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An Assessment of the Methodological Quality of Published Network Meta-Analyses: A Systematic Review

OBJECTIVE: To assess the methodological quality of published network meta-analysis. DESIGN: Systematic review. METHODS: We searched the medical literature for network meta-analyses of pharmaceuticals. We assessed general study characteristics, study transparency and reproducibility, methodological a...

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Autores principales: Chambers, James D., Naci, Huseyin, Wouters, Olivier J., Pyo, Junhee, Gunjal, Shalak, Kennedy, Ian R., Hoey, Mark G., Winn, Aaron, Neumann, Peter J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4414531/
https://www.ncbi.nlm.nih.gov/pubmed/25923737
http://dx.doi.org/10.1371/journal.pone.0121715
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author Chambers, James D.
Naci, Huseyin
Wouters, Olivier J.
Pyo, Junhee
Gunjal, Shalak
Kennedy, Ian R.
Hoey, Mark G.
Winn, Aaron
Neumann, Peter J.
author_facet Chambers, James D.
Naci, Huseyin
Wouters, Olivier J.
Pyo, Junhee
Gunjal, Shalak
Kennedy, Ian R.
Hoey, Mark G.
Winn, Aaron
Neumann, Peter J.
author_sort Chambers, James D.
collection PubMed
description OBJECTIVE: To assess the methodological quality of published network meta-analysis. DESIGN: Systematic review. METHODS: We searched the medical literature for network meta-analyses of pharmaceuticals. We assessed general study characteristics, study transparency and reproducibility, methodological approach, and reporting of findings. We compared studies published in journals with lower impact factors with those published in journals with higher impact factors, studies published prior to January 1(st), 2013 with those published after that date, and studies supported financially by industry with those supported by non-profit institutions or that received no support. RESULTS: The systematic literature search identified 854 citations. Three hundred and eighteen studies met our inclusion criteria. The number of network meta-analyses has grown rapidly, with 48% of studies published since January 2013. The majority of network meta-analyses were supported by a non-profit institution or received no support (68%). We found considerable inconsistencies among reviewed studies. Eighty percent reported search terms, 61% a network diagram, 65% sufficient data to replicate the analysis, and 90% the characteristics of included trials. Seventy percent performed a risk of bias assessment of included trials, 40% an assessment of model fit, and 56% a sensitivity analysis. Among studies with a closed loop, 69% examined the consistency of direct and indirect evidence. Sixty-four percent of studies presented the full matrix of head-to-head treatment comparisons. For Bayesian studies, 41% reported the probability that each treatment was best, 31% reported treatment ranking, and 16% included the model code or referenced publicly-available code. Network meta-analyses published in higher impact factors journals and those that did not receive industry support performed better across the assessment criteria. We found few differences between older and newer studies. CONCLUSIONS: There is substantial variation in the network meta-analysis literature. Consensus among guidelines is needed improve the methodological quality, transparency, and consistency of study conduct and reporting.
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spelling pubmed-44145312015-05-07 An Assessment of the Methodological Quality of Published Network Meta-Analyses: A Systematic Review Chambers, James D. Naci, Huseyin Wouters, Olivier J. Pyo, Junhee Gunjal, Shalak Kennedy, Ian R. Hoey, Mark G. Winn, Aaron Neumann, Peter J. PLoS One Research Article OBJECTIVE: To assess the methodological quality of published network meta-analysis. DESIGN: Systematic review. METHODS: We searched the medical literature for network meta-analyses of pharmaceuticals. We assessed general study characteristics, study transparency and reproducibility, methodological approach, and reporting of findings. We compared studies published in journals with lower impact factors with those published in journals with higher impact factors, studies published prior to January 1(st), 2013 with those published after that date, and studies supported financially by industry with those supported by non-profit institutions or that received no support. RESULTS: The systematic literature search identified 854 citations. Three hundred and eighteen studies met our inclusion criteria. The number of network meta-analyses has grown rapidly, with 48% of studies published since January 2013. The majority of network meta-analyses were supported by a non-profit institution or received no support (68%). We found considerable inconsistencies among reviewed studies. Eighty percent reported search terms, 61% a network diagram, 65% sufficient data to replicate the analysis, and 90% the characteristics of included trials. Seventy percent performed a risk of bias assessment of included trials, 40% an assessment of model fit, and 56% a sensitivity analysis. Among studies with a closed loop, 69% examined the consistency of direct and indirect evidence. Sixty-four percent of studies presented the full matrix of head-to-head treatment comparisons. For Bayesian studies, 41% reported the probability that each treatment was best, 31% reported treatment ranking, and 16% included the model code or referenced publicly-available code. Network meta-analyses published in higher impact factors journals and those that did not receive industry support performed better across the assessment criteria. We found few differences between older and newer studies. CONCLUSIONS: There is substantial variation in the network meta-analysis literature. Consensus among guidelines is needed improve the methodological quality, transparency, and consistency of study conduct and reporting. Public Library of Science 2015-04-29 /pmc/articles/PMC4414531/ /pubmed/25923737 http://dx.doi.org/10.1371/journal.pone.0121715 Text en © 2015 Chambers et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Chambers, James D.
Naci, Huseyin
Wouters, Olivier J.
Pyo, Junhee
Gunjal, Shalak
Kennedy, Ian R.
Hoey, Mark G.
Winn, Aaron
Neumann, Peter J.
An Assessment of the Methodological Quality of Published Network Meta-Analyses: A Systematic Review
title An Assessment of the Methodological Quality of Published Network Meta-Analyses: A Systematic Review
title_full An Assessment of the Methodological Quality of Published Network Meta-Analyses: A Systematic Review
title_fullStr An Assessment of the Methodological Quality of Published Network Meta-Analyses: A Systematic Review
title_full_unstemmed An Assessment of the Methodological Quality of Published Network Meta-Analyses: A Systematic Review
title_short An Assessment of the Methodological Quality of Published Network Meta-Analyses: A Systematic Review
title_sort assessment of the methodological quality of published network meta-analyses: a systematic review
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4414531/
https://www.ncbi.nlm.nih.gov/pubmed/25923737
http://dx.doi.org/10.1371/journal.pone.0121715
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