Construction and validation of a clinical prediction model for central lymph node metastasis in patients with high age-risk papillary thyroid cancer / 中华内分泌外科杂志
Chinese Journal of Endocrine Surgery
; (6): 45-50, 2024.
Article
en Zh
| WPRIM
| ID: wpr-1019489
Biblioteca responsable:
WPRO
ABSTRACT
Objective:To analyze the risk factors for central lymph node metastasis (CLNM) in patients with papillary thyroid cancer (PTC) aged 55 years and above, and to construct a predictive model with columnar graph.Methods:This retrospective study included 406 PTC patients aged 55 and above, treated at the First Affiliated Hospital of Zhengzhou University from Nov. 2019 to Feb. 2022. Data on demographic characteristics, disease features, and laboratory test results were collected. Univariate and multivariate logistic regression analyses were used to identify risk factors for CLNM and develop a clinical prediction model and nomogram.Results:The study involved 406 patients, divided into a modeling group (285 patients) and a validation group (121 patients). The predictive model identified independent risk factors for CLNM. In the modeling group, the model demonstrated a ROC AUC of 0.769, with 82.6% sensitivity, 63.0% specificity, and 67.7% accuracy. The validation group showed 66.7% sensitivity, 74.5% specificity, and 72.7% accuracy, with an AUC of 0.760. Hosmer-Lemeshow tests indicated good fit in both groups. Decision curve analysis confirmed the model's clinical decision-making value, showing better performance than traditional strategies and good generalizability and reliability.Conclusions:Sex, maximum tumor diameter, bilateral involvement of thyroid lobes, clinically evident cervical lymph nodes, and local invasion are independent predictive factors for CLNM in patients over 55 with papillary thyroid carcinoma (PTC). A clinical risk stratification nomogram model based on these risk factors demonstrates good predictive performance.
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Base de datos:
WPRIM
Idioma:
Zh
Revista:
Chinese Journal of Endocrine Surgery
Año:
2024
Tipo del documento:
Article