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CINeMA: Software for semiautomated assessment of the confidence in the results of network meta‐analysis

Campbell systematic review, 2020-03, Vol.16 (1), p.e1080-n/a [Peer Reviewed Journal]

2020 The Authors. published by John Wiley & Sons Ltd on behalf of The Campbell Collaboration ;2020 The Authors. Campbell Systematic Reviews published by John Wiley & Sons Ltd on behalf of The Campbell Collaboration. ;2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1891-1803 ;EISSN: 1891-1803 ;DOI: 10.1002/cl2.1080 ;PMID: 37131978

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  • Title:
    CINeMA: Software for semiautomated assessment of the confidence in the results of network meta‐analysis
  • Author: Papakonstantinou, Theodoros ; Nikolakopoulou, Adriani ; Higgins, Julian P. T. ; Egger, Matthias ; Salanti, Georgia
  • Subjects: Automation ; Bias ; Diabetes ; Meta-analysis ; Methods Research Paper ; Software ; Standard deviation ; Systematic review
  • Is Part Of: Campbell systematic review, 2020-03, Vol.16 (1), p.e1080-n/a
  • Description: Network meta‐analysis (NMA) compares several interventions that are linked in a network of comparative studies and estimates the relative treatment effects between all treatments, using both direct and indirect evidence. NMA is increasingly used for decision making in health care, however, a user‐friendly system to evaluate the confidence that can be placed in the results of NMA is currently lacking. This paper is a tutorial describing the Confidence In Network Meta‐Analysis (CINeMA) web application, which is based on the framework developed by Salanti et al (2014, PLOS One, 9, e99682) and refined by Nikolakopoulou et al (2019, bioRxiv). Six domains that affect the level of confidence in the NMA results are considered: (a) within‐study bias, (b) reporting bias, (c) indirectness, (d) imprecision, (e) heterogeneity, and (f) incoherence. CINeMA is freely available and open‐source and no login is required. In the configuration step users upload their data, produce network plots and define the analysis and effect measure. The dataset should include assessments of study‐level risk of bias and judgments on indirectness. CINeMA calls the netmeta routine in R to estimate relative effects and heterogeneity. Users are then guided through a systematic evaluation of the six domains. In this way reviewers assess the level of concerns for each relative treatment effect from NMA as giving rise to “no concerns,” “some concerns,” or “major concerns” in each of the six domains, which are graphically summarized on the report page for all effect estimates. Finally, judgments across the domains are summarized into a single confidence rating (“high,” “moderate,” “low,” or “very low”). In conclusion, the user‐friendly web‐based CINeMA platform provides a transparent framework to evaluate evidence from systematic reviews with multiple interventions.
  • Publisher: United States: John Wiley & Sons, Inc
  • Language: English
  • Identifier: ISSN: 1891-1803
    EISSN: 1891-1803
    DOI: 10.1002/cl2.1080
    PMID: 37131978
  • Source: AUTh Library subscriptions: ProQuest Central
    PubMed Central
    Directory of Open Access Journals
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