Regression-Based Proximal Reconciliation of Conflicting Trials with Unmeasured Effect Modifiers

2026-08-04

AI Summary

This study addresses the challenge of conflicting results in randomized controlled trials arising from distributional differences in unobserved effect modifiers and the absence of a formal framework for assessing harmonizability. To this end, the authors propose a causal inference approach based on proxy variables, formally defining both conditional and marginal harmonizability for the first time and introducing a “harmonization ratio” to quantify the degree of harmonizability. Conditional harmonizability is evaluated via proxy variable regression, while marginal harmonizability is assessed through an integrated analysis of transportability and equivalence. Application to the Meis and PROLONG trials reveals that commonly used proxy variables—such as cervical length—provide limited support for marginal harmonizability, offering regulators and clinicians a novel tool to inform decision-making.

Abstract

Randomized controlled trials with similar protocols may yield conflicting findings when the distribution of relevant effect modifiers differs across study populations. Yet no formal statistical framework exists for defining and assessing whether conflicting trials are reconcilable, despite the importance of this question for evidence synthesis and regulatory decision making. To address this gap, we develop a causal inference framework for evaluating conditional and marginal reconcilability on additive and multiplicative scales in the presence of unmeasured effect modifiers. Within this framework, we use proxy variables for hypothesized unmeasured effect modifiers to develop regression-based tests of conditional reconcilability under parametric structural models. To assess marginal reconcilability, we extend existing transportability methods and develop an equivalence testing framework. We also introduce a reconciliation proportion to quantify the degree of marginal reconciliation. We illustrate these methods using the conflicting Meis and PROLONG trials of 17-alpha-hydroxyprogesterone caproate for preventing recurrent preterm birth. The analyses provided limited evidence that unmeasured effect modifiers such as cervical length, as captured by the selected proxies, were sufficient to marginally reconcile the trials. These findings demonstrate how proximal reconciliation methods may help regulators, researchers, and clinicians evaluate whether differences in study populations explain conflicting trial findings.

Problem

• effect modifiers
• conflicting trials
• reconcilability
• unmeasured confounding
• evidence synthesis

Innovation

• causal inference
• effect modification
• transportability
• proxy variables
• equivalence testing