Tang Lei, Shen Jing
Department of Thyroid Surgery, The Second Affiliated Hospital of Jiaxing University, Jiaxing, China.
Department of Breast Surgery, The Second Affiliated Hospital of Jiaxing University, Jiaxing, China.
Gland Surg. 2025 Aug 31;14(8):1549-1557. doi: 10.21037/gs-2025-206. Epub 2025 Aug 25.
Although the incidence of double primary carcinoma (DPC) involving thyroid carcinoma is clinically significant, current literature lacks sufficient investigation of this population, particularly regarding central lymph node metastasis (CLNM) patterns. Accurate preoperative prediction in CLNM is crucial for optimal surgical planning and decision-making. This study aimed to investigate the influential factors of CLNM in DPC involving thyroid carcinoma and develop a nomogram for the prediction in CLNM.
A retrospective analysis of 62 cases with DPC involving thyroid carcinoma from January 2021 to May 2025 was performed. All patients presented with complete clinical data and underwent postoperative follow-up. Univariable and multivariable logistic regression analyses were used to identify the factors affecting CLNM. Based on the regression results, a nomogram model was constructed and internally validated using k-fold cross-validation. The C-index value, the calibration curve and the Hosmer-Lemeshow test were used to evaluate the performance of the model.
Analyses revealed that tumor size, tumor site, blood group and thyroglobulin (TG) were influential factors of CLNM in DPC involving thyroid carcinoma (P<0.05). These factors were incorporated into the construction of the nomogram [C-index =0.892, 95% confidence interval (CI): 0.878-0.906]. The sensitivity and specificity of the model were 75.0% and 91.3%. The k-fold cross-validation method (k=5) validated the high accuracy of the model (C-index =0.893). The model presented superior predictive power with a Hosmer-Lemeshow goodness-of-fit test value of χ=11.348, P=0.18.
Tumor size ≥0.95 cm and TG ≥15.62 mg/L were risk factors of CLNM in the DPC patients involving thyroid carcinoma. Meanwhile, lower tumor location in the thyroid and type B blood were risk factors of CLNM. The proposed nomogram could be a reliable tool for accurate prediction in CLNM. Additionally, our study showed that multifocal lung carcinoma patients always tended to have a higher rate of multifocality in thyroid carcinoma.
尽管涉及甲状腺癌的双原发癌（DPC）的发病率在临床上具有重要意义，但目前的文献对这一人群缺乏充分的研究，尤其是关于中央淋巴结转移（CLNM）模式。CLNM的准确术前预测对于优化手术规划和决策至关重要。本研究旨在探讨涉及甲状腺癌的DPC中CLNM的影响因素，并建立一种用于CLNM预测的列线图。
对2021年1月至2025年5月期间62例涉及甲状腺癌的DPC患者进行回顾性分析。所有患者均有完整的临床资料并接受了术后随访。采用单变量和多变量逻辑回归分析来确定影响CLNM的因素。基于回归结果，构建列线图模型并使用k折交叉验证进行内部验证。使用C指数值、校准曲线和Hosmer-Lemeshow检验来评估模型的性能。
分析显示，肿瘤大小、肿瘤部位、血型和甲状腺球蛋白（TG）是涉及甲状腺癌的DPC中CLNM的影响因素（P<0.05）。这些因素被纳入列线图的构建中[C指数=0.892，95%置信区间（CI）：0.878-0.906]。该模型的敏感性和特异性分别为75.0%和91.3%。k折交叉验证方法（k=5）验证了模型的高准确性（C指数=0.893）。该模型具有卓越的预测能力，Hosmer-Lemeshow拟合优度检验值χ=11.348，P=0.18。
肿瘤大小≥0.95 cm和TG≥15.62 mg/L是涉及甲状腺癌的DPC患者CLNM的危险因素。同时，甲状腺较低的肿瘤位置和B型血是CLNM的危险因素。所提出的列线图可能是CLNM准确预测的可靠工具。此外，我们的研究表明，多灶性肺癌患者的甲状腺癌多灶性发生率往往较高。
