Optimal Cutpoint Estimation with Censored Data
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Abstract:
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.
Subject Area:
General Biostatistics, Statistical Models, Survival Analysis
Suggested Citation:
Mithat Gonen and Camelia Sima, "Optimal Cutpoint Estimation with Censored Data" (November 2008). Memorial Sloan-Kettering Cancer Center Department of Epidemiology and Biostatistics Working Paper Series. Working Paper 16.
http://www.bepress.com/mskccbiostat/paper16