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September 2009 A new latent cure rate marker model for survival data
Sungduk Kim, Yingmei Xi, Ming-Hui Chen
Ann. Appl. Stat. 3(3): 1124-1146 (September 2009). DOI: 10.1214/09-AOAS238

Abstract

To address an important risk classification issue that arises in clinical practice, we propose a new mixture model via latent cure rate markers for survival data with a cure fraction. In the proposed model, the latent cure rate markers are modeled via a multinomial logistic regression and patients who share the same cure rate are classified into the same risk group. Compared to available cure rate models, the proposed model fits better to data from a prostate cancer clinical trial. In addition, the proposed model can be used to determine the number of risk groups and to develop a predictive classification algorithm.

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Sungduk Kim. Yingmei Xi. Ming-Hui Chen. "A new latent cure rate marker model for survival data." Ann. Appl. Stat. 3 (3) 1124 - 1146, September 2009. https://doi.org/10.1214/09-AOAS238

Information

Published: September 2009
First available in Project Euclid: 5 October 2009

zbMATH: 1196.62142
MathSciNet: MR2750389
Digital Object Identifier: 10.1214/09-AOAS238

Keywords: Deviance Information Criterion (DIC) , logarithm of pseudomarginal likelihood (LPML) , Markov chain Monte Carlo , PSA recurrence

Rights: Copyright © 2009 Institute of Mathematical Statistics

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Vol.3 • No. 3 • September 2009
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