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Development of a multiomics database for personalized prognostic forecasting in head and neck cancer: The Big Data to Decide EU Project.
- Source :
-
Head & neck [Head Neck] 2021 Feb; Vol. 43 (2), pp. 601-612. Date of Electronic Publication: 2020 Oct 27. - Publication Year :
- 2021
-
Abstract
- 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.<br />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.<br />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.<br />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.<br /> (© 2020 The Authors. Head & Neck published by Wiley Periodicals LLC.)
- Subjects :
- Female
Humans
Male
Neoplasm Recurrence, Local genetics
Prognosis
Squamous Cell Carcinoma of Head and Neck diagnostic imaging
Squamous Cell Carcinoma of Head and Neck genetics
Big Data
Head and Neck Neoplasms diagnostic imaging
Head and Neck Neoplasms genetics
Head and Neck Neoplasms therapy
Subjects
Details
- Language :
- English
- ISSN :
- 1097-0347
- Volume :
- 43
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Head & neck
- Publication Type :
- Academic Journal
- Accession number :
- 33107152
- Full Text :
- https://doi.org/10.1002/hed.26515