Bayesian models for aggregate and individual patient data component network meta-analysis.

ABSTRACT: Network meta-analysis can synthesize evidence from studies comparing multiple treatments for the same disease. Sometimes the treatments of a network are complex interventions, comprising several independent components in different combinations. A component network meta-analysis (CNMA) can be used to analyze such data and can in principle disentangle the individual effect of each component. However, components may interact with each other, either synergistically or antagonistically. Deciding which interactions, if any, to include in a CNMA model may be difficult, especially for large networks with many components. In this article, we present two Bayesian CNMA models that can be used to identify prominent interactions between components. Our models utilize Bayesian variable selection methods

SUBMITTER: Efthimiou O 

PROVIDER: S-EPMC9314605 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature