Bias amplification of unobserved confounding in pharmacoepidemiological studies using indication-based sampling.
Bias amplification of unobserved confounding in pharmacoepidemiological studies using indication-based sampling.
复制标题
使用基于适应症的抽样在药物流行病学研究中未观察到的混杂因素的偏差放大。
DOI：
10.1002/pds.5614
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发表时间：
2023
影响因子：
2.6
通讯作者：
Lee,BrianK
中科院分区：
文献类型：
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作者：
Ahlqvist,ViktorH;Madley-Dowd,Paul;Ly,Amanda;Rast,Jessica;Lundberg,Michael;Jónsson-Bachmann,Egill;Berglind,Daniel;Rai,Dheeraj;Magnusson,Cecilia;Lee,BrianK
目的估计观察性药物流行病学的因果效应是一项具有挑战性的任务，因为它经常受到指征混淆的困扰。将样本限制在具有药物使用指征的人身上是一种常用的程序；基于指征的采样确保暴露物和未暴露物在指征上是可交换的，从而限制了指征混淆的可能性。然而，尽管暴露相关的协变量控制存在危害，但基于适应症的抽样很少受到审查。方法通过模拟不同程度的混杂和应用实例，我们描述了基于指示的抽样下的偏置放大。结果我们证明，在存在未观察到的混杂的情况下，基于指指的抽样可能会导致偏倚放大，这是一种自我造成的现象，即通过不适当的协变量控制来放大已经存在的偏倚。此外，我们表明，基于指标的抽样通常比其他方法（如回归调整）导致更大的净偏差。最后，我们扩展了当存在不同临床相关效应（效应异质性）时，偏倚放大应该如何进行推理。结论：我们的结论是，使用适应症抽样的研究应该有充分的理由，绝不应该认为采用这种方法是无偏的。因此，我们建议未来的观察性研究在考虑药物适应症时对偏倚放大保持警惕。
PurposeEstimating causal effects in observational pharmacoepidemiology is a challenging task, as it is often plagued by confounding by indication. Restricting the sample to those with an indication for drug use is a commonly performed procedure; indication‐based sampling ensures that the exposed and unexposed are exchangeable on the indication—limiting the potential for confounding by indication. However, indication‐based sampling has received little scrutiny, despite the hazards of exposure‐related covariate control.MethodsUsing simulations of varying levels of confounding and applied examples we describe bias amplification under indication‐based sampling.ResultsWe demonstrate that indication‐based sampling in the presence of unobserved confounding can give rise to bias amplification, a self‐inflicted phenomenon where one inflates pre‐existing bias through inappropriate covariate control. Additionally, we show that indication‐based sampling generally leads to a greater net bias than alternative approaches, such as regression adjustment. Finally, we expand on how bias amplification should be reasoned about when distinct clinically relevant effects on the outcome among those with an indication exist (effect‐heterogeneity).ConclusionWe conclude that studies using indication‐based sampling should have robust justification ‐ and that it should by no means be considered unbiased to adopt such approaches. As such, we suggest that future observational studies stay wary of bias amplification when considering drug indications.