Department of Biostatistics, The University of Texas MD Anderson Cancer Center Houston, Houstan, Texas, USA.
Pharm Stat. 2021 Nov;20(6):1183-1199. doi: 10.1002/pst.2139. Epub 2021 May 19.
Bayesian sequential monitoring is widely used in adaptive phase II studies where the objective is to examine whether an experimental drug is efficacious. Common approaches for Bayesian sequential monitoring are based on posterior or predictive probabilities and Bayesian hypothesis testing procedures using Bayes factors. In the first part of the paper, we briefly show the connections between test-based (TB) and posterior probability-based (PB) sequential monitoring approaches. Next, we extensively investigate the choice of local and nonlocal priors for the TB monitoring procedure. We describe the pros and cons of different priors in terms of operating characteristics. We also develop a user-friendly Shiny application to implement the TB design.
贝叶斯序贯监测在自适应二期研究中被广泛应用,其目的在于检验试验药物是否有效。常见的贝叶斯序贯监测方法基于后验概率或预测概率,以及使用贝叶斯因子的贝叶斯假设检验程序。在本文的第一部分,我们简要展示了基于检验(TB)和基于后验概率(PB)的序贯监测方法之间的联系。接下来,我们深入研究了 TB 监测程序中局部和非局部先验的选择。我们从操作特性的角度描述了不同先验的优缺点。我们还开发了一个用户友好的 Shiny 应用程序来实现 TB 设计。