OBJECTIVES: To evaluate different statistical methodologies in a network meta-analysis (NMA) comparing the effectiveness of interferon-beta (IFNβ) therapies across several endpoints in relapsing-remitting multiple sclerosis (RRMS) to determine potential best practices. METHODS: A systematic literature review (1996-2014) was conducted to identify randomised, controlled trials of FDA- and EMA-approved IFNβ DMDs in RRMS, including subcutaneous (SC) IFNβ-1a (44μg or 22μg 3x/wk), SC pegIFNβ-1a (125μg every 2wks), intramuscular (IM) IFNβ-1a (30μg 1x/wk), and SC IFNβ-1b (250μg EOD). Data were extracted for patients relapse-free, patients without disability progression, and patients without new MRI activity at study end. A random-effects Bayesian model was utilised for the base case analysis, and sensitivity analyses investigated results using different analysis frameworks or effects distributions. RESULTS: CONCLUSIONS: While similar estimates for treatment effects were found across statistical methodologies, the combination of a Bayesian approach and a random-effects distribution with informative prior allowed for methodological robustness while yielding interpretable findings.