Heyard Rachel, Held Leonhard, Schneeweiss Sebastian, Wang Shirley V
Center for Reproducible Science, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland.
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 1620 Tremon St, Boston MA 02120.
medRxiv. 2023 Jul 13:2023.07.13.23292601. doi: 10.1101/2023.07.13.23292601.
While randomized controlled trials (RCTs) are considered a standard for evidence on the efficacy of medical treatments, non-randomized real-world evidence (RWE) studies using data from health insurance claims or electronic health records can provide important complementary evidence. The use of RWE to inform decision-making has been questioned because of concerns regarding confounding in non-randomized studies and the use of secondary data. RCT-DUPLICATE was a demonstration project that emulated the design of 32 RCTs with non-randomized RWE studies. We sought to explore how emulation differences relate to variation in results between the RCT-RWE study pairs.
We include all RCT-RWE study pairs from RCT-DUPLICATE where the measure of effect was a hazard ratio and use exploratory meta-regression methods to explain differences and variation in the effect sizes between the results from the RCT and the RWE study. The considered explanatory variables are related to design and population differences.
Most of the observed variation in effect estimates between RCT-RWE study pairs in this sample could be explained by three emulation differences in the meta-regression model: (i) in-hospital start of treatment (not observed in claims data), (ii) discontinuation of certain baseline therapies at randomization (not part of clinical practice), (iii) delayed onset of drug effects (missed by short medication persistence in clinical practice).
This analysis suggests that a substantial proportion of the observed variation between results from RCTs and RWE studies can be attributed to design emulation differences. (238 words).
虽然随机对照试验（RCT）被视为医学治疗疗效证据的标准，但使用医疗保险理赔数据或电子健康记录的非随机真实世界证据（RWE）研究可以提供重要的补充证据。由于对非随机研究中的混杂因素以及二次数据的使用存在担忧，利用RWE为决策提供信息受到了质疑。RCT-DUPLICATE是一个示范项目，它用非随机RWE研究模拟了32项RCT的设计。我们试图探究模拟差异如何与RCT-RWE研究对之间结果的差异相关。
我们纳入了RCT-DUPLICATE中所有效应量为风险比的RCT-RWE研究对，并使用探索性元回归方法来解释RCT和RWE研究结果之间效应大小的差异和变化。所考虑的解释变量与设计和人群差异有关。
在这个样本中，RCT-RWE研究对之间观察到的效应估计值的大部分差异可以通过元回归模型中的三个模拟差异来解释：（i）住院开始治疗（在理赔数据中未观察到），（ii）随机分组时某些基线治疗的中断（不属于临床实践的一部分），（iii）药物效应的延迟出现（在临床实践中因药物持续时间短而未发现）。
该分析表明，RCT和RWE研究结果之间观察到的很大一部分差异可归因于设计模拟差异。（238字）
