ANALYTICAL METHOD OF THE FORECAST OF KINETICS OF SURVIVAL OF ONCOLOGICAL PATIENTS AT THE COMBINED RADIATION THERAPY

Analytical method for prediction of the kinetics of survival (KS) and duration of the life expectancy (LE) in patients diagnosed with prostate cancer after combined radiation therapy was developed. It based on medical statistical data of the Federal state budget institution «Russian Research Center of Radiology and Surgical Technologies» (RRCRST) and the mathematical model of the kinetic aging theory of living systems. The quality of life indicators — KS and LE are determined by the solution of the differential equations describing the rate of aging homogeneous groups of patients and taking into account the four main stages of life from birth: «normal» (standard) life before the disease with probability of death for various reasons, life with additional cancer, determining at this stage the likely predominant cause of death from cancer, life is in the process of treatment and after its completion. Each stage of life has its own corresponding parameters of the mathematical model of aging rate, representing the competition of two opposite processes: the accumulation of damages of structural and functional relationships of the organism and their recovery speed. Their rate of destruction with cancer increases. The parameters of the mathematical model are determined by statistical processing of health indicators collected in banks demographic data CDR NES and medical data RRCRST. The main ideology of the developed model based on statistical correlation with survival in the published works of experts of the RRCRST. For patients with prostate cancer is the prostate-specific antigen (PSA) doubling time (PSADT), for patients with breast cancer is the value of S-index (indicator of the degree of radiation-induced DNA decomposition of blood samples in vitro) before treatment of patients. The model is tested on the example of prediction KS and LE in patients of RRCRST treated with radiation therapy that were grouped according to similar values of PSADT and S-index. The ability to improve forecast accuracy by reducing the number of individuals in the group due to the need to have a health and demographic information for each patient and, above all, on the rate of growth of cancer.

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