Objective: To analyze the risk factors affecting regional lymph node metastasis in salivary gland mucoepidermoid carcinoma (MEC) and to establish a nomogram model for individually predicting lymph node metastasis in salivary gland MEC. Methods: The clinical data of 2 152 patients with salivary gland MEC from 1975 to 2020 were collected from the Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute. The collected data were divided into training cohort (1 506 cases) and validation cohort (646 cases) according to the ratio of 7∶3. Single-factor regression and multi-factor logistic regression were used to screen factors related to local lymph node metastasis in salivary gland MEC, with constructing of a nomogram. Calibration curve, receiver operating characteristic (ROC) curve, area under the ROC curve (AUC) and decision curve analysis were used to evaluate model performance in the validation cohort and the total cohort. Statistical tests were performed using SPSS (26.0) and R (4.3.0) software. Results: Multivariate logistic regression results showed that M stage [OR(95%CI):12.360(3.295-46.365), P=0.014], pathological grade Ⅱ、Ⅲ、Ⅳ[OR(95%CI): 1.956(1.329-2.879), 9.654(6.309-14.772), 9.298(6.072-14.238), P<0.001], T staging T2, T3, T4[OR(95%CI): 1.706(0.932-3.124), 3.021(1.790-5.096), 3.311(1.925-5.695), P<0.001], and gender [OR(95%CI):0.759(0.593-0.972), P=0.029] were independent factors affecting local lymph node metastasis in salivary gland MEC. Through verification in the validation cohort and the total cohort, the AUC values were greater than 0.8, and the calibration curve was close to the perfect reference line, proving that the constructed nomogram model had good specificity and sensitivity for predicting local lymph node metastasis in salivary gland MEC. Conclusion: M stage, pathological grade, T stage, and gender are risk factors for predicting regional lymph node metastasis and the established-nomogram has good predictive performance for local lymph node metastasis in salivary gland MEC.
目的： 通过探究影响唾液腺黏液表皮样癌（mucoepidermoid carcinoma，MEC）患者局部淋巴结转移的风险因素，建立可个体化预测唾液腺MEC患者淋巴结转移的列线图模型。 方法： 收集美国国家癌症研究所监测、流行病学及最终结果（Surveillance，Epidemiology，and End Results，SEER）数据库中1975年至2020年2 152例唾液腺MEC患者的临床资料。将其按照7∶3的比例分为训练队列（1 506例）和验证队列（646例）。采用单因素回归以及多因素Logistic回归筛选与唾液腺MEC患者局部淋巴结转移相关的因素，构建列线图。在验证队列及总队列中利用校准曲线、受试者工作特征（ROC）曲线、ROC曲线下面积（AUC）和决策曲线评价模型性能。使用SPSS（26.0）与R（4.3.0）软件进行统计学检验。 结果： 多因素Logistic回归结果显示M分期［OR（95%CI）为12.360（3.295~46.365），P=0.014］、病理分级Ⅱ、Ⅲ、Ⅳ［OR（95%CI）分别为1.956（1.329～2.879）、9.654（6.309～14.772）、9.298（6.072～14.238）,P<0.001］、T分期T2、T3、T4[OR（95%CI）分别为1.706（0.932～3.124）、3.021（1.790～5.096）、3.311（1.925～5.695）,P<0.001］以及性别［OR（95%CI）为0.759（0.593~0.972），P=0.029］是唾液腺MEC患者局部淋巴结转移的影响因素。经过验证队列以及总队列验证，列线图AUC值均大于0.8，校准曲线接近完美参考线。 结论： M分期、病理分级、T分期、性别是预测唾液腺MEC患者局部淋巴结转移的危险因素。据此建立的列线图具有良好的预测性能，可对唾液腺MEC患者局部淋巴结转移的概率进行个体化预测。.