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通过逆概率加权法比较动态治疗方案

Comparison of dynamic treatment regimes via inverse probability weighting.

作者信息

Hernán Miguel A, Lanoy Emilie, Costagliola Dominique, Robins James M

机构信息

Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA.

出版信息

Basic Clin Pharmacol Toxicol. 2006 Mar;98(3):237-42. doi: 10.1111/j.1742-7843.2006.pto_329.x.

DOI:10.1111/j.1742-7843.2006.pto_329.x
PMID:16611197
Abstract

Appropriate analysis of observational data is our best chance to obtain answers to many questions that involve dynamic treatment regimes. This paper describes a simple method to compare dynamic treatment regimes by artificially censoring subjects and then using inverse probability weighting (IPW) to adjust for any selection bias introduced by the artificial censoring. The basic strategy can be summarized in four steps: 1) define two regimes of interest, 2) artificially censor individuals when they stop following one of the regimes of interest, 3) estimate inverse probability weights to adjust for the potential selection bias introduced by censoring in the previous step, 4) compare the survival of the uncensored individuals under each regime of interest by fitting an inverse probability weighted Cox proportional hazards model with the dichotomous regime indicator and the baseline confounders as covariates. In the absence of model misspecification, the method is valid provided data are available on all time-varying and baseline joint predictors of survival and regime discontinuation. We present an application of the method to compare the AIDS-free survival under two dynamic treatment regimes in a large prospective study of HIV-infected patients. The paper concludes by discussing the relative advantages and disadvantages of censoring/IPW versus g-estimation of nested structural models to compare dynamic regimes.

摘要

对观察性数据进行恰当分析是我们获取许多涉及动态治疗方案问题答案的最佳机会。本文描述了一种通过人为截尾受试者,然后使用逆概率加权(IPW)来调整因人为截尾引入的任何选择偏倚,从而比较动态治疗方案的简单方法。基本策略可概括为四个步骤:1)定义两种感兴趣的方案;2)当个体停止遵循其中一种感兴趣的方案时对其进行人为截尾;3)估计逆概率权重,以调整上一步截尾引入的潜在选择偏倚;4)通过拟合一个将二分方案指标和基线混杂因素作为协变量的逆概率加权Cox比例风险模型,比较每种感兴趣方案下未被截尾个体的生存情况。在不存在模型设定错误的情况下,只要有关于生存和方案终止的所有随时间变化的和基线联合预测因子的数据,该方法就是有效的。我们展示了该方法在一项针对HIV感染患者的大型前瞻性研究中比较两种动态治疗方案下无艾滋病生存情况的应用。本文最后讨论了截尾/IPW与嵌套结构模型的g估计在比较动态方案方面的相对优缺点。

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