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Updated: May 15, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Population-based study evaluating and predicting the probability of death resulting from thyroid cancer and other
Limin Yang1, Weidong Shen, Naoko Sakamoto
1National Research Institute for Child Health and Development, Tokyo, Japan.
Purpose:
The purpose of this study was to evaluate the probability of death for patients with thyroid cancer and construct a comprehensive nomogram based on a competing risks model to predict cumulative incidence of death resulting from thyroid cancer, other cancers, and non-cancer-related causes.
Patients And Methods:
Patients diagnosed with thyroid cancer between 1988 and 2003 were selected for the study from the Surveillance, Epidemiology, and End Results program. We estimated probabilities of death resulting from thyroid cancer, other cancers, and noncancer causes and analyzed associations of patient and tumor characteristics with probability of death. A nomogram for predicting probability of death was built using a proportional subdistribution hazard competing risks model.
Results:
The entire cohort comprised 29,225 patients with malignant thyroid cancer. Median duration of follow-up until censoring or death was 85 months (range, 0 to 239 months). Five-year probabilities of death resulting from thyroid cancer, other cancer, and noncancer causes were 1.9%, 0.8%, and 1.7%, respectively. Increasing age and tumor size, male sex, poorly differentiated carcinoma, lymph node involvement, and regional and metastatic disease were associated with increased cumulative incidence of death resulting from thyroid cancer.
Conclusion:
A nomogram based on a competing risks model was developed for predicting the probability of death for patients with thyroid cancer. Performance of the model was excellent. This nomogram may be useful for patients and clinicians when predictions are needed.
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