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Review
. 2014 Feb;20(2):105-13.
doi: 10.1111/1469-0691.12474.

Systematic reviews and meta-analyses of diagnostic test accuracy

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Free article
Review

Systematic reviews and meta-analyses of diagnostic test accuracy

M M G Leeflang. Clin Microbiol Infect. 2014 Feb.
Free article

Abstract

Systematic reviews of diagnostic test accuracy summarize the accuracy, e.g. the sensitivity and specificity, of diagnostic tests in a systematic and transparent way. The aim of such a review is to investigate whether a test is sufficiently specific or sensitive to fit its role in practice, to compare the accuracy of two or more diagnostic tests, or to investigate where existing variation in results comes from. The search strategy should be broad and preferably fully reported, to enable readers to assess the completeness of it. Included studies usually have a cross-sectional design in which the tests of interest, ideally both the index test and its comparator, are evaluated against the reference standard. They should be a reflection of the situation that the review question refers to. The quality of included studies is assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 checklist, containing items such as a consecutive and all-inclusive patient selection process, blinding of index test and reference standard assessment, a valid reference standard, and complete verification of all included participants. Studies recruiting cases separately from (healthy) controls are regarded as bearing a high risk of bias. For meta-analysis, the bivariate model or the hierarchical summary receiver operating characteristic model is used. These models take into account potential threshold effects and the correlation between sensitivity and specificity. They also allow addition of covariates for investigatation of potential sources of heterogeneity. Finally, the results from the meta-analyses should be explained and interpreted for the reader, to be well understood.

Keywords: diagnosis; diagnostic test accuracy; evidence-based medicine; meta-analyses; sensitivity and specificity; systematic reviews.

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