Going beyond randomised controlled trials to assess treatment effect heterogeneity across target populations

David G. Lugo‐Palacios, Patrick Bidulka, Stephen O’Neill, Orlagh Carroll, Anirban Basu, Amanda Adler, Karla DíazOrdaz, Andrew Briggs and Richard Grieve

Health Economics, 2025, vol. 34, issue 1, 85-104

Abstract: Methods have been developed for transporting evidence from randomised controlled trials (RCTs) to target populations. However, these approaches allow only for differences in characteristics observed in the RCT and real‐world data (overt heterogeneity). These approaches do not recognise heterogeneity of treatment effects (HTE) according to unmeasured characteristics (essential heterogeneity). We use a target trial design and apply a local instrumental variable (LIV) approach to electronic health records from the Clinical Practice Research Datalink, and examine both forms of heterogeneity in assessing the comparative effectiveness of two second‐line treatments for type 2 diabetes mellitus. We first estimate individualised estimates of HTE across the entire target population defined by applying eligibility criteria from national guidelines (n = 13,240) within an overall target trial framework. We define a subpopulation who meet a published RCT's eligibility criteria (‘RCT‐eligible’, n = 6497), and a subpopulation who do not (‘RCT‐ineligible’, n = 6743). We compare average treatment effects for pre‐specified subgroups within the RCT‐eligible subpopulation, the RCT‐ineligible subpopulation, and within the overall target population. We find differences across these subpopulations in the magnitude of subgroup‐level treatment effects, but that the direction of estimated effects is stable. Our results highlight that LIV methods can provide useful evidence about treatment effect heterogeneity including for those subpopulations excluded from RCTs.

Date: 2025
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https://doi.org/10.1002/hec.4903

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Persistent link: https://EconPapers.repec.org/RePEc:wly:hlthec:v:34:y:2025:i:1:p:85-104

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