Dosimetry of Submandibular Glands on Xerostomia for Nasopharyngeal Carcinoma - Pan, Xin-Bin; Liu, Yang; Huang, Shi-Ting; Pei, Su; Chen, Kai-Hua; Qu, Song; Li, Ling; Zhu, Xiao-Dong (Frontiers in Oncology, 2021)
Purpose: To investigate dosimetry of submandibular glands on xerostomia after intensity-modulated radiotherapy for nasopharyngeal carcinoma (NPC). Methods: From September 2015 to March 2016, 195 NPC patients were investigated. Xerostomia was evaluated at 12 months after treatment via the RTOG/EORTC system. The least absolute shrinkage and selection operator regression model was used to optimize feature selection for grade 2-3 xerostomia. Multivariable logistic regression analysis was applied to build a predicting model incorporating the feature selected in the least absolute shrinkage and selection operator regression model. Discrimination, calibration, and clinical usefulness of the predicting model were assessed using the C-index, calibration plot, and decision curve analysis. Results: The V30 of the parotid glands was selected based on the least absolute shrinkage and selection operator regression. The nomogram displayed good discrimination with a C-index of 0.698 (95% confidence interval [CI]: 0.626-0.771) and good calibration (model 1). Addition of the dosimetric parameters including the mean dose to the submandibular glands, V50 of the submandibular glands, and volume of the submandibular glands to the model 1 failed to show incremental prognostic value (model 2). The model 2 showed a C-index of 0.704 (95% CI: 0.632-0.776). Decision curve analysis demonstrated that the model 1 was clinically useful when intervention was decided at the possibility threshold of > 20%. Within this range, net benefit was comparable between the model 1 and model 2. Conclusion: PGv30 was a major predictive factor of grade 2-3 xerostomia for NPC. In contrast, the mean dose to the submandibular glands, V50 of the submandibular glands, and volume of the submandibular glands were not independent predictive factors.