AI 中文总结
研究具有二元终点的单臂II期试验中贝叶斯因子的无模拟功效和样本量计算方法，通过该方法设计试验并校准相关概率，以适应临床试验设计创新现代化，两个肿瘤学例子及代码展示了该方法。
AI 中文摘要
贝叶斯因子为相互竞争的假设提供了连贯的贝叶斯证据度量，最近被用作具有二元终点的单臂II期试验设计的基础。与基于检验统计量和p值的经典功效分析不同，基于贝叶斯因子的样本量计算目标是在给定预先指定的贝叶斯因子阈值的情况下，获得关于相关治疗效果或原假设的有力证据的高概率。本文解释了如何使用贝叶斯因子设计单臂II期二项式试验，重点是对贝叶斯和频率论功效、I型错误以及原假设有力证据概率的无模拟校准。两个肿瘤学相关的例子说明了该方法，并在bfbin2arm R包中实现，附录中提供了代码。该方法自然地适用于当前通过贝叶斯和自适应方法对临床试验设计进行创新和现代化的努力。
英文摘要
Bayes factors provide a coherent Bayesian measure of evidence for competing hypotheses and have recently been used as the basis for single-arm phase II trial designs with binary endpoints. In contrast to classical power analyses based on test statistics and p-values, Bayes-factor based sample size calculations target high probabilities of obtaining compelling evidence either for a relevant treatment effect or for the null hypothesis, given pre-specified Bayes-factor thresholds. This paper explains how to design single-arm phase II binomial trials using Bayes factors with a focus on simulation-free calibration of Bayesian and frequentist power, type-I-error, and the probability of compelling evidence for the null. Two oncology-motivated examples illustrate the approach and are implemented in the bfbin2arm R package, with code provided in an appendix. The methodology fits naturally into current efforts to innovate and modernize clinical trial design through Bayesian and adaptive methods.
Comments29 pages, 8 figures
