Skip to main content

ORIGINAL RESEARCH article

Front. Endocrinol.
Sec. Thyroid Endocrinology
Volume 15 - 2024 | doi: 10.3389/fendo.2024.1429382
This article is part of the Research Topic Papillary Thyroid Cancer: Prognostic Factors and Risk Assessment View all 15 articles

A comprehensive prediction model for central lymph node metastasis in papillary thyroid carcinoma with Hashimoto's thyroiditis: BRAF may not be a valuable predictor

Provisionally accepted
Yanwei Chen Yanwei Chen Shuangshuang Zhao Shuangshuang Zhao Zheng Zhang Zheng Zhang Zheming Chen Zheming Chen Bingxin Jiang Bingxin Jiang Maohui An Maohui An Mengyuan Shang Mengyuan Shang Xincai Wu Xincai Wu Xin Zhang Xin Zhang Baoding Chen Baoding Chen *
  • Affiliated Hospital of Jiangsu University, Zhenjiang, China

The final, formatted version of the article will be published soon.

    Papillary thyroid carcinoma (PTC) frequently coexists with Hashimoto's thyroiditis (HT), which poses challenges in detecting central lymph node metastasis (CLNM) and determining optimal surgical management. Our study aimed to identify the independent predictors for CLNM in PTC patients with HT and develop a comprehensive prediction model for individualized clinical decision-making. In this retrospective study, a total of 242 consecutive PTC patients who underwent thyroid surgery and central lymph node dissection between February 2019 and December 2021 were included. 129 patients with HT were enrolled as the case group and 113 patients without HT as control. The results of patients’ general information, laboratory examination, ultrasound features, pathological evaluation, and BRAF mutation were collected. Multivariate logistic regression analysis was used to identify independent predictors, and the prediction model and nomogram were developed for PTC patients with HT. The performance of the model was assessed using the receiver operating characteristic curve, calibration curve, decision curve analysis, and clinical impact curve. In addition, the impact of the factor BRAF mutation was further evaluated. Multivariate analysis revealed that gender (OR = 8.341, P = 0.013, 95% CI: 1.572, 44.266), maximum diameter (OR = 0.316, P = 0.029, 95% CI: 0.113, 0.888), multifocality (OR = 3.238, P = 0.010, 95% CI: 1.319, 7.948), margin (OR = 2.750, P = 0.046, 95% CI: 1.020, 7.416), and thyrotropin receptor antibody (TR-Ab) (OR = 0.054, P = 0.003, 95% CI: 0.008, 0.374) were identified as independent predictors for CLNM in PTC patients with HT. The area under the curve of the model was 0.82, with accuracy, sensitivity, and specificity of 77.5%, 80.3% and 75.0%, respectively. Meanwhile, the model showed satisfactory performance in the internal validation. Moreover, the results revealed that BRAF mutation cannot further improve the efficacy of the prediction model. Male, maximum diameter > 10mm, multifocal tumors, irregular margin, and lower TR-Ab level have significant predictive value for CLNM in PTC patients with HT. Meanwhile, BRAF mutation may not have a valuable predictive role for CLNM in these cases. The nomogram constructed offers a convenient and valuable tool for clinicians to determine surgical decision and prognostication for patients.

    Keywords: Papillary thyroid carcinoma, Hashimoto's thyroiditis, central lymph node metastasis, Prediction model, BRAF mutation, nomogram

    Received: 08 May 2024; Accepted: 28 Aug 2024.

    Copyright: © 2024 Chen, Zhao, Zhang, Chen, Jiang, An, Shang, Wu, Zhang and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Baoding Chen, Affiliated Hospital of Jiangsu University, Zhenjiang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.