[Prediction of life expectancy for prostate cancer patients based on the kinetic theory of aging of living systems].

Autor:	Viktorov AA; State Research Center - Burnasyan Federal Medical Biophysical Center of Federal Medical Biological Agency (SRC-FMBC), 46, Zhivopisnaya str., Moscow, 123182, Russian Federation; a-victorov@mail.ru., Zharinov GM; Federal State Budget Institution Russian Research Center of Radiology and Surgical Technologies, 70, Leningradskaya str., Pesochny, St. Petersburg, 197758, Russian Federation; asatur15@mail.ru., Neklasova NJ; Federal State Budget Institution Russian Research Center of Radiology and Surgical Technologies, 70, Leningradskaya str., Pesochny, St. Petersburg, 197758, Russian Federation; asatur15@mail.ru., Morozova EE; Central Children's Clinical Hospital, Russian Federal Medical and Biological Agency, 20, Moskvorech'e str., Moscow, 115309, Russian Federation; ev.e.morozova@mail.ru.
Jazyk:	ruština
Zdroj:	Advances in gerontology = Uspekhi gerontologii [Adv Gerontol] 2017; Vol. 30 (3), pp. 356-362.
Abstrakt:	The article presents a methodical approach for prediction of life expectancy for people diagnosed with prostate cancer based on the kinetic theory of aging of living systems. The life expectancy is calculated by solving the differential equation for the rate of aging for three different stage of life - «normal» life, life with prostate cancer and life after combination therapy for prostate cancer. The mathematical model of aging for each stage of life has its own parameters identified by the statistical analysis of healthcare data from the Zharinov's databank and Rosstat CDR NES databank. The core of the methodical approach is the statistical correlation between growth rate of the prostate specific antigen level (PSA-level) or the PSA doubling time (PSA DT) before therapy, and lifespan: the higher the PSA DT is, the greater lifespan. The patients were grouped under the «fast PSA DT» and «slow PSA DT» categories. The satisfactory matching between calculations and experiment is shown. The prediction error of group life expectancy is due to the completeness and reliability of the main data source. A detailed monitoring of the basic health indicators throughout the each person life in each analyzed group is required. The absence of this particular information makes it impossible to predict the individual life expectancy.
Databáze:	MEDLINE
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