Trial reportLangenbeck's archives of surgery2023
Construction and validation of a nomogram for predicting cervical lymph node metastasis in diffuse sclerosing variant of papillary thyroid carcinoma.
Trial report in Langenbeck's archives of surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Posterior minimal extrathyroidal extension as an independent risk factor for lateral lymph node metastasis in papillary thyroid carcinoma: a retrospective study based on a nomogram prediction model.Frontiers in endocrinology · 2026Article
- Nomogram for predicting the risk of central lymph node metastasis in papillary thyroid microcarcinoma: a combination of sonographic findings and clinical factors.Gland surgery · 2024Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo 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.
methodsClinical 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.
resultsAge, 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.
conclusionAge, 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.
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