A comprehensive and comparative review of optimal cut-points selection methods for diseases with multiple ordinal stages

Abstract

Cut-points selection is a key topic in the field of diagnostic studies. For binary classification, there exist several well-developed methods, some of which have been extended to three-class settings and beyond. This paper focuses on optimal cut-points selection methods for diseases with multiple ordinal stages. The purpose of this paper is two-fold: 1) to propose three new cut-points selection methods; and 2) to present a comprehensive simulation study to assess and compare the performance of all the available methods. Two real data sets, one from ovarian cancer and the other from pancreatic cancer, are analyzed.

Keywords: ROC curve; ROC surface; Youden index; area under ROC curve; volume under ROC surfac.