vitjВрач и информационные технологииMedical Doctor and Information Technologies1811-01932413-5208Pirogov National Medical and Surgical Center10.25881/18110193_2026_3_32vitj-406Research ArticleОБЗОРЫREVIEWSПропущенные данные в исследованиях реальной клинической практики: стратегия управления от планирования до анализаMissing data in real-world evidence studies: management strategy from planning to analysishttps://orcid.org/0009-0006-2294-6819ГабидуллинаА. М.GabidullinaA. M.

г. Екатеринбург

Yekaterinburg

asiagabid@gmail.comhttps://orcid.org/0009-0002-8928-0776УпитисН. Б.UpitisN. B.

г. Москва

Moscow

n.upitis86@gmail.comhttps://orcid.org/0009-0000-8542-9997ГабидуллинР. А.GabidullinR. A.

к.м.н.

г. Санкт-Петербург

PhD

St. Petersburg

rishat@gabidullin.ruhttps://orcid.org/0000-0002-2680-7035ГольдинаТ. А.GoldinaT. A.

к.б.н.

г. Москва

г. Санкт-Петербург

PhD

Moscow

St. Petersburg

tatiana.goldina@prorwesolutions.ruООО «Сайнсфайлз»РоссияSciencefiles LLCRussian FederationНациональная ассоциация экспертов по редким заболеваниямРоссияNational Association of Experts on Rare DiseasesRussian FederationАО «БИОКАД»РоссияJSC "BIOCAD"Russian FederationАНО «Центр развития исследований реальной клинической практики «Про ИРКП»; ООО «Про РВЕ Солюшнс»РоссияANO «Center for the development of real-world evidence studies «Pro RWE»; PRO RWE SOLUTIONS, LLCRussian Federation202617102026033249Copyright © Габидуллина А.М., Упитис Н.Б., Габидуллин Р.А., Гольдина Т.А., 20262026Габидуллина А.М., Упитис Н.Б., Габидуллин Р.А., Гольдина Т.А.Gabidullina A.M., Upitis N.B., Gabidullin R.A., Goldina T.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.vit-j.ru/jour/article/view/406

Пропущенные данные представляют собой одну из ключевых характеристик/особенностей данных реальной клинической практики и являются неотъемлемой частью исследований реальной клинической практики (ИРКП), они возникают на всех этапах сбора информации как в проспективных, так и в ретроспективных дизайнах. Настоящий обзор посвящен всестороннему анализу проблемы пропущенных данных в ИРКП на всех этапах исследовательского процесса — от планирования научной концепции исследования до интерпретации результатов и их представления в научных публикациях.

В первой части обзора рассматриваются теоретические основы: термин «пропущенные данные» («missing data») в нормативных документах ICH, FDA, EMA, ЕАЭС и его различающиеся определения, роль источника данных в формировании пропусков, классификация механизмов пропусков по Рубину (MCAR, MAR, MNAR) и их значение для выбора статистических методов. Вторая часть обзора посвящена системному подходу и описывает 8 этапов работы с пропущенными данными.

Подчеркивается, что эффективное управление пропущенными данными начинается задолго до статистического анализа — на этапе разработки дизайна исследования. Эффективное управление пропущенными данными представляет собой сквозной, проактивный процесс, интегрированный в жизненный цикл ИРКП.

Завершающая часть отчета описывает статистические подходы к пропущенным данным: подходы к анализу данных без замещения пропусков, методы однократного замещения, множественное замещение. Определяются требования к отчету об ИРКП и научным публикациям с точки зрения пропущенных данных.

В заключении обосновывается необходимость системного подхода к проблеме пропущенных данных как важному элементу обеспечения надежности ИРКП, имеющего прямое значение для их применения решений в системе здравоохранения.

Missing data is one of the key characteristics of Real-World Data and they are an integral part of the Real-World Evidence studies (RWE studies). They arise at all stages of data collection in both prospective and retrospective designs. This review provides a comprehensive analysis of the issue of missing data in the RWE studies at all stages of the research process – the initial conceptualization of the study to the interpretation of results and their presentation in scientific publications.

The first part of the review examines the theoretical foundations: the term "missing data" in the regulatory documents of ICH, FDA, EMA, EAEU and its slightly different definitions, the role of the data source in the occurrence of missing data, the classification of missing data mechanisms according to Rubin (MCAR, MAR, MNAR) and their significance for selecting statistical methods.

The second part of the review focuses on a systematic approach and outlines eight stages of handling missing data. It is emphasized that effective missing data management begins well before statistical analysis — at the study design stage. Effective missing data management is an end-to-end, proactive process integrated into the RWE study lifecycle.

The conclusion of the report substantiates the need for a systematic approach to the issue of missing data as a crucial element in ensuring the reliability of RWE, which is directly relevant to the application of their findings within the healthcare system.

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The authors declare that there are no conflicts of interest present.