Li Pei-Jing, Li Kai-Xin, Jin Ting, Lin Hua-Ming, Fang Jia-Ben, Yang Shuang-Yan, Shen Wei, Chen Jia, Zhang Jiang, Chen Xiao-Zhong, Chen Ming, Chen Yuan-Yuan
Department of Radiation Oncology, Cancer Hospital of University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Zhejiang Key Laboratory of Radiation Oncology, Hangzhou, China.
Department of Radiation Oncology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, China.
Front Oncol. 2020 Nov 5;10:596822. doi: 10.3389/fonc.2020.596822. eCollection 2020.
To explore risk factors for severe acute oral mucositis of nasopharyngeal carcinoma (NPC) patients receiving chemo-radiotherapy, build predictive models and determine preventive measures.
Two hundred and seventy NPC patients receiving radical chemo-radiotherapy were included. Oral mucosa structure was contoured by oral cavity contour (OCC) and mucosa surface contour (MSC) methods. Oral mucositis during treatment was prospectively evaluated and divided into severe mucositis group (grade ≥ 3) and non-severe mucositis group (grade < 3) according to RTOG Acute Reaction Scoring System. Nineteen clinical features and nineteen dosimetric parameters were included in analysis, least absolute shrinkage and selection operator (LASSO) logistic regression model was used to construct a risk score (RS) system.
Two predictive models were built based on the two delineation methods. MSC based model is more simplified one, it includes body mass index (BMI) classification before radiation, retropharyngeal lymph node (RLN) area irradiation status and MSC V55%, RS = -1.480 + (0.021 × BMI classification before RT) + (0.126 × RLN irradiation) + (0.052 × MSC V55%). The cut-off of MSC based RS is -1.011, with an area under curve (AUC) of 0.737 (95%CI: 0.672-0.801), a specificity of 0.595 and a sensitivity of 0.786. OCC based model involved more variables, RS= -4.805+ (0.152 × BMI classification before RT) + (0.080 × RT Technique) + (0.097 × Concurrent Nimotuzumab) + (0.163 × RLN irradiation) + (0.028 × OCC V15%) + (0.120 × OCC V60%). The cut-off of OCC based RS is -0.950, with an AUC of 0.767 (95%CI: 0.702-0.831), a specificity of 0.602 and a sensitivity of 0.819. Analysis in testing set shown higher AUC of MSC based model than that of OCC based model (AUC: 0.782 vs 0.553). Analysis in entire set shown AUC in these two method-based models were close (AUC: 0.744 vs 0.717).
We constructed two risk score predictive models for severe oral mucositis based on clinical features and dosimetric parameters of nasopharyngeal carcinoma patients receiving chemo-radiotherapy. These models might help to discriminate high risk population in clinical practice that susceptible to severe oral mucositis and individualize treatment plan to prevent it.
探讨接受放化疗的鼻咽癌（NPC）患者发生严重急性口腔黏膜炎的危险因素，建立预测模型并确定预防措施。
纳入270例接受根治性放化疗的NPC患者。采用口腔轮廓（OCC）和黏膜表面轮廓（MSC）方法勾勒口腔黏膜结构。前瞻性评估治疗期间的口腔黏膜炎，并根据RTOG急性反应评分系统分为严重黏膜炎组（≥3级）和非严重黏膜炎组（<3级）。分析纳入19项临床特征和19项剂量学参数，采用最小绝对收缩和选择算子（LASSO）逻辑回归模型构建风险评分（RS）系统。
基于两种勾画方法建立了两个预测模型。基于MSC的模型更简化，包括放疗前体重指数（BMI）分类、咽后淋巴结（RLN）区域照射状态和MSC V55%，RS = -1.480 +（0.021×放疗前BMI分类）+（0.126×RLN照射）+（0.052×MSC V55%）。基于MSC的RS的截断值为-1.011，曲线下面积（AUC）为0.737（95%CI：0.672-0.801），特异性为0.595，敏感性为0.786。基于OCC的模型涉及更多变量，RS = -4.805 +（0.152×放疗前BMI分类）+（0.080×放疗技术）+（0.097×同期尼妥珠单抗）+（0.163×RLN照射）+（0.028×OCC V15%）+（0.120×OCC V60%）。基于OCC的RS的截断值为-0.950，AUC为0.767（95%CI：0.702-0.831），特异性为0.602，敏感性为0.819。测试集分析显示基于MSC的模型的AUC高于基于OCC的模型（AUC：0.782对0.553）。全集分析显示这两种基于方法的模型的AUC接近（AUC：
