随机临床试验中的路径特异效应的调解分析与重复测量调解器和结果的随机临床试验
Martin Linder1, Jesper Madsen1, Stijn Vansteelandt2
1Novo Nordisk, Søborg, Denmark.
Pharmaceutical statistics
|July 29, 2025
概括
这项研究引入了临床试验的新型因果调解分析框架,允许使用纵向数据和调整混因素直接确定药物作用机制 (MoA).
科学领域:
- 临床试验方法论 临床试验方法论
- 医学中的因果推理.
- 药理动力学是什么 药理动力学
背景情况:
- 了解药物作用机制对于科学和监管机构至关重要.
- 因果调解分析可以阐明MoA,当它还没有建立.
- 现有的方法可能无法充分利用纵向数据或充分调整混.
研究的目的:
- 为在临床试验中以重复的纵向测量进行因果调解分析提供一个一般框架.
- 通过分析路径特异性效应,使药物MOA能够直接确定.
- 提供一种能够考虑所有纵向数据的方法,并为基线后的混因素进行调整.
主要方法:
- 一个因果调解分析框架的开发,灵感来自于时间到事件的结果方法.
- 使用因果图来定义从纵向测量变量的路径特异效应.
- 整合了一种用于重复测量和混调整的估计方法.
主要成果:
- 拟议的框架有助于直接确定MoA.
- 该方法有效地利用了整个纵向数据.
- 实现了对混变量进行适当的调整.
结论:
- 本框架为纵向临床试验中的因果调解分析提供了强有力的方法.
- 这种方法通过利用全面的数据和因果推断来增强对药物MOA的理解.
- 提供SAS代码允许在类似的研究环境中普遍应用.
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