Cavalieri, StefanoStefanoCavalieriCecco, L. deL. deCeccoBrakenhoff, R.H.R.H.BrakenhoffSerafini, M.S.M.S.SerafiniCanevari, S.S.CanevariRossi, S.S.RossiLanfranco, D.D.LanfrancoHoebers, F.J.P.F.J.P.HoebersWesseling, F.W.R.F.W.R.WesselingKeek, S.S.KeekScheckenbach, K.K.ScheckenbachMattavelli, D.D.MattavelliHoffmann, T.T.HoffmannLópez Pérez, L.L.López PérezFico, G.G.FicoBologna, M.M.BolognaNauta, I.I.NautaLeemans, C.R.C.R.LeemansTrama, A.A.TramaKlausch, T.T.KlauschBerkhof, J.H.J.H.BerkhofTountopoulos, V.V.TountopoulosShefi, R.R.ShefiMainardi, L.L.MainardiMercalli, F.F.MercalliPoli, T.T.PoliLicitra, L.L.LicitraWesarg, S.S.Wesarg2022-03-062022-03-062021https://publica.fraunhofer.de/handle/publica/27085310.1002/hed.26515Background 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.enLead Topic: Individual HealthResearch Line: Modeling (MOD)Research Line: Machine Learning (ML)Big Dataoral cancerpatient model006journal article