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Construction and validation of a nomogram for predicting cervical lymph node metastasis in diffuse sclerosing variant
Xunyi Lin1, Jiaxing Huo2, Huan Zhang1
1Department of Thyroid and Breast Surgery, Hebei General Hospital Affiliated to Hebei North University, Shijiazhuang, 050051, Hebei province, China.
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.
