[IMS Seminar] Randomized Phase II Selection Trial Design with Order Constrained Strata

ON2024-09-10TAG: ShanghaiTech UniversityCATEGORY: Lecture

Topic: Randomized Phase II Selection Trial Design with Order Constrained Strata

Speaker: Professor Yu Menggang, Department of Biostatistics, University of Michigan (UMich)
Date and time: September 11, 16:00–17:00
Venue: Room S408, SCA Building

Abstract:
The exploratory nature of phase II trials makes it quite common to include heterogeneous patient subgroups with different prognoses in the same trial. Incorporating such patient heterogeneity or stratification into statistical calculation for sample size can improve efficiency and reduce sample sizes in single-arm phase II trials with binary outcomes. However, such consideration is lacking in randomized phase II trials. In this talk, we propose methods that can utilize some natural order constraints which may exist in stratified population to gain statistical efficiency for randomized phase Il designs. For thoroughness and simplicity, we focus on the randomized phase II selection designs in this talk, although our method can be easily generalized to the randomized phase II screening designs. We will focus on explaining our method using binary outcomes, however results for both binary and time-to-event outcomes will be demonstrated. Compared with methods that do not use order constraints, our method is shown to improve the probabilities of correct selection or reduce sample size in our simulation and real examples.

Biography:
Dr. Yu Menggang is a professor at the Department of Biostatistics, University of Michigan. He is an elected fellow of the American Statistical Association (ASA). Dr. Yu conducts broad statistical methodology research, all motivated by his daily collaborative experience with medical investigators. His publications cover extensive topics including clinical trial design and analysis, causal inference, personalized medicine and biomarker development, and machine learning methods for biomedical research. Dr. Yu is also a devoted statistical collaborator. He strives to make integral contributions to scientific research that has direct impact on human health. His scientific collaboration is mainly in cancer and health care research. He has co-authored over 140 collaborative medical papers, among which over 25% are in highly impactful medical journals (with 5-year impact factors ranging from 10 to 500).