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

Abstract

ObjectiveTo 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).DesignMeta-analysis of RCT-DUPLICATE data.Data sourcesTrials 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 studiesTrials where the primary analysis resulted in a hazard ratio; 29 RCT-RWE study pairs from RCT-DUPLICATE.ResultsDifferences 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).ConclusionsThis 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.