科学研究

Yong Zang is an Assistant Professor in Biostatistics and the Associate Director for Clinical Research at Biostatistics and Data Management Core, IU Simon Comprehensive Cancer Center, Department of Biostatistics and Health Data Sciences, Indiana University. He received his Ph.D. in Statistics from The University of Hong Kong in 2011, and worked as a Postdoc fellow in Biostatistics at The University of Texas MD Anderson Cancer Center during 2011-2014. His Research Interests are: Theory, algorithms and software for adaptive clinical trial design; Methods and tests for statistical genetics. His work has been published in Pharmaceutical Statistics、Statistical Method in Medical Research、Statistics in Medicine、Biometrics、Statistics in Bioscience、Computational Statistics and Data analysis、Statistical Methods in Medical Research、Journal of the Royal Statistical Society、American Journal of Human Genetics.

Early-phase dose-finding clinical trials are often subject to the issue of late-onset outcomes. In phase I/II clinical trials, the issue becomes more intractable because toxicity and efficacy can be competing risk outcomes such that the occurrence of the first outcome will terminate the other one. In this paper, we propose a novel Bayesian adaptive phase I/II clinical trial design to address the issue of late-onset competing risk outcomes. We use the continuation-ratio (CR) model to characterize the trinomial response outcomes and the cause-specific hazard rate method to model the competing-risk survival outcomes. We treat the late-onset outcomes as missing data and develop a Bayesian data augmentation method to impute the missing data from the observations. We also propose an adaptive dose-finding algorithm to allocate patients and identify the optimal biological dose (OBD) during the trial. Simulation studies show that the proposed design yields desirable operating characteristics.