Controlling for time-dependent confounding using marginal structural models
Controlling for time-dependent confounding using marginal structural models
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DOI：
10.1177/1536867x0400400403
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发表时间：
2004-12-01
期刊：
影响因子：
4.8
通讯作者：
Sterne, Jonathan A. C.
中科院分区：
文献类型：
--
作者：
Fewell, Zoe;Hernan, Miguel A.;Sterne, Jonathan A. C.
随着时间的推移，反复测量暴露、混杂因素和结果的纵向研究有可能对暴露对结果的影响进行因果推断。在难以或不可能进行随机对照试验的情况下，估计药物治疗(或其他干预措施)的因果效应尤其令人感兴趣。然而，在纵向研究中估计暴露效应的标准方法是有偏见的，因为存在受先前治疗影响的时间依赖的混杂因素。本文描述了使用边际结构模型(由Robins，Hern an和Brumback[2000]描述)来估计在存在受先前治疗影响的时间依赖混杂因素的情况下暴露或治疗效果。该方法是建立在反治疗概率权重的基础上的，然后将其用于混合Logistic回归模型，以估计治疗对结果的因果影响。我们使用边缘结构模型来评估甲氨蝶呤对类风湿关节炎患者死亡率的影响。
Longitudinal studies in which exposures, confounders, and outcomes are measured repeatedly over time have the potential to allow causal inferences about the effects of exposure on outcome. There is particular interest in estimating the causal effects of medical treatments (or other interventions) in circumstances in which a randomized controlled trial is difficult or impossible. However, standard methods for estimating exposure effects in longitudinal studies are biased in the presence of time-dependent confounders affected by prior treatment.This article describes the use of marginal structural models (described by Robins, Hern'an, and Brumback [2000]) to estimate exposure or treatment effects in the presence of time-dependent confounders affected by prior treatment. The method is based on deriving inverse-probability-of-treatment weights, which are then used in a pooled logistic regression model to estimate the causal effect of treatment on outcome. We demonstrate the use of marginal structural models to estimate the effect of methotrexate on mortality in persons suffering from rheumatoid arthritis.