A robust method for estimating optimal treatment regimes.
A robust method for estimating optimal treatment regimes.
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DOI：
10.1111/j.1541-0420.2012.01763.x
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发表时间：
2012-12
期刊：
影响因子：
1.9
通讯作者：
Davidian M
中科院分区：
文献类型：
--
作者：
Zhang B;Tsiatis AA;Laber EB;Davidian M
治疗方案是一种规则，根据患者观察到的特征，在一组可能的治疗方法中为患者分配一种治疗方法，从而对患者进行“个性化”治疗。目标是确定最佳治疗方案，如果整个患者群体都遵循该方案，平均而言将产生最佳结果。给定来自临床试验或观察性研究的数据，对于单个治疗决策，可以通过假设治疗和协变量条件下预期结果的回归模型来找到最佳方案，其中，对于给定的一组协变量，最佳治疗是产生最有利的预期结果的治疗。然而，如果不正确地指定回归模型，则通过这种制度分配治疗是可疑的。认识到，即使错误指定，这样的回归模型定义了一类制度，我们转而考虑通过寻找制度来优化总体平均结果的估计量，从而在这样的一类中找到最优制度。为了考虑观察研究中可能存在的混杂因素并提高精度，我们为此使用了双鲁棒增广逆概率加权估计器。通过对乳腺癌临床试验数据的仿真和应用，验证了该方法的有效性。
A treatment regime is a rule that assigns a treatment, among a set of possible treatments, to a patient as a function of his/her observed characteristics, hence “personalizing” treatment to the patient. The goal is to identify the optimal treatment regime that, if followed by the entire population of patients, would lead to the best outcome on average. Given data from a clinical trial or observational study, for a single treatment decision, the optimal regime can be found by assuming a regression model for the expected outcome conditional on treatment and covariates, where, for a given set of covariates, the optimal treatment is the one that yields the most favorable expected outcome. However, treatment assignment via such a regime is suspect if the regression model is incorrectly specified. Recognizing that, even if misspecified, such a regression model defines a class of regimes, we instead consider finding the optimal regime within such a class by finding the regime the optimizes an estimator of overall population mean outcome. To take into account possible confounding in an observational study and to increase precision, we use a doubly robust augmented inverse probability weighted estimator for this purpose. Simulations and application to data from a breast cancer clinical trial demonstrate the performance of the method.
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