Ivan D. Florez , Juan E. De La Cruz-Mena , Areti-Angeliki Veroniki
{"title":"Network meta-analysis: a powerful tool for clinicians, decision-makers, and methodologists","authors":"Ivan D. Florez , Juan E. De La Cruz-Mena , Areti-Angeliki Veroniki","doi":"10.1016/j.jclinepi.2024.111537","DOIUrl":null,"url":null,"abstract":"<div><div>Network Meta-analysis (NMA) is an advanced statistical method that combines direct evidence (ie, from head-to-head comparisons) and indirect evidence (ie, estimated from the direct available evidence) to obtain network estimates. NMAs are helpful to determine the comparative effectiveness of interventions that have not been directly compared and may provide more precise estimates for those comparisons that have been directly compared. NMA provides hierarchies which can be helpful for decision-making, much more in scenarios when multiple interventions exist for the same indication. In this article we provide a summary of the key concepts that users, namely, clinicians and methodologists need to consider when using an NMA to inform decision making.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"176 ","pages":"Article 111537"},"PeriodicalIF":7.3000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Clinical Epidemiology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0895435624002932","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Network Meta-analysis (NMA) is an advanced statistical method that combines direct evidence (ie, from head-to-head comparisons) and indirect evidence (ie, estimated from the direct available evidence) to obtain network estimates. NMAs are helpful to determine the comparative effectiveness of interventions that have not been directly compared and may provide more precise estimates for those comparisons that have been directly compared. NMA provides hierarchies which can be helpful for decision-making, much more in scenarios when multiple interventions exist for the same indication. In this article we provide a summary of the key concepts that users, namely, clinicians and methodologists need to consider when using an NMA to inform decision making.
期刊介绍:
The Journal of Clinical Epidemiology strives to enhance the quality of clinical and patient-oriented healthcare research by advancing and applying innovative methods in conducting, presenting, synthesizing, disseminating, and translating research results into optimal clinical practice. Special emphasis is placed on training new generations of scientists and clinical practice leaders.