Randomized controlled trials (RCT) are often regarded as the ‘gold standard’ of clinical evidence. However, their strict eligibility criteria can impact cohort diversity and limit the inclusion of some subgroups, including patients with comorbidities, older individuals or those from minority ethnic groups. Observational data, including data from electronic health records, can be used to bridge the gap in evidence but are subject to bias and confounding owing to the lack of randomization.

The ‘target trial’ emulation framework, which emulates the design of a hypothetical ‘target trial’ using observational data, has increasingly been used for causal inference^1,2. Despite this approach implementing design decisions to limit the effects of bias and confounding, uncertainty remains as to whether the observed result aligns with those which would have been obtained in RCT settings. Using a specified existing RCT (the ‘reference trial’) offers an opportunity to add further validity to inferences. This goal is achieved by basing the target trial design on the reference trial and benchmarking findings from the emulated study against the reference trial results. This approach adds confidence to the results obtained from the observational study before extending analysis to trial-underrepresented groups.

随机对照试验 （RCT） 通常被视为临床证据的“黄金标准”。然而，他们严格的资格标准会影响队列多样性并限制某些亚组的纳入，包括患有合并症的患者、老年人或少数族裔群体。观察数据，包括来自电子健康记录的数据，可用于弥合证据差距，但由于缺乏随机化，因此存在偏倚和混杂因素。

“目标试验”仿真框架使用观察数据模拟假设的“目标试验”的设计，已越来越多地用于因果推理^1,2。尽管这种方法实施了设计决策来限制偏倚和混杂因素的影响，但观察到的结果是否与在 RCT 环境中获得的结果一致仍然存在不确定性。使用指定的现有 RCT（“参考试验”）提供了进一步提高推理有效性的机会。这一目标是通过将目标试验设计基于参考试验，并将模拟研究的结果与参考试验结果进行基准测试来实现的。在将分析扩展到试验代表性不足的群体之前，这种方法增加了从观察性研究中获得的结果的可信度。