GRADE guidelines: 5. Rating the quality of evidence - Publication bias

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

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)1277-1282
Number of pages6
JournalJournal of Clinical Epidemiology
Volume64
Issue number12
DOIs
StatePublished - Dec 2011

Fingerprint

Publication Bias
Guidelines
Sample Size
Observational Studies

Keywords

  • Conflict of interest
  • Funnel plot
  • GRADE
  • Pharmaceutical industry
  • Publication bias
  • Quality of evidence

ASJC Scopus subject areas

  • Epidemiology

Cite this

Guyatt, G. H., Oxman, A. D., Montori, V., Vist, G., Kunz, R., Brozek, J., ... Schünemann, H. J. (2011). GRADE guidelines: 5. Rating the quality of evidence - Publication bias. Journal of Clinical Epidemiology, 64(12), 1277-1282. https://doi.org/10.1016/j.jclinepi.2011.01.011

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.

In: Journal of Clinical Epidemiology, Vol. 64, No. 12, 12.2011, p. 1277-1282.

Research output: Contribution to journalArticle

Guyatt, GH, Oxman, AD, Montori, V, Vist, G, Kunz, R, Brozek, J, Alonso-Coello, P, Djulbegovic, B, Atkins, D, Falck-Ytter, Y, Williams, JW, Meerpohl, J, Norris, SL, Akl, EA & Schünemann, HJ 2011, 'GRADE guidelines: 5. Rating the quality of evidence - Publication bias', Journal of Clinical Epidemiology, vol. 64, no. 12, pp. 1277-1282. https://doi.org/10.1016/j.jclinepi.2011.01.011
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. / GRADE guidelines : 5. Rating the quality of evidence - Publication bias. In: Journal of Clinical Epidemiology. 2011 ; Vol. 64, No. 12. pp. 1277-1282.
@article{cd035581cfb4482c971a7513ff8848a8,
title = "GRADE guidelines: 5. Rating the quality of evidence - Publication bias",
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.",
keywords = "Conflict of interest, Funnel plot, GRADE, Pharmaceutical industry, Publication bias, Quality of evidence",
author = "Guyatt, {Gordon H.} and Oxman, {Andrew D.} and Victor Montori and Gunn Vist and Regina Kunz and Jan Brozek and Pablo Alonso-Coello and Ben Djulbegovic and David Atkins and Yngve Falck-Ytter and Williams, {John W.} and Joerg Meerpohl and Norris, {Susan L.} and Akl, {Elie A.} and Sch{\"u}nemann, {Holger J.}",
year = "2011",
month = "12",
doi = "10.1016/j.jclinepi.2011.01.011",
language = "English (US)",
volume = "64",
pages = "1277--1282",
journal = "Journal of Clinical Epidemiology",
issn = "0895-4356",
publisher = "Elsevier USA",
number = "12",

}

TY - JOUR

T1 - GRADE guidelines

T2 - 5. Rating the quality of evidence - Publication bias

AU - Guyatt, Gordon H.

AU - Oxman, Andrew D.

AU - Montori, Victor

AU - Vist, Gunn

AU - Kunz, Regina

AU - Brozek, Jan

AU - Alonso-Coello, Pablo

AU - Djulbegovic, Ben

AU - Atkins, David

AU - Falck-Ytter, Yngve

AU - Williams, John W.

AU - Meerpohl, Joerg

AU - Norris, Susan L.

AU - Akl, Elie A.

AU - Schünemann, Holger J.

PY - 2011/12

Y1 - 2011/12

N2 - 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.

AB - 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.

KW - Conflict of interest

KW - Funnel plot

KW - GRADE

KW - Pharmaceutical industry

KW - Publication bias

KW - Quality of evidence

UR - http://www.scopus.com/inward/record.url?scp=80054759619&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80054759619&partnerID=8YFLogxK

U2 - 10.1016/j.jclinepi.2011.01.011

DO - 10.1016/j.jclinepi.2011.01.011

M3 - Article

C2 - 21802904

VL - 64

SP - 1277

EP - 1282

JO - Journal of Clinical Epidemiology

JF - Journal of Clinical Epidemiology

SN - 0895-4356

IS - 12

ER -