A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis
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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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Overall certainty of evidence was assessed using the GRADE framework.
“The overall certainty of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework [45].”
From The Effect of Different Psychological Interventions on Athletes' Competitive Anxiety: A Systematic Review and Bayesian Network Meta-Analysis. (2026) · cites this paper as [45]
The quality of evidence was downgraded for the comparison between SGLT2i and finerenone, and between SGLT2i and GLP-1 RA.
“Therefore, we downgraded the quality of evidence for the comparison between SGLT2i and finerenone, SGLT2i and GLP-1 RA.”
Network meta-analysis, rather than pairwise meta-analysis, provides useful information about the comparative effectiveness of treatments that have not been tested head to head.
“Network meta-analysis, rather than pairwise meta-analysis, provides useful information about the comparative effectiveness of treatments that have not been tested head to head.”
From Drug treatments for covid-19: living systematic review and network meta-analysis (2020) · cites this paper as [5]
The incorporation of indirect evidence can strengthen evidence in comparisons that were tested head to head.
“Moreover, the incorporation of indirect evidence can strengthen evidence in comparisons that were tested head to head.5”
From Drug treatments for covid-19: living systematic review and network meta-analysis (2020) · cites this paper as [5]
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“incoherence when finalizing the assessment of each network estimate [2].”
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“We followed the GRADE approach to rate the quality of evidence of estimates derived from network meta-analysis.(17,27) In this approach, direct evidence from RCTs starts at high quality and can be rated down, based on risk of bias, indirectness, imprecision, inconsistency (or heterogeneity), and/or publication bias, t…”
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Systemic Immunomodulatory Treatments for Patients With Atopic Dermatitis
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Uterotonic agents for preventing postpartum haemorrhage: a network meta-analysis
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“org) to assess and report the certainty of each NMA estimate as either high, moderate, low, or very low certainty [21, 22].”
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“We used the lower certainty rating of the two pairwise estimates contributing as firstorder loop for indirect comparisons.(21) 22 To rate the NMA estimates, we evaluated the ratings of the direct and indirect evidence and their coherence.”
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“21 Publication bias in our analysis was assessed through a comparison adjusted funnel plot.”
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Assessment of Noninvasive Brain Stimulation Interventions for Negative Symptoms of Schizophrenia
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“The quality of the evidence has been assessed using the GRADE approach as outlined in the GRADE handbook [13] in order to assess the quality of the body of evidence relating to the following outcomes.”
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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].”
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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.
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2014-09-24
- Volume
- 349
- Issue
- sep24 5
- Pages
- g5630-g5630
- ISSN
- 1756-1833 (ISSN-L)
- 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 · 2013: 1
- 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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