Abstract

PurposeThe purpose of this study was to investigate the ability of predictive models for patient-rated xerostomia (XER6M) and sticky saliva (STIC6M) at 6months after completion of primary (chemo)radiation developed in head and neck cancer patients treated with 3D-conformal radiotherapy (3D-CRT) to predict outcome in patients treated with intensity modulated radiotherapy (IMRT). Methods and materialsRecently, we published the results of a prospective study on predictive models for patient-rated xerostomia and sticky saliva in head and neck cancer patients treated with 3D-CRT (3D-CRT based NTCP models). The 3D-CRT based model for XER6M consisted of three factors, including the mean parotid dose, age, and baseline xerostomia (none versus a bit). The 3D-CRT based model for STIC6M consisted of the mean submandibular dose, age, the mean sublingual dose, and baseline sticky saliva (none versus a bit).In the current study, a population consisting of 162 patients treated with IMRT was used to test the external validity of these 3D-CRT based models. External validity was described by the explained variation (R2 Nagelkerke) and the Brier score. The discriminative abilities of the models were calculated using the area under the receiver operating curve (AUC) and calibration (i.e. the agreement between predicted and observed outcome) was assessed with the Hosmer–Lemeshow “goodness-of-fit” test. ResultsOverall model performance of the 3D-CRT based predictive models for XER6M and STIC6M was significantly worse in terms of the Brier score and R2 Nagelkerke among patients treated with IMRT. Moreover the AUC for both 3D-CRT based models in the IMRT treated patients were markedly lower. The Hosmer–Lemeshow test showed a significant disagreement for both models between predicted risk and observed outcome. Conclusion3D-CRT based models for patient-rated xerostomia and sticky saliva among head and neck cancer patients treated with primary radiotherapy or chemoradiation turned out to be less valid for patients treated with IMRT. The main message from these findings is that models developed in a population treated with a specific technique cannot be generalised and extrapolated to a population treated with another technique without external validation.

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