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Updated: Feb 9, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Novel nomogram for screening the risk of developing diabetes in a Korean population
Seung Min Chung1, Jae Cheol Park2, Jun Sung Moon1
1Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeungnam College of Medicine, Daegu, Republic of Korea.
Aims:
We propose a novel nomogram, which graphically expresses the numerical relationship between type 2 diabetes (T2D) and disease-related risk factors.
Methods:
Data of 8999 patients from the 2013-2014 Korean National Health and Nutrition Examination Survey were analyzed. Multiple logistic regression analysis was performed to assess risk factors for T2D and a nomogram was constructed based on screened risk factors. A receiver operating curve (ROC) and calibration plot were created to evaluate the accuracy of the nomogram.
Results:
The risk factor with the greatest impact on the prevalence of T2D was age over 60 years (95% CI 5.97-15.00, OR = 9.46), followed by presence of dyslipidemia and cardiovascular disease (95% CI 5.90-13.68, OR = 8.98), family history of T2D (95% CI 2.33-3.64, OR = 2.92), abdominal obesity (OR = 1.76), hypertension (OR = 1.75), male gender (OR = 1.55), current-smoking status (OR = 1.52), lower education level (OR = 1.42), and lower income (OR = 1.30). The area under the ROC curve (AUC) showed statistically significant determination (AUC = 0.83). The equation of the calibration plot was drawn along the ideal line; coefficient of determination was 0.864.
Conclusion:
Our proposed nomogram could accurately predict the risk of T2D from nationwide data. The novel nomogram can be a useful tool for screening patients with T2D risk in a Korean population.
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