Predictive value of ultrasound features combined with Galectin-3 expression in the primary lesion of papillary thyroid carcinoma for central lymph node metastasis

GAO Yushu; ZHU Xiaohui; XU Linlin

doi:10.3969/j.issn.1009-0460.2025.07.014

Abstract：Objective To develop a predictive model for central lymph node metastasis(CLNM)by analyzing the ultrasonographic characteristics of primary lesions in papillary thyroid carcinoma(PTC)in combination with the expression level of the molecular biomarker Galectin-3(Gal-3).Methods A retrospective analysis was conducted on the clinical data of 360 patients with solitary PTC admitted to Yancheng Third People's Hospital between January 2022 and April 2024.According to the inclusion and exclusion criteria,295 patients were ultimately enrolled in the study.Based on postoperative pathological results,patients were divided into a CLNM group(118 cases)and a non-CLNM group(177 cases).Comprehensive clinical baseline data,preoperative ultrasonographic features and immunohistochemical detection indicators of postoperative pathological specimens were systematically collected for all patients.Univariate analysis was used to screen for indicators with statistically significant differences between the two groups,and these indicators were subsequently incorporated into multivariate logistic regression analysis to identify independent predictive factors for CLNM.Based on the multivariate analysis results,an individualized CLNM risk prediction nomogram model was constructed.The model's discriminative ability,calibration accuracy,and clinical utility were comprehensively evaluated using receiver operating characteristic curve analysis,calibration curve analysis,and decision curve analysis.Results The median age of patients in the CLNM group was significantly higher than that in the non-CLNM group(53 years vs.50 years,P=0.032),and males were more prone to CLNM(28.8%vs.14.1%,P<0.001).Ultrasonographic features revealed significantly higher proportions of microcalcifications(83.9%vs.46.3%),blurred margins(55.1%vs.27.1%),capsular contact(62.7%vs.35.6%),maximum tumor diameter>10 mm(69.5%vs.24.3%),and horizontal growth orientation(53.4%vs.39.5%)in the CLNM group(P<0.05).Pathological analysis showed significantly elevated positive expression rates of Gal-3(83.1%vs.67.8%)and epidermal growth factor receptor(78.8%vs.66.7%)in the CLNM group(P<0.05).Multivariate analysis identified microcalcifications(OR=6.330),horizontal growth orientation(OR=7.112),maximum tumor diameter>10 mm(OR=2.375),Gal-3 positivity(OR=2.473),and epidermal growth factor receptor positivity(OR=1.833)as independent risk factors,while smooth margins(OR=0.493)and absence of capsular contact(OR=0.442)were protective factors.The nomogram prediction model constructed based on these findings demonstrated excellent discriminative ability(area under the curve=0.897)and calibration(χ2=6.523,P=0.589),with a sensitivity of 85.6%and specificity of 82.5%.Conclusion The nomogram model constructed using features such as calcification,indistinct margins,maximum diameter,and Gal-3 immunohistochemical results has good predictive performance for CLNM in PTC patients.This model can reduce the missed diagnosis rate of atypical sonographic CLNM,thereby providing additional imaging information for clinical decision-making.