Lin Xunyi, Fang Lan, Li Ming, Yin Jianwu, Yang Chao, Chen Yanting
Department of Thyroid and Breast Surgery, Huizhou No. 2 Women's and Children's Healthcare Hospital, Huizhou, Guangdong, 516001, China.
Department of Pediatrics, Huizhou No. 2 Women's and Children's Healthcare Hospital, Huizhou, Guangdong, 516001, China.
Eur Arch Otorhinolaryngol. 2025 Apr;282(4):2087-2094. doi: 10.1007/s00405-024-09050-9. Epub 2024 Oct 29.
To analyze the risk factors associated with the occurrence of cervical lymph node metastasis (LNM) in patients with tall cell variant of papillary thyroid carcinoma (TCV-PTC) and to establish a nomogram.
Clinical data of 727 patients with TCV-PTC from SEER database were obtained, and they were randomly divided into the training group (n = 508) and validation group (n = 219). The clinicopathological characteristics were analyzed by logistic regression, including age, marital status, race, gender, tumor size(cm), T stage, M stage, bilaterality, capsular invasion, extrathyroidal extension (ETE), vascular invasion and multifocality. The C-index, calibration curves, and DCA were utilized to validate the model from the differentiation and calibration of the nomogram, respectively.
Tumor size, extrathyroidal extension, and multifocality were independent risk factors for the development of LNM in patients with TCV-PTC (P < 0.05). In the training and validation groups, the C-index of internal validation of the nomogram were 0.727 (95% CI: 0.571-0.785) and 0.712 (95%CI: 0.700-0.714). The calibration curves indicated that the model was in good agreement, and the DCA indicated that the nomogram model had good clinical utility.
Tumor size, extrathyroidal extension, and multifocality are independent risk factors for developing LNM in TCV-PTC. The nomogram model can predict the risk of developing LNM in TCV-PTC patients and provide clinical guidance.
分析甲状腺乳头状癌高细胞变异型(TCV-PTC)患者发生颈部淋巴结转移(LNM)的相关危险因素,并建立列线图。
获取美国监测、流行病学和最终结果(SEER)数据库中727例TCV-PTC患者的临床资料,将其随机分为训练组(n = 508)和验证组(n = 219)。采用逻辑回归分析临床病理特征,包括年龄、婚姻状况、种族、性别、肿瘤大小(cm)、T分期、M分期、双侧性、包膜侵犯、甲状腺外侵犯(ETE)、血管侵犯和多灶性。分别利用C指数、校准曲线和决策曲线分析(DCA)从列线图的区分度和校准度方面验证模型。
肿瘤大小、甲状腺外侵犯和多灶性是TCV-PTC患者发生LNM的独立危险因素(P < 0.05)。在训练组和验证组中,列线图内部验证的C指数分别为0.727(95%CI:0.571 - 0.785)和0.712(95%CI:0.700 - 0.714)。校准曲线表明模型拟合良好,DCA表明列线图模型具有良好的临床实用性。
肿瘤大小、甲状腺外侵犯和多灶性是TCV-PTC发生LNM的独立危险因素。列线图模型可预测TCV-PTC患者发生LNM的风险并提供临床指导。