Statistical Methods For The Analysis of Adverse Experience Data

SUZANNE EDWARDS Statistical Methods for the Analysis of Adverse Experience Data from Clinical Trials of New Drugs (Under the direction of GARY G. KOCH) In premarketing clinical trials of new drugs, data are collected to evaluate both the efficacy and the safety of the new drug relative to the control (s) . One aspect of the safety evaluation is the ascertainment of adverse experiences (e.g., headaches, nausea), which occur during the treatment period. The usual analysis of these adverse experience data has been simply to tabulate the percent of patients in each treatment group who had each of the adverse experiences of interest. In this presentation, alternative methods for summarization and analysis of this type of data are discussed. Four attributes of adverse experiences are delineated: occurrence/ non-occurrence, severity, frequency/duration, and timing. Summary measures characteriZing each of these attributes are constructed, and designand model-based methods for analysis of these summary measures are discussed. The design-based methods include randomization statistics with covariate-adjustment and/or stratification, exact tests, and nonparametric tests for group comparisons of time to first adverse experience. Model-based methods include logistic regression for dichotomous response variables, extensions of logistic regression for ordinal variables, weighted least squares methods for analysis of counts and rates, and Cox regression and piecewise exponential modeling for time to first adverse experience. ·e The analyses are illustrated using data from two randomized olacebo-controlled trials: a short-term trial of a new combination L antihistamine/decongestant drug, and a medium length trial of a new antidepressant. A third example involves the analysis of a series of trials for a new analgesic. Ackrowledgements It is with great appreciation that I acknowledge the assistance, gUidance, and support of my very patient committee chairman, Gary G. Koch. I also wish to thank each of my committee members for their helpful suggestions: Michael Symons (my first advisor at UNC and the one who suggested I go on for a doctorate), Anthony Segreti, Craig Turnbull, and Caroline Becker. Thanks also are due to Walt Cummings, who suggested the topic and helped coordinate my assistantship at Burroughs Wellcome along with Dr. Koch; Dan Heatherington, who lent his expertise in the field of adverse experiences in a very thorough review of my Chapter I; Joseph Janis and Woody Setzer for their help in providing me a printer for my final copy; and my fellow students at UNC and coworkers at Burroughs Wellcome, of whom I have asked many questions (in particular, Sue Allen, Ingrid Amara, Gail Knowlton, Jerry Schindler, John Schoenfelder, Robert Starbuck, and Maura Stokes). Finally, I wish to thank my husband, Joseph Newberry, for his patience and understanding throughout the time my dissertation was in progress.