Abstract
Introduction
To develop a prediction model based on the prognostic nutritional index for grade 2 or higher radiation-induced oral mucositis in patients with nasopharyngeal carcinoma, providing a basis for early identification of patients at high risk.
Methods
We retrospectively included 192 patients with primary nasopharyngeal carcinoma who received chemoradiotherapy at the First Affiliated Hospital of Bengbu Medical University between May 2020 and December 2025. Patients were randomly assigned in a 7:3 ratio to a training set (n = 133) and an internal validation set (n = 59). Baseline characteristics were compared after tests of normality and homogeneity of variance. Candidate variables were selected jointly using LASSO, random forest, and support vector machine recursive feature elimination, followed by univariable and multivariable logistic regression to identify factors associated with grade 2 or higher radiation-induced oral mucositis. A nomogram was constructed, and Firth penalized likelihood regression was used to reduce small-sample bias. Model performance was assessed using receiver operating characteristic analysis and calibration curves, while clinical utility was evaluated by decision curve analysis. Propensity score matching was then used for sensitivity analysis.
Results
The prognostic nutritional index was an independent protective factor of grade 2 or higher radiation-induced oral mucositis. The area under the curve was 0.842 in the training set and 0.725 in the validation set. Patients in the group with high prognostic nutritional index values had a markedly lower risk (OR = 0.067, P
Conclusion
The prognostic nutritional index is an independent predictor of grade 2 or higher radiation-induced oral mucositis, and the model showed useful predictive performance for this outcome in patients with NPC receiving chemoradiotherapy.