Chiocchia, Virginia; Holloway, Alexander; Salanti, Georgia (2023). 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. BMC Medical research methodology, 23(1), p. 223. BioMed Central 10.1186/s12874-023-02038-9
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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 ).
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM) |
UniBE Contributor: |
Chiocchia, Virginia, Holloway, Alexander Patrick, Salanti, Georgia |
Subjects: |
600 Technology > 610 Medicine & health 300 Social sciences, sociology & anthropology > 360 Social problems & social services |
ISSN: |
1471-2288 |
Publisher: |
BioMed Central |
Funders: |
[4] Swiss National Science Foundation |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
09 Oct 2023 08:32 |
Last Modified: |
29 Oct 2023 02:25 |
Publisher DOI: |
10.1186/s12874-023-02038-9 |
PubMed ID: |
37805460 |
BORIS DOI: |
10.48350/186978 |
URI: |
https://boris.unibe.ch/id/eprint/186978 |
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