m+Medelevator.RU
← Поиск публикаций
Head & neck · 2020

Development of a multiomics database for personalized prognostic forecasting in head and neck cancer: The Big Data to Decide EU Project.

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Cavalieri Stefano, De Cecco Loris, Brakenhoff Ruud H, Serafini Mara Serena, Canevari Silvana, Rossi Silvia, Lanfranco Davide, Hoebers Frank J P, Wesseling Frederik W R, Keek Simon, Scheckenbach Kathrin, Mattavelli Davide, Hoffmann Thomas, López Pérez Laura, Fico Giuseppe, Bologna Marco, Nauta Irene, Leemans C René, Trama Annalisa, Klausch Thomas, Berkhof Johannes Hans, Tountopoulos Vasilis, Shefi Ron, Mainardi Luca, Mercalli Franco, Poli Tito, Licitra Lisa, BD2Decide Consortium

Аннотация

BACKGROUND: Despite advances in treatments, 30% to 50% of stage III-IV head and neck squamous cell carcinoma (HNSCC) patients relapse within 2 years after treatment. The Big Data to Decide (BD2Decide) project aimed to build a database for prognostic prediction modeling.

METHODS: Stage III-IV HNSCC patients with locoregionally advanced HNSCC treated with curative intent (1537) were included. Whole transcriptomics and radiomics analyses were performed using pretreatment tumor samples and computed tomography/magnetic resonance imaging scans, respectively.

RESULTS: The entire cohort was composed of 71% male (1097)and 29% female (440): oral cavity (429, 28%), oropharynx (624, 41%), larynx (314, 20%), and hypopharynx (170, 11%); median follow-up 50.5 months. Transcriptomics and imaging data were available for 1284 (83%) and 1239 (80%) cases, respectively; 1047 (68%) patients shared both.

CONCLUSIONS: This annotated database represents the HNSCC largest available repository and will enable to develop/validate a decision support system integrating multiscale data to explore through classical and machine learning models their prognostic role.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты