Calibrated non-inferiority margin: a new pragmatic method to account for population shift in stroke trials

Abstract Introduction Non-inferiority trials in acute ischemic stroke (AIS) are crucial to improve access to high-quality care. Population shifts must be accounted for when estimating non-inferiority margins, eg, changes in population characteristics (trial vs historical data); however, existing methods have practical and statistical limitations. We propose a pragmatic conceptual approach and fully pre-specifiable procedure for calibrating non-inferiority margins that account for population shifts in observed trial populations. Patients and methods Our approach splits trial and historical data into subgroups based on relevant effect-modifying covariates. Trial data from TASTE, which investigated the effect (mRS score 0–1 at day 90) of tenecteplase vs alteplase, were compared to historical data from the Stroke Thrombolysis Trialists’ Collaboration (STTC) meta-analysis (alteplase vs control). We reweighted the STTC treatment effect to match the shifted AIS population in TASTE before deriving the calibrated non-inferiority margin. Results For both datasets, subgroups were based on onset-to-treatment time and baseline NIHSS values. The reweighted risk difference for alteplase vs control was 11.70% (95% CI, 6.67–16.73); the conservative treatment-effect estimate was 6.67%, corresponding to a risk difference of 3.33% (50% reduction). Hence, the calibrated margin for comparing alternative interventions to alteplase was set at −3.33%, consistent with the European Stroke Organisation’s clinically recommended margin (−3.0%). Conclusion Our conceptual approach to estimate calibrated non-inferiority margins is a simple and pragmatic alternative to existing methods to account for population shifts in stroke trials. The supporting procedure has already been applied.