Department of Biostatistics, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY, USA.
J Biopharm Stat. 2020;30(1):46-68. doi: 10.1080/10543406.2019.1632876. Epub 2019 Jun 28.
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.
临界点选择是诊断研究领域的一个关键课题。对于二分类问题，已经存在一些成熟的方法，其中一些方法已经扩展到了三分类甚至更多分类的情况。本文主要关注具有多个有序阶段疾病的最优临界点选择方法。本文的目的有两个：1）提出三种新的临界点选择方法；2）进行全面的模拟研究，以评估和比较所有可用方法的性能。分析了两个真实数据集，一个来自卵巢癌，另一个来自胰腺癌。
