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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">myrwd</journal-id><journal-title-group><journal-title xml:lang="ru">Реальная клиническая практика: данные и доказательства</journal-title><trans-title-group xml:lang="en"><trans-title>Real-World Data &amp; Evidence</trans-title></trans-title-group></journal-title-group><issn pub-type="epub">2782-3784</issn><publisher><publisher-name>Publishing House OKI</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.37489/2782-3784-myrwd-14</article-id><article-id custom-type="edn" pub-id-type="custom">ZZVWRB</article-id><article-id custom-type="elpub" pub-id-type="custom">myrwd-17</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>МЕТОДОЛОГИЯ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>METHODOLOGY</subject></subj-group></article-categories><title-group><article-title>Объединение данных реальной клинической практики с результатами рандомизированных клинических исследований для лучшей информированности при принятии решений в онкологии</article-title><trans-title-group xml:lang="en"><trans-title>Combining real-world data with randomized controlled trials results in better information oncology decision making</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-2827-1382</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Усманова</surname><given-names>Т. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Usmanova</surname><given-names>T. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Усманова Татьяна Андреевна — клинический ординатор кафедры клинической фармакологии и доказательной медицины</p><p>Санкт-Петербург</p></bio><bio xml:lang="en"><p>St. Petersburg</p></bio><email xlink:type="simple">smirnovatatyana01@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-3770-993X</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Вербицкая</surname><given-names>Е. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Verbitskaya</surname><given-names>E. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Вербицкая Елена Владимировна — доцент кафедры клинической фармакологии и доказательной медицины, зав. отделом биомедицинской статистики</p><p>Санкт-Петербург</p></bio><bio xml:lang="en"><p>St. Petersburg</p></bio><email xlink:type="simple">elena.verbitskaya@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГБОУ ВО «Первый Санкт-Петербургский государственный медицинский университет имени И. П. Павлова»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>FSBEI HE I. P. Pavlov SPbSMU MOH Russia</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2022</year></pub-date><pub-date pub-type="epub"><day>01</day><month>08</month><year>2022</year></pub-date><volume>2</volume><issue>2</issue><fpage>21</fpage><lpage>31</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Усманова Т.А., Вербицкая Е.В., 2022</copyright-statement><copyright-year>2022</copyright-year><copyright-holder xml:lang="ru">Усманова Т.А., Вербицкая Е.В.</copyright-holder><copyright-holder xml:lang="en">Usmanova T.A., Verbitskaya E.V.</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.myrwd.ru/jour/article/view/17">https://www.myrwd.ru/jour/article/view/17</self-uri><abstract><p>Рандомизированные контролируемые исследования (РКИ) являются «золотым стандартом» оценки действенности противоопухолевой терапии. Несмотря на высокую внутреннюю валидность таких исследований, их обобщаемость, то есть возможность перенести полученные результаты на широкую популяцию пациентов, ограничена, в связи с чем пользователи и работники системы здравоохранения могут столкнуться с более низкой эффективностью вмешательства в реальной практике, чем было заявлено в РКИ. Можно выделить множество причин формирования разрыва между действенностью и эффективностью (efficacy-effectiveness gap; EEG), то есть мерой воздействия в РКИ и в реальной клинической практике (РКП). Сюда относятся, например, различные характеристики пациентов в испытании и в РКП, приверженность терапии, особенности оказания медицинской помощи и другие. Для того чтобы проиллюстрировать эту проблему, представлен обзор ряда исследований, посвящённых оценке величины и анализу возможных причин указанного несоответствия. В большинстве приведённых исследований был выявлен EEG, предложены вероятные объяснения его наличия, а также произведены дополнительные оценки для установления вклада различных факторов в его величину. Авторы этих публикаций показывают, что, в отличие от участников РКИ, «реальные» пациенты старше, имеют худший функциональный статус, большее количество сопутствующих заболеваний, чаще являются женщинами, реже завершают начатое лечение или переход к следующей линии терапии. Кроме того, в данной статье предложены различные аналитические подходы к определению веса основных причинных факторов в формировании</p><p>несоответствия между действенностью и эффективностью, что может использоваться при разработке методологии соответствующих исследований.</p><p>Имея в доступе информацию о размере EEG при использовании различных схем лечения в своём регионе и понимая, в какой степени тот или иной фактор может оказать влияние на величину этого разрыва, клиницист сможет прогнозировать эффективность лечения и выбирать оптимальную тактику для конкретного больного.</p></abstract><trans-abstract xml:lang="en"><p>Randomized controlled trials (RCTs) are the gold standard for testing the efficacy of cancer therapy. Although the results of clinical trials have high internal validity, their generalizability, that is, the ability to transfer the results to a wide patient population, is limited. Therefore, users and health care workers may experience less effective intervention in real practice than stated in the RCT. There are many reasons for the formation of a gap between efficacy and effectiveness (efficacyeffectiveness gap; EEG), that is, the measure of impact on RCTs and the real-world. These reasons include, for example, different characteristics of patients in the trial and real practice, compliance to treatment, features of medical care, and others. To illustrate this problem, a review of some studies on the estimation of the magnitude and analysis of the possible causes of this gap is presented. In most of the studies cited, EEG was identified, its probable explanations were proposed, and additional estimates were made to establish the contribution of various factors to its magnitude. These publications» authors show that real-world patients are older, have worse functional status, and have a greater number of comorbidities. They are women mostly and are less likely to complete the treatment they have started or move to the next line of therapy, in contrast to participants in RCTs. Additionally, this article proposes various analytical approaches to determine the weight of the main causal factors in the formation of a discrepancy between efficacy and effectiveness, which can be used in the development of the methodology of relevant studies.</p><p>Knowing the size of the EEG when using different treatment regimens in their region and understanding the extent to which one or another factor can influence the size of this gap, the clinician will be able to predict the effectiveness of treatment and choose the best therapy for a particular patient.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>действенность</kwd><kwd>эффективность</kwd><kwd>несоответствие между действенностью и эффективностью</kwd><kwd>доказательства</kwd><kwd>собранные в реальной клинической практике</kwd><kwd>RWD</kwd><kwd>RWE</kwd></kwd-group><kwd-group xml:lang="en"><kwd>efficacy</kwd><kwd>effectiveness</kwd><kwd>efficacy-effectiveness gap</kwd><kwd>EEG</kwd><kwd>real-world evidence</kwd><kwd>RWD</kwd><kwd>RWE</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">Mamtani R, Lund J, Hubbard RA. 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