Background: Head-to-head clinical trials are the gold-standard for comparing the efficacy and safety of different treatments. In the absence of head-to-head trials, results from indirect treatment comparisons (ITCs) are used by physicians, regulatory agencies, and payers to assess benefit:risk of different therapies to support decision making. Valid ITCs require a set of conditions to be met, including comparable study designs (eg, follow-up time, visit schedules) and the ability to adjust for differences in baseline (BL) characteristics. Matching adjusted indirect comparison (MAIC) is a statistical methodology used to account for cross-trial differences in BL characteristics to reduce bias in outcome comparisons.
Objective: To use MAICs to illustrate how the results of ITCs can be influenced by confounding factors, using an example from infantile-onset SMA.
Methods: Unanchored MAICs were conducted for outcomes with comparable assessment schedules using data from the ENDEAR/SHINE study for nusinersen and the STR1VE-US study for onasemnogene abeparvovec.
Results: ENDEAR/SHINE and STR1VE-US participants differed on multiple prognostic factors and inclusion/exclusion criteria differed across the trials. ENDEAR/SHINE participants were more severely affected at BL; on average, they were older at treatment initiation and had lower BL motor functioning. A sub-population of ENDEAR/SHINE patients (n=48) that fulfilled STR1VE-US’s inclusion/exclusion criteria were identified. MAIC was then used to create weights for the individual patient-level data from ENDEAR/SHINE to induce balance with the aggregate BL characteristics reported for STR1VE-US. After weighting, event-free, overall and permanent ventilation survival curves for STR1VE-US and ENDEAR/SHINE were not significantly different (p=0.45, p=0.83, and p=0.41, respectively). In contrast, naive comparisons without BL adjustment incorrectly concluded that participants in the STR1VE-US study experienced fewer events for these outcomes than those in ENDEAR/SHINE.
Conclusions: ITCs are an important but limited tool for assessing relative treatment effects and their application must be carefully considered to produce valid results, particularly in rare diseases, such as SMA, where BL characteristics are known predictors of treatment response. BL adjustment via MAIC or other methods should be thoughtfully applied when appropriate; unadjusted or incomplete ITCs may yield erroneous conclusions.
Study Support: Biogen