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J Clin Epidemiol. 2005 Oct;58(10):982-90.

Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews.

Author information

  • 1Department of Clinical Epidemiology and Biostatistics, Academic Medical Center, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, The Netherlands. j.reitsma@amc.uva.nl

Abstract

BACKGROUND AND OBJECTIVES:

Studies of diagnostic accuracy most often report pairs of sensitivity and specificity. We demonstrate the advantage of using bivariate meta-regression models to analyze such data.

METHODS:

We discuss the methodology of both the summary Receiver Operating Characteristic (sROC) and the bivariate approach by reanalyzing the data of a published meta-analysis.

RESULTS:

The sROC approach is the standard method for meta-analyzing diagnostic studies reporting pairs of sensitivity and specificity. This method uses the diagnostic odds ratio as the main outcome measure, which removes the effect of a possible threshold but at the same time loses relevant clinical information about test performance. The bivariate approach preserves the two-dimensional nature of the original data. Pairs of sensitivity and specificity are jointly analyzed, incorporating any correlation that might exist between these two measures using a random effects approach. Explanatory variables can be added to the bivariate model and lead to separate effects on sensitivity and specificity, rather than a net effect on the odds ratio scale as in the sROC approach. The statistical properties of the bivariate model are sound and flexible.

CONCLUSION:

The bivariate model can be seen as an improvement and extension of the traditional sROC approach.

Comment in

PMID:
16168343
[PubMed - indexed for MEDLINE]
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