Age-related carcinogenesis: Risk assessment and risk evolution

Within this study, a phenomenological mathematical model has been developed and parameterized; it is based on the system of evolution equations and designed for quantification of effects produced by age on population cancer risk. The model describes risk dynamics as the function of likelihood of cancer and its severity relying on retrospective population data. The 10th percentile of incidence per administrative territories was used to identify the background age-related component cleared from influence of local carcinogenic factors. The equation parameters were estimated by the least square method.

The model parameterization revealed considerable inter-nosology variability in key parameters, which reflected specific features of pathogenesis of different tumor types. Analysis of age-related dynamics in the risk structure revealed that contributions made by specific nosologies were re-distributed systemically. We established progressive predominance of malignant neoplasms of the digestive system in the cancer risk structure since they became the leading age-related pathology in older age groups. A parallel considerable decline was found as regards contributions made by other nosologies, breast cancer included.

The resulting picture of age-related evolution of cancer risk shows a discrepancy from the conventional priorities in oncological care, which are often oriented at nosologies with high median incidence. The modeling results highlight the necessity to shift the attention focus on pathologies with the most intensive age-related risk and fatality accumulation. This primarily includes tumors of the digestive system since they make the major contribution to age-related cancer mortality, which is not fully considered within the existing approaches. This emphasizes the necessity to adapt preventive and screening strategies considering the biologically determined structure of population risk. The focus should be shifted on targeted gerontological oncology. The developed model adequately describes age-related carcinogenesis and provides solid basis for assessing additional risks caused by specific endo- and exogenous effects as well as for developing targeted gerontological oncological strategies.