Network Meta-Analysis
A statistical method that compares multiple treatments simultaneously by combining direct evidence (from head-to-head trials) with indirect evidence (from trials sharing a common comparator). Network meta-analyses enable ranking of treatments even when they have not been directly compared.
Technical Context
NMA (also called mixed treatment comparison, MTC) creates a network of evidence connecting treatments through direct comparisons (A vs B head-to-head) and indirect comparisons (A vs C and B vs C → indirect comparison of A vs B). NMA requires: the transitivity assumption (populations across studies are similar enough for indirect comparisons to be valid) and consistency (direct and indirect estimates agree). Statistical approaches: frequentist (graph-theoretical methods) or Bayesian (Markov chain Monte Carlo — MCMC — modelling). NMA enables ranking of treatments using SUCRA (Surface Under Cumulative Ranking Curve) or P-score values. For GLP-1 RAs, NMAs comparing semaglutide vs tirzepatide vs liraglutide vs dulaglutide vs exenatide provide comprehensive efficacy and safety rankings informing clinical guidelines and health technology assessments (NICE, ICER).