Development and validation of Prediction models for radiation-induced hypoglossal neuropathy in patients with nasopharyngeal carcinoma.

BACKGROUND AND PURPOSE: To establish predictive models for radiation-induced hypoglossal neuropathy (RIHN) in patients with nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT).

MATERIALS AND

METHODS

Data from 423 NPC patients receiving IMRT-based treatment were retrospectively reviewed. They were randomly (3:2) divided into a training set (n = 256) and a testing set (n = 167). Dosimetric variables were selected by penalized regression and machine learning, with area under the receiver operating curve (AUC) calculated. Clinical variables were selected by the competitive risk analysis. A competitive risk model including clinical and dosimetric variables was performed, and a nomogram was generated as a visualization of the model to predict the incidence of RIHN.

RESULTS

During a median follow-up of 102 months (IQR: 89.5 to 112.9 months), the cumulative incidence of RIHN at 3, 5, and 8 years were 2.1 %, 5.4 %, and 10.5 %, respectively. D1cc and aV75 were the most predictive dosimetric variables. The dose-effect curve plotted with D1cc indicated the tolerance dose for a 5 % probability of developing RIHN in 8 years (TD5/8) was 77.3 Gy (EQD2). The restricted cubic spline between aV75 and RIHN indicated a volume threshold of 0.81 cm3. A competitive risk model including hypoglossal canal involvement, concurrent chemotherapy, D1cc, and aV75 was established, with the C-index of the training set and testing set being 0.726 and 0.691, respectively. The nomogram-defined high-risk group had the higher RIHN incidences in the training and testing sets.

CONCLUSIONS

This study identified the most critical dosimetric predictors, which is expected to become a feasible dose constraint for hypoglossal nerves in radiation plan. Combining dosimetric and clinical predictors, we further proposed and validated the first nomogram model to quantify the risk of RIHN, contributing to identifying high-risk patients and early intervention. Further multicenter studies are needed to validate or complement our findings.