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<article 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" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Journal of Modern Oncology</journal-id><journal-title-group><journal-title xml:lang="en">Journal of Modern Oncology</journal-title><trans-title-group xml:lang="ru"><trans-title>Современная онкология</trans-title></trans-title-group></journal-title-group><issn publication-format="print">1815-1434</issn><issn publication-format="electronic">1815-1442</issn><publisher><publisher-name xml:lang="en">LLC Obyedinennaya Redaktsiya</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">375366</article-id><article-id pub-id-type="doi">10.26442/18151434.2023.4.202371</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>CLINICAL ONCOLOGY</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>КЛИНИЧЕСКАЯ ОНКОЛОГИЯ</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Comorbid pathology in SARS-CoV-2 infected in cancer practice as a predictor of severe outcomes in COVID-19. COVID-19 prognostic online risk assessment tool in oncology: A retrospective study</article-title><trans-title-group xml:lang="ru"><trans-title>Коморбидная патология у инфицированных SARS-CoV-2 в онкологической практике – предиктор тяжелых исходов при COVID-19. Прогностический онлайн-инструмент оценки риска COVID-19 в онкологии</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0015-7094</contrib-id><contrib-id contrib-id-type="scopus">24342526600</contrib-id><contrib-id contrib-id-type="spin">4801-3742</contrib-id><name-alternatives><name xml:lang="en"><surname>Sekacheva</surname><given-names>Marina I.</given-names></name><name xml:lang="ru"><surname>Секачева</surname><given-names>Марина Игоревна</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>D. Sci. (Med.), Prof.</p></bio><bio xml:lang="ru"><p>доктор мед. наук, проф., дир. Института</p></bio><email>sekacheva_m_i@staff.sechenov.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0658-9130</contrib-id><contrib-id contrib-id-type="scopus">57244423900</contrib-id><contrib-id contrib-id-type="researcherid">AEH-8251-2022</contrib-id><contrib-id contrib-id-type="spin">4785-2353</contrib-id><name-alternatives><name xml:lang="en"><surname>Rusanov</surname><given-names>Alexander S.</given-names></name><name xml:lang="ru"><surname>Русанов</surname><given-names>Александр Сергеевич</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>Graduate Student</p></bio><bio xml:lang="ru"><p>аспирант Института персонализированной онкологии Центра «Цифровой биодизайн и персонализированное здравоохранение»</p></bio><email>rusanov_a_s@staff.sechenov.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0716-0923</contrib-id><contrib-id contrib-id-type="spin">1346-6767</contrib-id><name-alternatives><name xml:lang="en"><surname>Kokhanovskaia</surname><given-names>Iana I.</given-names></name><name xml:lang="ru"><surname>Кохановская</surname><given-names>Яна Юрьевна</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>Trainee Researcher</p></bio><bio xml:lang="ru"><p>стажер-исследователь Института персонализированной онкологии Центра «Цифровой биодизайн и персонализированное здравоохранение»</p></bio><email>kokhanovskaya_ya_yu@staff.sechenov.ru</email><xref ref-type="aff" rid="aff1"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Sechenov First Moscow State Medical University (Sechenov University)</institution></aff><aff><institution xml:lang="ru">ФГАОУ ВО «Первый Московский государственный медицинский университет им. И. М. Сеченова» Минздрава России (Сеченовский Университет)</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2023-12-20" publication-format="electronic"><day>20</day><month>12</month><year>2023</year></pub-date><volume>25</volume><issue>4</issue><issue-title xml:lang="en"/><issue-title xml:lang="ru"/><fpage>490</fpage><lpage>497</lpage><history><date date-type="received" iso-8601-date="2023-05-23"><day>23</day><month>05</month><year>2023</year></date><date date-type="accepted" iso-8601-date="2023-12-07"><day>07</day><month>12</month><year>2023</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2023, Consilium Medicum</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2023, ООО "Консилиум Медикум"</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="en">Consilium Medicum</copyright-holder><copyright-holder xml:lang="ru">ООО "Консилиум Медикум"</copyright-holder><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">https://creativecommons.org/licenses/by-nc-sa/4.0</ali:license_ref></license></permissions><self-uri xlink:href="https://modernonco.orscience.ru/1815-1434/article/view/375366">https://modernonco.orscience.ru/1815-1434/article/view/375366</self-uri><abstract xml:lang="en"><p><bold>Aim. </bold>Evaluation of comorbid pathology in SARS-CoV-2 infected in cancer practice as a predictor of severe outcomes. Testing the COVID-19 risk assessment tool in oncology (CORONET), to predict the likely severity of COVID-19 course in cancer patients on inpatient treatment.</p> <p><bold>Materials and methods. </bold>A retrospective analysis of 173 cancer patient disease stories was conducted. The study was conducted as part of the program of the World-Class Research Center “Digital Biodesine and Personalized Health Care” of the University of Sechenov, with participation in the ESMO-CoCARE Register project. Based on the ESMO COVID-19 and CAncerREgistry (ESMO-CoCARE) registry, taking into account the entered our patient sample (n=173), a COVID-19 risk assessment tool in oncology (CORONET) was developed.</p> <p><bold>Results. </bold>Cancer patients with comorbid pathology have been shown to have an increased risk of COVID-19 course of the disease from this sample by CORONET (mean conclusion score CORONET 2.44 pointsseverity). Prognosis of probable severity of outcomes in cancer patients infected with SARS-CoV-2 depends on associated diseases. The presence of a history of ≥3 comorbid pathologies in COVID-19 patients was detected in 106 people (61.27%). 15 patients were included in the risk of severe course. Retrospective analysis obtained actual confirmation of the prognosis of severe course of the disease in this group followed by death in all these patients (71.42% of all deaths). Indicators such as low albumin levels, high levels of C-reactive protein and neutrophils showed high prognostic significance of the likely severity of coronavirus infection in cancer patients on inpatient treatment for COVID-19. The mortality rate of patients admitted with COVID-19 and cancer was 12.14%.</p> <p><bold>Conclusion. </bold>The most informative predictors of severe outcomes in COVID-19 in inpatient cancer patients to assess the prognosis of disease severity are: number of comorbidities, age, NEWS2 scale, ECOG patient activity status, albumin level, C-reactive protein level and absolute neutrophil level. The benefits gained in the use of the online decision support tool CORONET are considered convincing not only during the decision-making phase of hospitalization, but also in cancer patients on inpatient treatment.</p></abstract><trans-abstract xml:lang="ru"><p><bold>Цель. </bold>Оценить коморбидную патологию у инфицированных вирусом SARS-CoV-2 (Severe Acute Respiratory Syndrome CoronaVirus-2), являющимся возбудителем коронавирусной болезни (COVID-19), в онкологической практике как предиктор тяжелых исходов, апробировать в онкологии инструмент оценки риска COVID-19 CORONET в целях прогноза вероятной тяжести течения заболевания у онкологических пациентов (ОП), находящихся на стационарном лечении.</p> <p><bold>Материалы и методы. </bold>Проведен ретроспективный анализ 173 историй болезни ОП. Исследование осуществлено в рамках программы Научного центра мирового уровня «Цифровой биодизайн и персонализированное здравоохранение» ФГАОУ ВО «Первый МГМУ им. И. М. Сеченова» (Сеченовский Университет) с участием в проекте ESMO-CoCARE (European Society for Medical Oncology COVID-19 and CAncerREgistry). На основе реестра ESMO-CoCARE, с учетом внесенной выборки пациентов (n=173), разработан CORONET – инструмент оценки риска COVID-19 в онкологии.</p> <p><bold>Результаты. </bold>Показано, что ОП с коморбидной патологией имеют повышенный риск тяжелого течения COVID-19. Прогноз вероятной тяжести исходов у ОП, инфицированных SARS-CoV-2, зависит от сопутствующих заболеваний. Наличие в анамнезе ≥3 коморбидных патологий выявлено у 106 (61,27%) больных COVID-19. В группу риска тяжелого течения заболевания из данной выборки по CORONET включены 15 больных (средний балл заключения CORONET – 2,44). При ретроспективном анализе получено фактическое подтверждение прогноза тяжелого течения заболевания пациентов исследуемой группы с последующим их смертельным исходом (71,42% всех умерших). Выявлено, что такие показатели, как низкий уровень альбумина, высокий уровень С-реактивного белка и нейтрофилов, обладают высокой прогностической значимостью в оценке вероятной тяжести течения COVID-19 у ОП, находящихся на стационарном лечении по поводу указанного заболевания. Уровень смертности пациентов, поступивших с COVID-19 и онкозаболеванием, составил 12,14%.</p> <p><bold>Заключение. </bold>Наиболее информативными предикторами тяжелых исходов при COVID-19 у ОП, находящихся на стационарном лечении, позволяющими прогнозировать тяжесть течения заболевания, являются число сопутствующих болезней, возраст, оценка по шкале NEWS2, оценка статуса активности пациента по шкале ECOG, уровень альбумина и C-реактивного белка, абсолютный уровень нейтрофилов. Выявленные преимущества использования онлайн-инструмента поддержки принятия решений CORONET признаны убедительными не только на этапе принятия решения о госпитализации, но и уже во время нахождения ОП на стационарном лечении.</p></trans-abstract><kwd-group xml:lang="en"><kwd>COVID-19</kwd><kwd>cancer</kwd><kwd>comorbid pathology</kwd><kwd>severe flow risk factors</kwd><kwd>CORONET</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>COVID-19</kwd><kwd>онкологические заболевания</kwd><kwd>коморбидная патология</kwd><kwd>факторы риска тяжелого течения</kwd><kwd>CORONET</kwd></kwd-group><funding-group/></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Bhogal T, Khan UT, Lee R, et al. Haematological malignancy and nosocomial transmission are associated with an increased risk of death from COVID-19: results of a multi-center UK cohort. Leuk Lymphoma. 2021;62(7):1682-91. 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