谁将受益?谁将受益? 在使用贝叶斯方法的适应性试验中发现治疗效果的隐藏异质性:系统性审查
Rachel Giblon1,2, Chengyang Gao3,4, Kuan Liu5,6
1Division of Biostatistics, University of Toronto Dalla Lana School of Public Health, Toronto, ON, Canada. rachel.giblon@mail.utoronto.ca.
Trials
|November 26, 2025
概括
贝叶斯方法在适应性临床试验中有望检测治疗效果的隐藏异质性 (HTE). 需要进一步的研究来验证这些方法,并确保在临床研究中得到公平的应用.
科学领域:
- 临床试验 临床试验
- 生物统计学 生物统计学
- 健康 公平 卫生 公平
背景情况:
- 适应性临床试验越来越多地试图确定个性化医学的治疗效果 (HTE) 的异质性.
- 当前的自适应设计通常依赖于预定义的子组,限制了未知的HTE源的发现.
- 贝叶斯统计方法为实时学习和试验中的适应提供了灵活性.
研究的目的:
- 审查在适应性临床试验中检测未知的HTE的贝叶斯方法.
- 评估这些贝叶斯式方法的方法论创新,操作特征和股权考虑.
- 识别应用贝叶斯方法在适应性试验设计中的差距和未来方向.
主要方法:
- 在主要数据库 (MEDLINE,Embase等) 中进行系统的文献搜索. ) 的情况.
- 根据设计,方法,操作特征,可复制性和公平因素,对符合条件的研究进行审查和综合.
- 分析包括与代表性不足的人群和交叉子组效应相关的变量.
主要成果:
- 七项研究符合纳入标准,探索诸如随机分区模型和机器学习分类器之类的方法.
- 与非贝叶斯方法相比,模拟显示了更好的子组检测,效率和功率.
- 报告指出,可复制性有限,没有明确的方法来解决健康不平等问题.
结论:
- 贝叶斯方法显示在适应性试验中检测HTE的初步承诺,增强适应性和包容性.
- 目前的证据在很大程度上是概念性的,经验验证有限.
- 未来的发展需要一个公平的镜头,经验验证和开放的科学实践,以获得公平研究的实际价值.
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