POSC313 Network Meta-Interpolation; A Fast, Novel NMA Approach Accounting for Effect Modification

Abstract

Effect modification (EM) causes bias in network meta-analyses (NMA) if EM varies across treatments in the network. Several methods have been developed, dealing with EM in NMAs when aggregated data (AgD) is available for at least one trial in the network. These methods typically make the shared effect modification assumption (SEMA) and disregard the available information the EM contains on the relative treatment effect (RTE) in the AgD trials. The SEMA is debatable, especially when comparing different classes of therapies.