GRADE guidelines: 5. Rating the quality of evidence—publication bias

Guyatt, Gordon H.; Oxman, Andrew D.; Montori, Victor; Vist, Gunn; Kunz, Regina; Brozek, Jan; Alonso-Coello, Pablo; Djulbegovic, Ben; Atkins, David; Falck-Ytter, Yngve; Williams, John W.; Meerpohl, Joerg; Norris, Susan L.; Akl, Elie A.; Schünemann, Holger J.

doi:10.1016/j.jclinepi.2011.01.011

Cited by 1,819Meta-analysis and systematic reviewsStatistical Methods in EpidemiologyPharmaceutical industry and healthcare

GRADE guidelines: 5. Rating the quality of evidence—publication bias

Guyatt, Gordon H., Oxman, Andrew D., Montori, Victor, Vist, Gunn, Kunz, Regina, Brozek, Jan, Alonso-Coello, Pablo, Djulbegovic, Ben +7 more·2011·Journal of Clinical Epidemiology

DOI 10.1016/j.jclinepi.2011.01.011

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Abstract

In the GRADE approach, randomized trials start as high-quality evidence and observational studies as low-quality evidence, but both can be rated down if a body of evidence is associated with a high risk of publication bias. Even when individual studies included in best-evidence summaries have a low risk of bias, publication bias can result in substantial overestimates of effect. Authors should suspect publication bias when available evidence comes from a number of small studies, most of which have been commercially funded. A number of approaches based on examination of the pattern of data are available to help assess publication bias. The most popular of these is the funnel plot; all, however, have substantial limitations. Publication bias is likely frequent, and caution in the face of early results, particularly with small sample size and number of events, is warranted.

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Small-sample studies are generally more prone to bias, and their relatively large confidence intervals suggest high uncertainty around point estimates.
“Small-sample studies are generally more prone to bias, and the relatively large confidence intervals presented in these studies suggest high uncertainty around the point estimates [47, 48].”
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The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology will be used to assess the certainty of the findings' body of evidence.
“To assess the certainty of the findings’ body of evidence, we will use the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology, which evaluates five pillars: risk of bias, imprecision, inconsistency, indirect assessment of outcomes, and publication bias [35].”
From Dialectical Behavior Therapy as an intervention for Treatment Resistant Depression in adults: A protocol for systematic review and meta-analysis (2024) · cites this paper as [35]
The overall quality of evidence was graded using the GRADE approach, considering study limitations, inconsistency, indirectness, imprecision and publication bias.
“The overall quality of evidence was graded using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach, considering study limitations, inconsistency, indirectness, imprecision and publication bias [40–44].”
From Efficacy of manual therapy by different healthcare professionals on pain and function in temporomandibular disorders: a systematic review of randomized controlled trials (2026) · cites this paper as [43]
Quality of evidence in included systematic reviews was assessed by outcome using the GRADE system criteria.
“Quality of evidence in included systematic reviews was assessed by outcome using the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system criteria [17-27].”
From Effects of Home Telemonitoring Interventions on Patients With Chronic Heart Failure: An Overview of Systematic Reviews (2015) · cites this paper as [21]
The GRADE approach was used to determine the quality of evidence.
“To determine the quality of evidence, the GRADE approach was used [29–36].”
From RETRACTED: Effectiveness of psychosocial interventions for infertile women: A systematic review and meta-analysis with a focus on a method-critical evaluation (2023) · cites this paper as [34]

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The Perils of Misinterpreting and Misusing “Publication Bias” in Meta-analyses: An Education Review on Funnel Plot-Based Methods
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Authors: Guyatt, G. H., Oxman, A. D., Montori, V., Vist, G., Kunz, R., Brozek, J., Alonso-Coello, P., Djulbegovic, B., Atkins, D., Falck-Ytter, Y., Williams, J. W., Meerpohl, J., Norris, S. L., Akl, E. A., & Schünemann, H. J.
Affiliations: McMaster University (CA)
Nasjonalt Kunnskapssenter for Helsetjenesten (NO)
University Hospital of Basel (CH)
VA Office of Research and Development (US)
Case Western Reserve University (US)
Duke Medical Center (US)
University Medical Center Freiburg (DE)
Oregon Health & Science University (US)
University at Buffalo, State University of New York (US)
ORCID: Guyatt, Gordon H.
Oxman, Andrew D.
Vist, Gunn
Kunz, Regina
Atkins, David
Falck-Ytter, Yngve
Williams, John W.
Meerpohl, Joerg
Norris, Susan L.
Akl, Elie A.
Schünemann, Holger J.
Venue: Journal of Clinical Epidemiology
Publisher: Elsevier BV
Published: 2011-12
Volume: 64
Issue: 12
Pages: 1277-1282
ISSN: 0895-4356 (ISSN-L)
DOI: 10.1016/j.jclinepi.2011.01.011
OpenAlex: W2109346853
Cited by: 1,819
References: 54
Citations by year: 2026: 75 · 2025: 142 · 2024: 153 · 2023: 144 · 2022: 172 · 2021: 180 · 2020: 196 · 2019: 120 · 2018: 122 · 2017: 123 · 2016: 109 · 2015: 109 · 2014: 77 · 2013: 51 · 2012: 40
FWCI: 57.89
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Journal of Clinical Epidemiology (publishedVersion)
PubMed (publishedVersion)
Topics: Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmaceutical industry and healthcare
Keywords: publication bias, GRADE, quality of evidence, funnel plot, small-study effects, commercial funding, risk of bias
MeSH terms: Cross-Sectional Studies, Drug Industry, Review Literature as Topic, Statistics as Topic, Meta-Analysis as Topic, Randomized Controlled Trials as Topic, Practice Guidelines as Topic, Publication Bias, Evidence-Based Medicine

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GRADE guidelines: 5. Rating the quality of evidence—publication bias

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