Targeted diagnostics of breast cancer based on a comprehensive analysis of risk factors

Abstract

BACKGROUND: To date, there are no effective methods for early diagnosis and screening of breast cancer. High-tech methods, such as magnetic resonance imaging and contrasted computed tomography, as well as positron emission computed tomography have high resolution, but their high cost does not allow the use of these techniques for screening and primary diagnosis.

AIM: To improve the quality and efficiency of diagnostic measures for breast cancer through a personalized approach based on an analysis of a set of risk factors.

MATERIALS AND METHODS: Data from the population cancer registry of the Altai Territory, created at the Altai Regional Oncology Center (Barnaul, Russia), were used. To date, the register includes information on 308 550 patients with malignant neoplasms, including 31 783 women with breast cancer.

Based on the method of targeted prevention by A.F. Lazarev “Method for determining the risk of breast cancer according to Lazarev A.F.” (Patent No. 2651131) an “Automated program for early diagnosis of breast cancer” was developed. The program significantly reduces the time for the formation of groups of high cancer risk precancers and increases the efficiency of breast cancer detection, and also makes it possible to develop a set of targeted preventive measures personally for each patient. Testing of this algorithm included testing of 512 patients, as a result of which a high-risk precancer group was formed. In the established register, patients underwent a complex of in-depth examinations (ultrasound examination, mammography, magnetic resonance imaging with dynamic contrast, and puncture of tumors if indicated).

RESULTS: The precancer group at high risk of developing breast cancer consisted of 92 patients, in-depth examination revealed 7 patients with established breast cancer, which amounted to 7.6%. All cases of breast cancer were detected in stages I and II.

CONCLUSION: Targeted diagnostics using the “Automated program for early diagnosis of breast cancer” allows to improve the quality and efficiency of diagnostic measures for breast cancer identification through personalized approach, using multiple risk factors.

Keywords

breast cancer / digital technologies in diagnostics / prevention and early diagnosis

References

[1] Surveillance, Epidemiology, and End Results Program. Breast cancer. USA : National Cancer Institute. [cited 01 Jan 2023]. Available from: http://www.seer.cancer.gov

[2] Surveillance, Epidemiology, and End Results Program. Breast cancer. USA : National Cancer Institute. [дата обращения: 01.01.2023]. Доступ по ссылке: http://www.seer.cancer.gov

[3] Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209–249. doi: 10.3322/caac.21660

[4] Sung H., Ferlay J., Siegel R.L., et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries // CA Cancer J Clin. 2021. Vol. 71, N 3. P. 209–249. doi: 10.3322/caac.21660

[5] Kaprin AD, Starinskii VV, Shakhzadova AO, editors. Malignant neoplasms in Russia in 2021 (morbidity and mortality). Moscow: P.A. Herzen MNIOI — branch of FGBU NMC Radiology of the Ministry of Health of Russia; 2022. (In Russ).

[6] Злокачественные новообразования в России в 2021 году (заболеваемость и смертность) / под ред. А.Д. Каприна, В.В. Старинского, А.О. Шахзадовой. Москва : МНИОИ им. П.А. Герцена — филиал ФГБУ «НМИЦ радиологии» Минздрава России, 2022.

[7] Kaprin AD, Starinskii VV, Shakhzadova AO, editors. State of oncological care for the Russian population in 2022. Moscow: P.A. Herzen MNIOI - branch of FGBU NMC Radiology of the Ministry of Health of Russia; 2022. (In Russ).

[8] Состояние онкологической помощи населению России в 2022 году / под ред. А.Д. Каприна, В.В. Старинского, А.О. Шахзадовой. Москва : МНИОИ им. П.А. Герцена — филиал ФГБУ «НМИЦ радиологии» Минздрава России, 2022.

[9] Gazhonova VE, Efremova MP, Dorokhova EA. Modern methods of non-invasive radiation diagnostics of breast cancer. Russkii Meditsinskii Zhurnal. 2016;(5):321–324.

[10] Гажонова В.Е., Ефремова М.П., Дорохова Е.А. Современные методы неинвазивной лучевой диагностики рака молочной железы // Русский Медицинский Журнал. 2016. № 5. С. 321–324.

[11] Breast cancer. Clinical guidelines. ID 615. Approved by the Scientific and Practical Council of the Ministry of Health of the Russian Federation. 2021. Available from: https://cr.minzdrav.gov.ru/recomend/379_4 (In Russ)

[12] Клинические рекомендации — Рак молочной железы. ID 379. Одобрено Научно-практическим Советом Минздрава РФ. 2021. Режим доступа: https://cr.minzdrav.gov.ru/recomend/379_4 Дата обращения: 01.01.2023

[13] Certificate of state registration of the computer program №2008611703/ 31.03.2008. Lazarev AF. Territorial Cancer Registry. (In Russ).

[14] Свидетельство о государственной регистрации программы для ЭВМ №2008611703/ 31.03.2008. Лазарев А.Ф. Территориальный раковый регистр.

[15] Lazarev AF. Formation of cancer risk groups using digital technologies: methodological recommendations for physicians, residents and students. Lazarev AF, Lazarev SA, editors. Barnaul: Izd-vo FGBOU VO AGMU Minzdrava Rossii; 2020. (In Russ).

[16] Лазарев А.Ф. Формирование групп онкологического риска с использованием цифровых технологий: методические рекомендации для врачей, ординаторов и студентов / под ред. А.Ф. Лазарева, С.А. Лазарева. Барнаул : Изд-во ФГБОУ ВО АГМУ Минздрава России, 2020.

[17] Patent RUS № 2651131/ 18.04.2018. Lazarev AF. Method for determining the risk of breast cancer according to Lazarev A.F. (In Russ).

[18] Патент РФ № 2651131/ 18.04.2018. Лазарев А.Ф. Способ определения риска рака молочной железы по Лазареву А.Ф.

[19] Certificate of state registration of the computer program № 2019662415/ 24.09.2019. Lazarev AF, Pokornyak VP, Marchkov VA, Lazarev SA, Petrova VD. Automated program for early diagnosis of breast cancer (BC). (In Russ).

[20] Свидетельство о государственной регистрации программы для ЭВМ № 2019662415/ 24.09.2019. Лазарев А.Ф., Покорняк В.П., Марчков В.А., Лазарев С.А., Петрова В.Д. Автоматизированная программа ранней диагностики рака молочной железы (РМЖ).

Funding

Грант №1 Губернатора Алтайского края «Разработка и апробация цифровых технологий в ранней диагностике и профилактике ведущих локализаций в структуре онкологической заболеваемости и смертности: рака молочной и предстательной железы» ФГБОУ ВО АГМУ Минздрава России в рамках в рамках проекта в сфере медицинской профилактики, реабилитации и здоровьесбережения населенияGrant No. 1 of the Governor of the Altai Territory «Development and testing of digital technologies in early diagnosis and prevention of leading localizations in the structure of cancer morbidity and mortality: breast and prostate cancer» of the Federal State Budgetary Educational Institution of Higher Education «Altai State Medical University» of the Ministry of Health of Russia as part of a project in the field of medical prevention, rehabilitation and health preservation of population

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