ArticleJournal of cancer research and clinical oncology2023
Development and validation of a nomogram for predicting the early death of anaplastic thyroid cancer: a SEER population-based study.
Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Forecasting the risk of early death among patients suffering from lung cancer with brain metastasis after radiotherapy using interpretable machine learning: a study based on the SEER database.Journal of thoracic disease · 2026Article
- Risk factors and predictive nomograms for early mortality in patients with thyroid cancer lung metastasis based on the SEER database and a Chinese population study.Gland surgery · 2025Article
- Machine learning-based prognostic model for patients with anaplastic thyroid carcinoma.Discover oncology · 2025Article
- Evaluation of conditional survival outcomes in patients with redefined anaplastic thyroid carcinoma.Frontiers in endocrinology · 2025Article
- An overview of the contemporary diagnosis and management approaches for anaplastic thyroid carcinoma.World journal of clinical oncology · 2024Article
- Development of a predictive nomogram for intermediate-risk differentiated thyroid cancer patients after fixed 3.7GBq (100mCi) radioiodine remnant ablation.Frontiers in endocrinology · 2024Article
- Knowledge mapping of anaplastic thyroid cancer treatments: a bibliometric analysis (2000-2023).Frontiers in oncology · 2024Article
- Development of a novel dynamic nomogram for predicting overall survival in anaplastic thyroid cancer patients with distant metastasis: a population-based study based on the SEER database.Frontiers in endocrinology · 2024Article
- Update on current diagnosis and management of anaplastic thyroid carcinoma.World journal of clinical oncology · 2023Review
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6 authors.
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Abstract
backgroundAnaplastic thyroid cancer (ATC) is a highly aggressive malignancy with dismal prognosis. This study aimed to identify the independent risk factors and construct a readily-to-use nomogram to predict the probability of early death in ATC patients.
methodPatients diagnosed with ATC between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled in this study for model development and internal validation. Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for early death of ATC. Nomograms for predicting the probability of all-cause early death (ACED) and cancer-specific early death (CSED) of ATC were subsequently developed. The performance of the nomograms was comprehensively evaluated and validated in an internal cohort.
resultA total of 696 ATC patients were included in this study, of which 488 patients in the training cohort and 208 patients in the validation cohort. The univariate and multivariate logistic regression analyses identified five independent factors (tumor size, M stage, surgery, radiotherapy and chemotherapy) in the ACED model and six variables in the CSED (gender, tumor size, M stage, surgery, radiotherapy and chemotherapy) model for the establishment of the nomograms. Calibration curves and receiver operating characteristic (ROC) curves showed satisfactory efficacy and consistency both in the training (ACED: AUC values: 0.814 (0.776-0.852); CSED: 0.778 (0.736-0.820)) and validation sets (ACED: 0.762 (0.696-0.827); CSED: 0.745 (0.678-0.812)). In addition, the decision curve analysis (DCA) demonstrated the favorable potential of the two nomograms in clinical application.
conclusionThe two nomograms assist clinicians to identify risk factors and predict the early death probability among ATC patients, thus guide individualized treatment to improve the prognosis.
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