ArticleBMC endocrine disorders2018
A predictive model of thyroid malignancy using clinical, biochemical and sonographic parameters for patients in a multi-center setting.
Article in BMC endocrine disorders, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
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Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Sociodemographic and clinical predictors of malignancy in thyroid nodules: a systematic review and meta-analysis.Frontiers in endocrinology · 2026Pooled it
- The associations between thyroid-related hormones and the risk of thyroid cancer: An overall and dose-response meta-analysis.Frontiers in endocrinology · 2022Pooled it
- Correlation between ultrasonographic and cytologic features of thyroid nodules: a single-center cross-sectional study.Journal of medicine and life · 2024Article
- Application of ultrasound elastography and radiomic for predicting central cervical lymph node metastasis in papillary thyroid microcarcinoma.Frontiers in oncology · 2024Article
- Comparative analysis of the image quality and diagnostic performance of the zooming technique with diffusion-weighted imaging using different b-values for thyroid papillary carcinomas and benign nodules.Frontiers in oncology · 2024Article
- Diagnostic performance of the EU TI-RADS and ACR TI-RADS scoring systems in predicting thyroid malignancy.Endocrinology, diabetes & metabolism · 2023Article
- Prophylactic central lymph node dissection performed selectively with cN0 papillary thyroid carcinoma according to a risk-scoring model.Gland surgery · 2022Article
- Contrast-Enhanced Ultrasound in the Differential Diagnosis and Risk Stratification of ACR TI-RADS Category 4 and 5 Thyroid Nodules With Non-Hypovascular.Frontiers in oncology · 2021Article
- Factors Associated with Malignancy in Patients with Maximal Thyroid Nodules ≥2 Cm.Cancer management and research · 2021Article
- Using ultrasound features and radiomics analysis to predict lymph node metastasis in patients with thyroid cancer.BMC surgery · 2020Article
- A Predictive Model to Distinguish Papillary Thyroid Carcinomas from Benign Thyroid Nodules Using Ultrasonographic Features: A Single-Center, Retrospective Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2019Article
- A comparative analysis of diffusion-weighted imaging and ultrasound in thyroid nodules.BMC medical imaging · 2019Article
- Positive thyroid antibodies and risk of thyroid cancer: A systematic review and meta-analysis.Molecular and clinical oncology · 2019Article
- Mathematical models applied to thyroid cancer.Biophysical reviews · 2019Review
- Diagnostic efficacy of multiple MRI parameters in differentiating benign vs. malignant thyroid nodules.BMC medical imaging · 2018Article
- Taller-than-wide Thyroid Nodules With Microcalcifications Are at High Risk of Malignancy.In vivo (Athens, Greece)Article
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Abstract
backgroundThyroid nodules are highly prevalent, but a robust, feasible method for malignancy differentiation has not yet been well documented. This study aimed to establish a practical model for thyroid nodule discrimination.
methodsRecords for 2984 patients who underwent thyroidectomy were analyzed. Clinical, laboratory, and US variables were assessed retrospectively. Multivariate logistic regression analysis was performed and a mathematical model was established for malignancy prediction.
resultsThe results showed that the malignant group was younger and had smaller nodules than the benign group (43.5 ± 11.6 vs. 48.5 ± 11.5 y, p < 0.001; 1.96 ± 1.16 vs. 2.75 ± 1.70 cm, p < 0.001, respectively). The serum thyrotropin (TSH) level (median = 1.63 mIU/L, IQR (0.89-2.66) vs. 1.19 (0.59-2.10), p < 0.001) was higher in the malignant group than in the benign group. Patients with malignancies tested positive for anti-thyroglobulin antibody (TGAb) and anti-thyroid peroxidase antibody (TPOAb) more frequently than those with benign nodules (TGAb, 30.3% vs. 15.0%, p < 0.001; TPOAb, 25.6% vs. 18.0%, p = 0.028). The prevalence of ultrasound (US) features (irregular shape, ill-defined margin, solid structure, hypoechogenicity, microcalcifications, macrocalcifications and central intranodular flow) was significantly higher in the malignant group. Multivariate logistic regression analysis confirmed that age (OR = 0.963, 95% CI = 0.934-0.993, p = 0.017), TGAb (OR = 4.435, 95% CI = 1.902-10.345, p = 0.001), hypoechogenicity (OR = 2.830, 95% CI = 1.113-7.195, p = 0.029), microcalcifications (OR = 4.624, 95% CI = 2.008-10.646, p < 0.001), and central intranodular flow (OR = 2.155, 95% CI = 1.011-4.594, p < 0.05) were independent predictors of thyroid malignancy. A predictive model including four variables (age, TGAb, hypoechogenicity and microcalcification) showed an optimal discriminatory accuracy (area under the curve, AUC) of 0.808 (95% CI = 0.761-0.855). The best cut-off value for prediction was 0.52, achieving sensitivity and specificity of 84.6% and 76.3%, respectively.
conclusionA predictive model of malignancy that combines clinical, laboratory and sonographic characteristics would aid clinicians in avoiding unnecessary procedures and making better clinical decisions.
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