Causal Inference and Estimands in Clinical Trials
Causal Inference and Estimands in Clinical Trials
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DOI：
10.1080/19466315.2019.1697739
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发表时间：
2020-01-23
影响因子：
1.8
通讯作者：
Mallinckrodt, Craig H.
中科院分区：
文献类型：
--
作者：
Lipkovich, Ilya;Ratitch, Bohdana;Mallinckrodt, Craig H.
国家研究理事会关于预防和处理缺失数据的报告强调需要明确规定因果被估量。这种关注从根本上改变了临床试验中如何看待和解决缺失数据问题。最近的ICH E9（R1）附录是促进使用因果被估量框架的另一个重要步骤，这将进一步影响临床试验方案和统计分析计划的编写和实施。在因果推断文献中被广泛接受的潜在结局语言在临床试验界未得到广泛认可，并且未用于定义NRC报告或ICH E9（R1）中的因果被估量。在这篇文章中，我们试图弥合因果推理界和临床试验者之间的差距，以进一步推进因果被估量在临床试验中的使用。我们说明了因果文献中的概念，如潜在的结果和动态治疗方案，可以促进定义和实施因果被估量，并可能提供一个统一的语言来描述观察性和随机临床试验的目标。
The National Research Council's report on the prevention and treatment of missing data highlighted the need to clearly specify causal estimands. This focus fundamentally changed how the missing data problem was perceived and addressed in clinical trials. The recent ICH E9(R1) addendum is another major step in promoting the use of the causal estimands framework that should further influence how clinical trial protocols and statistical analysis plans are written and implemented. The language of potential outcomes that is widely accepted in the causal inference literature is not widely recognized in the clinical trialists community and was not used in defining causal estimands in the NRC report or the ICH E9(R1). In this article, we attempt to bridge the gap between the causal inference community and clinical trialists to further advance the use of causal estimands in clinical trial settings. We illustrate how concepts from causal literature, such as potential outcomes and dynamic treatment regimens, can facilitate defining and implementing causal estimands and may provide a unifying language to describing the targets for both observational and randomized clinical trials.