Prediction of Coronary Heart Disease Risk in Korean Patients with Diabetes Mellitus.
10.12997/jla.2018.7.2.110
- Author:
Bo Kyung KOO
1
;
Sohee OH
;
Yoon Ji KIM
;
Min Kyong MOON
Author Information
1. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea. mkmoon@snu.ac.kr
- Publication Type:Original Article
- Keywords:
Coronary heart disease;
Diabetes mellitus;
Korea
- MeSH:
Cohort Studies;
Coronary Disease*;
Diabetes Mellitus*;
Female;
Humans;
Korea;
Male;
Proportional Hazards Models;
Prospective Studies;
ROC Curve
- From:Journal of Lipid and Atherosclerosis
2018;7(2):110-121
- CountryRepublic of Korea
- Language:English
-
Abstract:
OBJECTIVE: We developed a new equation for predicting coronary heart disease (CHD) risk in Korean diabetic patients using a hospital-based cohort and compared it with a UK Prospective Diabetes Study (UKPDS) risk engine. METHODS: By considering patients with type 2 diabetes aged ≥30 years visiting the diabetic center in Boramae hospital in 2006, we developed a multivariable equation for predicting CHD events using the Cox proportional hazard model. Those with CHD were excluded. The predictability of CHD events over 6 years was evaluated using area under the receiver operating characteristic (AUROC) curves, which were compared using the DeLong test. RESULTS: A total of 732 participants (304 males and 428 females; mean age, 60±10 years; mean duration of diabetes, 10±7 years) were followed up for 76 months (range, 1–99 month). During the study period, 48 patients (6.6%) experienced CHD events. The AUROC of the proposed equation for predicting 6-year CHD events was 0.721 (95% confidence interval [CI], 0.641–0.800), which is significantly larger than that of the UKPDS risk engine (0.578; 95% CI, 0.482–0.675; p from DeLong test=0.001). Among the subjects with <5% of risk based on the proposed equation, 30.6% (121 out of 396) were classified as ≥10% of risk based on the UKPDS risk engine, and their event rate was only 3.3% over 6 years. CONCLUSION: The UKPDS risk engine overestimated CHD risk in type 2 diabetic patients in this cohort, and the proposed equation has superior predictability for CHD risk compared to the UKPDS risk engine.
