The strong focus on positive results in abstracts may cause bias in systematic reviews: a case study on abstract reporting bias.

Abstract Bladder cancer Diesel exhaust exposure Epidemiology Keywords Reporting bias Search engines Systematic reviews

Journal

Systematic reviews
ISSN: 2046-4053
Titre abrégé: Syst Rev
Pays: England
ID NLM: 101580575

Informations de publication

Date de publication:
17 07 2019
Historique:
received: 11 02 2019
accepted: 28 06 2019
entrez: 19 7 2019
pubmed: 19 7 2019
medline: 21 8 2020
Statut: epublish

Résumé

Research articles tend to focus on positive findings in their abstract, especially if multiple outcomes have been studied. At the same time, search queries in databases are generally limited to the abstract, title and keywords fields of an article. Negative findings are therefore less likely to be detected by systematic searches and to appear in systematic reviews. We aim to assess the occurrence of this 'abstract reporting bias' and quantify its impact in the literature on the association between diesel exhaust exposure (DEE) and bladder cancer. We set up a broad search query related to DEE and cancer in general. Full-texts of the articles identified in the search output were manually scanned. Articles were included if they reported, anywhere in the full-text, the association between DEE and bladder cancer. We assume that the use of a broad search query and manual full-text scanning allowed us to catch all the relevant articles, including those in which bladder cancer was not mentioned in the abstract, title or keywords. We identified 28 articles. Only 12 of these (43%) had mentioned bladder in their abstract, title or keywords. A meta-analysis based on these 12 detectable articles yielded a pooled risk estimate of 1.10 (95% confidence interval [CI] 0.97-1.25), whereas the meta-analysis based on all 28 articles yielded a pooled estimate of 1.03 (95% CI 0.96-1.11). This case study on abstract reporting bias shows that (a) more than half of all relevant articles were missed by a conventional search query and (b) this led to an overestimation of the pooled effect. Detection of articles will be improved if all studied exposure and outcome variables are reported in the keywords. The restriction on the maximum number of keywords should be lifted.

Sections du résumé

BACKGROUND
Research articles tend to focus on positive findings in their abstract, especially if multiple outcomes have been studied. At the same time, search queries in databases are generally limited to the abstract, title and keywords fields of an article. Negative findings are therefore less likely to be detected by systematic searches and to appear in systematic reviews. We aim to assess the occurrence of this 'abstract reporting bias' and quantify its impact in the literature on the association between diesel exhaust exposure (DEE) and bladder cancer.
METHODS
We set up a broad search query related to DEE and cancer in general. Full-texts of the articles identified in the search output were manually scanned. Articles were included if they reported, anywhere in the full-text, the association between DEE and bladder cancer. We assume that the use of a broad search query and manual full-text scanning allowed us to catch all the relevant articles, including those in which bladder cancer was not mentioned in the abstract, title or keywords.
RESULTS
We identified 28 articles. Only 12 of these (43%) had mentioned bladder in their abstract, title or keywords. A meta-analysis based on these 12 detectable articles yielded a pooled risk estimate of 1.10 (95% confidence interval [CI] 0.97-1.25), whereas the meta-analysis based on all 28 articles yielded a pooled estimate of 1.03 (95% CI 0.96-1.11).
CONCLUSIONS
This case study on abstract reporting bias shows that (a) more than half of all relevant articles were missed by a conventional search query and (b) this led to an overestimation of the pooled effect. Detection of articles will be improved if all studied exposure and outcome variables are reported in the keywords. The restriction on the maximum number of keywords should be lifted.

Identifiants

pubmed: 31315665
doi: 10.1186/s13643-019-1082-9
pii: 10.1186/s13643-019-1082-9
pmc: PMC6637611
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

174

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Auteurs

Bram Duyx (B)

Nutrition and Translational Research in Metabolism (School NUTRIM), Maastricht University, Maastricht, The Netherlands. b.duyx@maastrichtuniversity.nl.

Gerard M H Swaen (GMH)

Nutrition and Translational Research in Metabolism (School NUTRIM), Maastricht University, Maastricht, The Netherlands.

Miriam J E Urlings (MJE)

Nutrition and Translational Research in Metabolism (School NUTRIM), Maastricht University, Maastricht, The Netherlands.

Lex M Bouter (LM)

Department of Epidemiology and Biostatistics, Amsterdam University Medical Centers, Amsterdam, The Netherlands.
Department of Philosophy, Faculty of Humanities, Vrije Universiteit, Amsterdam, The Netherlands.

Maurice P Zeegers (MP)

Nutrition and Translational Research in Metabolism (School NUTRIM), Maastricht University, Maastricht, The Netherlands.
Care and Public Health Research Institute (School CAPHRI), Maastricht University, Maastricht, The Netherlands.

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Classifications MeSH