<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">clinvest</journal-id><journal-title-group><journal-title xml:lang="ru">Качественная клиническая практика</journal-title><trans-title-group xml:lang="en"><trans-title>Kachestvennaya Klinicheskaya Praktika = Good Clinical Practice</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2588-0519</issn><issn pub-type="epub">2618-8473</issn><publisher><publisher-name>ООО «Издательство ОКИ</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.24411/2588-0519-2019-10072</article-id><article-id custom-type="elpub" pub-id-type="custom">clinvest-451</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ФАРМАКОЭКОНОМИКА</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>PHARMACOECONOMICS</subject></subj-group></article-categories><title-group><article-title>Обзор математических моделей рака молочной железы</article-title><trans-title-group xml:lang="en"><trans-title>Overview of mathematical models of breast cancer</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Юркова</surname><given-names>Ю. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Yurkova</surname><given-names>Yu. P.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Юркова Юлия Петровна - врач-статистик</p><p>SPIN-код: 4697-6433</p></bio><bio xml:lang="en"><p>Yurkova Yulia - Medical statistician</p><p>SPIN-code: 4697-6433</p></bio><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-3031-4572</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Курылёв</surname><given-names>А. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Kurylev</surname><given-names>A. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Курылёв Алексей Александрович - ассистент кафедры клинической фармакологии и доказательной медицины</p><p>SPIN-код: 4470-7845</p></bio><bio xml:lang="en"><p>Kurylev Alexey - Assistant of professor Department of Clinical Pharmacology and Evidence-Based Medicine</p><p>SPIN-code: 4470-7845</p></bio><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-1919-2909</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Колбин</surname><given-names>А. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Kolbin</surname><given-names>A. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Колбин Алексей Сергеевич Автор - доктор медицинских наук, профессор, заведующий кафедрой клинической фармакологии и доказательной медицины, ФГБОУ ВО ПСПбГМУ им. акад. И.П. Павлова МР; профессор кафедры фармакологии медицинского факультета СПбГУ</p><p>SPIN-код: 7966-0845</p></bio><bio xml:lang="en"><p>Kolbin Alexey - MD, DrSci, Professor, Head of the Department of Clinical Pharmacology and Evidence-Based Medicine, FSBEI HE I.P. Pavlov SPbSMU MOH Russia; professor of the Department of Pharmacology, Medical Faculty St. Petersburg SU</p><p>SPIN-code: 7966-0845</p></bio><email xlink:type="simple">alex.kolbin@mail.ru</email><xref ref-type="aff" rid="aff-3"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">ФГБУ «НМИЦ онкологии им. Н.Н. Петрова» Минздрава России<country>Россия</country></aff><aff xml:lang="en">FSBI N.N. Petrov National Medical Research Center of Oncology<country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru">ФГБОУ ВПО Первый Санкт-Петербургский государственный медицинский университет им И.П. Павлова<country>Россия</country></aff><aff xml:lang="en">FSBEI HE I.P. Pavlov SPbSMU MOH Russia<country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-3"><aff xml:lang="ru">ФГБОУ ВПО Первый Санкт-Петербургский государственный медицинский университет им И.П. Павлова; ФГБОУ ВО Санкт-Петербургский государственный университет<country>Россия</country></aff><aff xml:lang="en">FSBEI HE I.P. Pavlov SPbSMU MOH Russia; Saint-Petersburg State University<country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2019</year></pub-date><pub-date pub-type="epub"><day>21</day><month>10</month><year>2019</year></pub-date><volume>0</volume><issue>2</issue><fpage>45</fpage><lpage>54</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Юркова Ю.П., Курылёв А.А., Колбин А.С., 2019</copyright-statement><copyright-year>2019</copyright-year><copyright-holder xml:lang="ru">Юркова Ю.П., Курылёв А.А., Колбин А.С.</copyright-holder><copyright-holder xml:lang="en">Yurkova Y.P., Kurylev A.A., Kolbin A.S.</copyright-holder><license license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.clinvest.ru/jour/article/view/451">https://www.clinvest.ru/jour/article/view/451</self-uri><abstract><sec><title>Актуальность</title><p>Актуальность. Рак молочной железы (РМЖ) является сегодня в РФ лидирующей онкологической патологией. Использование новых методов лечения сопряжено со значительными затратами системы здравоохранения. Эпидемиологическое прогнозирование и планирование затрат на лечение РМЖ невозможно без построения его математической модели.</p></sec><sec><title>Цель</title><p>Цель. Провести обзор литературы, посвящённой математическому моделированию РМЖ. Материалы и методы. Был проведён систематический обзор литературы путём поиска публикаций в базах данных (PubMed). Из 547 первично отобранных публикаций 20 были включены в конечный анализ. Не включённые публикации можно разделить на следующие группы: клинико-экономические модели эффекта отдельных лекарств, модели эффективности скрининга, модели клеточного роста опухоли, модели оценки медицинских изображений (УЗИ, МРТ).</p></sec><sec><title>Результаты</title><p>Результаты. Эпидемиологическая модель РМЖ должна быть основана на данных регистров пациентов, при среднем времени наблюдения не менее 5 лет, построена с использованием метода Маркова, быть негомогенной. В модели необходимо выделить максимальное количество состояний, в том числе учитывать гистологический тип опухоли и стадию заболевания.</p></sec><sec><title>Выводы</title><p>Выводы. В РФ на сегодня не существует математической эпидемиологической модели РМЖ.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Rationale</title><p>Rationale. Breast cancer (BC) today is the leading oncologic pathology in Russia. The use of new treatments is associated with high healthcare costs. The epidemiological forecast and cost planning are not possible without the building of the mathematical model of BC.</p></sec><sec><title>Aim</title><p>Aim. The perform a literature review of BC models.</p></sec><sec><title>Materials and methods</title><p>Materials and methods. The systematic literature review was performed by searching databases (PubMed). From 547 initially got publications 20 were included in the analysis. Not included publications could be divided into groups: pharmacoeconomic model of particular drug, BC screening models, model of tumor growth, models of ВС imaging (US, MRI).</p></sec><sec><title>Results</title><p>Results. BC epidemiologic mathematical model should be based on the patient data from national register, the time horizon should be not less than 5 years, it should be based on Markov modelling and be non-homogenous. The model has to differentiate several tumor types and disease stage.</p></sec><sec><title>Conclusion</title><p>Conclusion. Today in Russia there is no epidemiologic mathematical model of BC.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>математическое моделирование</kwd><kwd>рак молочной железы</kwd><kwd>систематический обзор</kwd></kwd-group><kwd-group xml:lang="en"><kwd>mathematical modelling</kwd><kwd>breast cancer</kwd><kwd>systematic review</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Мерабишвили В.М. Эпидемиология и выживаемость больных раком молочной железы // Вопросы онкологии. — 2013. — Т.59. — №3. — С.314-319.</mixed-citation><mixed-citation xml:lang="en">VM. Merabishvili. Epidemiologiya i vyzhivaemost’ bol’nyh rakom molochnoj zhelezy. Voprosy onkologii. 2013;59(3):314-319. (In Russ).</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">СемиглазовВ.Ф. Эпидемиология и скрининг рака молочной железы // Вопросы онкологии. — 2017. — Т.63. — №3. — С.375-384.</mixed-citation><mixed-citation xml:lang="en">VF. Semiglazov Epidemiologiya i skrining raka molochnoj zhelezy Voprosy onkologii. 2017;63(3):375-384. (In Russ).</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Под ред. А.Д. Каприна, В.В. Старинского, Г.В. Петровой. Состояние онкологической помощи населению России в 2017 году. — М.: МНИОИ им. П.А. Герцена, филиал ФГБУ «НМИЦ радиологии» Минздрава России; 2018.</mixed-citation><mixed-citation xml:lang="en">Pod red. AD Kaprina, VV Starinskogo, GV Petrovoj. Sostoyanie onkologicheskoj pomoshchi naseleniyu Rossii v 2017 godu. Moscow. MNIOI im. P.A. Gercena, filial FGBU «NMIC radiologii» Minzdrava Rossii; 2018. (In Russ).</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Колбин А.С. Научный анализ исходов в онкологии. особенности фармакоэкономической экспертизы // Медицинские технологии. Оценка и выбор. — 2012. — Т.8. — №2. — С.87-93.</mixed-citation><mixed-citation xml:lang="en">Kolbin AS. Nauchnyj analiz iskhodov v onkologii. osobennosti farmakoekonomicheskoj ekspertizy. Medicinskie tekhnologii. Ocenka i vybor. 2012;8(2):87-93. (In Russ).</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Yang G. Neyman, Markov processes and survival analysis Lifetime Data Anal (2013) 19:393-411. DOI: 10.1007/s10985-013-9250-z</mixed-citation><mixed-citation xml:lang="en">Yang G. Neyman, Markov processes and survival analysis Lifetime Data Anal (2013) 19:393-411. DOI: 10.1007/s10985-013-9250-z</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Abdollahian M, et al. A MDP model for breast and ovarian cancer intervention strategies for BRCA1/2 mutation carriers. IEEE J Biomed Health Inform. 2015 Mar;19(2):720-7. DOI: 10.1109/JBHI.2014.2319246</mixed-citation><mixed-citation xml:lang="en">Abdollahian M, et al. A MDP model for breast and ovarian cancer intervention strategies for BRCA1/2 mutation carriers. IEEE J Biomed Health Inform. 2015 Mar;19(2):720-7. DOI: 10.1109/JBHI.2014.2319246</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Beauchemin C, et al. A global economic model to assess the cost-effectiveness of new treatments for advanced breast cancer in Canada. J Med Econ. 2016 Jun;19(6):619-29. DOI: 10.3111/13696998.2016.1151431</mixed-citation><mixed-citation xml:lang="en">Beauchemin C, et al. A global economic model to assess the cost-effectiveness of new treatments for advanced breast cancer in Canada. J Med Econ. 2016 Jun;19(6):619-29. DOI: 10.3111/13696998.2016.1151431</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Buyukdamgaci-Alogan G, et al. A decision-analytic model for early stage breast cancer: lumpectomy vs mastectomy. Neoplasma. 2008;55(3):222-8.</mixed-citation><mixed-citation xml:lang="en">Buyukdamgaci-Alogan G, et al. A decision-analytic model for early stage breast cancer: lumpectomy vs mastectomy. Neoplasma. 2008;55(3):222-8.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Karter KJ, et al. Analysis of Three Decision-making Methods: A Breast Cancer Patient as a Model. Med Decis Making. 1999;19:49-57. DOI: 10.1177/0272989X9901900107</mixed-citation><mixed-citation xml:lang="en">Karter KJ, et al. Analysis of Three Decision-making Methods: A Breast Cancer Patient as a Model. Med Decis Making. 1999;19:49-57. DOI: 10.1177/0272989X9901900107</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Crowther MJ, et al. Parametric multistate survival models: Flexible modelling allowing transition-specific distributions with application to estimating clinically useful measures of effect differences. Stat Med. 2017 Dec 20;36(29):4719-4742.</mixed-citation><mixed-citation xml:lang="en">Crowther MJ, et al. Parametric multistate survival models: Flexible modelling allowing transition-specific distributions with application to estimating clinically useful measures of effect differences. Stat Med. 2017 Dec 20;36(29):4719-4742.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Eulenburg C, et al. A Comprehensive Multistate Model Analyzing Associations of Various Risk Factors With the Course of Breast Cancer in a Population-Based Cohort of Breast Cancer Cases. Am J Epidemiol. 2016 Feb 15;183(4):325-34. DOI: 10.1093/aje/kwv163</mixed-citation><mixed-citation xml:lang="en">Eulenburg C, et al. A Comprehensive Multistate Model Analyzing Associations of Various Risk Factors With the Course of Breast Cancer in a Population-Based Cohort of Breast Cancer Cases. Am J Epidemiol. 2016 Feb 15;183(4):325-34. DOI: 10.1093/aje/kwv163</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Genser B, et al. Joint modelling of repeated transitions in follow-up data--a case study on breast cancer data. Biom J. 2005 Jun;47(3):388-401.</mixed-citation><mixed-citation xml:lang="en">Genser B, et al. Joint modelling of repeated transitions in follow-up data--a case study on breast cancer data. Biom J. 2005 Jun;47(3):388-401.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Holland RR, et al. Life expectancy estimation with breast cancer: bias of the declining exponential function and an alternative to its use. Med Decis Making. 1999 Oct-Dec;19(4):385-93. DOI: 10.1177/0272989X9901900406</mixed-citation><mixed-citation xml:lang="en">Holland RR, et al. Life expectancy estimation with breast cancer: bias of the declining exponential function and an alternative to its use. Med Decis Making. 1999 Oct-Dec;19(4):385-93. DOI: 10.1177/0272989X9901900406</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Hsu CY, et al. Bayesian negative-binomial-family-based multistate Markov model for the evaluation of periodic population-based cancer screening considering incomplete information and measurement errors. Stat Methods Med Res. 2018 Aug;27(8):2519-2539.</mixed-citation><mixed-citation xml:lang="en">Hsu CY, et al. Bayesian negative-binomial-family-based multistate Markov model for the evaluation of periodic population-based cancer screening considering incomplete information and measurement errors. Stat Methods Med Res. 2018 Aug;27(8):2519-2539.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Hubbard RA, et al. Using semi-Markov processes to study timeliness and tests used in the diagnostic evaluation of suspected breast cancer. Stat Med. 2016 Nov 30;35(27):4980-4993. DOI: 10.1002/sim.7055</mixed-citation><mixed-citation xml:lang="en">Hubbard RA, et al. Using semi-Markov processes to study timeliness and tests used in the diagnostic evaluation of suspected breast cancer. Stat Med. 2016 Nov 30;35(27):4980-4993. DOI: 10.1002/sim.7055</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Hui-Min WuG, et al. A bayesian random-effects markov model for tumor progression in women with a family history of breast cancer. Biometrics. 2008 Dec;64(4):1231-7. DOI: 10.1111/j.1541-0420.2007.00979.x</mixed-citation><mixed-citation xml:lang="en">Hui-Min WuG, et al. A bayesian random-effects markov model for tumor progression in women with a family history of breast cancer. Biometrics. 2008 Dec;64(4):1231-7. DOI: 10.1111/j.1541-0420.2007.00979.x</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Lange JM, et al. A joint model for multistate disease processes and random informative observation times, with applications to electronic medical records data. Biometrics. 2015 Mar;71(1):90-101.</mixed-citation><mixed-citation xml:lang="en">Lange JM, et al. A joint model for multistate disease processes and random informative observation times, with applications to electronic medical records data. Biometrics. 2015 Mar;71(1):90-101.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Meier-Hirmer C, et al. Multi-state model for studying an intermediate event using time-dependent covariates: application to breast cancer. BMC Med Res Methodol. 2013 Jun 20;13:80. DOI: 10.1186/1471-2288-13-80</mixed-citation><mixed-citation xml:lang="en">Meier-Hirmer C, et al. Multi-state model for studying an intermediate event using time-dependent covariates: application to breast cancer. BMC Med Res Methodol. 2013 Jun 20;13:80. DOI: 10.1186/1471-2288-13-80</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Pobiruchin M. A method for using real world data in breast cancer modeling. J Biomed Inform. 2016 Apr;60:385-94. DOI: 10.1016/j.jbi.2016.01.017</mixed-citation><mixed-citation xml:lang="en">Pobiruchin M. A method for using real world data in breast cancer modeling. J Biomed Inform. 2016 Apr;60:385-94. DOI: 10.1016/j.jbi.2016.01.017</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Perez-Ocon R. A piecewise Markov process for analysing survival from breast cancer in different risk groups. Stat Med. 2001 Jan 15;20(1):109-122.</mixed-citation><mixed-citation xml:lang="en">Perez-Ocon R. A piecewise Markov process for analysing survival from breast cancer in different risk groups. Stat Med. 2001 Jan 15;20(1):109-122.</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Taghipour S. Using Simulation to Model and Validate Invasive Breast Cancer Progression in Women in the Study and Control Groups of the Canadian National Breast Screening Studies I and II. Med Decis Making. 2017 Feb;37(2):212-223.</mixed-citation><mixed-citation xml:lang="en">Taghipour S. Using Simulation to Model and Validate Invasive Breast Cancer Progression in Women in the Study and Control Groups of the Canadian National Breast Screening Studies I and II. Med Decis Making. 2017 Feb;37(2):212-223.</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Witteveen A, et al. Risk-based breast cancer follow-up stratified by age. Cancer Med. 2018 Oct;7(10):5291-5298. DOI: 10.1002/cam4.1760</mixed-citation><mixed-citation xml:lang="en">Witteveen A, et al. Risk-based breast cancer follow-up stratified by age. Cancer Med. 2018 Oct;7(10):5291-5298. DOI: 10.1002/cam4.1760</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Wong SM Breast cancer prevention strategies in lobular carcinoma in situ: A decision analysis. Cancer. 2017 Jul 15;123(14):2609-2617. DOI: 10.1002/cncr.30644</mixed-citation><mixed-citation xml:lang="en">Wong SM Breast cancer prevention strategies in lobular carcinoma in situ: A decision analysis. Cancer. 2017 Jul 15;123(14):2609-2617. DOI: 10.1002/cncr.30644</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
