甲状腺结节恶性风险分析及列线图的构建与验证OA

Objective:To analyze the independent risk factors for thyroid malignancy,develop a nomogram prediction model for the malignant risk of thyroid nodules,and validate its clinical application value.Methods:A retrospective analysis was conducted on the baseline data,micro flow imaging(MFI)findings,and pathological data of 120 patients(with a total of 121 nodules)with thyroid nodules treated at the Sixth People's Hospital of Yibin from January 2021 to December 2023.Independent risk factors for thyroid malignancy were identified through univariate and multivariate Logistic regression analyses,and a nomogram prediction model was constructed based on these factors.Internal validation was performed using the Bootstrap method to assess the predictive performance of the model.Results:MFI type Ⅳ,microcalcification,and C-TIRADS score of ≥2 were identified as independent risk factors for thyroid malignancy.The nomogram model constructed based on these factors demonstrated significantly superior diagnostic performance(AUC=0.897)compared to the individual application of each risk factor.The corrected C-index for internal validation of the model was 0.894,and both the calibration curve and decision curve analysis indicated good predictive ability of the model.Conclusion:The nomogram model constructed based on MFI type,microcalcification,and C-TIRADS score can effectively predict the benign or malignant nature of thyroid nodules,demonstrating high clinical application value.