Estimating the Effect of a Treatment When There Is Nonadherence in a Trial.
Estimating the Effect of a Treatment When There Is Nonadherence in a Trial.
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试验中出现不依从性时评估治疗效果。
DOI：
10.1093/aje/kwad141
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发表时间：
2023
影响因子：
5
通讯作者：
TchetgenTchetgen,EricJ
中科院分区：
文献类型：
--
作者：
Richardson,DavidB;Dukes,Oliver;TchetgenTchetgen,EricJ
随机试验提供了一个强有力的策略来估计治疗对结果的影响。然而，当研究受试者没有接受分配给他们的治疗时，对试验结果的解释可能会变得复杂;这被称为不依从。先前的作者描述了分析不依从试验数据的工具变量方法;在他们的方法下，初始治疗分配被用作工具。然而，他们的方法需要假设初始分配治疗对结果没有直接影响，除非通过实际接受的治疗（即，排除限制），这可能是不可信的。我们提出了一种方法，以确定治疗的因果关系，在试验中的单侧不遵守，而不假设排除限制。所提出的方法利用最初分配到对照状态的研究对象作为未暴露的参考人群;然后，我们采用定制的工具变量分析，其中的关键假设是协变量与治疗组和对照组结果之间的关联的“部分互换”。我们提供了一个正式的描述的因果效应识别的条件，说明使用模拟的方法，并提供了一个实证的应用。
Randomized trials offer a powerful strategy for estimating the effect of a treatment on an outcome. However, interpretation of trial results can be complicated when study subjects do not take the treatment to which they were assigned; this is referred to as nonadherence. Prior authors have described instrumental variable approaches to analyze trial data with nonadherence; under their approaches, the initial assignment to treatment is used as an instrument. However, their approaches require the assumption that initial assignment to treatment has no direct effect on the outcome except via the actual treatment received (i.e., the exclusion restriction), which may be implausible. We propose an approach to identification of a causal effect of treatment in a trial with 1-sided nonadherence without assuming exclusion restriction. The proposed approach leverages the study subjects initially assigned to control status as an unexposed reference population; we then employ a bespoke instrumental variable analysis, where the key assumption is “partial exchangeability” of the association between a covariate and an outcome in the treatment and control arms. We provide a formal description of the conditions for identification of causal effects, illustrate the method using simulations, and provide an empirical application.