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Accès ouvert déclaré 2022 article

Development of a prognostic model of overall survival in oropharyngeal cancer from real-world data: PRO.M.E.THE.O.

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11Institutions déclarées
1Pays d’affiliation déclarés

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Le résumé fourni par la source

Objective: The PRO.M.E.THE.O. study (PredictiOn Models in Ent cancer for anti-EGFR based THErapy Optimization) aimed to develop a predictive model (PM) of overall survival (OS) for patients with locally advanced oropharyngeal cancer (LAOC) treated with radiotherapy (RT) and cetuximab (Cet) from an Italian dataset. Methods: We enrolled patients with LAOC from 6 centres treated with RT-Cet. Clinical and treatment variables were collected. Patients were randomly divided into training (TS) (80%) and validation (VS) (20%) sets. A binary logistic regression model was used on the TS with stepwise feature selection and then on VS. Timepoints of 2, 3 and 5 years were considered. The area under the curve (AUC) of receiver operating characteristic of 2, 3 and 5 year and confusion matrix statistics at 5-threshold were used as performance criteria. Results: Overall, 218 patients were enrolled and 174 (79.8%) were analysed. Age at diagnosis, gender, ECOG performance, clinical stage, dose to high-risk volume, overall treatment time and day of RT interruption were considered in the final PMs. The PMs were developed and represented by nomograms with AUC of 0.75, 0.73 and 0.73 for TS and 0.713, 0.713, 0.775 for VS at 2, 3 and 5 years, respectively. Conclusions: PRO.M.E.THE.O. allows the creation of a PM for OS in patients with LAOC treated with RT-Cet.

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DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Development of a prognostic model of overall survival in oropharyngeal cancer from real-world data: PRO.M.E.THE.O. Sviluppo di un modello predittivo in pazienti affetti da neoplasia dell’orofaringe: PRO.M.E.THE.O.
Date Crossref
01/06/2022
Éditeur
Pacini Editore
Type
journal-article

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Les sujets associés

Head and Neck Cancer StudiesRadiomics and Machine Learning in Medical ImagingScientific and Engineering Research Topics

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