• 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, and Holger J Schünemann.
• Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario L8N 3Z5, Canada. guyatt@mcmaster.ca
• J Clin Epidemiol. 2011 Dec 1;64(12):1277-82.

AbstractIn 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.Copyright © 2011 Elsevier Inc. All rights reserved.

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