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

¹ Applied Statistics, School of Biological Sciences, University of Reading, Reading, UK and
² Statistics and Methods, Institute for Psychology IV, University of Münster, Münster, Germany

^* To whom correspondence should be addressed.

	Abstract

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. Themeasure 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 ableto cope with unobserved heterogeneity via a nonparametric mixture model. Allmethods are illustrated at hand of an example on a diagnostic meta-analysis onduplex doppler ultrasound, with angiography as the standard for stroke prevention.

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