Construction and validation of nomograms to predict central lymph node metastasis in clinical node-negative unilateral papillary thyroid carcinoma.

The scope of neck lymph node dissection remains controversial for unilateral papillary thyroid carcinoma (UPTC) patients with no clinical evidence of lymph node metastasis (cN0). This study aims to build and validate a model for predicting central lymph node metastasis (CLNM) in UPTC patients through preoperative basic information and intraoperative rapid frozen pathology results. Retrospective analysis covered 1928 patients with PTC from the Wuhan Union Hospital database (2010-2020), randomly split into training and validation sets in a 7:3 ratio. Univariate and multivariate logistic regression analyses were performed to assess the risk factors for ipsilateral CLNM and contralateral CLNM in UPTC patients with cN0. Identified six risk factors for ipsilateral CLNM and seven risk factors for contralateral CLNM in cN0 UPTC patients. Two separate nomograms were constructed to visualize the results. The C-index for predicting ipsilateral and contralateral CLNM nomograms is 0.746 (95% CI 0.723-0.768) and 0.712 (95% CI 0.679-0.744), respectively. The calibration curves presented good agreement between prediction by nomograms and actual observation. The clinical decision curves suggest a net benefit from this model. UPTC patients can use these two nomograms to predict the probability of ipsilateral CLNM and contralateral CLNM separately, enabling risk stratification and aiding in surgical decision-making.
Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethical approval: The study follows the 2013 revised Helsinki Declaration and has been approved by the Ethics Committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (Approval No. 0304-01). This is an observational study that does not involve collecting personal information of patients, therefore the ethics committee of our institution eliminates the need for obtaining informed consent.
(© 2025. The Author(s).)