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A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis

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Puhan, M. A., Schunemann, H. J., Murad, M. H., Li, T., Brignardello-Petersen, R., Singh, J. A., Kessels, A. G., Guyatt, G. H., for the GRADE Working Group·2014·BMJ

DOI 10.1136/bmj.g5630

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Abstract

Network meta-analysis (NMA), combining direct and indirect comparisons, is increasingly being used to examine the comparative effectiveness of medical interventions. Minimal guidance exists on how to rate the quality of evidence supporting treatment effect estimates obtained from NMA. We present a four-step approach to rate the quality of evidence in each of the direct, indirect, and NMA estimates based on methods developed by the GRADE working group. Using an example of a published NMA, we show that the quality of evidence supporting NMA estimates varies from high to very low across comparisons, and that quality ratings given to a whole network are uninformative and likely to mislead.

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Wasted research when systematic reviews fail to provide a complete and up-to-date evidence synthesis: the example of lung cancer
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“Networks of trials and their synthesis through network meta-analysis could increase the value of research when treatment recommendations are based on an exhaustive up-to-date network of randomized evidence [72].”
Background
Comparative effectiveness of physical exercise interventions for chronic non-specific neck pain: a systematic review with network meta-analysis of 40 randomised controlled trials
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Authors: Puhan, M. A., Schunemann, H. J., Murad, M. H., Li, T., Brignardello-Petersen, R., Singh, J. A., Kessels, A. G., Guyatt, G. H., & for the GRADE Working Group
Affiliations: University of Zurich (CH)
Mayo Clinic (US)
Johns Hopkins University (US)
University of Alabama (US)
Maastricht University (NL)
McMaster University (CA)
Corresponding author: Puhan, M. A.
ORCID: Puhan, M. A.
Murad, M. H.
Li, T.
Singh, J. A.
Guyatt, G. H.
Venue: BMJ
Publisher: BMJ
Published: 2014-09-24
Volume: 349
Issue: sep24 5
Pages: g5630-g5630
ISSN: 1756-1833 (ISSN-L)
DOI: 10.1136/bmj.g5630
OpenAlex: W2155798268
Cited by: 1,812
References: 39
Citations by year: 2026: 160 · 2025: 177 · 2024: 216 · 2023: 175 · 2022: 205 · 2021: 276 · 2020: 201 · 2019: 128 · 2018: 96 · 2017: 72 · 2016: 63 · 2015: 36 · 2014: 4
FWCI: 57.15
Type: journal article
Language: en
Update notices: correction (2015-06-17)
Open access: bronze
doi.org
Locations: BMJ (publishedVersion)
PubMed (publishedVersion)
Research Publications (Maastricht University) (publishedVersion, other-oa)
Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, other-oa)
HighWire Press Open Archive (submittedVersion)
Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
Research Publications (Maastricht University) (submittedVersion, other-oa)
Zurich Open Repository and Archive (University of Zurich)
Topics: Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Social Sciences › Sociology and Political Science › Delphi Technique in Research
Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
Keywords: network meta-analysis, quality of evidence, GRADE, treatment effect estimates, comparative effectiveness
MeSH terms: Humans, Quality Assurance, Health Care, Meta-Analysis as Topic, Practice Guidelines as Topic, Evidence-Based Medicine, Guideline Adherence

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A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis

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