Establishing a Predictive Nomogram for Cervical Lymph Node Metastasis in Patients With Papillary Thyroid Carcinoma

Frontiers in Oncology

Oncology

Wu Yin¹  Ling-Ling Li²  Qiao Hu²  Quan-Li Su²  Fei-Fei Lin²  Li Liang²  Wang-Jian Zhang³ 

[1] Department of Pathology, The People’s Hospital of Guangxi Zhuang Autonomous Region & Guangxi Academy of Medical Sciences, Nanning, China;Department of Ultrasound, The People’s Hospital of Guangxi Zhuang Autonomous Region & Guangxi Academy of Medical Sciences, Nanning, China;School of Public Health, Sun Yet-Sen University, Guangzhou, China;

关键词: nomogram;    papillary thyroid carcinoma;    cervical lymph node;    metastasis;    predictor;   

DOI  :  10.3389/fonc.2021.766650

 received in 2021-08-29, accepted in 2021-12-27,  发布年份 2022

来源: Frontiers

【 摘 要 】

ObjectivesThe purpose of this study was to establish a nomogram for predicting cervical lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC).Materials and MethodsA total of 418 patients with papillary thyroid carcinoma undergoing total thyroidectomy with cervical lymph node dissection were enrolled in the retrospective study from January 2016 to September 2019. Univariate and multivariate Logistic regression analysis were performed to screen the clinicopathologic, laboratory and ultrasound (US) parameters influencing cervical lymph nodes metastasis and develop the predicting model.ResultsCLNM was proved in 34.4% (144/418) of patients. In the multivariate regression analysis, Male, Age < 45 years, Tumor size > 20mm, multifocality, ambiguous boundary, extracapsular invasion and US-suggested lymph nodes metastasis were independent risk factors of CLNM (p < 0.05). Prediction nomogram showed an excellent discriminative ability, with a C-index of 0.940 (95% confidence interval [CI], 0.888-0.991), and a good calibration.ConclusionThe established nomogram showed a good prediction of CLNM in patients with PTC. It is conveniently used and should be considered in the determination of surgical procedures.

【 授权许可】

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Copyright © 2022 Hu, Zhang, Liang, Li, Yin, Su and Lin