基于多模态数据的甲状腺髓样癌中央区淋巴结转移术前预测模型的构建与分析OA

Objective:To develop and validate a multimodal data-based predictive model for central lymph node metastasis(CLNM)in patients with medullary thyroid carcinoma(MTC)and evaluate its clinical significance.Methods:We retrospectively analyzed clinical-pathological data,preoperative imaging features,and laboratory parameters of 104 MTC patients treated at the First Affiliated Hospital of Nanjing Medical University between January 2017 and May 2025.Potential predictors(P<0.1 in univariate analysis)were included in a multivariate logistic regression model with backward stepwise selection to identify independent risk factors for CLNM.A prediction model was constructed and a nomogram was drawn.The receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA)were used to evaluate the discrimination,calibration,and clinical applicability of the model.Internal validation was performed via bootstrap resampling.Results:According to the presence or absence of CLNM in the pathological results,104 MTC patients were classified into CLNM-positive(n=55)and CLNM-negative(n=49)groups.Compared to the CLNM-negative group,CLNM-positive patients showed significant differences in sex(P=0.001),whether the ultrasound(US)tumor morphology was regular(P<0.001),whether US tumor margin was smooth(P<0.001),serum carcinoembryonic antigen(CEA)level(P=0.006),and serum calcitonin(CT)level(P<0.001).Multivariate analysis identified male gender(OR=6.50,95%CI:2.03-20.81;P=0.002),non-circumscribed US margins(OR=9.77,95%CI:3.12-30.59,P<0.001),and elevated serumCT(OR=1.25,95%CI:1.10-1.42,P<0.001)as independent risk factors for CLNM.The nomogram integrating these factors demonstrated excellent discrimination(AUC=0.873,95%CI:0.808-0.939),with good calibration and clinical utility on DCA.Bootstrap validation confirmed model stability(AUC=0.874,95%CI:0.865-0.879).Conclusion:A multimodal model incorporating sex,US tumor margin status,and serum CT levels effectively predicts CLNM risk in MTC patients,providing a valuable tool for clinical decision-making.