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

Abstract

Objective: 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.

Methods: 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.

Results: 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.

Conclusion: 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.