Construction and validation of a nomogram for predicting cervical lymph node metastasis in tall cell variant of papillary thyroid carcinoma

To analyze the risk factors associated with the occurrence of cervical lymph node metastasis (LNM) in patients with tall cell variant of papillary thyroid carcinoma (TCV-PTC) and to establish a nomogram.

Clinical data of 727 patients with TCV-PTC from SEER database were obtained, and they were randomly divided into the training group (n = 508) and validation group (n = 219). The clinicopathological characteristics were analyzed by logistic regression, including age, marital status, race, gender, tumor size(cm), T stage, M stage, bilaterality, capsular invasion, extrathyroidal extension (ETE), vascular invasion and multifocality. The C-index, calibration curves, and DCA were utilized to validate the model from the differentiation and calibration of the nomogram, respectively.

Tumor size, extrathyroidal extension, and multifocality were independent risk factors for the development of LNM in patients with TCV-PTC (P < 0.05). In the training and validation groups, the C-index of internal validation of the nomogram were 0.727 (95% CI: 0.571–0.785) and 0.712 (95%CI: 0.700-0.714). The calibration curves indicated that the model was in good agreement, and the DCA indicated that the nomogram model had good clinical utility.

Tumor size, extrathyroidal extension, and multifocality are independent risk factors for developing LNM in TCV-PTC. The nomogram model can predict the risk of developing LNM in TCV-PTC patients and provide clinical guidance.