Introduction: In the Primorsky Region, there is a steady upward trend in breast cancer morbidity and mortality. Lifestyle, material wellbeing, availability and timeliness of receiving medical care, along with genetic predisposition, have a significant impact on life expectancy and mortality of cancer patients, which is of great importance for public health, especially when developing a strategy to improve the quality of life and health status of the population.
Objective: The study aimed to analyze the situation and to develop a model for mortality prediction based on breast cancer prevalence rates and socio-economic indicators of the population of the Primorsky Region.
Materials and methods: The study was carried out based on data from the Federal State Statistics Service and the Medical Information Analytical Center of the Primorsky Region for 1994–2019. Correlation analysis was used to analyze statistical data and the prediction model was developed using artificial neural networks.
Results: In 2000–2019, there was a rise in breast cancer mortality by 39.13 % in the region. The statistical analysis of the relationship
between socio-economic indicators and the mortality rate showed significant correlations, which were further used for the development of a neural network model. We observed that predictions were most influenced by parameters of material well-being and health care quality.
Conclusion: The established relationships prove the necessity of considering them when designing management decisions aimed to increase life expectancy and improve the quality of life in breast cancer patients.
ANALYSIS OF SOME SOCIO-ECONOMIC INDICATORS OF DEVELOPING COUNTRIES
