The aim of clinical effectiveness research using repositories of electronic health records is to identify what health interventions ‘work best’ in real-world settings. Since there are several reasons why the net benefit of intervention may differ across patients, current comparative effectiveness literature focuses on investigating heterogeneous treatment effect and predicting whether an individual might benefit from an intervention. The majority of this literature has concentrated on the estimation of the effect of treatment on binary outcomes. However, many medical interventions are evaluated in terms of their effect on future events, which are subject to loss to follow-up. In this study, we describe a framework for the estimation of heterogeneous treatment effect in terms of differences in time-to-event (survival) probabilities. We divide the problem into three phases: (1) estimation of treatment effect conditioned on unique sets of the covariate vector; (2) identification of features important for heterogeneity using non-parametric variable importance methods; and (3) estimation of treatment effect on the reference classes defined by the previously selected features, using one-step Targeted Maximum Likelihood Estimation. We conducted a series of simulation studies and found that this method performs well when either sample size or event rate is high enough and the number of covariates contributing to the effect heterogeneity is moderate. An application of this method to a clinical case study was conducted by estimating the effect of oral anticoagulants on newly diagnosed non-valvular atrial fibrillation patients using data from the UK Clinical Practice Research Datalink.

使用电子健康记录存储库进行临床有效性研究的目的是确定在现实环境中哪种健康干预措施“效果最佳”。由于干预的净收益可能因患者而异的原因有很多，因此，当前的比较有效性文献重点研究了异质性治疗效果并预测个人是否会从干预中受益。该文献的大部分集中在对二进制结果的治疗效果的估计上。但是，许多医疗干预措施是根据其对未来事件的影响进行评估的，这些事件可能会遭受后续损失。在这项研究中，我们根据事件发生时间（生存）概率的差异，描述了一种评估异构治疗效果的框架。我们将问题分为三个阶段：（1）以协变量向量的唯一集合为条件的治疗效果估计；（2）使用非参数变量重要性方法识别对异构性重要的特征；（3）使用单步目标最大似然估计来估计对先前选择的特征所定义的参考类别的治疗效果。我们进行了一系列的模拟研究，发现当样本量或事件发生率足够高且影响效果异质性的协变量数量适中时，此方法效果良好。通过使用UK Clinical Practice Research Datalink的数据评估口服抗凝剂对新诊断的非瓣膜性心房颤动患者的作用，将该方法应用于临床案例研究。