gms | German Medical Science

62. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

17.09. - 21.09.2017, Oldenburg

Comparing treatments evaluated in studies which form disconnected networks of evidence: A review of methods

Meeting Abstract

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  • John Stevens - Centre for Bayesian Statistics in Health Economics, University of Sheffield, Sheffield, Vereinigtes Königreich Großbritannien und Nordirland

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 62. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Oldenburg, 17.-21.09.2017. Düsseldorf: German Medical Science GMS Publishing House; 2017. DocAbstr. 178

doi: 10.3205/17gmds039, urn:nbn:de:0183-17gmds0399

Veröffentlicht: 29. August 2017

© 2017 Stevens.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe



A network meta-analysis allows a simultaneous comparison between treatments evaluated in RCTs that share at least one treatment with at least one other study. Estimates of treatment effects may be required for treatments across disconnected networks of evidence, which requires a different statistical approach and modelling assumptions to account for imbalances in prognostic factors between studies. In this paper, we review and discuss methods for comparing treatments evaluated in studies which form disconnected networks of evidence. Several methods have been proposed [1], [2], [3], [4], [5], [6], [7], [8], [9], [10] but assessing which are appropriate often depends on the clinical context as well as the availability of data. Most methods account only for sampling variation. We suggest that further research is required to assess the properties of methods and the use of approaches that allow the incorporation of external information to reflect parameter and structural uncertainty.

Der Vortrag gehört zum Workshop "Methods for Generalized Evidence Synthesis".

Organisatoren: R. Bender, K.H. Herrmann, K. Jensen, D. Hauschke, F. Leverkus & T. Friede

Die Autoren geben an, dass kein Interessenkonflikt besteht.

Die Autoren haben keine Angabe zur Beratung durch einen Ethikkommission gemacht.


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