Statistics Seminar
June 11 (Thursday) 2020, 9:00～10:00am (Beijing Time)
ZOOM Conference ID：984 8059 3697 [Passcode: 490397]
Incorporating historical information to improve phase I clinical trial designs
Dr Ying Yuan
Bettyann Asche Murray Distinguished Professor
Department of Biostatistics
University of Texas MD Anderson Cancer Center
Abstract:
Incorporating historical data or real-world evidence has a great potential to improve the efficiency of phase I clinical trials and to accelerate drug development. For model based designs, such as the continuous reassessment method (CRM), this can be conveniently carried out by specifying a “skeleton”, i.e., the prior estimate of dose limiting toxicity (DLT) probability at each dose. In contrast, little work has been done to incorporate historical data or real-world evidence into model-assisted designs, such as the Bayesian optimal interval (BOIN), keyboard, and modified toxicity probability interval (mTPI) designs. This has led to the misconception that model-assisted designs cannot incorporate prior information. In this paper, we propose a unified framework that allows for incorporating historical data or real-world evidence into model-assisted designs. The proposed approach uses the well-established “skeleton approach, combined with the concept of prior effective sample size, thus it is easy to understand and use. More importantly, our approach maintains the hallmark of model-assisted designs: simplicity-the dose escalation/de-escalation rule can be tabulated prior to the trial conduct. Extensive simulation studies show that the proposed method can be effectively incorporate prior information to improve the operating characteristics of model assisted designs, similarly to model-based designs.