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已发表论文
预测甲状腺乳头状癌远处转移：一种结合性别、组织学、双侧性及甲状腺外侵犯的术后列线图
Received 16 June 2025
Accepted for publication 29 August 2025
Published 12 September 2025 Volume 2025:18 Pages 5409—5419
DOI https://doi.org/10.2147/IJGM.S547317
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Ching-Hsien Chen
Jiaxi Wang, Zhiyu Li, Chuang Chen
Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, People’s Republic of China
Correspondence: Zhiyu Li, Email lizhiyu@whu.edu.cn Chuang Chen, Email chenc2469@whu.edu.cn
Background: Papillary thyroid carcinoma (PTC) generally has a good prognosis, but distant metastasis (DM) significantly reduces survival. Existing predictive models for DM have limited accuracy. This study aimed to identify independent risk factors for DM in PTC and develop a clinical prediction model using routine pathological parameters.
Methods: We retrospectively analyzed a cohort of 4127 PTC patients who underwent surgery between 2017 and 2022. Patients were divided into DM (n = 30) and non-DM (n = 4097) groups. Key variables, including sex, age, pathological subtype, tumor size, bilaterality, multifocality, extrathyroidal extension (ETE), and lymph node metastasis (LNM), were collected. We used univariate and multivariate logistic regression to identify independent predictors. A nomogram model was built and its performance was evaluated using ROC curves and other metrics.
Results: Univariate analysis identified male sex (OR = 0.362, p = 0.006), solid variant (OR = 36.509, p < 0.001), Multifocal (OR = 0.247, p < 0.001), bilaterality (OR = 2.847, p = 0.004), and ETE (OR = 4.360, p = 0.016) as significant risk factors. Multivariate analysis confirmed male sex (OR = 0.434, p = 0.029), solid variant (OR = 23.483, p < 0.001), bilaterality (OR = 1.309, p = 0.047), and ETE (OR = 3.094, p = 0.012) as independent predictors. The nomogram model showed a moderate discriminative ability with an AUC of 0.737, a sensitivity of 66.7%, and a specificity of 68.7%.
Conclusion: In this large-scale Chinese cohort study, we identified male sex, solid variant, bilaterality, and ETE as independent risk factors for PTCDM. The resulting model offers a practical tool for postoperative risk assessment, which can help guide customized surveillance and treatment for high-risk patients. Future research should focus on validating this model with external and multicenter cohorts and incorporating molecular biomarkers to further improve its predictive accuracy.
Keywords: papillary thyroid carcinoma, distant metastasis, risk factors, predictive model, nomogram
Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, People’s Republic of China
Correspondence: Zhiyu Li, Email lizhiyu@whu.edu.cn Chuang Chen, Email chenc2469@whu.edu.cn
Background: Papillary thyroid carcinoma (PTC) generally has a good prognosis, but distant metastasis (DM) significantly reduces survival. Existing predictive models for DM have limited accuracy. This study aimed to identify independent risk factors for DM in PTC and develop a clinical prediction model using routine pathological parameters.
Methods: We retrospectively analyzed a cohort of 4127 PTC patients who underwent surgery between 2017 and 2022. Patients were divided into DM (n = 30) and non-DM (n = 4097) groups. Key variables, including sex, age, pathological subtype, tumor size, bilaterality, multifocality, extrathyroidal extension (ETE), and lymph node metastasis (LNM), were collected. We used univariate and multivariate logistic regression to identify independent predictors. A nomogram model was built and its performance was evaluated using ROC curves and other metrics.
Results: Univariate analysis identified male sex (OR = 0.362, p = 0.006), solid variant (OR = 36.509, p < 0.001), Multifocal (OR = 0.247, p < 0.001), bilaterality (OR = 2.847, p = 0.004), and ETE (OR = 4.360, p = 0.016) as significant risk factors. Multivariate analysis confirmed male sex (OR = 0.434, p = 0.029), solid variant (OR = 23.483, p < 0.001), bilaterality (OR = 1.309, p = 0.047), and ETE (OR = 3.094, p = 0.012) as independent predictors. The nomogram model showed a moderate discriminative ability with an AUC of 0.737, a sensitivity of 66.7%, and a specificity of 68.7%.
Conclusion: In this large-scale Chinese cohort study, we identified male sex, solid variant, bilaterality, and ETE as independent risk factors for PTCDM. The resulting model offers a practical tool for postoperative risk assessment, which can help guide customized surveillance and treatment for high-risk patients. Future research should focus on validating this model with external and multicenter cohorts and incorporating molecular biomarkers to further improve its predictive accuracy.
Keywords: papillary thyroid carcinoma, distant metastasis, risk factors, predictive model, nomogram