Background . The prevalence of cervical cancer (Cca) in Russian women makes it crucial to study modern epidemiological characteristics and adjust control measures accordingly. The aim . To analyze trends in the incidence of cervical cancer in the Russian Federation. Materials and methods . A retrospective epidemiological study was conducted on cervical cancer incidence in Russian Federation from 2008 to 2021. The materials of annual statistical data “Malignant neoplasms in Russia (morbidity and mortality)” and “Status of oncological assistance to the population of Russia” (2008–2022), data of the federal statistical reporting form No. 5 “Information about preventive vaccinations” (2021), data on the number of studies conducted (cytological study and HPV-test based on RT-PCR) in the clinical diagnostic laboratory of Central Research Institute of Epidemiology of Rospotrebnadzor (2013–2021) were used. Results and discussion . The trends of Cca incidence varied depending on the women’s age. Starting in 2016, there was a stabilization of the level of morbidity in women aged 30–49 with the subsequent decrease from 2019 due to the strengthening of secondary prevention measures, including the active introduction of HPV-test into the diagnostic schemes conducted in the Russian Federation. Increased control of cervical cancer caused a rise in the proportion of cases diagnosed at an early stage (carcinomas in situ and I–II stages Cca), the increase of detection rate of in situ carcinomas per 100 cases of Cca, the growth of the proportion of carcinomas in situ to I–II stages Cca, rise of the percentage of the cases detected actively, decrease of the number of Cca cases detected at later stages and one-year mortality index. Conclusion . The epidemiological analysis of cervical cancer incidence shows that preventive measures are effective and that there is a need to intensify and increase their coverage.

O. B. Kuleshova

E. A. Domonova

Current epidemiological characteristics of cervical cancer in the Russian Federation

ivySCI AI Smartly Parses PDF, Answers Researchers' Questions, and Helps You Understand Papers in Seconds

Journal Info