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

Objective: To analyze the risk factors associated with the occurrence of cervical lymph node metastasis (LNM) in patients with diffuse sclerosing variant of papillary thyroid carcinoma (DSV-PTC) and to establish a nomogram model.

Methods: Clinical data of 199 DSV-PTC patients from SEER database were obtained, and they were randomly divided into training group (n=139) and validation group (n=60). 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), and multifocality. The Validation was carried out using C-index, calibration curves, and Decision Curve Analysis (DCA) in terms of differentiation and calibration of the nomogram model, respectively.

Results: Age, tumor size(cm), capsular invasion, and multifocality were independent risk factors for the development of LNM in patients with DSV-PTC (P<0.05). In the training and validation groups, the C-index of internal validation of the nomogram was 0.808 (95%CI: 0.733-0.755) and 0.813 (95% CI: 0.591-0.868), the calibration curves showed that the model was in good agreement, and the decision curve (DCA) indicated that the nomogram model had good clinical utility.  CONCLUSION: Age, tumor size(cm), capsular invasion, and multifocality are independent risk factors for the development of LNM in DSV-PTC. The nomogram model can predict the risk of developing LNM in DSV-PTC patients and provide clinical guidance.