Importance of assessing and adjusting for cross-study heterogeneity in network meta-analysis: a case study of psoriasis.

ABSTRACT

AIM: The importance of adjusting for cross-study heterogeneity when conducting network meta-analyses (NMAs) was demonstrated using a case study of biologic therapies for moderate-to-severe plaque psoriasis. METHODS: Bayesian NMAs were conducted for Psoriasis Area and Severity Index 90 response. Several covariates were considered to account for cross-trial differences baseline risk (i.e., placebo response), prior biologic use, body weight, psoriasis duration, age, race and baseline Psoriasis Area and Severity Index score. Model fit was evaluated. RESULTS: The baseline risk-adjusted NMA, which adjusts for multiple observed and unobserved effect modifiers, was associated with the best model fit. Lack of adjustment for cross-trial differences led to different clinical interpretations of findings. CONCLUSION: Failure to adjust for cross-trial differences in NMA can have important implications for clinical interpretations when studying the comparative efficacy of healthcare interventions.