ArticleCancer control : journal of the Moffitt Cancer Center
Identification of Risk Factors for Cause-specific Mortality in Advanced Papillary Thyroid Cancer and Construction of a Competing Risk Model: A SEER-Based Study.
Article in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- ATA 2015-2025 risk stratification transition: prognostic significance of N1b disease in papillary thyroid carcinoma with limited nodal burden.The oncologist · 2026Article
- A dynamic nomogram and risk stratification system for predicting cancer-specific survival in patients with locally advanced differentiated thyroid cancer: a population-based study.Gland surgery · 2025Article
- Elevated suicide risk in thyroid cancer patients: determining mortality rates and identifying predictive factors using Surveillance, Epidemiology, and End Results (SEER) data.Translational cancer research · 2025Article
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10 authors.
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Abstract
IntroductionPapillary thyroid carcinoma (PTC) generally has a favorable prognosis, yet advanced PTC has higher recurrence and mortality risks. This study constructs and validates a competing risk model for cause-specific mortality (CSM) in advanced PTC.MethodsStage III-IV PTC cases (AJCC 7th edition) from the SEER database (2010-2015) were analyzed. Patients were split into training and validation sets (7:3). Univariate and multivariate analyses identified independent CSM predictors, forming the basis of a risk prediction nomogram. Model accuracy was evaluated via the C-index and calibration curve.ResultsA total of 11 913 advanced PTC cases were analyzed. Competing risk model analysis unraveled that age, race, sex, grade, stage, T stage, M stage, surgery, chemotherapy, and tumor size were risk factors for CSM in advanced PTC. The AUC values of the constructed nomogram in predicting 3-, 5-, and 8-year survival were 0.931 (95%CI 0.909-0.953), 0.915 (95%CI 0.897-0.933), and 0.902 (95%CI 0.883-0.92) in the training set, and 0.948 (95%CI 0.916-0.981), 0.93 (95 % CI 0.903-0.957), and 0.917 (95%CI 0.891-0.943) in the validation cohort, respectively. The C-index of the nomogram for advanced PTC was 0.908 and 0.921 in the training and validation cohorts, respectively. The calibration curve unveiled that the predicted estimates by the model were basically congruent with the observed values, suggesting a high degree of calibration.ConclusionThe competing risk model offers a reliable tool for assessing prognosis in advanced PTC, supporting personalized treatment and risk management in clinical practice.
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