Prediction of Life Expectancy in Prostate Cancer Patients Based on the Kinetic Theory of the Aging of Living Systems

Abstract

We propose a method for the prediction of life expectancy (LE) in patients diagnosed with prostate cancer based on the kinetic theory of the aging of living systems. The life expectancy (survival time) is calculated from the differential equation for the rate of aging for three different life stages—“normal” life, life with prostate cancer, and life after combination therapy for prostate cancer. The method is based on the statistical correlation between the growth rate of the level of prostate specific antigen (PSA level) or the PSA doubling time (PSA DT) before therapy and the survival time: the higher the PSA DT is, the greater is the LE. The adequacy of prediction is proved by the satisfactory agreement rate of experimental data on survival time obtained in the group of patients from “fast PSA DT” and “slow PSA DT” categories. The prediction error of group LE is due to the completeness and reliability of the medical parameters and baseline values. Detailed monitoring of the basic health parameters throughout life for each patient in each analyzed group is needed to minimize such a prediction error. The absence of this particular information makes it impossible to predict individual life expectancy.