A simple PSA-based computational approach predicts the timing of cancer relapse in prostatectomized patients

Recurrences of prostate cancer affect approximately one-quarter of patients who have undergone radical prostatectomy. Reliable factors to predict time to relapse in specific individuals are lacking. Here we present a mathematical model that evaluates a biologically sensible parameter ($\alpha$) which can be estimated by the available follow-up data, in particular by the prostate specific antigen (PSA) series. This parameter is robust and highly predictive for the time to relapse, also after administration of adjuvant androgen deprivation therapies. We present a practical computational method based on the collection of only four post-surgical PSA values. This study offers a simple tool to predict PCa relapse.