An introduction to Network Meta-analyses in clinical microbiology and infectious diseases.

Abstract

Background: Network Meta-Analysis (NMA) allows synthesizing results from studies comparing all available interventions. It uses direct evidence from studies comparing directly two interventions (say B and C) but also indirect evidence if there are studies comparing each of B and C to a common comparator (say A). By synthesizing both direct and indirect evidence, NMA allows for the comparison of multiple interventions within a single framework. Additionally, NMA enables comparing interventions that have not been directly compared, provides more precise estimates compared to pairwise meta-analysis and creates a ranking hierarchy based on any specific outcome.

Objectives: We aim to provide a thorough introduction to NMA tailored for clinicians and scientists working in the fields of clinical microbiology and infectious diseases.

Sources: We illustrated all steps of NMA using a published example from the field of clinical microbiology and infectious diseases. We considered cases and use examples of published NMAs.

Content: We outlined the key concepts and assumptions of NMA using illustrative examples from common infectious diseases. We presented some common pitfalls and misconceptions that are frequently encountered in real-world practice. To reduce the gap between theory and practice, we applied the broad steps for conducting and interpretating an NMA to a published NMA evaluating the efficacy of different monotherapies for chronic hepatitis B infection.

Implications: By clarifying methodological challenges and providing practical guidance, this paper aims to enhance infectious disease practitioners' understanding of NMA, assuring its proper application and interpretation.