Optimal Cutpoint Estimation with Censored Data
We consider the problem of selecting an optimal cutpoint for a continuous marker when the outcome of interest is subject to right censoring. Maximal chi square methods and receiver operating characteristic (ROC) curves-based methods are commonly-used when the outcome is binary. In this article we show that selecting the cutpoint that maximizes the concordance, a metric similar to the area under an ROC curve, is equivalent to maximizing the Youden index, a popular criterion when the ROC curve is used to choose a threshold. We use this as a basis for proposing maximal concordance as a metric to use with censored endpoints. Through simulations we evaluate the performance of two concordance estimates and three chi-square statistics under various assumptions. Maximizing the partial likelihood ratio test statistic has the best performance in our simulations.
Mithat Gonen and Camelia Sima. "Optimal Cutpoint Estimation with Censored Data" Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series (2008).
Available at: http://works.bepress.com/mithat_gonen/19