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

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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.

About the authors

Alexander F. Lazarev

Altai State Medical University

Email: lazarev@akzs.ru
ORCID iD: 0000-0003-1080-5294
SPIN-code: 1161-8387
Russian Federation, Barnaul

Valentina D. Petrova

Altai State Medical University

Email: valyusha_petrova_2024@mail.ru
ORCID iD: 0000-0001-7169-9646
SPIN-code: 2941-6649
Russian Federation, Barnaul

Sergey A. Lazarev

Altai State Medical University

Email: serglazarev@bk.ru
ORCID iD: 0000-0001-7748-0784
Russian Federation, Barnaul

Zhanna I. Vakhlova

Consultative Diagnostic Center of the Altai Territory

Email: office@dcak.ru
Russian Federation, Barnaul

Maria G. Nikolaeva

Altai State Medical University

Email: nikolmg@yandex.ru
ORCID iD: 0000-0001-9459-5698
SPIN-code: 8295-9290
Russian Federation, Barnaul

Tatyana V. Repkina

Altai State Medical University

Email: reppkina@yandex.ru
ORCID iD: 0000-0003-4583-313X
SPIN-code: 5855-5780
Russian Federation, Barnaul

Svetlana A. Terekhova

Altai State Medical University

Author for correspondence.
Email: quip@list.ru
ORCID iD: 0009-0001-4594-4529
SPIN-code: 7564-1647

MD, Cand. Sci. (Med.)

Russian Federation, Barnaul

Ilya S. Osipov

Medical Institute named after Berezin Sergey

Email: quip@list.ru
ORCID iD: 0009-0008-4560-2933
Russian Federation, Barnaul

Evgenia V. Shlyaptseva

Consultative Diagnostic Center of the Altai Territory

Email: office@dcak.ru
ORCID iD: 0009-0004-6517-9088
Russian Federation, Barnaul

Anna N. Komarova

Altai State Medical University

Email: a.n.komarova@bk.ru
ORCID iD: 0000-0003-4622-1506
SPIN-code: 4554-9864
Russian Federation, Barnaul

Dmitriy I. Ganov

Altai State Medical University

Email: ganovdmit@yandex.ru
ORCID iD: 0000-0002-7118-1668
SPIN-code: 2100-7576
Russian Federation, Barnaul

References

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  4. 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).
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  8. 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).
  9. Patent RUS № 2651131/ 18.04.2018. Lazarev AF. Method for determining the risk of breast cancer according to Lazarev A.F. (In Russ).
  10. 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).

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