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Heterogeneity in Teriflunomide Treatment Arms: A Systematic Review and Meta‑Regression of Randomised Multiple
Francesca Bovis1, Alessio Signori1,2, Mirko Capanna1
1Department of Health Sciences, University of Genoa, Via Pastore 1, 16132, Genova, Italy.
Background:
Teriflunomide is widely used as an active comparator in Phase 3 randomised trials for relapsing multiple sclerosis (RMS). Temporal changes in disease activity within teriflunomide-treated cohorts have not been systematically examined.
Objectives:
To assess temporal trends in relapse and disability outcomes across teriflunomide arms of Phase 3 multiple sclerosis (MS) trials and identify predictors of between-trial heterogeneity.
Methods:
We performed a systematic review and meta-analysis of Phase 3 randomised controlled trials including a teriflunomide arm. PubMed, Scopus, and ClinicalTrials.gov were searched up to October 2025. Annualised relapse rate (ARR) and 12- and 24-week confirmed disability worsening (CDW) were extracted together with baseline characteristics. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool. Random-effects meta-analyses, meta-regression, and sensitivity analyses were performed.
Results:
Twelve teriflunomide cohorts from eight trials involving 4,900 adults with RMS were included. ARR ranged from 0.11 to 0.37 with substantial heterogeneity (I2 = 94%). Trial start year was inversely associated with ARR and explained a large proportion of between-study variability in exploratory meta-regression analyses. Confirmed disability worsening outcomes also showed substantial heterogeneity with a weaker trend toward lower event rates in more recent trials.
Conclusion:
Teriflunomide-treated trial populations have shifted toward lower relapse activity over time, and trial start year was the principal predictor of between-trial heterogeneity in ARR in exploratory analyses. These findings most plausibly reflect evolving recruitment and diagnostic practices rather than changes in drug efficacy. Accounting for these temporal dynamics is essential when interpreting outcomes from RMS trial using teriflunomide as comparator.
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