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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">RUDN Journal of Medicine</journal-id><journal-title-group><journal-title xml:lang="en">RUDN Journal of Medicine</journal-title><trans-title-group xml:lang="ru"><trans-title>Вестник Российского университета дружбы народов. Серия: Медицина</trans-title></trans-title-group></journal-title-group><issn publication-format="print">2313-0245</issn><issn publication-format="electronic">2313-0261</issn><publisher><publisher-name xml:lang="en">Peoples’ Friendship University of Russia named after Patrice Lumumba (RUDN University)</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">38299</article-id><article-id pub-id-type="doi">10.22363/2313-0245-2024-28-1-76-85</article-id><article-id pub-id-type="edn">VDLAVQ</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>GINECOLOGY</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>ГИНЕКОЛОГИЯ</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">Predicting the development of vulvar lichen sclerosus</article-title><trans-title-group xml:lang="ru"><trans-title>Прогнозирование развития склеротического лихена вульвы</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-6537-2572</contrib-id><contrib-id contrib-id-type="spin">3707-3561</contrib-id><name-alternatives><name xml:lang="en"><surname>Kolesnikova</surname><given-names>Ekaterina V.</given-names></name><name xml:lang="ru"><surname>Колесникова</surname><given-names>Е. В.</given-names></name></name-alternatives><email>jokagyno@rambler.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5460-5959</contrib-id><contrib-id contrib-id-type="spin">5292-3261</contrib-id><name-alternatives><name xml:lang="en"><surname>Zharov</surname><given-names>Alexander V.</given-names></name><name xml:lang="ru"><surname>Жаров</surname><given-names>А. В.</given-names></name></name-alternatives><email>jokagyno@rambler.ru</email><xref ref-type="aff" rid="aff1"/><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0003-0257-6732</contrib-id><name-alternatives><name xml:lang="en"><surname>Osipova</surname><given-names>Lyudmila K.</given-names></name><name xml:lang="ru"><surname>Осипова</surname><given-names>Л. К.</given-names></name></name-alternatives><email>jokagyno@rambler.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0008-2554-9741</contrib-id><name-alternatives><name xml:lang="en"><surname>Dupleev</surname><given-names>Artem I.</given-names></name><name xml:lang="ru"><surname>Дуплеев</surname><given-names>А. И.</given-names></name></name-alternatives><email>jokagyno@rambler.ru</email><xref ref-type="aff" rid="aff1"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Kuban State Medical University</institution></aff><aff><institution xml:lang="ru">Кубанский государственный медицинский университет</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">Regional Clinical Hospital No. 2</institution></aff><aff><institution xml:lang="ru">Краевая клиническая больница № 2</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2024-03-15" publication-format="electronic"><day>15</day><month>03</month><year>2024</year></pub-date><volume>28</volume><issue>1</issue><issue-title xml:lang="en">DENTISTRY</issue-title><issue-title xml:lang="ru">СТОМАТОЛОГИЯ</issue-title><fpage>76</fpage><lpage>85</lpage><history><date date-type="received" iso-8601-date="2024-03-18"><day>18</day><month>03</month><year>2024</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2024, Kolesnikova E.V., Zharov A.V., Osipova L.K., Dupleev A.I.</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2024, Колесникова Е.В., Жаров А.В., Осипова Л.К., Дуплеев А.И.</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="en">Kolesnikova E.V., Zharov A.V., Osipova L.K., Dupleev A.I.</copyright-holder><copyright-holder xml:lang="ru">Колесникова Е.В., Жаров А.В., Осипова Л.К., Дуплеев А.И.</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/4.0</ali:license_ref></license></permissions><self-uri xlink:href="https://journals.rudn.ru/medicine/article/view/38299">https://journals.rudn.ru/medicine/article/view/38299</self-uri><abstract xml:lang="en"><p style="text-align: justify;">Relevance. The issue of timely diagnosis and treatment of vulvar lichen sclerosus has become especially acute in recent years due to the “rejuvenation” of the disease and the risk of its malignancy. In this regard, it is urgent to search for effective methods for predicting and early detection of the disease. The aim of the study - to develop a model for predicting vulvar lichen sclerosus based on established clinical and anamnestic risk factors. Materials and Methods. The prospective case-control study included 404 women aged 20 to 70 years, of which 344 were patients with vulvar lichen sclerosus and 60 were women without vulvar diseases. At the first stage, a comparative statistical correlation analysis of the clinical and anamnestic data of the subjects was carried out using the Spearman correlation coefficient (R &gt; 0.15), Chi-square tests, Phi and Cramer statistics, the Mann-­Whitney U test and the Student t test (p  &lt;   0.05). The data obtained were used to develop a neural network model for predicting vulvar lichen sclerosus in the second stage of the study. Results and Discussion. Based on established reliably significant (p  &lt;  0.05) obstetric-­gynecological, somatic, infectious, hygienic and household factors influencing the risk of developing vulvar lichen sclerosus (R indicator - from 0.16 to 0.38 confirms the statistical significance of correlations), a neural network model for predicting vulvar lichen sclerosus was developed (the percentage of correct classification on the test sample is the maximum possible value - 100%) and a computer program was written that automates the procedure for predicting the disease. Conclusion. The neural network model for predicting the disease, developed on the basis of reliably (p  &lt;  0.05) significant risk factors for vulvar lichen sclerosus, has high prognostic properties, and a computer program written on its basis allows the doctor in a matter of minutes to identify the patient at risk for the development of vulvar lichen sclerosus and give she needs preventive recommendations aimed at preventing or early detection of the disease.</p></abstract><trans-abstract xml:lang="ru"><p style="text-align: justify;">Актуальность. Особенно остро в последние годы встал вопрос о своевременной диагностике и лечении склеротического лихена вульвы в связи с «омоложением» заболевания и риском его малигнизации. В связи с этим актуальным является поиск эффективных методов прогнозирования и раннего выявления заболевания. Цель исследования - разработать модель прогнозирования склеротического лихена вульвы на основе установленных клинико-­анамнестических факторов риска. Материалы и методы. В проспективное исследование «случай - контроль» были включены 404 женщины от 20 до 70 лет, из них 344 - больные склеротическим лихеном вульвы и 60 - женщины без заболеваний вульвы. На первом этапе проведен сравнительный статистический корреляционный анализ клинико-­анамнестических данных исследуемых с использованием коэффициента корреляции Спирмена (R &gt; 0,15), критериев Хи-квадрат, статистиками Фи, Крамера, U-критерия Манна - Уитни и t-критерия Стьюдента (p &lt; 0,05). Полученные данные использовались для разработки на втором этапе исследования нейросетевой модели прогнозирования склеротического лихена вульвы. Результаты и обсуждение. На основе установленных достоверно значимых (p &lt; 0,05) акушерско-­гинекологических, соматических, инфекционных, гигиенических и бытовых факторов, влияющих на риск развития склеротического лихена вульвы (показатель R - от 0,16 до 0,38 подтверждает статистическую значимость корреляционных связей), разработана нейросетевая модель прогнозирования склеротического лихена вульвы (доля правильной классификации на тестовой выборке составляет максимально возможное значение - 100%) и написана компьютерная программа, автоматизирующая процедуру прогнозирования заболевания. Выводы. Разработанная на основе достоверно (p &lt; 0,05) значимых факторах риска склеротического лихена вульвы нейросетевая модель прогнозирования заболевания обладает высокими прогностическими свой­ствами, а написанная на ее основе компьютерная программа позволяет врачу за считанные минуты определить обследуемую в группу риска по развитию склеротического лихена вульвы и дать ей необходимые профилактические рекомендации, направленные на предупреждение, либо раннее выявление заболевания.</p></trans-abstract><kwd-group xml:lang="en"><kwd>vulvar lichen sclerosus</kwd><kwd>scleroatrophic lichen</kwd><kwd>risk factors</kwd><kwd>comorbidity</kwd><kwd>pathology of the vulva</kwd><kwd>prediction</kwd><kwd>neural network model</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>склеротический лихен вульвы</kwd><kwd>склероатрофический лишай</kwd><kwd>факторы риска</kwd><kwd>коморбидность</kwd><kwd>патология вульвы</kwd><kwd>прогнозирование</kwd><kwd>нейросетевая модель</kwd></kwd-group><funding-group/></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Chamli A, Souissi A. 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