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<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">10.37489/2588-0519-2020-3-35-39</article-id><article-id custom-type="elpub" pub-id-type="custom">clinvest-502</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>Анализ долгосрочной эффективности лекарственного препарата в терапии хронического заболевания — основа рациональной фармакотерапии (на примере использования рофлумиласта в терапии хронической обструктивной болезни лёгких)</article-title><trans-title-group xml:lang="en"><trans-title>Analysis of the long-term effectiveness of a drug in the treatment of a chronic disease is the basis of rational pharmacotherapy (on the example of the use of roflumilast in the treatment of chronic obstructive pulmonary disease)</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-6454-1346</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Жукова</surname><given-names>О. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Zhukova</surname><given-names>O. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Жукова Ольга Вячеславовна - к. ф. н., доцент кафедры управления и экономики фармации и фармацевтической технологии</p><p>Нижний Новгород</p></bio><bio xml:lang="en"><p>Zhukova Olga V. - PhD in Pharmaceutical Sciences, Associate Professor of the Department of management and Economics of pharmacy and pharmaceutical technology</p><p>Nizhny Novgorod</p></bio><email xlink:type="simple">ov-zhukova@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0032-0341</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Хохлов</surname><given-names>А. Л.</given-names></name><name name-style="western" xml:lang="en"><surname>Khokhlov</surname><given-names>A. L.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Хохлов Александр Леонидович - д. м. н., профессор, член-корр. РАН, зав. кафедрой клинической фармакологии</p><p>SPIN-код: 9389-8926</p><p>Ярославль</p></bio><bio xml:lang="en"><p>Khokhlov Alexander L. - D. Sci. in Medicine, Professor, Corresponding Member of the Russian Academy of Sciences, Head of the Department of the Clinical Pharmacology</p><p>SPIN code: 9389-8926</p><p>Yaroslavl</p></bio><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГБОУ ВО «Приволжский исследовательский медицинский университет» Министерства здравоохранения Российской Федерации</institution><country>Россия</country></aff><aff xml:lang="en"><institution>FSBEI HE PRMU MOH Russia</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>ФГБОУ ВО «Ярославский государственный медицинский университет»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Yaroslavl State Medical University of the Ministry of Health of Russia</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2020</year></pub-date><pub-date pub-type="epub"><day>26</day><month>09</month><year>2020</year></pub-date><volume>0</volume><issue>3</issue><fpage>35</fpage><lpage>39</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Жукова О.В., Хохлов А.Л., 2020</copyright-statement><copyright-year>2020</copyright-year><copyright-holder xml:lang="ru">Жукова О.В., Хохлов А.Л.</copyright-holder><copyright-holder xml:lang="en">Zhukova O.V., Khokhlov A.L.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" 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/502">https://www.clinvest.ru/jour/article/view/502</self-uri><abstract><p>Цель исследования заключалась в оценке долгосрочной эффективности лекарственного препарата в терапии хронического заболевания на основании Марковского моделирования (на примере использования рофлумиласта в терапии хронической обструктивной болезни лёгких).</p><sec><title>Материалы и методы</title><p>Материалы и методы. Материалами для исследования послужили данные, полученные в исследовании ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) о зависимости обострений от стадии ХОБЛ. Моделирование проводилось с использованием программного обеспечения MO Excel на основании Марковской модели. Входными данными служили 1 000 пациентов с ХОБЛ II стадии. Временной горизонт составил 10 лет. Марковский цикл составлял 1 год. Дополнительные пациенты в модель не включались и не выбывали в ходе моделирования.</p></sec><sec><title>Результаты</title><p>Результаты. При добавлении в схему терапии ХОБЛ рофлумиласта число пациентов с IV стадией на последний цикл моделирования (10-й год) составит 265 пациентов, без рофлумиласта — этот показатель составит 296 пациентов. Добавление рофлумиласта в схему терапии ХОБЛ замедляет переход в IV стадию ХОБЛ на 10,5 % в течение 10 лет.</p></sec><sec><title>Заключение</title><p>Заключение. Марковская модель перехода пациентов, страдающих ХОБЛ, по стадиям заболевания характеризует течение заболевания на временном горизонте в 10 лет. Из модельной группы в 1 000 пациентов, страдающих ХОБЛ II стадии, в данной стадии на конец моделирования остаются лишь 48,4 % пациентов. На последний цикл временного горизонта моделирования в III стадии находится 22,1 % от начальной когорты пациентов, в IV — 29,6 %. При моделировании с использованием частот переходов между состояниями, полученными в ходе исследований, в которых изучалась эффективность добавления к схемам лечения ингибитора ФДЭ-4 рофлуми-ласта, в ходе моделирования установлено замедление темпов прогрессирования заболевания.</p></sec></abstract><trans-abstract xml:lang="en"><p>The aim of the study consisted in assessing the long-term effectiveness of the drug in the treatment of chronic disease based on Markov modeling (on the example of the use of roflumilast in the treatment of chronic obstructive pulmonary disease).</p><sec><title>Materials and methods</title><p>Materials and methods. The data on the dependence of exacerbations on the stage of COPD from the ECLIPSE study (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) were used as materials for the study. The simulation was carried out using MO Excel software based on the Markov model. The input data were 1 000 patients with COPD II stage. The time horizon was 10 years. The Markov cycle was 1 year. Additional patients were not included in the model and did not drop out during the simulation.</p></sec><sec><title>Results</title><p>Results. The number of patients with stage IV for the last modeling cycle (10 years) will be 265 patients with the addition of roflumilast to COPD, then without roflumilast, this figure will be 296 patients. The addition of roflumilast to COPD therapy slows the transition to stage IV COPD by 10.5 % for 10 years.</p></sec><sec><title>The conclusion</title><p>The conclusion. The Markov model of the transition of patients suffering from COPD through stages of the disease characterizes the course of the disease on the time horizon at 10 years. Of the model group of 1000 patients (suffering from stage II COPD), only 48.4 % of patients remain in this stage at the end of the simulation. On the last cycle of the modeling time horizon, in stage III there are 22.1% of the initial cohort of patients, in stage IV — 29.6 %. ttese data reflect actual clinical practice. When modeling using the frequencies of transitions between states obtained during studies in which the efficacy of adding roflumilast, inhibitor of PDE-4 to treatment regimens was studied, modeling slowed down the progression of the disease.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>ХОБЛ</kwd><kwd>модель Маркова</kwd><kwd>рофлумиласт</kwd><kwd>ингибитор ФДЭ-4</kwd></kwd-group><kwd-group xml:lang="en"><kwd>COPD</kwd><kwd>Markov model</kwd><kwd>roflumilast</kwd><kwd>inhibitor of PDE-4</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">Хроническая обструктивная болезнь легких: клинические рекомендации. Министерство здравоохранения Российской Федерации. Год пересмотра — 2018. 69 с. 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