A nomogram for predicting the central lymph node metastasis in double primary carcinoma involving thyroid carcinoma.

Abstract

Background: Although the incidence of double primary carcinoma (DPC) involving thyroid carcinoma is clinically significant, current literature lacks sufficient investigation of this population, particularly regarding central lymph node metastasis (CLNM) patterns. Accurate preoperative prediction in CLNM is crucial for optimal surgical planning and decision-making. This study aimed to investigate the influential factors of CLNM in DPC involving thyroid carcinoma and develop a nomogram for the prediction in CLNM.

Methods: A retrospective analysis of 62 cases with DPC involving thyroid carcinoma from January 2021 to May 2025 was performed. All patients presented with complete clinical data and underwent postoperative follow-up. Univariable and multivariable logistic regression analyses were used to identify the factors affecting CLNM. Based on the regression results, a nomogram model was constructed and internally validated using k-fold cross-validation. The C-index value, the calibration curve and the Hosmer-Lemeshow test were used to evaluate the performance of the model.

Results: Analyses revealed that tumor size, tumor site, blood group and thyroglobulin (TG) were influential factors of CLNM in DPC involving thyroid carcinoma (P<0.05). These factors were incorporated into the construction of the nomogram [C-index =0.892, 95% confidence interval (CI): 0.878-0.906]. The sensitivity and specificity of the model were 75.0% and 91.3%. The k-fold cross-validation method (k=5) validated the high accuracy of the model (C-index =0.893). The model presented superior predictive power with a Hosmer-Lemeshow goodness-of-fit test value of χ²=11.348, P=0.18.

Conclusions: Tumor size ≥0.95 cm and TG ≥15.62 mg/L were risk factors of CLNM in the DPC patients involving thyroid carcinoma. Meanwhile, lower tumor location in the thyroid and type B blood were risk factors of CLNM. The proposed nomogram could be a reliable tool for accurate prediction in CLNM. Additionally, our study showed that multifocal lung carcinoma patients always tended to have a higher rate of multifocality in thyroid carcinoma.