ArticleFrontiers in endocrinology2023
Risk factor analysis and prediction model for papillary thyroid carcinoma with lymph node metastasis.
Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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14 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Diagnostic performance of machine learning and deep learning algorithms for thyroid cancer metastasis: a systematic review and meta-analysis.BMC medical informatics and decision making · 2025Pooled it
- Development of a clinically applicable prediction tool for lymph node metastasis in papillary thyroid carcinoma using lasso-logistic regression.BMC cancer · 2026Article
- Predicting cervical lymph node metastasis in papillary thyroid carcinoma using capsule disruption length measured by 3D-US.European radiology · 2026Article
- A clinically practical machine learning nomogram for preoperative CLNM prediction in PTMC: tumor-capsule distance and D2-40 evidence.Frontiers in oncology · 2026Article
- Utility of quantitative contrast-enhanced ultrasound: a valuable prediction for capsule invasion assessment in papillary thyroid cancer.Quantitative imaging in medicine and surgery · 2025Article
- Clinicopathological predictors of right para esophageal lymph node metastasis in papillary thyroid carcinoma: A systematic review and meta-analysis.World journal of clinical oncology · 2025Article
- A predictive model using platelets and neutrophil-to-lymphocyte ratio for the number of lymph node metastases in papillary thyroid carcinoma: a retrospective analysis.Gland surgery · 2025Article
- The value of ultrasonographic scoring method and nomogram in assessing cervical lymph node metastasis of papillary thyroid carcinoma.Thyroid research · 2025Article
- Visibility of mpMRI region of interest on ultrasound during cognitive fusion targeted biopsy predicts prostate cancer detection: a prospective single-center study.Abdominal radiology (New York) · 2025Article
- Development and validation of nomogram models for predicting immune-related adverse events in recurrent and metastatic nasopharyngeal carcinoma patients treated with PD-L1 inhibitors.Frontiers in oncology · 2025Article
- Liver metastases in thyroid cancer: epidemiology, risk stratification and survival outcomes in the immunotherapy era.Frontiers in immunology · 2025Article
- Multimodal ultrasonographic and clinicopathological model for predicting high-volume lymph node metastasis in cN0 papillary thyroid carcinoma.Frontiers in endocrinology · 2025Article
- Radiomics and deep learning for large volume lymph node metastasis in papillary thyroid carcinoma.Gland surgery · 2024Article
- Development and validation of a nomogram for preoperative prediction of ipsilateral cervical central lymph node metastasis in papillary thyroid cancer: a population-based study.Gland surgery · 2024Article
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7 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Objective: We aimed to identify the clinical factors associated with lymph node metastasis (LNM) based on ultrasound characteristics and clinical data, and develop a nomogram for personalized clinical decision-making. Methods: A retrospective analysis was performed on 252 patients with papillary thyroid carcinoma (PTC). The patient's information was subjected to univariate and multivariate logistic regression analyses to identify risk factors. A nomogram to predict LNM was established combining the risk factors. The performance of the nomogram was evaluated using receiver operating characteristic (ROC) curve, calibration curve, cross-validation, decision curve analysis (DCA), and clinical impact curve. Results: There are significant differences between LNM and non-LNM groups in terms of age, sex, tumor size, hypoechoic halo around the nodule, thyroid capsule invasion, lymph node microcalcification, lymph node hyperechoic area, peak intensity of contrast (PI), and area under the curve (AUC) of the time intensity curve of contrast ( Conclusion: Age, sex, thyroid capsule invasion, and lymph node microcalcification were identified as significant risk factors for predicting LNM in patients with PTC. The visualized nomogram model may assist clinicians in predicting the likelihood of LNM in patients with PTC prior to surgery.
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