ArticleMedical science monitor : international medical journal of experimental and clinical research2019
Nomograms Predict Survival in Patients with Anaplastic Thyroid Carcinoma.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Expression of pY397-FAK and Its miR Regulators Drive Dedifferentiation in the Thyroid Neoplasia Spectrum.Cells · 2023Article
- Comparison of the cox regression to machine learning in predicting the survival of anaplastic thyroid carcinoma.BMC endocrine disorders · 2023Article
- Prediction of lung metastases in thyroid cancer using machine learning based on SEER database.Cancer medicine · 2022Article
- Establishment of a Risk Prediction Model for Pulmonary Infection in Patients with Advanced Cancer.Applied bionics and biomechanics · 2022Article
- Development of Nomograms for Predicting Lymph Node Metastasis and Distant Metastasis in Newly Diagnosed T1-2 Non-Small Cell Lung Cancer: A Population-Based Analysis.Frontiers in oncology · 2021Article
- Review
- The Role of Exosomes in Thyroid Cancer and Their Potential Clinical Application.Frontiers in oncology · 2020Review
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4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Anaplastic thyroid carcinoma (ATC) is a very rare, highly lethal malignant cancer. Our aim in this study was to develop nomograms that predict survival in ATC patients. MATERIAL AND METHODS ATC incidence and mortality were assessed via joinpoint regression analysis of 567 ATC patients selected from the Surveillance, Epidemiology, and End Results 18 Registries Research database. Predictive models were established via univariate and multivariate Cox regression analysis of potential risk factors and used to produce nomograms. Performance of the nomograms in terms of discrimination ability and calibration was evaluated by determining the concordance index (C-index) and by generating calibration plots, respectively. RESULTS The incidence and mortality rates for ATC increased from 2000 to 2015 according to the collected data (p<0.05). Two nomograms were constructed based on 2 predictive models: nomogram 1 considered age, tumor size, and metastasis (all before surgery), and nomogram 2 considered age, tumor size, metastasis, surgery, and extrathyroidal extension (all after surgery). Both nomogram 1 (C-index, 0.6803; 95% confidence interval, 0.6517-0.7089) and nomogram 2 (C-index, 0.7064; 95% confidence interval, 0.6783-0.7345) had good discrimination ability. The validated C-index values were 0.6783 and 0.7029 for nomogram 1 and 2, respectively. The observed values were in agreement with the calibration curves. CONCLUSIONS Nomogram 1 can assist in preoperative prediction of survival time in ATC patients, whereas nomogram 2 can provide additional outcome-related information.
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