Design differences and variation in results between randomised trials and non-randomised emulations: meta-analysis of RCT-DUPLICATE data.

BMJ medicine Pub Date : 2024-02-05 eCollection Date: 2024-01-01 DOI:10.1136/bmjmed-2023-000709
Rachel Heyard, Leonhard Held, Sebastian Schneeweiss, Shirley V Wang
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Abstract

Objective: To explore how design emulation and population differences relate to variation in results between randomised controlled trials (RCT) and non-randomised real world evidence (RWE) studies, based on the RCT-DUPLICATE initiative (Randomised, Controlled Trials Duplicated Using Prospective Longitudinal Insurance Claims: Applying Techniques of Epidemiology).

Design: Meta-analysis of RCT-DUPLICATE data.

Data sources: Trials included in RCT-DUPLICATE, a demonstration project that emulated 32 randomised controlled trials using three real world data sources: Optum Clinformatics Data Mart, 2004-19; IBM MarketScan, 2003-17; and subsets of Medicare parts A, B, and D, 2009-17.

Eligibility criteria for selecting studies: Trials where the primary analysis resulted in a hazard ratio; 29 RCT-RWE study pairs from RCT-DUPLICATE.

Results: Differences and variation in effect sizes between the results from randomised controlled trials and real world evidence studies were investigated. Most of the heterogeneity in effect estimates between the RCT-RWE study pairs in this sample could be explained by three emulation differences in the meta-regression model: treatment started in hospital (which does not appear in health insurance claims data), discontinuation of some baseline treatments at randomisation (which would have been an unusual care decision in clinical practice), and delayed onset of drug effects (which would be under-reported in real world clinical practice because of the relatively short persistence of the treatment). Adding the three emulation differences to the meta-regression reduced heterogeneity from 1.9 to almost 1 (absence of heterogeneity).

Conclusions: This analysis suggests that a substantial proportion of the observed variation between results from randomised controlled trials and real world evidence studies can be attributed to differences in design emulation.

随机试验与非随机模拟之间的设计差异和结果差异:RCT-DUPLICATE 数据的荟萃分析。
目的以 RCT-DUPLICATE 计划(利用前瞻性纵向保险索赔重复进行的随机对照试验)为基础,探讨设计仿真和人群差异与随机对照试验 (RCT) 和非随机真实世界证据 (RWE) 研究结果差异之间的关系:设计:设计:对 RCT-DUPLICATE 数据进行元分析:RCT-DUPLICATE是一个示范项目,利用三个真实世界的数据源模拟了32项随机对照试验:Optum Clinformatics Data Mart,2004-19 年;IBM MarketScan,2003-17 年;Medicare A、B 和 D 部分子集,2009-17 年:主要分析结果为危险比的试验;来自 RCT-DUPLICATE 的 29 个 RCT-RWE 研究对:结果:调查了随机对照试验和真实世界证据研究结果之间效应大小的差异和变化。在该样本中,RCT-RWE 研究对之间效应估计值的大部分异质性可通过元回归模型中的三个仿真差异来解释:在医院开始治疗(这并不出现在医疗保险理赔数据中)、在随机化时中止某些基线治疗(这在临床实践中将是一个不寻常的护理决策)以及药物效应的延迟开始(由于治疗的持续时间相对较短,这在真实世界的临床实践中将被低估)。在元回归中加入这三种仿真差异后,异质性从 1.9 降至接近 1(无异质性):这项分析表明,在随机对照试验和实际证据研究的结果之间观察到的差异中,有很大一部分可归因于设计仿真的差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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