Normal Tissue Complication Probability Model for Acute Radiation Dermatitis in Patients With Head and Neck Cancer Treated With Carbon Ion Radiation Therapy.

PURPOSE: This study aimed to explore the prognostic factors associated with acute radiation dermatitis (ARD). A normal tissue complication probability (NTCP) model for ARD in patients with head and neck cancer treated with carbon ion radiation therapy was developed. MATERIALS AND METHODS: A total of 187 patients were included in the analysis, and the endpoint was ≥grade 2 ARD. The biological and physical dose-surface parameters associated with ARD were used in the logistic regression model. The mean areas under the receiver operating characteristic curve in the internal cross-validation and Akaike's corrected Information Criterion were examined for model evaluation and selection. The multivariate logistic regression NTCP models were established based on factors with weak correlation. RESULTS: Tumor volume, planning target volume to the skin, radiation technique and all dose-surface parameters were significantly associated with ARD (P < .05). Models with high performance for grade 2 to 3 ARD were constructed. The most significant prognostic predictors were S40Gy(relative biological effectiveness,RBE) and S20Gy (absolute surface area receiving RBE-weighted dose of 40 Gy (RBE) or physical dose of 20 Gy). The internal cross-validation-based areas under the receiver operating characteristic curve for models with S40Gy(RBE) and S20Gy were 0.78 and 0.77, respectively. The biological and physical dose-surface parameters had similar performance at various dose levels. However, the performance of the multivariate NTCP models based on 2 factors was not better than that of the univariate models. CONCLUSIONS: NTCP models for ARD may provide a basis for the development of individualized treatment strategies and reduce the incidence of severe ARD in patients with head and neck cancer receiving carbon ion radiation therapy. Furthermore, biological and physical dose-surface parameter-based models are comparable. However, further validation with more evaluation parameters is warranted.

Relationship between oral mucositis and the oral bacterial count in patients with head and neck cancer undergoing carbon ion radiotherapy: A prospective study.

BACKGROUND AND PURPOSE: Acute adverse events, such as oral mucositis, can affect treatment success in patients undergoing head and neck radiotherapy. In this study, we aimed to identify the relationship between oral mucositis and oral bacterial counts during carbon ion radiotherapy (C-ion RT) in patients with head and neck cancer. MATERIALS AND METHODS: This prospective study included patients with head and neck tumors treated with C-ion RT between 2017 and 2019. C-ion RT consisted of treatment at 57.6, 64.0, or 70.4 Gy (relative biological effectiveness) in 16 fractions. Bacterial counts in the saliva and the back of the tongue were measured using a rapid oral bacteria quantification system. The relationship between the oral bacterial count and oral mucositis was subsequently analyzed. RESULTS: In total, 46 patients were included in the analysis. The bacterial count in the saliva gradually increased from the commencement of C-ion RT and peaked at 16 fractions. Bacterial counts at the back of the tongue were already high at the beginning of C-ion RT; however, they decreased with continued treatment, peaked at 16 fractions, and subsequently decreased again. Patients with bacterial counts exceeding the mean before C-ion RT (high-count group) did not experience more severe mucositis than those with counts below the mean (low-count group). However, patients in the high-count group tended to experience faster-onset mucositis and slower healing than those in the low-count group. CONCLUSION: Bacterial counts may aid in the development of clinical strategies for C-ion RT-induced oral mucositis.