[Analysis of risk factors and construction of nomogram model for local lymph node metastasis in salivary gland mucoepidermoid carcinoma].

M J Zhang, Y S Yao, X Chen, Y K Mou, Y M Li, X C Song
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Abstract

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.

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[涎腺黏液表皮样癌局部淋巴结转移的危险因素分析及提名图模型构建]。
研究目的分析影响涎腺黏液表皮样癌(MEC)区域淋巴结转移的风险因素,并建立单独预测涎腺黏液表皮样癌淋巴结转移的提名图模型。方法:从美国国立癌症研究所的监测、流行病学和最终结果(SEER)数据库中收集1975年至2020年间2 152例唾液腺黏液瘤患者的临床数据。所收集的数据按照 7∶3 的比例分为训练队列(1 506 例)和验证队列(646 例)。采用单因素回归和多因素Logistic回归筛选涎腺MEC局部淋巴结转移的相关因素,并构建提名图。采用校准曲线、接收器操作特征曲线(ROC)、ROC 曲线下面积(AUC)和决策曲线分析来评估模型在验证队列和总队列中的表现。统计测试使用 SPSS (26.0) 和 R (4.3.0) 软件进行。结果多变量逻辑回归结果显示,M期[OR(95%CI):12.360(3.295-46.365), P=0.014]、病理分级Ⅱ、Ⅲ、Ⅳ[OR(95%CI): 1.956(1.329-2.879), 9.654(6.309-14.772), 9.298(6.072-14.238),POR(95%CI):1.706(0.932-3.124),3.021(1.790-5.096),3.311(1.925-5.695),POR(95%CI):0.759(0.593-0.972),P=0.029]是影响唾液腺 MEC 局部淋巴结转移的独立因素。通过在验证队列和总队列中的验证,AUC 值均大于 0.8,校正曲线接近完美参考线,证明所构建的提名图模型在预测涎腺 MEC 局部淋巴结转移方面具有良好的特异性和灵敏度。结论M分期、病理分级、T分期和性别是预测区域淋巴结转移的危险因素,所建立的提名图对涎腺癌局部淋巴结转移具有良好的预测效果。
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