title: Estimation of the Youden Index and its associated cutoff point.
abstract: The Youden Index is a frequently used summary measure of the ROC (Receiver Operating Characteristic) curve. It both, measures the effectiveness of a diagnostic marker and enables the selection of an optimal threshold value (cutoff point) for the marker. In this paper we compare several estimation procedures for the Youden Index and its associated cutoff point. These are based on (1) normal assumptions; (2) transformations to normality; (3) the empirical distribution function; (4) kernel smoothing. These are compared in terms of bias and root mean square error in a large variety of scenarios by means of an extensive simulation study. We find that the empirical method which is the most commonly used has the overall worst performance. In the estimation of the Youden Index the kernel is generally the best unless the data can be well transformed to achieve normality whereas in estimation of the optimal threshold value results are more variable.
authors.affiliation: Department of Statistics, University of Haifa 31905, Israel. rfluss@stat.haifa.ac.il
authors.forename: Ronen
authors.initials: R
authors.lastname: Fluss
authors.forename: David
authors.initials: D
authors.lastname: Faraggi
authors.forename: Benjamin
authors.initials: B
authors.lastname: Reiser
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000097:blood; D003198:Computer Simulation; D016001:Confidence Intervals; D003324:Coronary Artery Disease / Q000097:blood* / Q000175:diagnosis* / Q000201:enzymology; D003402:Creatine Kinase / Q000032:analysis*; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D012372:ROC Curve; D015203:Reproducibility of Results; D012107:Research Design; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index
chemical_list: D015415:Biomarkers; D003402:Creatine Kinase