Survival Analysis of Recurrent Events on Prostate Cancer: Facts from Cancer Genome

• Activity Number: 679 - Variable Selection and Prediction Models for Genomic Data
• Type: Contributed
• Date/Time: Thursday, August 2, 2018 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Munni Begum*
• Companies: Ball State University
• Keywords: Survival Modeling; Recurrent Events; Gene Expression; Prostate Cancer; TCGA

Abstract

Many diseases and clinical outcomes may recur to the same patient. These events are termed as recurrent events. Several statistical models have been proposed in the literature to analyze recurrent events. In this study, we identify the clinical and the genetic risk factors for recurring tumors among prostate cancer patients from The Cancer Genome Atlas (TCGA). Five statistical approaches for modeling recurrent time-to-event are implemented to identify and to determine the effects of the clinical and the genetic risk factors of tumor recurrence. In particular, we consider Andersen-Gill (A-G), Wei-Lin-Weissfeld (WLW), Prentice-Williams-Peterson Total Time (PWP-TT), Prentice-Williams-Peterson Gap Time (PWP-GT) and Frailty models. We present and discuss the risk factors influencing the recurrence of tumors and their impacts in prostate cancer patients obtained from five commonly used models in this paper.