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Revisiting youden's index as a useful measure of the misclassification error in meta-analysis of diagnostic studies

Applied Statistics, School of Biological Sciences, University of Reading, Reading, UK, d.a.w.bohning{at}reading.ac.uk

Walailuck Böhning

Statistics and Methods, Institute for Psychology IV, University of Münster, Münster, Germany

Heinz Holling

Statistics and Methods, Institute for Psychology IV, University of Münster, Münster, Germany

The paper considers meta-analysis of diagnostic studies that use a continuous score for classification of study participants into healthy or diseased groups. Classification is often done on the basis of a threshold or cut-off value, which might vary between studies. Consequently, conventional meta-analysis methodology focusing solely on separate analysis of sensitivity and specificity might be confounded by a potentially unknown variation of the cut-off value. To cope with this phenomena it is suggested to use, instead, an overall estimate of the misclassification error previously suggested and used as Youden's index and; furthermore, it is argued that this index is less prone to between-study variation of cut-off values. A simple Mantel—Haenszel estimator as a summary measure of the overall misclassification error is suggested, which adjusts for a potential study effect. The measure of the misclassification error based on Youden's index is advantageous in that it easily allows an extension to a likelihood approach, which is then able to cope with unobserved heterogeneity via a nonparametric mixture model. All methods are illustrated at hand of an example on a diagnostic meta-analysis on duplex doppler ultrasound, with angiography as the standard for stroke prevention.

This version was published on December 1, 2008

Statistical Methods in Medical Research, Vol. 17, No. 6, 543-554 (2008)
DOI: 10.1177/0962280207081867


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