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 radio-therapy (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 diag-nosis, gender, ECOG performance, clinical stage, dose to high-risk volume, overall treat-ment 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.

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

Franco, Pierfrancesco;Ricardi, Umberto;
2022-01-01

Abstract

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 radio-therapy (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 diag-nosis, gender, ECOG performance, clinical stage, dose to high-risk volume, overall treat-ment 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.
2022
42
3
205
214
cetuximab; head and neck tumour; personalised medicine; prediction model
Miccichè, Francesco; Chiloiro, Giuditta; Longo, Silvia; Autorino, Rosa; Massaccesi, Mariangela; Lenkowicz, Jacopo; Bonomo, Pierluigi; Desideri, Isacco...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1904492
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