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. 2016 Dec;121(3):381-386.
doi: 10.1016/j.radonc.2016.08.022. Epub 2016 Sep 15.

Toward a model-based patient selection strategy for proton therapy: External validation of photon-derived normal tissue complication probability models in a head and neck proton therapy cohort

Affiliations

Toward a model-based patient selection strategy for proton therapy: External validation of photon-derived normal tissue complication probability models in a head and neck proton therapy cohort

Pierre Blanchard et al. Radiother Oncol. 2016 Dec.

Abstract

Objective: To externally validate head and neck cancer (HNC) photon-derived normal tissue complication probability (NTCP) models in patients treated with proton beam therapy (PBT).

Methods: This prospective cohort consisted of HNC patients treated with PBT at a single institution. NTCP models were selected based on the availability of data for validation and evaluated by using the leave-one-out cross-validated area under the curve (AUC) for the receiver operating characteristics curve.

Results: 192 patients were included. The most prevalent tumor site was oropharynx (n=86, 45%), followed by sinonasal (n=28), nasopharyngeal (n=27) or parotid (n=27) tumors. Apart from the prediction of acute mucositis (reduction of AUC of 0.17), the models overall performed well. The validation (PBT) AUC and the published AUC were respectively 0.90 versus 0.88 for feeding tube 6months PBT; 0.70 versus 0.80 for physician-rated dysphagia 6months after PBT; 0.70 versus 0.68 for dry mouth 6months after PBT; and 0.73 versus 0.85 for hypothyroidism 12months after PBT.

Conclusion: Although a drop in NTCP model performance was expected for PBT patients, the models showed robustness and remained valid. Further work is warranted, but these results support the validity of the model-based approach for selecting treatment for patients with HNC.

Keywords: Head and neck cancer; Intensity-modulated proton therapy; Late toxicity; Model; Prediction; Radiation therapy.

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Conflict of interest statement

Conflict of Interest Statement: Dr. Frank receives honoraria from Hitachi, Varian and IBA and research grant from Elekta. The other authors declare to have no conflict of interest regarding the topic under consideration.

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