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Assessing variability in results in systematic reviews of diagnostic studies

BMC Medical Research Methodology. 2016;16(1):1-8 DOI 10.1186/s12874-016-0108-4

 

Journal Homepage

Journal Title: BMC Medical Research Methodology

ISSN: 1471-2288 (Online)

Publisher: BMC

LCC Subject Category: Medicine: Medicine (General)

Country of publisher: United Kingdom

Language of fulltext: English

Full-text formats available: PDF, HTML

 

AUTHORS


Christiana A. Naaktgeboren (Julius Center for Health Sciences and Primary Care, University Medical Center)

Eleanor A. Ochodo (Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center)

Wynanda A. Van Enst (Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center)

Joris A. H. de Groot (Julius Center for Health Sciences and Primary Care, University Medical Center)

Lotty Hooft (Dutch Cochrane Centre, Academic Medical Center)

Mariska M. G. Leeflang (Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center)

Patrick M. Bossuyt (Dutch Cochrane Centre, Academic Medical Center)

Karel G. M. Moons (Julius Center for Health Sciences and Primary Care, University Medical Center)

Johannes B. Reitsma (Julius Center for Health Sciences and Primary Care, University Medical Center)

EDITORIAL INFORMATION

Open peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 23 weeks

 

Abstract | Full Text

Abstract Background To describe approaches used in systematic reviews of diagnostic test accuracy studies for assessing variability in estimates of accuracy between studies and to provide guidance in this area. Methods Meta-analyses of diagnostic test accuracy studies published between May and September 2012 were systematically identified. Information on how the variability in results was investigated was extracted. Results Of the 53 meta-analyses included in the review, most (n=48; 91 %) presented variability in diagnostic accuracy estimates visually either through forest plots or ROC plots and the majority (n=40; 75 %) presented a test or statistical measure for the variability. Twenty-eight reviews (53 %) tested for variability beyond chance using Cochran’s Q test and 31 (58 %) reviews quantified it with I2. 7 reviews (13 %) presented between-study variance estimates (τ2) from random effects models and 3 of these presented a prediction interval or ellipse to facilitate interpretation. Half of all the meta-analyses specified what was considered a significant amount of variability (n=24; 49 %). Conclusions Approaches to assessing variability in estimates of accuracy varied widely between diagnostic test accuracy reviews and there is room for improvement. We provide initial guidance, complemented by an overview of the currently available approaches.