Approaches to interpreting and choosing the best treatments in network meta-analyses

When randomized trials have addressed multiple interventions for the same health problem, network meta-analyses (NMAs) permit researchers to statistically pool data from individual studies including evidence from both direct and indirect comparisons. Grasping the significance of the results of NMAs...

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Autores principales: Mbuagbaw, L., Rochwerg, B., Jaeschke, R., Heels-Andsell, D., Alhazzani, W., Thabane, L., Guyatt, Gordon H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Commentary
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5389085/
https://www.ncbi.nlm.nih.gov/pubmed/28403893
http://dx.doi.org/10.1186/s13643-017-0473-z
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author Mbuagbaw, L.
Rochwerg, B.
Jaeschke, R.
Heels-Andsell, D.
Alhazzani, W.
Thabane, L.
Guyatt, Gordon H.
author_facet Mbuagbaw, L.
Rochwerg, B.
Jaeschke, R.
Heels-Andsell, D.
Alhazzani, W.
Thabane, L.
Guyatt, Gordon H.
author_sort Mbuagbaw, L.
collection PubMed
description When randomized trials have addressed multiple interventions for the same health problem, network meta-analyses (NMAs) permit researchers to statistically pool data from individual studies including evidence from both direct and indirect comparisons. Grasping the significance of the results of NMAs may be very challenging. Authors may present the findings from such analyses in several numerical and graphical ways. In this paper, we discuss ranking strategies and visual depictions of rank, including the surface under the cumulative ranking (SUCRA) curve method. We present ranking approaches’ merits and limitations and provide an example of how to apply the results of a NMA to clinical practice.
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spelling pubmed-53890852017-04-14 Approaches to interpreting and choosing the best treatments in network meta-analyses Mbuagbaw, L. Rochwerg, B. Jaeschke, R. Heels-Andsell, D. Alhazzani, W. Thabane, L. Guyatt, Gordon H. Syst Rev Commentary When randomized trials have addressed multiple interventions for the same health problem, network meta-analyses (NMAs) permit researchers to statistically pool data from individual studies including evidence from both direct and indirect comparisons. Grasping the significance of the results of NMAs may be very challenging. Authors may present the findings from such analyses in several numerical and graphical ways. In this paper, we discuss ranking strategies and visual depictions of rank, including the surface under the cumulative ranking (SUCRA) curve method. We present ranking approaches’ merits and limitations and provide an example of how to apply the results of a NMA to clinical practice. BioMed Central 2017-04-12 /pmc/articles/PMC5389085/ /pubmed/28403893 http://dx.doi.org/10.1186/s13643-017-0473-z Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Commentary
Mbuagbaw, L.
Rochwerg, B.
Jaeschke, R.
Heels-Andsell, D.
Alhazzani, W.
Thabane, L.
Guyatt, Gordon H.
Approaches to interpreting and choosing the best treatments in network meta-analyses
title Approaches to interpreting and choosing the best treatments in network meta-analyses
title_full Approaches to interpreting and choosing the best treatments in network meta-analyses
title_fullStr Approaches to interpreting and choosing the best treatments in network meta-analyses
title_full_unstemmed Approaches to interpreting and choosing the best treatments in network meta-analyses
title_short Approaches to interpreting and choosing the best treatments in network meta-analyses
title_sort approaches to interpreting and choosing the best treatments in network meta-analyses
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5389085/
https://www.ncbi.nlm.nih.gov/pubmed/28403893
http://dx.doi.org/10.1186/s13643-017-0473-z
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