在篮子试验中比较贝叶斯的信息借款方法,并提出了修改的可交换性-无可交换性方法的新建议
Libby Daniells1, Pavel Mozgunov2, Alun Bedding3
1STOR-i Centre for Doctoral Training, Department of Mathematics and Statistics, Lancaster University, Lancaster, UK.
Statistics in medicine
|August 24, 2023
概括
本研究引入了用于篮子试验的新贝叶斯方法,提高了统计能力并控制了I型错误率. 这种新方法提高了临床试验结论的可靠性,特别是在患者反应异质的情况下.
科学领域:
- 临床试验的设计
- 生物统计学 生物统计学
- 瘤学研究的研究.
背景情况:
- 篮子试验在多个患者组 (篮子) 中测试一种治疗方法.
- 贝叶斯信息借用方法通过跨篮子共享数据来提高效率.
- 现有的方法可能会产生偏见的估计和膨胀的错误率,从而质疑试验的有效性.
研究的目的:
- 在篮子试验中审查和比较贝叶斯信息借用方法.
- 为改进I型错误控制和功率提出一个新的贝叶斯模型.
- 为了应对患者篮子中异质治疗反应带来的挑战.
主要方法:
- 贝叶斯层次模型 (BHM),校准贝叶斯层次模型 (CBHM),可交换性-不可交换性 (EXNEX) 模型和贝叶斯模型平均值的比较.
- 对于不同样本大小的CBHM的概括.
- 用Hellinger距离进行数据驱动的同质性评估的修改EXNEX模型的建议.
主要成果:
- 拟议的修改后的EXNEX模型有效地控制了名义级别的I型错误率.
- 这种方法保持了更好的统计能力,即使在篮子里有异质的响应.
- 该模型在具有相等和不相等样本大小的模拟中展示了强大的性能.
结论:
- 与现有方法相比,新的贝叶斯方法可以更好地控制I型错误率.
- 这种进步提高了从篮子试验中得出的结论的有效性和可靠性.
- 提出的方法在处理表现出异质治疗反应的患者群体时尤其有价值.
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