基于超声及临床特征的甲状腺滤泡癌预测模型构建OA

Objective To explore the diagnostic value of binary multivariate Logistic regression analysis prediction model based on ultrasound and clinical features in follicular thyroid carcinoma(FTC).Methods A total of 107 patients with thyroid follicular tumors who underwent preoperative ultrasound examination and pathological diagnosis at Quanzhou First Hospital Affiliated to Fujian Medical University from April 2020 to August 2025 were collected as subjects,they were divided into follicular adenoma(FA)group(n=62)and FTC group(n=45).The clinical and ultrasonic characteristics of the patients were collected and recorded,and the binary multivariate Logistic regression analysis prediction model was constructed.The receiver operating characteristic(ROC)curve was drawn,and the diagnostic efficacy was evaluated by calculating the area under the curve.Results Binary Logistic regression analysis showed that age,thyroglobulin,anti-thyroglobulin antibody,echo uniformity,halo integrity,halo thickness,and blood flow richness were statistically different between two groups(P<0.05).The above indicators were included in the regression analysis prediction model.The area under the ROC curve of the prediction model was 0.936.Conclusion The binary multivariate Logistic regression analysis prediction model based on clinical features and ultrasound findings showed good diagnostic efficacy in the diagnosis and differential diagnosis of benign and malignant thyroid follicular tumors.