Yuan Wenlin, Chen Ming-Hui, Zhong John
Department of Statistics, University of Connecticut at Storrs, CT 06269.
REGENXBIO Inc., 9804 Medical Center Drive, Rockville, MD 20850.
Stat Biopharm Res. 2022;14(4):433-443. doi: 10.1080/19466315.2022.2090429. Epub 2022 Jul 18.
In this paper, we lay out the basic elements of Bayesian sample size determination (SSD) for the Bayesian design of a two-arm superiority clinical trial. We develop a flowchart of the Bayesian SSD that highlights the critical components of a Bayesian design and provides a practically useful roadmap for designing a Bayesian clinical trial in real world applications. We empirically examine the amount of borrowing, the choice of noninformative priors, and the impact of model misspecification on the Bayesian type I error and power. A formal and statistically rigorous formulation of conditional borrowing within the decision rule framework is developed. Moreover, by extending the partial borrowing power priors, a new borrowing-by-parts power prior for incorporating historical data is proposed. Computational algorithms are also developed to calculate the Bayesian type I error and power. Extensive simulation studies are carried out to explore the operating characteristics of the proposed Bayesian design of a superiority trial.
在本文中,我们阐述了用于双臂优效性临床试验贝叶斯设计的贝叶斯样本量确定(SSD)的基本要素。我们开发了一个贝叶斯SSD流程图,突出了贝叶斯设计的关键组成部分,并为在实际应用中设计贝叶斯临床试验提供了切实有用的路线图。我们实证检验了信息借用的量、无信息先验的选择以及模型误设对贝叶斯I型错误和检验效能的影响。在决策规则框架内,我们给出了条件借用的形式化且统计严格的公式。此外,通过扩展部分借用效能先验,我们提出了一种用于纳入历史数据的逐部分借用效能先验。我们还开发了计算算法来计算贝叶斯I型错误和检验效能。我们进行了广泛的模拟研究,以探索所提出的优效性试验贝叶斯设计的操作特性。