Related Experiment Video
Updated: May 10, 2025
Quantification of Tumor Cell Adhesion in Lymph Node Cryosections
Published on: February 9, 2020
Nomograms for predicting cervical central lymph node metastases and high-volume cervical central lymph node
Xindong Huang1, Xiaoxiong Gan1, Jianhua Feng1
1Department of Thyroid Surgery, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
Background:
Cervical central lymph node metastasis (CLNM) is a known risk factor for recurrent thyroid cancer (TC), and cervical high-volume central lymph node metastases (HVCLNM) are associated with higher recurrence rates and shorter disease-specific survival. The status of CLNM is critical in determining surgical strategies for papillary thyroid carcinoma (PTC). We developed two separate nomograms to predict the probability of CLNM and HVCLNM.
Methods:
We retrospectively analyzed 590 PTC patients who underwent total thyroidectomy or lobectomy with central lymph node dissection (CLND) between January 2020 and May 2023. Univariate and multivariate analyses were conducted to identify risk factors associated with CLNM and HVCLNM. The nomograms were internally validated using bootstrapping and evaluated on a temporal validation cohort.
Results:
Between January 2020 and May 2023, 1,019 patients were screened, 590 (57.9%) were eligible, and they were divided into development (n=353) and validation (n=237) cohorts. HVCLNM was present in 41 patients (11.6%). The variables with the strongest predictive value for CLNM were younger age (P<0.001), male sex (P=0.045), tumor size (P<0.001), and tumor multifocality (P=0.001). The strongest predictors for HVCLNM were younger age (P=0.001), tumor size (P<0.001), bilateral lesions (P=0.005), and preoperative serum thyroid peroxidase antibody (TPOAb) ≤14.95 IU/mL (P=0.01). The area under the curve (AUC) for the CLNM model was 0.75, with similar results achieved in internal validation (0.74) and external validation (0.68). The AUC for the HVCLNM model was 0.80, with similar values in internal validation (0.79) and external validation (0.79). Both models demonstrated good calibration, with predictions closely aligning with observed outcomes.
Conclusions:
Based on the quantified risk stratification offered by our nomograms, clinicians can engage in comprehensive preoperative discussions with PTC patients. Prophylactic CLND and strict postoperative evaluation may be recommended for patients with high nomogram scores.
