Clinical Session, a Design Session chaired by Dr. Gross, a two-part Analysis Session chaired by Drs. Wei and Fisher, respectively, and a General Issues Session cochaired by Drs. Lachenbruch and Jack C. Lee. Drs. Vocci and Johnson presented papers during the Clinical Session; Dr. Cone (with Sandra L. Dickerson) and I presented papers during the Design Session; and Drs. Follmann (with Drs. Geller and Wu), Gross, Gupta, Mei-Ling Ting Lee, Weng, and I presented papers during the Analysis Session.