关键词: 头颈部肿瘤, 放射治疗, 口腔黏膜炎, 风险预测模型

Abstract: Objective: To analyze the influencing factors of moderate to severe radiation-induced oral mucositis (RIOM) in patients with head and neck tumors after radiotherapy and to construct a risk prediction model, thereby providing a basis for the identification of high-risk patients and the formulation of prevention strategies. Methods: The retrospective study was conducted on 395 patients with head and neck tumors who received radiotherapy between January 2022 and June 2025. According to the oral mucosa grading standard, the patients were divided into the mild RIOM group and the moderate-to-severe RIOM group. Univariate analysis and logistic regression analysis were used to screen for independent influencing factors of moderate to severe RIOM. The R 4.1.3 software was used to conduct a nomogram prediction model for the accuracy and predictive efficacy. Results: Among the 395 patients, 199 developed moderate to severe RIOM, with an incidence rate of 50.38%. Logistic regression analysis revealed that cumulative radiation dose, nutritional status, pre-radiotherapy oral frailty, diabetes, targeted therapy, and concurrent chemotherapy were influencing factors for RIOM in patients with head and neck tumors receiving radiotherapy (P<0.05). The area under the curve (AUC) for predicting moderate to severe RIOM was 0.839, with a sensitivity of 0.79 and a specificity of 0.83. The optimal threshold value was 0.487. The consistency test of the calibration curve shows that the predicted probability converges to the actual probability. Conclusion: Patients with head and neck tumors receiving radiotherapy are at a high risk of developing moderate to severe RIOM. Those with higher cumulative radiation doses, poorer nutritional status, pre-radiotherapy oral frailty, diabetes, targeted therapy, and concurrent chemotherapy are more likely to develop moderate to severe RIOM. The constructed risk prediction model demonstrates good predictive performance and can provide a reference for clinical healthcare professionals to predict the risk of moderate to severe RIOM in patients undergoing radiotherapy for head and neck tumors.

Key words: Head and neck tumors, Radiotherapy, Oral mucositis, Risk prediction model