Bayesian Design of Superiority Trials: Methods and Applications

被引:2
|
作者
Yuan, Wenlin [1 ]
Chen, Ming-Hui [1 ]
Zhong, John [2 ]
机构
[1] Univ Connecticut, Dept Stat, Storrs, CT 06269 USA
[2] REGENXBIO Inc, Rockville, MD USA
来源
STATISTICS IN BIOPHARMACEUTICAL RESEARCH | 2022年 / 14卷 / 04期
关键词
Borrowing-by-parts power prior; Conditional borrowing; Power prior; Sample size determination; SAMPLE-SIZE DETERMINATION; HISTORICAL CONTROL DATA; CLINICAL-TRIALS; SURVIVAL-DATA; MODEL; INFORMATION; DUCHENNE; PRIORS;
D O I
10.1080/19466315.2022.2090429
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In this article, 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.
引用
收藏
页码:433 / 443
页数:11
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