论文标题
用于建立代表性匹配对的有效算法，具有增强的推广性
Efficient algorithms for building representative matched pairs with enhanced generalizability
论文作者
论文摘要
许多最近的努力集中在评估由非随机，观察数据产生的现实证据（RWE）的能力，以产生与随机对照试验（RCT）兼容的结果。 RCT的重复计划是一项引人注目的努力（Franklin等，2020，2021）。为了更好地调和基于不同数据库的观察性研究和RCT或两项观察性研究的调查结果，希望消除研究人群之间的差异。我们概述了一种高效的，基于网络流的统计匹配算法，该算法从观察数据中设计出良好的对，类似于目标人群的协变量分布，例如，在RCT重复计划中，目标RCT符合目标人群或一般的科学利益人群。我们通过重新审查有关激素替代疗法（HRT）在妇女健康计划（WHI）临床试验和相应的观察性研究中的心脏保护作用的不一致来证明该方法的有用性。我们发现，试验与观察性研究之间的差异持续在针对研究人群的心血管风险状况调整的设计中，但在研究设计中似乎消失了，该研究设计进一步调整了HRT启动年龄和以前的雌激素 - plus-plus-progestin使用。所提出的方法集成到R软件包Match2c中。
Many recent efforts center on assessing the ability of real-world evidence (RWE) generated from non-randomized, observational data to produce results compatible with those from randomized controlled trials (RCTs). One noticeable endeavor is the RCT DUPLICATE initiative (Franklin et al., 2020, 2021). To better reconcile findings from an observational study and an RCT, or two observational studies based on different databases, it is desirable to eliminate differences between study populations. We outline an efficient, network-flow-based statistical matching algorithm that designs well-matched pairs from observational data that resemble the covariate distributions of a target population, for instance, the target-RCT-eligible population in the RCT DUPLICATE initiative studies or a generic population of scientific interest. We demonstrate the usefulness of the method by revisiting the inconsistency regarding a cardioprotective effect of the hormone replacement therapy (HRT) in the Women's Health Initiative (WHI) clinical trial and corresponding observational study. We found that the discrepancy between the trial and observational study persisted in a design that adjusted for study populations' cardiovascular risk profile, but seemed to disappear in a study design that further adjusted for the HRT initiation age and previous estrogen-plus-progestin use. The proposed method is integrated into the R package match2C.
