vestimИзвестия Национальной академии наук Беларуси. Серия медицинских наукProceedings of the National Academy of Sciences of Belarus, Medical series1814-60232524-2350The Republican Unitary Enterprise Publishing House "Belaruskaya Navuka"10.29235/1814-6023-2018-15-4-503-510vestim-464Research ArticleОБЗОРЫREVIEWSМодели риска развития рака молочной железыRisk models for breast cancerПятчанинаТ. В.PyatchaninaT. V.

канд. биол. наук, ст. науч. сотрудник, заведующий отделом

Ph. D. (Biol.), Senior researcher, Head of the Department. Department of Research Management and Innovation

tanya_pyatchanina@ukr.neОгородникА. Н.OhorodnykA. N.

канд. техн. наук, науч. сотрудник

Ph. D. (Tech.), Researcher

kassmail@ukr.netИнститут экспериментальной патологии, онкологии и радиобиологии имени Р. Е. Кавецкого НАН Украины, КиевR. E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology of the National Academy of Sciences of Ukraine, Kiev201814012019154503510Copyright © Пятчанина Т.В., Огородник А.Н., 20192019Пятчанина Т.В., Огородник А.Н.Pyatchanina T.V., Ohorodnyk A.N.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://vestimed.belnauka.by/jour/article/view/464

В настоящем обзоре изучен ряд моделей для определения вероятных путей течения опухолевого процесса, выживаемости пациентов и прогнозирования риска развития рака молочной железы. Данные модели учитывают такие факторы, как образ жизни, выявляемость мутации генов BRCA1 и BRCA2, семейная история, а также предикативные и прогностические факторы (клинические, молекулярно-биологические).

Scientific evidence indicates the stabilization of indicators of morbidity and mortality from breast cancer in women in Ukraine and the existence of a number of models for predicting the breast cancer risk with the consideration of life style factors, detectable mutations of BRCA1 and BRCA2 genes, family history, as well as predicative and prognostic factors (clinical, molecular-biological) to determine the possible ways of the tumor process and the survival of breast cancer patients.

рак молочной железыпрогностические модели риска развития рака молочной железыфакторы рискасемейная историярепродуктивные факторыbreast cancerprognostic risk models for breast cancerrisk factorsfamily historyreproductive factorsReferencesGLOBOCAN database [Electronic resource] // IARC: International Association of Cancer Registries. – Mode of access : http://www.iacr.com.fr/index.php?option=com_content&view=article&id=101&Itemid=578. – Date of access : 20.09.2018.GLOBOCAN database. IARC: International Association of Cancer Registries. Available at: http://www.iacr.com.fr/ index.php?option=com_content&view=article&id=101&Itemid=578 (accessed 20.09.2018).Данные ВОЗ по заболеваемостью раком, 2014 год [Электронный ресурс] // Всемирная организация здраво охранения. – Режим доступа : http://www.who.int/cancer/country-profiles/ru/. – Дата доступа : 20.09.2018.Cancer country profiles 2014. World Health Organization. Available at: http://www.who.int/cancer/country-profiles/ en/http://www.who.int/cancer/country-profiles/ru/ (accessed 20.09.2018).Онкогеном РГЗ [Электронный ресурс] // Майбутнє без раку. – Режим доступа : http://breast-cancer.org.ua/ database.html. – Дата доступа : 20.09.2018.Onkogene of RGZ. The future is cancer free. Available at: http://breast-cancer.org.ua/database.html (accessed 20.09.2018) (in Russian).Projecting individulized probabilities of developing breast cancer for white females who are being examined annually / M. Gail [et al.] // J. Natl. Cancer Inst. – 1989. – Vol. 81, N 24. – P. 1879–1886. https://doi.org/10.1093/jnci/81.24.1879Gail M. H., Brinton L. A., Byar D. P., Corle D. K., Green S. B., Schairer C., Mulvihill J. J. Projecting individulized probabilities of developing breast cancer for white females who are being examined annually. Journal of the National Cancer Institute, 1989, vol. 81, no. 24, pp. 1879–1886. https://doi.org/10.1093/jnci/81.24.1879Claus, E. B. Autosomal dominant inheritance of early onset breast cancer / E. B. Claus, N. Risch, W. D. Thomp son // Cancer. – 1994. – Vol. 73, N 3. – P. 643–651. https://doi.org/10.1002/1097-0142(19940201)73:33.0.co;2-5Claus E. B., Risch N., Thompson W. D. Autosomal dominant inheritance of early onset breast cancer. Cancer, 1994, vol. 73, no. 3, pp. 643–651. https://doi.org/10.1002/1097-0142(19940201)73:33.0.co;2-5Evaluation of models to predict BRCA germline mutations / H. H. Kang [et al.] // Br. J. Cancer. – 2006. – Vol. 95, N 7. – P. 914–920. https://doi.org/10.1038/sj.bjc.6603358Kang H. H., Williams R., Leary J., Ringland C., Kirk J., Ward R. Evaluation of models to predict BRCA germline mutations. British Journal of Cancer, 2006, vol. 95, no. 7, pp. 914–920. https://doi.org/10.1038/sj.bjc.6603358The BOADICEA model of genetic susceptibility to breast and ovarian cancer / A. C. Antoniou [et al.] // Br. J. Cancer. – 2004. – Vol. 91, N 8. – P. 1580–1590. https://doi.org/10.1038/sj.bjc.6602175Antoniou A. C., Pharoah P. P. D., Smith P., Easton D. F. The BOADICEA model of genetic susceptibility to breast and ovarian cancer. British Journal of Cancer, 2004, vol. 91, no. 8, pp. 1580–1590. https://doi.org/10.1038/sj.bjc.6602175Optimal selection for BRCA1 and BRCA2 mutation testing using a combination of ‘easy to apply’ probability models / D. Bodmer [et al.] // Br. J. Cancer. – 2006. – Vol. 95, N 6. – P. 757–762. https://doi.org/10.1038/sj.bjc.6603306Bodmer D., Ligtenberg M. J. L., van der Hout A. H., Gloudemans S., Ansink K., Oosterwijk J. C., Hoogerbrugge N. Optimal selection for BRCA1 and BRCA2 mutation testing using a combination of ‘easy to apply’ probability models. British Journal of Cancer, 2006, vol. 95, no. 6, pp. 757–762. https://doi.org/10.1038/sj.bjc.6603306Model-based predictions of BRCA1/2 mutation status in breast carcinoma patients treated at an academic medical center / K. M. Shannon [et al.] // Cancer. – 2002. – Vol. 94, N 2. – P. 305–313. https://doi.org/10.1002/cncr.10223Shannon K. M., Lubratovich M. L., Finkelstein D. M., Smith B. L., Powell S. N., Seiden M. V. Model-based predictions of BRCA1/2 mutation status in breast carcinoma patients treated at an academic medical center. Cancer, 2002, vol. 94, no. 2, pp. 305–313. https://doi.org/10.1002/cncr.10223Alcohol consumption and ethyl carbamate / IARC Working Group on the Evaluation of Carcinogenic Risks to Humans. – Lion : International Agency for Research on Cancer, 2010. – 1424 p. – (IARC Monographs on the Evaluation of Carcinogenic Risks in Humans ; Vol. 96).IARC Monographs on the Evaluation of Carcinogenic Risks in Humans. Alcohol consumption and ethyl carbamate. Vol. 96. Lion, International Agency for Research on Cancer, 2010. 1424 p.Cancer risk prediction models: a workshop on development, evaluation, and application / A. Freedman [et al.] // J. Natl. Cancer Inst. – 2005. – Vol. 97, N 10. – P. 715–723. https://doi.org/10.1093/jnci/dji128Freedman A. N., Seminara D., Gail M. H., Hartge P., Colditz G. A., Ballard-Barbash R., Pfeiffer R. M. Cancer risk prediction models: a workshop on development, evaluation, and application. Journal of the National Cancer Institute, 2005, vol. 97, no. 10, pp. 715–723. https://doi.org/10.1093/jnci/dji128BRCA1 mutations in women attending clinics that evaluate the risk of breast cancer / F. Couch [et al.] // N. Engl. J. Med. – 1997. – Vol. 336, N 20. – P. 1409–1415. https://doi.org/10.1056/nejm199705153362002Couch F. J., DeShano M. L., Blackwood M. A., Calzone K., Stopfer J., Campeau L., Ganguly A., Rebbeck T., Weber B. L., Jablon L., Cobleigh M. A., Hoskins K., Garber J. E. BRCA1 mutations in women attending clinics that evaluate the risk of breast cancer. New England Journal of Medicine, 1997, no. 336, pp. 1409–1415. https://doi.org/10.1056/nejm199705153362002Comparisons of two breast cancer risk estimates in women with a family history of breast cancer / A. McTiernan [et al.] // Cancer Epidemiol. Biomarkers Prev. – 2001. – Vol. 10, N 4. – P. 333–338.McTiernan A., Kuniyuki A., Yasui Y., Bowen D., Burke W., Culver J. B., Anderson R., Durfy S. Comparisons of two breast cancer risk estimates in women with a family history of breast cancer. Cancer Epidemiology Biomarkers and Prevention, 2001, vol. 10, nо. 4, pp. 333–338.Parmigiani, G. Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2 / G. Parmigiani, D. A. Berry, O. Aguilar // Am. J. Hum. Genet. – 1998. – Vol. 62, N 1. – P. 145–158. https://doi.org/10.1086/301670Parmigiani G., Berry D. A., Aguilar O. Determining carrier-probabilities for breast cancer susceptibility genes BRCA1 and BRCA2. American Journal of Human Genetics, 1998, vol. 62, no.1, pp. 145–158. https://doi.org/10.1086/301670IBIS software (Tyrer-Сuzick model) [Electronic resource] // Cancer Research UK. – Mode of access : http://www.cancertechnology.co.uk/ibis-software-tyrer-cuzick-model. – Date of access : 20.09.2018.IBIS software (Tyrer-Сuzick model). Cancer Research UK. Available at: http://www.cancertechnology.co.uk/ ibis-software-tyrer-cuzick-model (accessed: 20.09.2018).Cuzick, J. A brief review of the International Breast Cancer Intervention Study (IBIS), the other current breast cancer prevention trials, and proposals for future trials / J. Cuzick // Ann. N. Y. Acad. Sci. – 2001. – Vol. 949. – P. 123–133.Cuzick J. A brief review of the International Breast Cancer Intervention Study (IBIS), the other current breast cancer prevention trials, and proposals for future trials. Annals of the New York Academy of Sciences, 2001, vol. 949, pp. 123–133.Amir, E. Evaluation of breast cancer risk assessment packages in the family history evaluation and screening programme / E. Amir // J. Med. Genet. – 2003. – Vol. 40, N 11. – P. 807–814. https://doi.org/10.1136/jmg.40.11.807Amir E. Evaluation of breast cancer risk assessment packages in the family history evaluation and screening programme. Journal of Medical Genetics, 2003, vol. 40, no. 11, pp. 807–814. https://doi.org/10.1136/jmg.40.11.807BRCA1 sequence analysis in women at high risk for susceptibility mutations: risk factor analysis and implications for genetic testing / D. Shattuck-Eidens [et al.] // JAMA. – 1997. – Vol. 278, N 15. – P. 1242–1250. https://doi.org/10.1001/jama. 1997.03550150046034Shattuck-Eidens D., Oliphant A., McClure M., McBride C., Gupte J., Rubano T., Pruss D., Tavtigian S. V., Teng D. H.-F., Adey N., Staebell M., Gumpper K., Lundstrom R., Hulick M., Kelly M., Holmen J., Lingenfelter B., Manley S., Fujimura F., Luce M., Ward B., Cannon-Albright L., Steele L., Offit K., Gilewski T., Norton L., Brown K., Schulz Ch., Hampel H., Schluger A., Giulotto E., Zoli W., Ravaioli A., Nevanlinna H., Pyrhonen S., Rowley P., Loader S., Osborne M. P., Daly M., Tepler I., Weinstein P. L., Scalia J. L., Michaelson R., Scott R. J., Radice P., Pierotti M. A., Garber J. E., Isaacs C., Peshkin B., Lippman M. E., Dosik M. H., Caligo M. A., Greenstein R. M., Pilarski R., Weber B., Burgemeister R., Frank Th. S., Skolnick M. H., Thomas A. BRCA1 sequence analysis in women at high risk for susceptibility mutations: risk factor analysis and implications for genetic testing. JAMA, 1997, vol. 278, no. 15, pp. 1242–1250. https://doi.org/10.1001/jama.1997.03550150046034Addition of pathology and biomarker information significantly improves the performance of the Manchester scoring system for BRCA1 and BRCA2 testing / D. G. Evans [et al.] // J. Med. Genet. – 2009. – Vol. 46, N 12. – P. 811–817. https://doi.org/10.1136/jmg.2009.067850Evans D. G., Lalloo F., Cramer A., Jones E. A., Knox F., Amir E., Howell A. Addition of pathology and biomarker information significantly improves the performance of the Manchester scoring system for BRCA1 and BRCA2 testing. Journal of Medical Genetics, 2009, vol. 46, no. 12, pp. 811–817. https://doi.org/10.1136/jmg.2009.067850The Penn II risk model [Electronic resource] // Basser Center for BRCA. – Mode of access : http://www.afcri.upenn. edu/itacc/penn2. – Date of access : 20.09.2018.The Penn II risk model. Basser Center for BRCA. Available at: http://www.afcri.upenn.edu/itacc/penn2 (accessed 20.09.2018).BRCA Risk Calculator [Electronic resource] // MYRIAD. – Mode of access : http://www.myriadpro.com/brca-riskcalculator/. – Date of access : 20.09.2018.BRCA Risk Calculator. MYRIAD. Available at: http://www.myriadpro.com/brca-risk-calculator/ (accessed 20.09.2018).Логистическая регрессия и ROC-анализ – математический аппарат [Электронный ресурс] // BaseGroup Labs. Технологии анализа данных. – Режим доступа : http://www.basegroup.ru/library/analysis/regression/logistic/. – Дата доступа : 20.09.2018.Logistic regression and ROC analysis are mathematical tools. BaseGroup Labs. Data Analysis Technologies. Available at: http://www.basegroup.ru/library/analysis/regression/logistic/ (accessed 20.09.2018) (in Russian).Рак в Україні, 2014–2015. Захворюваність, смертність, показники діяльності онкологічної служби [Электронный ресурс] / З. П. Федоренко [та ін.] // Бюл. Нац. канцер-реестру України. – 2016. – № 17. – Режим доступа : http://www.ncru.inf.ua/publications/BULL_17/index.htm. – Дата доступа : 20.09.2018.Fedorenko Z. P., Gulak L. O., Mikhailovich Yu. I., Gorokh Є. L., Rizhov A. Yu., Sumkіna O. V., Kutsenko L. B. Cancer in Ukraine, 2014–2015. Incidence, mortality, indicators of the oncological service. Byuleten’ Natsіonal’nogo kantser-reestru [Ukraїni Bulletin of the National Chancellery of Ukraine], 2016, no. 17. Available at: http://www.ncru.inf.ua/publications/ BULL_17/index.htm (accessed 20.09.2018) (in Ukrainian).

The authors declare that there are no conflicts of interest present.