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.
Development of a multiomics database for personalized prognostic forecasting in head and neck cancer: The Big Data to Decide EU Project / S. Cavalieri, L. De Cecco, R.H. Brakenhoff, M.S. Serafini, S. Canevari, S. Rossi, D. Lanfranco, F.J.P. Hoebers, F.W.R. Wesseling, S. Keek, K. Scheckenbach, D. Mattavelli, T. Hoffmann, L. Lopez Perez, G. Fico, M. Bologna, I. Nauta, C.R. Leemans, A. Trama, T. Klausch, J.H. Berkhof, V. Tountopoulos, R. Shefi, L. Mainardi, F. Mercalli, T. Poli, L. Licitra. - In: HEAD & NECK. - ISSN 1043-3074. - (2020). [Epub ahead of print]
Development of a multiomics database for personalized prognostic forecasting in head and neck cancer: The Big Data to Decide EU Project
S. Cavalieri
;S. Rossi;D. Mattavelli;G. Fico;L. Mainardi;L. Licitra
2020
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. 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.File | Dimensione | Formato | |
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