title: Assessing the dependence of sensitivity and specificity on prevalence in meta-analysis.
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.
authors.affiliation: Department of Statistics & Applied Probability, Duke-NUS Graduate Medical School, National University of Singapore, Singapore 117546,. stalj@nus.edu.sg.
authors.forename: Jialiang
authors.initials: J
authors.lastname: Li
authors.forename: Jason P
authors.initials: JP
authors.lastname: Fine
mesh_terms: D014408:Biomarkers, Tumor / Q000032:analysis; D056808:Biostatistics; D018394:CA-125 Antigen / Q000032:analysis; D003952:Diagnostic Imaging; D005260:Female; D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D009369:Neoplasms / Q000175:diagnosis; D010051:Ovarian Neoplasms / Q000175:diagnosis; D049268:Positron-Emission Tomography; D015995:Prevalence; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed
chemical_list: D014408:Biomarkers, Tumor; D018394:CA-125 Antigen