Georgios Seitidis, Ourania Koutsiouroumpa, Roland van Rensburg, Michael McCaul, Isabelle Boutron, Dimitris Mavridis
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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.</p><p><strong>Objectives: </strong>We aim to provide a thorough introduction to NMA tailored for clinicians and scientists working in the fields of clinical microbiology and infectious diseases.</p><p><strong>Sources: </strong>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.</p><p><strong>Content: </strong>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.</p><p><strong>Implications: </strong>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.</p>","PeriodicalId":10444,"journal":{"name":"Clinical Microbiology and Infection","volume":" ","pages":""},"PeriodicalIF":8.5000,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An introduction to Network Meta-analyses in clinical microbiology and infectious diseases.\",\"authors\":\"Georgios Seitidis, Ourania Koutsiouroumpa, Roland van Rensburg, Michael McCaul, Isabelle Boutron, Dimitris Mavridis\",\"doi\":\"10.1016/j.cmi.2025.09.022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Objectives: </strong>We aim to provide a thorough introduction to NMA tailored for clinicians and scientists working in the fields of clinical microbiology and infectious diseases.</p><p><strong>Sources: </strong>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.</p><p><strong>Content: </strong>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. 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An introduction to Network Meta-analyses in clinical microbiology and infectious diseases.
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.
期刊介绍:
Clinical Microbiology and Infection (CMI) is a monthly journal published by the European Society of Clinical Microbiology and Infectious Diseases. It focuses on peer-reviewed papers covering basic and applied research in microbiology, infectious diseases, virology, parasitology, immunology, and epidemiology as they relate to therapy and diagnostics.