A NEW LATENT CURE RATE MARKER MODEL FOR SURVIVAL DATA

• 成果类型: Article
• 署名作者: Kim, Sungduk; Xi, Yingmei; Chen, Ming-Hui
• 署名单位: National Institutes of Health (NIH) - USA; NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD); Biogen; University of Connecticut
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/09-AOAS238
• 发表日期: 2009
• 页码: 1124-1146
• 关键词: beam radiation-therapy; time-to-event; bayesian model; radical prostatectomy; joint analysis; long-term

摘要

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.