Emulating Randomized Controlled Trials with Hybrid Control Arms in Oncology: A Case Study

Abstract

This proof-of-concept study retrospectively assessed the feasibility of applying a hybrid control arm design to a completed phase III randomized controlled trial (RCT; CheckMate-057) in advanced non-small cell lung cancer using a real-world data (RWD) source. The emulated trial consists of an experimental arm (patients from the RCT experimental cohort) and a hybrid control arm (patients from the RCT and RWD control cohorts). For the RWD control cohort, this study used a nationwide electronic health record-derived de-identified database. Three frequentist statistical borrowing methods were evaluated: a two-step Cox model, a fixed Cox model, and propensity score-integrated composite likelihood (“Methods 1–3”). The experimental treatment effect for hybrid control designs were evaluated using hazard ratios (HRs) with 95% confidence interval (CI) estimated from the Cox models accounting for covariate differences. The reduction in study duration compared to the RCT was also evaluated. All three statistical borrowing methods achieved comparable experimental treatment effects to that observed in the CheckMate-057 clinical trial, with HRs of 0.73 (95% CI: 0.59, 0.92), 0.74 (95% CI: 0.61, 0.91), 0.72 (95% CI: 0.59, 0.88) for Methods 1–3, respectively. Reduction in study duration time was 99–115 days when borrowing 30–38 events for Methods 1–3, respectively. This study demonstrated that it is feasible to emulate an RCT using a hybrid control arm design using three frequentist propensity-score based statistical borrowing methods. Selection of an appropriate, fit-for-use RWD cohort is critical to minimizing bias in experimental treatment effect.