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. Copyright © 2012 John Wiley & Sons, Ltd.