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Assessing the dependence of sensitivity and specificity on prevalence in meta-analysis
1Department of Statistics & Applied Probability, Duke-NUS Graduate Medical School, National University of Singapore, Singapore 117546,. stalj@nus.edu.sg.
Abstract:
We consider modeling the dependence of sensitivity and specificity on the disease prevalence in diagnostic accuracy studies. Many meta-analyses compare test accuracy across studies and fail to incorporate the possible connection between the accuracy measures and the prevalence. We propose a Pearson type correlation coefficient and an estimating equation-based regression framework to help understand such a practical dependence. The results we derive may then be used to better interpret the results from meta-analyses. In the biomedical examples analyzed in this paper, the diagnostic accuracy of biomarkers are shown to be associated with prevalence, providing insights into the utility of these biomarkers in low- and high-prevalence populations.
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