Methods for detecting, quantifying, and adjusting for dissemination bias in meta-analysis are described.

Détails

ID Serval
serval:BIB_5ACA06382B74
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Methods for detecting, quantifying, and adjusting for dissemination bias in meta-analysis are described.
Périodique
Journal of clinical epidemiology
Auteur(s)
Mueller K.F., Meerpohl J.J., Briel M., Antes G., von Elm E., Lang B., Motschall E., Schwarzer G., Bassler D.
ISSN
1878-5921 (Electronic)
ISSN-L
0895-4356
Statut éditorial
Publié
Date de publication
12/2016
Volume
80
Pages
25-33
Langue
anglais
Notes
Publication types: Review ; Journal Article
Publication Status: ppublish
Résumé
To systematically review methodological articles which focus on nonpublication of studies and to describe methods of detecting and/or quantifying and/or adjusting for dissemination in meta-analyses. To evaluate whether the methods have been applied to an empirical data set for which one can be reasonably confident that all studies conducted have been included.
We systematically searched Medline, the Cochrane Library, and Web of Science, for methodological articles that describe at least one method of detecting and/or quantifying and/or adjusting for dissemination bias in meta-analyses.
The literature search retrieved 2,224 records, of which we finally included 150 full-text articles. A great variety of methods to detect, quantify, or adjust for dissemination bias were described. Methods included graphical methods mainly based on funnel plot approaches, statistical methods, such as regression tests, selection models, sensitivity analyses, and a great number of more recent statistical approaches. Only few methods have been validated in empirical evaluations using unpublished studies obtained from regulators (Food and Drug Administration, European Medicines Agency).
We present an overview of existing methods to detect, quantify, or adjust for dissemination bias. It remains difficult to advise which method should be used as they are all limited and their validity has rarely been assessed. Therefore, a thorough literature search remains crucial in systematic reviews, and further steps to increase the availability of all research results need to be taken.

Mots-clé
Dissemination bias, Full publication, Publication bias, Small-study effect, Statistical methods, The OPEN project, Underreporting
Pubmed
Web of science
Création de la notice
12/01/2017 16:25
Dernière modification de la notice
20/08/2019 15:13
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