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. 2025 Jan-Dec:32:10732748251336412.
doi: 10.1177/10732748251336412. Epub 2025 Apr 23.

Identification of Risk Factors for Cause-specific Mortality in Advanced Papillary Thyroid Cancer and Construction of a Competing Risk Model: A SEER-Based Study

Yunyi Yang  1 , Xiaoli He  1 , Xiaoxiao Qu  1 , Shufa Tan  2 , Xinyi Fu  1 , Jiawen You  1 , Weijin Huang  1 , Jiayuan Cai  1 , Yanming He  1 , Hongjie Yang  1
Affiliations

Identification of Risk Factors for Cause-specific Mortality in Advanced Papillary Thyroid Cancer and Construction of a Competing Risk Model: A SEER-Based Study

Yunyi Yang et al. Cancer Control. 2025 Jan-Dec.

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.

Keywords: SEER; advanced PTC; cause-specific mortality; competing risk model.

Plain language summary

Papillary thyroid cancer (PTC) is the most common type of thyroid cancer, and it usually has a good outlook. However, for patients with advanced stages of the disease, the risks of complications and death are higher. This study aimed to identify the factors that contribute to death caused specifically by advanced PTC and to develop a tool to predict these risks. We analyzed data from over 11 000 patients with advanced PTC collected between 2010 and 2015 from a large database in the United States. By using advanced statistical methods, we identified key factors that affect the risk of death from advanced PTC, such as age, tumor size, cancer stage, and whether the patient underwent surgery or chemotherapy. We used this information to create a prediction tool called a “nomogram,” which can estimate the chances of survival for three, five, and eight years after diagnosis. The tool was tested and found to be highly accurate in predicting outcomes, making it a valuable resource for doctors. It helps them assess risks and make more personalized treatment decisions for patients with advanced PTC. For example, doctors can use the nomogram to identify patients who may benefit from surgery or other targeted treatments.

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Conflict of interest statement

Declarations Conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Nomogram for Forecasting 3-, 5-, and 8-Year Disease-specific Survival in Patients with Advanced PTC in the Training Cohort.
Figure 2.
Figure 2.
ROC Curve of the Nomogram for Cause-specific Survival in Advanced PTC. (A) Training Cohort; (B) Validation Cohort.
Figure 3.
Figure 3.
Calibration Curve for Forecasting Survival Probability in Patients with Advanced PTC. (A) Training Cohort; (B) Validation Cohort.
See this image and copyright information in PMC

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