Sun Jian-Da, Chen Ze-Kai, Liu Shu-Peng, Ye Feng, Tang Ting-Xi, Zhou Zhen-Hua, Zhang Han-Bin, Zhang Long-Shan, Xiao Ting, Xiao Lin-Lin, Wang Xiao-Qing, Guan Jian
Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Department of Radiation Oncology, Meizhou People's Hospital, Meizhou, China.
Adv Radiat Oncol. 2025 Jan 11;10(2):101690. doi: 10.1016/j.adro.2024.101690. eCollection 2025 Feb.
The objective of this study was to explore the performance of a predictive model for swallowing-induced breakthrough pain established using a redefined delineation method based on the common occurrence sites of radiation-induced oral mucositis (RIOM) in locally advanced nasopharyngeal carcinoma (NPC).
A total of 208 patients with locally advanced NPC were included in the study cohort, and the test cohort consisted of 88 patients. The oral mucosa structure was contoured using oral cavity contour (OCC), mucosal surface contour (MSC), and oral-pharyngeal mucosa (OPM) methods, and relevant dosimetric parameters were collected. Assessment of the severity of RIOM was made with the National Cancer Institute's Common Terminology Criteria for Adverse Events, version 4.0. The random forest classification method was chosen to establish and validate the predictive models based on 3 contouring methods.
The area under the curve of the OPM-based model was higher than that of the OCC- and MSC-based models in both the validation cohort and the test cohort (0.800, 0.739, and 0.750; 0.670, 0.605, and 0.609, respectively). Better predictive performance could also be observed under the OPM method than the OCC and MSC methods in terms of accuracy. The OPM-based model showed high specificity (greater than 90%) in both the validation cohort and the test cohort. According to the mean decrease in the Gini index, the maximum dose was the most important predictor of severe oral mucositis in the OPM-based model.
We redefined a delineation method for oral mucosa structure based on the common occurrence sites of RIOM in locally advanced NPC. The model for swallowing-induced breakthrough pain constructed based on this method demonstrated good predictive performance. New parameters were found as predictors of severe swallowing-induced breakthrough pain in locally advanced NPC.
本研究的目的是探索一种预测模型在吞咽引起的突破性疼痛方面的表现,该模型是使用基于局部晚期鼻咽癌(NPC)放射性口腔黏膜炎(RIOM)常见发生部位的重新定义的勾画方法建立的。
研究队列共纳入208例局部晚期NPC患者,测试队列由88例患者组成。使用口腔轮廓(OCC)、黏膜表面轮廓(MSC)和口咽黏膜(OPM)方法勾画口腔黏膜结构,并收集相关剂量学参数。采用美国国立癌症研究所不良事件通用术语标准第4.0版评估RIOM的严重程度。选择随机森林分类方法,基于3种勾画方法建立并验证预测模型。
在验证队列和测试队列中,基于OPM的模型的曲线下面积均高于基于OCC和MSC的模型(分别为0.800、0.739和0.750;0.670、0.605和0.609)。在准确性方面,与OCC和MSC方法相比,OPM方法也表现出更好的预测性能。基于OPM的模型在验证队列和测试队列中均显示出高特异性(大于90%)。根据基尼指数的平均下降情况,最大剂量是基于OPM的模型中严重口腔黏膜炎的最重要预测因素。
我们基于局部晚期NPC中RIOM的常见发生部位重新定义了口腔黏膜结构的勾画方法。基于该方法构建的吞咽引起的突破性疼痛模型显示出良好的预测性能。发现了新的参数可作为局部晚期NPC中严重吞咽引起的突破性疼痛的预测因素。