ArticleHeliyon2024
Enhancing clinical decision-making: A novel nomogram for stratifying cancer-specific survival in middle-aged individuals with follicular thyroid carcinoma utilizing SEER data.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Novel a new prognostic model of thyroid carcinoma based on macrophage and cuproptosis-related lncRNA.Cancer cell international · 2026Article
- TC check: a web app for thyroid cancer recurrence prediction using explainable machine learning.Journal of cancer research and clinical oncology · 2025Article
- Nomogram Model for Prognosis of Distant Metastatic DTC Based on Inflammatory and Clinicopathological Factors.Journal of the Endocrine Society · 2025Article
- Development and validation of a nomogram for predicting sleep disturbance in pregnant and postpartum women: A pilot study.Heliyon · 2024Article
- Nomogram for predicting early death in elderly patients with laryngeal squamous cell carcinoma: A population-based SEER study.PloS one · 2024Article
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Authors and funding
10 authors.
Funding
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Abstract
Background: Thyroid cancer (TC) is the most common malignant tumor in the endocrine system, is also one of the head and neck tumor. Follicular Thyroid Carcinoma (FTC) plays an important role in the pathological classification of thyroid cancer. This study aimed to develop an innovative predictive tool, a nomogram, for predicting cancer specific survival (CSS) in middle-aged FTC patients. Methods: We collected patient data from the Surveillance, Epidemiology, and End Results (SEER) database. The data from patients between 2004 and 2015 were used as the training set, and the data from patients between 2016 and 2018 were used as the validation set. To identify independent risk factors affecting patient survival, univariate and multivariate Cox regression analyses were performed. Based on this, we developed a nomogram model aimed at predicting CSS in middle-aged patients with FTC. The consistency index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and the calibration curve were used to evaluate the accuracy and confidence of the model. Results: A total of 2470 patients were enrolled in this study, in which patients from 2004 to 2015 were randomly assigned to the training cohort (N = 1437) and validation cohort (N = 598), and patients from 2016 to 2018 were assigned to the external validation cohort (N = 435) in terms of time. Univariate and multivariate Cox regression analysis showed that marriage, histological grade and TNM stage were independent risk factors for survival. The C-index for the training cohort was 0.866 (95 % CI: 0.805-0.927), for the validation cohort it was 0.944 (95 % CI: 0.903-0.985), and for the external validation cohort, it reached 0.999 (95 % CI: 0.997-1.001). Calibration curves and AUC suggest that the model has good accuracy. Conclusions: We developed an innovative nomogram to predict CSS in middle-aged patients with FTC. Our model after a rigorous internal validation and external validation process, based on the time proved that the high level of accuracy and reliability. This tool helps healthcare professionals and patients make informed clinical decisions.
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