Li Hong, Zhang Lanli, Wang Yanbing, Tong Shengju, Shi Yang, Lu Shengnan, Bu Yanling
Department of Ultrasound, The Third Affiliated Hospital of Qiqihar Medical University, Qiqihar, China.
Computer Center, The Third Affiliated Hospital of Qiqihar Medical University, Qiqihar, China.
Front Endocrinol (Lausanne). 2024 Nov 18;15:1461865. doi: 10.3389/fendo.2024.1461865. eCollection 2024.
This study aimed to assess the viability of a multivariate regression model utilizing ultrasound findings and serum markers for predicting thyroid cancer metastasis.
A retrospective analysis of 98 thyroid patients admitted from January 2022 to October 2022 was conducted to categorize them into a metastasis group (n=20) and a non-metastasis group (n=78) based on postoperative pathological results. Both groups underwent ultrasound examination and serum marker testing. Correlative analysis was performed to explore the association between various indicators and thyroid cancer metastasis. A multivariate regression model was developed, and receiver operating characteristic (ROC) curves were used to assess the predictive value of ultrasound findings, serum markers, and their combination for thyroid cancer metastasis.
Statistically significant differences were found in the levels of ultrasound findings and serum markers between the two groups. Nodule boundaries, presence or absence of halos, margins, lobulation, capsular invasion, surface smoothness, nodule aspect ratio, uric acid, total cholesterol, triglyceride, and LDL cholesterol levels were predictors of metastasis in thyroid cancer. The AUC value of 0.950 for the prediction of thyroid cancer metastasis by ultrasound signs combined with serologic indicators was significantly higher than 0.728 and 0.711 predicted by ultrasound signs or serologic indicators alone.
The multivariate regression model incorporating ultrasound findings and serum markers enhances the predictive accuracy for thyroid cancer metastasis, offering essential guidance for early prediction and intervention in a clinical setting.
本研究旨在评估利用超声检查结果和血清标志物的多元回归模型预测甲状腺癌转移的可行性。
对2022年1月至2022年10月收治的98例甲状腺患者进行回顾性分析，根据术后病理结果将其分为转移组（n = 20）和非转移组（n = 78）。两组均接受超声检查和血清标志物检测。进行相关性分析以探讨各项指标与甲状腺癌转移之间的关联。建立多元回归模型，并使用受试者操作特征（ROC）曲线评估超声检查结果、血清标志物及其联合检测对甲状腺癌转移的预测价值。
两组之间的超声检查结果和血清标志物水平存在统计学显著差异。结节边界、有无晕环、边缘、分叶、包膜侵犯、表面光滑度、结节纵横比、尿酸、总胆固醇、甘油三酯和低密度脂蛋白胆固醇水平是甲状腺癌转移的预测指标。超声征象联合血清学指标预测甲状腺癌转移的AUC值为0.950，显著高于单独超声征象或血清学指标预测的0.728和0.711。
结合超声检查结果和血清标志物的多元回归模型提高了甲状腺癌转移的预测准确性，为临床早期预测和干预提供了重要指导。
