Zhejiang Chinese Medical University, Hangzhou, China.
The 2nd Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, China.
Biomed Res Int. 2022 May 14;2022:4680064. doi: 10.1155/2022/4680064. eCollection 2022.
Papillary thyroid carcinoma (PTC) is the most common thyroid carcinoma and is prone to cervical lymph node metastases (CLNM). We aim to analyze the correlation between clinical information, ultrasonic parameters of PTC, and CLNM.
1335 patients who had pathologically confirmed unifocal PTC were enrolled in this retrospective cohort study. Univariate and multivariate logistic analyses were performed to predict CLNM in PTC patients. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance.
Univariate analysis showed that gender, age, maximum tumor diameter and volume, and cross-sectional and longitudinal aspect ratio were related to CLNM ( < 0.05). Multivariate logistic analysis showed that gender, age, maximum tumor diameter, and volume were independent correlative factors, and the cross-sectional aspect ratio had significant difference for PTC2 to predict CLNM. The area under the curve (AUC) of the maximum tumor diameter and volume was 0.738 and 0.733, respectively. Maximum tumor diameter and volume and the cross-sectional and longitudinal aspect ratio were statistically significant following analysis of variance ( < 0.05).
Younger age, male, and larger tumor were high risk factors for CLNM in patients with unifocal PTC. The cross-sectional aspect ratio had a more effective predictive value for CLNM in patients with larger thyroid tumors.
甲状腺乳头状癌（PTC）是最常见的甲状腺癌，易发生颈部淋巴结转移（CLNM）。我们旨在分析 PTC 的临床信息、超声参数与 CLNM 之间的相关性。
本回顾性队列研究纳入了 1335 例经病理证实为单发 PTC 的患者。采用单因素和多因素逻辑分析来预测 PTC 患者的 CLNM。使用受试者工作特征（ROC）曲线评估诊断性能。
单因素分析显示，性别、年龄、最大肿瘤直径和体积以及横截面积与长径比与 CLNM 相关（<0.05）。多因素逻辑分析显示，性别、年龄、最大肿瘤直径和体积是独立的相关因素，而横截面积对预测 CLNM 方面，PTC2 具有显著差异。最大肿瘤直径和体积的曲线下面积（AUC）分别为 0.738 和 0.733。最大肿瘤直径和体积以及横截面积与长径比的方差分析结果具有统计学意义（<0.05）。
年龄较小、男性和较大的肿瘤是单发 PTC 患者 CLNM 的高危因素。对于甲状腺较大肿瘤的患者，横截面积对 CLNM 具有更有效的预测价值。
