A Bayesian Optimal Phase II Design for Randomized Immunotherapy Trials with Delayed Treatment Effects
具有延迟治疗效应的随机免疫治疗试验贝叶斯最优二期设计
Immunotherapy has transformed cancer treatment, yet its delayed therapeutic effects often lead to non-proportional hazards, rendering many conventional phase II designs underpowered and prone to type I error inflation. To address this issue, we propose a novel Bayesian Optimal Phase II design (DTE-BOP2) that explicitly models the uncertainty in the separation timing of treatment effect. The treatment separation timepoint (denoted by S) is endowed with a truncated-Gamma…