Speaker: Massimiliano Russo, Associate Biostatistician and Instructor of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine Brigham and Women’s Hospital & Harvard Medical School
Title: Inference in response-adaptive trials when the patient population varies during time
Abstract: A common assumption of data analysis in clinical trials is that the patient population, as well as treatment effects, do not vary during the study. However, when trials enroll patients over several years, this hypothesis may be violated. Ignoring variations of the outcome distributions over time, under the control and experimental treatments, can lead to biased treatment effect estimates and poor control of false positive results. We propose and compare two procedures that account for possible variations of the outcome distributions over time to correct treatment effect estimates, and to control type-I error rates. The first procedure models trends of patient outcomes with splines. The second leverages conditional inference principles, which have been introduced to analyze randomized trials when patient prognostic profiles are unbalanced across arms. These two procedures are applicable in response-adaptive clinical trials. We illustrate the consequences of trends in the outcome distributions in response-adaptive designs and in platform trials and investigate the proposed methods in the analysis of a glioblastoma study.
Note: Seminars are free and open to the public. Reception to follow.