Wang S S, Miao S C, Shan J L, Zhang D, Wang Q Q, Ni Q C, Fang J
Department of General Surgery, Nantong University Affiliated Hospital, Nantong 226001, China Department of General Surgery, Suqian Hospital Affiliated to Xuzhou Medical University (Nanjing Gulou Hospital Group Suqian Hospital), Suqian 223800, China.
Medical School of Nantong University, Nantong 226001, China.
Zhonghua Yi Xue Za Zhi. 2024 Sep 24;104(36):3416-3421. doi: 10.3760/cma.j.cn112137-20240524-01180.
To explore the risk factors of contralateral central lymph nodes (Cont-CLNs) metastasis in intermediate-to-high risk unilateral papillary thyroid carcinoma and establish a prediction model. The clinical data of 206 patients receiving thyroid cancer surgery at Nantong University Affiliated Hospital between January 2021 and June 2023 were retrospectively analyzed, including 50 males and 156 females, with an age of [(, )] 49.0(33.8, 57.0) years old. The risk factors of Cont-CLNs metastasis were screened by univariate analysis and multivariate logistic regression analysis. A nomogram was constructed for predicting Cont-CLNs metastasis in intermediate-to-high risk uPTC. The area under the receiver operating characteristic (ROC) curve(AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the model's predictive ability, accuracy, and clinical applicability, respectively. R language was used to randomly select 70% of the patients to establish a validation group for internal validation of the model. Patients were divided into a metastasis group (=56) and a non-metastasis group (=150) based on the occurrence of Cont-CLNs metastasis. The ages of the two groups were 39.0 (28.0, 56.8) years and 51.0 (38.8, 57.0) years, respectively. There were statistically significant differences in gender, maximum tumor diameter (>1 cm), ipsilateral central lymph nodes (Ipsi-CLNs) metastasis, number of Ipsi-CLNs metastases (≥4), and lateral lymph node metastasis and Cont-CLNs metastasis between the two groups (all <0.05). The results of multivariate logistic regression analyses showed that males(=2.926, : 1.063-8.051), maximum tumor diameter>1 cm(=4.471, : 1.344-14.877), and number of Ipsi-CLNs metastases≥4 (=5.011, : 1.815-13.834) were risk factors for Cont-CLNs metastasis (all <0.05). The AUC of the ROC curve, sensitivity, and specificity for predicting Cont-CLNs metastasis in intermediate-to-high risk uPTC by the prediction model in the modeling group were 0.821 (95%: 0.744-0.898), 82.5%, and 63.4%, respectively. In the internal validation group, the AUC of the ROC curve, sensitivity, and specificity for predicting Cont-CLNs metastasis in intermediate-to-high risk uPTC by the prediction model were 0.810 (95%: 0.717-0.902), 63.3%, and 83.7%, respectively. The calibration curves of the modeling group and the validation group showed that the model had good calibration ability. The DCA curves of the modeling group and the validation group indicated that the prediction model had good clinical adaptability. The prediction model constructed in this study has good predictive performance for Cont-CLNs metastasis in intermediate-to-high uPTC. When patient with intermediate-to-high risk uPTC is male, with maximum tumor diameter>1 cm, and the number of Ipsi-CLNs metastases≥4 should be alert to Cont-CLNs metastasis, and bilateral central lymph node dissection may be considered.
探讨中高风险单侧甲状腺乳头状癌对侧中央淋巴结（Cont-CLNs）转移的危险因素并建立预测模型。回顾性分析2021年1月至2023年6月在南通大学附属医院接受甲状腺癌手术的206例患者的临床资料，其中男性50例，女性156例，年龄为[(, )]49.0（33.8，57.0）岁。通过单因素分析和多因素logistic回归分析筛选Cont-CLNs转移的危险因素。构建预测中高风险甲状腺乳头状癌（uPTC）患者Cont-CLNs转移的列线图。采用受试者操作特征（ROC）曲线下面积（AUC）、校准曲线和决策曲线分析（DCA）分别评估模型的预测能力、准确性和临床适用性。使用R语言随机选取70%的患者建立验证组对模型进行内部验证。根据Cont-CLNs转移情况将患者分为转移组（=56）和非转移组（=150）。两组患者年龄分别为39.0（28.0，56.8）岁和51.0（38.8，57.0）岁。两组患者在性别、最大肿瘤直径（>1 cm）、同侧中央淋巴结（Ipsi-CLNs）转移、Ipsi-CLNs转移数量（≥4个）、侧方淋巴结转移及Cont-CLNs转移方面差异均有统计学意义（均<0.05）。多因素logistic回归分析结果显示，男性（=2.926，: 1.063 - 8.051）、最大肿瘤直径>1 cm（=4.471，: 1.344 - 14.877）及Ipsi-CLNs转移数量≥4个（=5.011，: 1.815 - 13.834）是Cont-CLNs转移的危险因素（均<0.05）。建模组预测模型预测中高风险uPTC患者Cont-CLNs转移的ROC曲线AUC、灵敏度和特异度分别为0.821（95%: 0.744 - 0.898）、82.5%和63.4%。在内部验证组中，预测模型预测中高风险uPTC患者Cont-CLNs转移的ROC曲线AUC、灵敏度和特异度分别为0.810（95%: 0.717 - 0.902）、63.3%和83.7%。建模组和验证组的校准曲线显示模型具有良好的校准能力。建模组和验证组的DCA曲线表明预测模型具有良好的临床适用性。本研究构建的预测模型对中高风险uPTC患者Cont-CLNs转移具有良好的预测性能。当中高风险uPTC患者为男性、最大肿瘤直径>1 cm且Ipsi-CLNs转移数量≥4个时，应警惕Cont-CLNs转移，可考虑行双侧中央淋巴结清扫术。
