ArticleFrontiers in endocrinology2022
Preoperative prognostic risk stratification model for papillary thyroid carcinoma based on clinical and ultrasound characteristics.
Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Correlation between ultrasound calcification patterns, and clinicopathological factors and recurrence risk in papillary thyroid carcinoma.Gland surgery · 2025Article
- Predicting Distant Metastasis in Papillary Thyroid Carcinoma: A Postoperative Nomogram Integrating Sex, Histology, Bilaterality, and Extrathyroidal Extension.International journal of general medicine · 2025Article
- Construction and validation of a diagnostic model for high-risk papillary thyroid microcarcinoma.Frontiers in endocrinology · 2024Article
- Insight of novel biomarkers for papillary thyroid carcinoma through multiomics.Frontiers in oncology · 2023Article
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Authors and funding
4 authors.
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Abstract
Background: The preoperative risk stratification for patients with papillary thyroid carcinoma (PTC) plays a crucial role in guiding individualized treatment. We aim to construct a predictive model that aids in distinguishing between patients with low-risk and high-risk PTC based on preoperative clinical and ultrasound characteristics. Materials and methods: Patients who underwent open surgery and were diagnosed with PTC Results: A total of 1,875 patients with PTC were enrolled. Eight variables (sex, age, number of foci, maximum tumor diameter on ultrasound, calcification, capsule, lymph node status on ultrasound, and thyroid peroxidase (TPO) antibody level) significantly associated with risk stratification were included in the predictive model. A nomogram was constructed for clinical utility. The model showed good discrimination, and the area under the curve was 0.777 [95% confidence interval (CI): 0.752-0.803] and 0.769 (95% CI: 0.729-0.809) in the training set and validation set, respectively. The calibration curve exhibited a rather good consistency with the perfect prediction. Furthermore, decision curve analysis and clinical impact curve showed that the model had good efficacy in predicting the prognostic risk of PTC. Conclusions: The nomogram model based on preoperative indicators for predicting the prognostic stratification of PTC showed a good predictive value. This could aid surgeons in deciding on individualized precision treatments.
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