Construction and validation of nomograms to predict central lymph node metastasis in clinical node-negative unilateral papillary thyroid carcinoma
Abstract 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 patien...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-86201-w |
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| Summary: | Abstract 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. |
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| ISSN: | 2045-2322 |