Future oncology (London, England) · 2025
Personalized risk prediction of lateral lymph node metastasis in male papillary thyroid cancer: a sex-specific model leveraging central lymph node ratio.
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Zhang Xue, Qin Yuan, Hou Niuniu, Zhang Yunjiao, Yan Changjiao, Chen Xi, Liu Chutuo, Chen Chong, Ling Rui
Аннотация
AIMS: Notable sex-based disparities exist in papillary thyroid carcinoma (PTC), necessitating male-specific models for predicting lateral lymph node metastasis (LLNM) to guide treatment.
METHODS: We developed and validated two nomograms, based on central lymph node ratio (LNR) and preoperative ultrasound (US), respectively, using data from 433 male PTC patients who underwent total thyroidectomy (TT) with central and lateral neck lymph node dissection. Multivariable analysis identified key risk factors. Model performance was evaluated using ROC curves, calibration curves, and decision curve analysis (DCA) across training and validation sets.
RESULTS: Male patients had 1.33-fold higher odds of central lymph node metastasis (CLNM) and 1.51-fold higher odds of LLNM than female patients (p < 0.05). Multivariable analysis identified multifocality, tumor size >20 mm, preoperative US nodal status, and an elevated LNR as independent risk factors for LLNM in males (p < 0.05). The LNR-based nomogram demonstrated superior predictive accuracy, with AUCs of 0.828 (training), 0.812 (internal validation), and 0.832 (external validation), outperforming the US-based model. Risk stratification using nomogram scores effectively categorized patients into three distinct groups with significantly different LLNM rates.
CONCLUSIONS: The nomogram based on the central LNR provides a precise and clinically valuable tool for the individualized prediction of LLNM in male PTC patients.
METHODS: We developed and validated two nomograms, based on central lymph node ratio (LNR) and preoperative ultrasound (US), respectively, using data from 433 male PTC patients who underwent total thyroidectomy (TT) with central and lateral neck lymph node dissection. Multivariable analysis identified key risk factors. Model performance was evaluated using ROC curves, calibration curves, and decision curve analysis (DCA) across training and validation sets.
RESULTS: Male patients had 1.33-fold higher odds of central lymph node metastasis (CLNM) and 1.51-fold higher odds of LLNM than female patients (p < 0.05). Multivariable analysis identified multifocality, tumor size >20 mm, preoperative US nodal status, and an elevated LNR as independent risk factors for LLNM in males (p < 0.05). The LNR-based nomogram demonstrated superior predictive accuracy, with AUCs of 0.828 (training), 0.812 (internal validation), and 0.832 (external validation), outperforming the US-based model. Risk stratification using nomogram scores effectively categorized patients into three distinct groups with significantly different LLNM rates.
CONCLUSIONS: The nomogram based on the central LNR provides a precise and clinically valuable tool for the individualized prediction of LLNM in male PTC patients.