ArticleBMC cancer2020
Novel nomogram to predict risk of bone metastasis in newly diagnosed thyroid carcinoma: a population-based study.
Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 20 citations in OpenAlex.
- The Lymphatic-Bone Axis in Cancer Metastasis.Cancers · 2026Review
- Prediction of Patients With Anaplastic Thyroid Carcinoma With Bone Metastasis: A Population-Based Study.International journal of endocrinology · 2025Article
- Development and validation of an interpretable machine learning model for predicting the risk of distant metastasis in papillary thyroid cancer: a multicenter study.EClinicalMedicine · 2024Article
- Baseline and interimFrontiers in oncology · 2024Article
- Development and validation of a lung metastases-predicting nomogram for intermediate- to high-risk differentiated thyroid carcinoma patients.Future oncology (London, England) · 2024Article
- Osseous Metastases in Thyroid Cancer: Unveiling Risk Factors, Disease Outcomes, and Treatment Impact.Cancers · 2023Article
- A nomogram to predict residual cavity formation after thoracoscopic decortication in chronic tuberculous empyema.Interactive cardiovascular and thoracic surgery · 2022Article
- Establishment and validation of an individualized nomogram to predict distant metastasis in chondrosarcoma patients: a population-based study.Translational cancer research · 2022Article
- Early distinction of lymph node metastasis in patients with soft tissue sarcoma and individualized survival prediction using the online available nomograms: A population-based analysis.Frontiers in oncology · 2022Article
- A Nomogram for Predicting the Risk of Bone Metastasis in Newly Diagnosed Head and Neck Cancer Patients: A Real-World Data Retrospective Cohort Study From SEER Database.Frontiers in genetics · 2022Article
- Nomogram individually predicts the risk for distant metastasis and prognosis value in female differentiated thyroid cancer patients: A SEER-based study.Frontiers in oncology · 2022Article
- Bone metastases in newly diagnosed patients with thyroid cancer: A large population-based cohort study.Frontiers in oncology · 2022Article
- Individualized assessment of risk and overall survival in patients newly diagnosed with primary osseous spinal neoplasms with synchronous distant metastasis.Frontiers in public health · 2022Article
- Two simple-to-use web-based nomograms to predict overall survival and cancer-specific survival in patients with extremity fibrosarcoma.Frontiers in oncology · 2022Article
- Construction and validation of nomogram to predict distant metastasis in osteosarcoma: a retrospective study.Journal of orthopaedic surgery and research · 2021Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of this study was to develop and validate a visual nomogram for predicting the risk of bone metastasis (BM) in newly diagnosed thyroid carcinoma (TC) patients.
methodsThe demographics and clinicopathologic variables of TC patients from 2010 to 2015 in the Surveillance, Epidemiology and End Results (SEER) database were retrospectively reviewed. Chi-squared (χ2) test and logistic regression analysis were performed to identify independent risk factors. Based on that, a predictive nomogram was developed and validated for predicting the risk of BM in TC patients. The C-index was used to compute the predictive performance of the nomogram. Calibration curves and decision curve analysis (DCA) were furthermore used to evaluate the clinical value of the nomogram.
resultsAccording to the inclusion and exclusion criteria, the data of 14,772 patients were used to analyze in our study. After statistical analysis, TC patients with older age, higher T stage, higher N stage, poorly differentiated, follicular thyroid carcinoma (FTC) and black people had a higher risk of BM. We further developed a nomogram with a C-index of 0.925 (95%CI,0.895-0.948) in the training set and 0.842 (95%CI,0.777-0.907) in the validation set. The calibration curves and decision curve analysis (DCA) also demonstrated the reliability and accuracy of the clinical prediction model.
conclusionsThe present study developed a visual nomogram to accurately identify TC patients with high risk of BM, which might help to further provide more individualized clinical decision guidelines.
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