Wang Wen-Jie, Li Miao, Pan Xin-Bin
Department of Oncology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430014, P.R. China.
Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi 530021, P.R. China.
J Cancer. 2022 Oct 9;13(13):3452-3462. doi: 10.7150/jca.77768. eCollection 2022.
To identify risk factors of secondary cancer in nasopharyngeal carcinoma (NPC) patients after radiotherapy. The data of NPC patients with secondary cancer were extracted from the Surveillance, Epidemiology, and End Results database from 2004 to 2016. Univariate and multivariate logistic regression analysis was performed to identify risk factors of secondary cancer. Risk factors selected from the multivariable logistic regression analysis were used to build a predicting model. A total of 3931 patients were included: 329 (8.37%) patients developed secondary cancers and 3602 (91.63%) patients did not have secondary cancers. Univariate logistic regression analysis revealed that age, race, and the American Joint Committee on Cancer (AJCC) stage were risk factors of secondary cancer. Multivariable analysis demonstrated that age [Odds ratio (OR) = 1.03, P < 0.001], race (OR = 1.17, P = 0.010), AJCC stage (OR = 0.82, P = 0.002), and chemotherapy (OR = 1.55, P = 0.028) were independent risk factors of secondary cancer. Age, race, AJCC stage, and chemotherapy were entered into a nomogram for predicting secondary cancer. The area under the ROC curve of the nomogram was 0.645 [95% confidence interval (CI): 0.617-0.673]. The decision curve showed that if the threshold probability is between 4% and 25%, using the nomogram added more benefit than either the treat-all-patients scheme or the treat-none scheme. Age, race, AJCC stage, and chemotherapy were independent risk factors of secondary cancer in nasopharyngeal carcinoma patients after radiotherapy.
为了确定鼻咽癌(NPC)患者放疗后发生继发性癌症的风险因素。从2004年至2016年的监测、流行病学和最终结果数据库中提取了发生继发性癌症的NPC患者的数据。进行单因素和多因素逻辑回归分析以确定继发性癌症的风险因素。从多因素逻辑回归分析中选择的风险因素用于构建预测模型。共纳入3931例患者:329例(8.37%)发生继发性癌症,3602例(91.63%)未发生继发性癌症。单因素逻辑回归分析显示,年龄、种族和美国癌症联合委员会(AJCC)分期是继发性癌症的风险因素。多因素分析表明,年龄[比值比(OR)=1.03,P<0.001]、种族(OR=1.17,P=0.010)、AJCC分期(OR=0.82,P=0.002)和化疗(OR=1.55,P=0.028)是继发性癌症的独立风险因素。将年龄、种族、AJCC分期和化疗纳入预测继发性癌症的列线图。列线图的ROC曲线下面积为0.645[95%置信区间(CI):0.617-0.673]。决策曲线显示,如果阈值概率在4%至25%之间,使用列线图比全治疗方案或不治疗方案带来更多益处。年龄、种族、AJCC分期和化疗是鼻咽癌患者放疗后发生继发性癌症的独立风险因素。