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Background <p>Metastasis to lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLN) in papillary thyroid carcinoma (PTC) presents significant surgical challenges due to its deep anatomical location and association with disease recurrence.</p> Objective <p>To identify risk factors for LN-prRLN metastasis and develop a validated prediction model for clinical decision-making.</p> Methods <p>A retrospective analysis of 341 PTC patients underwent LN-prRLN dissection (May 2022–September 2024) at the First Affiliated Hospital of Guangxi Medical University was conducted. Clinicopathological characteristics were compared between metastasis-positive and negative groups. Independent risk factors were identified through univariate and multivariate logistic regression and utilized to construct a nomogram. Model performance was assessed using Receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).</p> Results <p>Male (odds ratio = 2.670, 95%CI:1.094–6.516), Tumor diameter (odds ratio = 1.931, 95%CI:1.140–3.270), Multifocality (odds ratio = 3.658, 95%CI:1.251–10.692), LN-arRLN metastasis (odds ratio = 1.340, 95%CI:1.122–1.602), Lateral lymph node metastasis (odds ratio = 7.815, 95%CI:2.857–21.379), Extrathyroidal extension (OR = 3.627, 95%CI:1.133–11.611) were identified as the independent risk factors for LN-prRLN metastasis. The nomogram demonstrated excellent discrimination (AUC: training cohort = 0.889; validation cohort = 0.858). The calibration curves demonstrated good concordance between predicted probabilities and the actual observed probabilities. The DCA curve indicates robust clinical utility for the model.</p> Conclusion <p>This study extends prior research by identifying additional independent risk factors, the model evaluation results indicated satisfactory predictive performance, facilitates individualized surgical planning to balance therapeutic efficacy against procedural risks.</p>

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Risk factors and prediction model for lymph node metastasis posterior to the right recurrent laryngeal nerve in papillary thyroid carcinoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月14日

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  • Xiaowen Fang,
  • Jihao Qin,
  • Chenxi Liang,
  • Siyu Li,
  • Xueyu Zeng,
  • Zhu Chen,
  • Jie-Hua Li

摘要

Background

Metastasis to lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLN) in papillary thyroid carcinoma (PTC) presents significant surgical challenges due to its deep anatomical location and association with disease recurrence.

Objective

To identify risk factors for LN-prRLN metastasis and develop a validated prediction model for clinical decision-making.

Methods

A retrospective analysis of 341 PTC patients underwent LN-prRLN dissection (May 2022–September 2024) at the First Affiliated Hospital of Guangxi Medical University was conducted. Clinicopathological characteristics were compared between metastasis-positive and negative groups. Independent risk factors were identified through univariate and multivariate logistic regression and utilized to construct a nomogram. Model performance was assessed using Receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).

Results

Male (odds ratio = 2.670, 95%CI:1.094–6.516), Tumor diameter (odds ratio = 1.931, 95%CI:1.140–3.270), Multifocality (odds ratio = 3.658, 95%CI:1.251–10.692), LN-arRLN metastasis (odds ratio = 1.340, 95%CI:1.122–1.602), Lateral lymph node metastasis (odds ratio = 7.815, 95%CI:2.857–21.379), Extrathyroidal extension (OR = 3.627, 95%CI:1.133–11.611) were identified as the independent risk factors for LN-prRLN metastasis. The nomogram demonstrated excellent discrimination (AUC: training cohort = 0.889; validation cohort = 0.858). The calibration curves demonstrated good concordance between predicted probabilities and the actual observed probabilities. The DCA curve indicates robust clinical utility for the model.

Conclusion

This study extends prior research by identifying additional independent risk factors, the model evaluation results indicated satisfactory predictive performance, facilitates individualized surgical planning to balance therapeutic efficacy against procedural risks.