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.

Development of a multiomics database for personalized prognostic forecasting in head and neck cancer: The Big Data to Decide EU Project / 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. - In: HEAD & NECK. - ISSN 1043-3074. - 43:2(2020), pp. 601-612. [10.1002/hed.26515]

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

Rossi, Silvia
Investigation
;
Lanfranco, Davide
Investigation
;
Poli, Tito
Investigation
;
2020-01-01

Abstract

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.
2020
Development of a multiomics database for personalized prognostic forecasting in head and neck cancer: The Big Data to Decide EU Project / 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. - In: HEAD & NECK. - ISSN 1043-3074. - 43:2(2020), pp. 601-612. [10.1002/hed.26515]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2881384
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 15
  • ???jsp.display-item.citation.isi??? 14
social impact