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 in uencing the
recurrence of tumors and their impacts in prostate cancer patients obtained from
five commonly used models in this paper.