Combined clinicopathological and ultrasonographic features for predicting extrathyroidal extension in thyroid cancer
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: Extrathyroidal extension (ETE) critically impacts the treatment and prognosis of thyroid cancer, necessitating accurate preoperative prediction models. This study aimed to develop and validate such a model combining clinicopathological and ultrasonographic features. Methods: This retrospective study enrolled 435 thyroid cancer patients from The First Affiliated Hospital of Nanchang University, categorized as non-ETE and ETE groups based on postoperative pathology. Patients were randomly divided into training (70%) and validation (30%) cohorts, with an external test cohort (n=70) from Huashan Hospital, Fudan University. Clinicopathological and ultrasonographic features were analyzed. Significant variables (P<0.05) identified via univariate logistic regression were incorporated into multivariate models: a clinicopathological model, an ultrasonographic model, and a combined clinicopathological-ultrasonographic model. Performance was evaluated using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Results: 0.845) (P>0.05). Conclusions: The clinicopathological-ultrasonographic model provides reliable preoperative ETE prediction, facilitating personalized surgical planning and improved patient outcomes.
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7155965037