Statistics Seminar Series
Title: Discrete Time-to-Event and Rank-based Methods with Application to Composite Endpoint for Assessing Evidence of Disease Activity
ABSTRACT: We consider discrete time-to-event and rank-based statistical analyses methods for estimation of and inference about treatment effects on a composite measure of evidence of disease activity. The composite measure is a function of endpoints with known event times and another endpoint whose exact time of occurrence is unknown, but the endpoint is only known to have occurred within an interval. Unlike crude incidence rate approach that ignores subjects’ differential follow-up times and makes unverifiable assumptions about evidence of disease activity status of censored subjects, discrete time-to-event approaches allow incorporation of subjects’ differential follow-up times and appropriate handling of censoring. The rank-based method captures severity of disease activity that may be eluded by the collapsed binary composite outcome. Moreover, the rank-based method, besides providing crude estimates of proportion of subjects with no evidence of disease activity, also addresses possible clouding effect of any of the component endpoint that occurs with higher frequency. Applications are demonstrated using data set from multiple sclerosis clinical trials.
BIO: Macaulay Okwuokenye is an associate director, biostatistics at Syros Pharmaceutical, Inc. Cambridge, MA; an adjunct faculty of biostatistics at the Jiann-Ping Hsu College of Public Health (JPHCOPH), Georgia Southern University (GSU), and an adjunct faculty at the University of New England. He teaches graduate-level biostatistics class at the latter. He supports or has supported design, conduct, and statistical analyses of clinical trials, comparative effectiveness, real-world studies, and exploratory data analyses in different therapeutic areas. Macaulay is adept in evidentiary inference for clinical trials and comparative effectiveness. He has years of academic research and several years of experience in clinical research, statistical consultation, and pharmaceutical/biotechnology industry. He received the masters and doctoral degree in biostatistics from the JPHCOPH, GSU. He has several publications in international statistical and applied scientific journals and he is a reviewer for international statistical journals. He has written book chapter on statistical analysis methods for clinical trial data. He has taught short course at conferences and he is a speaker at international conferences, statistical workshops, and academic seminars.