贝叶斯主动动态借款利用倾向度得分对混合控制臂的重叠以及各种偏差的影响:一个模拟研究
Kai Wang1,2, Han Cao1,3, Chen Yao1,2,4
1Department of Biostatistics, Peking University First Hospital, Beijing, China.
Journal of evidence-based medicine
|April 8, 2025
概括
本研究引入了临床试验的积极动态借款方法,改善了在选择偏差下对外部控制的使用. 然而,严重的偏差影响倾向性得分估计和结果可能会降低性能.
科学领域:
- 生物统计学 生物统计学
- 临床试验设计 临床试验设计
- 健康研究方法 健康研究方法
背景情况:
- 外部控制可以通过减少样本大小来提高临床试验的效率.
- 贝叶斯借款方法与倾向性评分 (PS) 集成,根据先前数据冲突或共同变量相似性调整外部控制.
- 现有的方法可能无法充分利用共变量和结果的相似性来实现最佳的借贷.
研究的目的:
- 提出一个与PS集成的贝叶斯主动动态借款方法,考虑共变量和结果相似性.
- 通过模拟来评估拟议方法对偏差的性能.
- 将新方法与现有的贝叶斯借贷技术进行比较.
主要方法:
- 一个两阶段的策略平衡了在设计阶段使用PS的共变量,独立于结果.
- 在分析阶段使用电力先验,弹性先验和混合先验,随机折扣.
- 使用的PS在并发和外部控制之间重叠,以告知一个信息不足的初始先验.
主要成果:
- 拟议的方法在选择偏差下表现优于标准贝叶斯动态借款.
- 与拟议方法相比,将折扣参数固定在PS重叠上显示出更好的偏差控制和I型错误率.
- 这种方法产生了比非信息化先验更高的功率和更窄的可信度间隔.
- 其他偏差,包括未测量的混因素和测量错误,对所有PS集成方法的性能产生了负面影响.
结论:
- 提出的方法表明在存在选择偏差时借用外部控制的优势.
- 影响PS估计和结果的严重偏差可能会损害PS集成贝叶斯借款的有效性,特别是那些只依赖于共同变量相似性的借款.
- 在实施外部控制借贷策略时,仔细考虑潜在的偏见至关重要.
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