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Semi-automated assessment of the risk of bias due to missing evidence in network meta-analysis: a guidance paper for the ROB-MEN web-application

Authors :
Virginia Chiocchia
Alexander Holloway
Georgia Salanti
Source :
BMC Medical Research Methodology, Vol 23, Iss 1, Pp 1-11 (2023)
Publication Year :
2023
Publisher :
BMC, 2023.

Abstract

Abstract Network meta-analysis compares multiple interventions and estimates the relative treatment effects between all interventions, combining both direct and indirect evidence. Recently, a framework was developed to assess the Risk Of Bias due to Missing Evidence in Network meta-analysis (ROB-MEN) which is part of the more comprehensive framework to evaluate the Confidence In the evidence for Network Meta-Analysis (CINeMA). To produce an overall risk of bias judgement for each network estimate, ROB-MEN: performs an assessment of the bias due to missing evidence in each possible pairwise comparison; combines the assessment with the contribution from the direct pairwise comparisons; considers the potential for small-study effects. To facilitate and semi-automate this process, ROB-MEN has been implemented in a user-friendly web-application ( https://cinema.ispm.unibe.ch/rob-men ). Here we provide a tutorial detailing the functionality and use of the application consisting of data upload, analysis configuration, output visualisation, and production of the tool’s output tables for recording the risk of bias assessment. We also illustrate an example application using the demo dataset available for download on the application’s homepage. The ROB-MEN web-application is open-source and freely available ( https://github.com/esm-ispm-unibe-ch/rob-men ).

Subjects

Subjects :
Medicine (General)
R5-920

Details

Language :
English
ISSN :
14712288
Volume :
23
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Medical Research Methodology
Publication Type :
Academic Journal
Accession number :
edsdoj.6183d3490f2a45e5a3f15abcad85a5a5
Document Type :
article
Full Text :
https://doi.org/10.1186/s12874-023-02038-9