Cain Lauren E, Robins James M, Lanoy Emilie, Logan Roger, Costagliola Dominique, Hernán Miguel A
Harvard School of Public Health, USA.
Int J Biostat. 2010;6(2):Article 18. doi: 10.2202/1557-4679.1212.
Dynamic treatment regimes are the type of regime most commonly used in clinical practice. For example, physicians may initiate combined antiretroviral therapy the first time an individual's recorded CD4 cell count drops below either 500 cells/mm3 or 350 cells/mm3. This paper describes an approach for using observational data to emulate randomized clinical trials that compare dynamic regimes of the form “initiate treatment within a certain time period of some time-varying covariate first crossing a particular threshold." We applied this method to data from the French Hospital database on HIV (FHDH-ANRS CO4), an observational study of HIV-infected patients, in order to compare dynamic regimes of the form "initiate treatment within m months after the recorded CD4 cell count first drops below x cells/mm3" where x takes values from 200 to 500 in increments of 10 and m takes values 0 or 3. We describe the method in the context of this example and discuss some complications that arise in emulating a randomized experiment using observational data.
动态治疗方案是临床实践中最常用的方案类型。例如，当个体记录的CD4细胞计数首次降至500个细胞/mm³或350个细胞/mm³以下时，医生可能会启动联合抗逆转录病毒治疗。本文描述了一种利用观察性数据来模拟随机临床试验的方法，该试验比较的是“在某个随时间变化的协变量首次越过特定阈值后的一定时间段内启动治疗”这种形式的动态方案。我们将此方法应用于法国医院HIV数据库（FHDH - ANRS CO4）的数据，这是一项针对HIV感染患者的观察性研究，以便比较“在记录的CD4细胞计数首次降至x个细胞/mm³以下后的m个月内启动治疗”这种形式的动态方案，其中x取值范围为200至500，以10为增量，m取值为0或3。我们在这个例子的背景下描述该方法，并讨论在使用观察性数据模拟随机实验时出现的一些复杂情况。
