Seung Min Chung1, Jae Cheol Park2, Jun Sung Moon3, Jea Young Lee4. 1. Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeungnam College of Medicine, Daegu, Republic of Korea. 2. Department of Statistics, Yeungnam University, Gyeongbuk, Republic of Korea. 3. Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeungnam College of Medicine, Daegu, Republic of Korea. Electronic address: mjs7912@yu.ac.kr. 4. Department of Statistics, Yeungnam University, Gyeongbuk, Republic of Korea. Electronic address: jlee@yu.ac.kr.
Abstract
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.
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.