SPATIO-TEMPORAL CLUSTERS OF CANCER INCIDENCE IN THE ROSTOV REGION

Introduction: Malignant neoplasms represent a substantial medical and social problem of this century. Neither significant progress in our ability to diagnose caner at an early stage nor advancements in treatment contributed to the reduction in the incidence of cancer. A need for better understanding of the distribution of cancer over time and space warrants studies of spatio-temporal clusters of the most common malignant neoplasms. Aim: To study spatiotemporal clusters in the incidence of the most common cancers in the Rostov region, Southern Russia. Methods: We studied the incidence of lung-, breast-, colon- and prostate cancers from 2001 through 2016 in the Rostov region using the official statistical data. Spatio-temporal analysis of the data and their visualization was performed using the tool "Analysis of emerging hot spots" from the "In-depth analysis of spatiotemporal patterns" set of tools of the ArcGIS Pro software environment. Results: The incidence of prostate- and breast cancer increased by 119.6 % from 9.7 in 2001 to 21.3 cases per 100 thousand population (p < 0.05) and by 27.2 % from 26.8 to 34.1 cases per 100 thousand population (p < 0.05), respectively. The incidence of lung cancer decreased by 32.3 % from 51.0 to 34.5 cases per 100 thousand population (p < 0.05). The analysis showed that the prevalence of cancer varies significantly across individual territorial systems. Spatial clusters of low incidence of cancer are localized in the northern and central parts of the region. The "Hot spots" of the cancer incidence are located mainly in the southern part of the region. Conclusions: Identification of spatial and temporal clusters of the incidence of malignant neoplasms allows to set priorities in the implementation of measures aimed at management of factors which increase the incidence of cancer. Temporal trends in the incidence of malignant neoplasms reflects the level of the ecological well-being of the region.

malignant neoplasms, spatio-temporal clusters, geographic information technologies, incidence, Russia