Classification accuracy and cut point selection.
In biomedical research and practice, quantitative tests or biomarkers are often used for diagnostic or screening purposes, with a cut point established on the quantitative measurement to aid binary classification. This paper introduces an alternative to the traditional methods based on the Youden index and the closest-to-(0, 1) criterion for threshold selection. A concordance probability evaluating the classification accuracy of a dichotomized measure is defined as an objective function of the possible cut point. A nonparametric approach is used to search for the optimal cut point maximizing the objective function. The procedure is shown to perform well in a simulation study. Using data from a real-world study of arsenic-induced skin lesions, we apply the method to a measure of blood arsenic levels, selecting a cut point to be used as a warning threshold.
Department of Biostatistics, Columbia University, New York, NY 10032, USA. xl26@columbia.edu
Xinhua
X
Liu
D000328:Adult; D019540:Area Under Curve; D001151:Arsenic / Q000097:blood; D015415:Biomarkers / Q000032:analysis*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D012372:ROC Curve; D012871:Skin Diseases / Q000139:chemically induced
D015415:Biomarkers; D001151:Arsenic