Keum Ji Jung1, Yangsoo Jang2, Dong Joo Oh3, Byung-Hee Oh4, Sang Hoon Lee5, Seong-Wook Park6, Ki-Bae Seung7, Hong-Kyu Kim8, Young Duk Yun9, Sung Hee Choi10, Jidong Sung11, Tae-Yong Lee12, Sung Hi Kim13, Sang Baek Koh14, Moon Chan Kim15, Hyeon Chang Kim16, Heejin Kimm17, Chungmo Nam16, Sungha Park2, Sun Ha Jee18. 1. Department of Public Health, Graduate School, Yonsei University, Seoul, Republic of Korea. 2. Severance Cardiovascular Hospital, Yonsei University Health System, Seoul, Republic of Korea. 3. Cardiovascular Center, Korea University Guro Hospital, Seoul, Republic of Korea. 4. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea. 5. Division of Cardiology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 6. Division of Cardiology, Department of Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea. 7. Department of Internal Medicine, The Catholic University of Korea, School of Medicine, Seoul, Republic of Korea. 8. The Health Screening and Promotion Center, Asan Medical Center, Seoul, Republic of Korea. 9. Health Insurance Policy Research Institute, National Health Insurance Service, Seoul, Republic of Korea. 10. Seoul National University College of Medicine, Bundang Hospital, Sungnam, Republic of Korea. 11. Division of Cardiology, Department of Internal Medicine, Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 12. Department of Preventive Medicine & Public Health, College of Medicine, Chungnam National University, Daejeon, Republic of Korea. 13. Department of Family Medicine, Daegu Catholic Hospital, Daegu, Republic of Korea. 14. Institute of Genomic Cohort, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea. 15. Department of Family Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea. 16. Department of Preventive Medicine and Public Health, Yonsei University College of Medicine, Seoul, Republic of Korea. 17. Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea. 18. Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA. Electronic address: jsunha@yuhs.ac.
Abstract
BACKGROUND AND AIMS: To evaluate the performance of the American College of Cardiology/American Heart Association (ACC/AHA) 2013 Pooled Cohort Equations in the Korean Heart Study (KHS) population and to develop a Korean Risk Prediction Model (KRPM) for atherosclerotic cardiovascular disease (ASCVD) events. METHODS: The KHS cohort included 200,010 Korean adults aged 40-79 years who were free from ASCVD at baseline. Discrimination, calibration, and recalibration of the ACC/AHA Equations in predicting 10-year ASCVD risk in the KHS cohort were evaluated. The KRPM was derived using Cox model coefficients, mean risk factor values, and mean incidences from the KHS cohort. RESULTS: In the discriminatory analysis, the ACC/AHA Equations' White and African-American (AA) models moderately distinguished cases from non-cases, and were similar to the KRPM: For men, the area under the receiver operating characteristic curve (AUROCs) were 0.727 (White model), 0.725 (AA model), and 0.741 (KRPM); for women, the corresponding AUROCs were 0.738, 0.739, and 0.745. Absolute 10-year ASCVD risk for men in the KHS cohort was overestimated by 56.5% (White model) and 74.1% (AA model), while the risk for women was underestimated by 27.9% (White model) and overestimated by 29.1% (AA model). Recalibration of the ACC/AHA Equations did not affect discriminatory ability but improved calibration substantially, especially in men in the White model. Of the three ASCVD risk prediction models, the KRPM showed best calibration. CONCLUSIONS: The ACC/AHA Equations should not be directly applied for ASCVD risk prediction in a Korean population. The KRPM showed best predictive ability for ASCVD risk.
BACKGROUND AND AIMS: To evaluate the performance of the American College of Cardiology/American Heart Association (ACC/AHA) 2013 Pooled Cohort Equations in the Korean Heart Study (KHS) population and to develop a Korean Risk Prediction Model (KRPM) for atherosclerotic cardiovascular disease (ASCVD) events. METHODS: The KHS cohort included 200,010 Korean adults aged 40-79 years who were free from ASCVD at baseline. Discrimination, calibration, and recalibration of the ACC/AHA Equations in predicting 10-year ASCVD risk in the KHS cohort were evaluated. The KRPM was derived using Cox model coefficients, mean risk factor values, and mean incidences from the KHS cohort. RESULTS: In the discriminatory analysis, the ACC/AHA Equations' White and African-American (AA) models moderately distinguished cases from non-cases, and were similar to the KRPM: For men, the area under the receiver operating characteristic curve (AUROCs) were 0.727 (White model), 0.725 (AA model), and 0.741 (KRPM); for women, the corresponding AUROCs were 0.738, 0.739, and 0.745. Absolute 10-year ASCVD risk for men in the KHS cohort was overestimated by 56.5% (White model) and 74.1% (AA model), while the risk for women was underestimated by 27.9% (White model) and overestimated by 29.1% (AA model). Recalibration of the ACC/AHA Equations did not affect discriminatory ability but improved calibration substantially, especially in men in the White model. Of the three ASCVD risk prediction models, the KRPM showed best calibration. CONCLUSIONS: The ACC/AHA Equations should not be directly applied for ASCVD risk prediction in a Korean population. The KRPM showed best predictive ability for ASCVD risk.
Authors: Dennis T Ko; Atul Sivaswamy; Maneesh Sud; Gynter Kotrri; Paymon Azizi; Maria Koh; Peter C Austin; Douglas S Lee; Idan Roifman; George Thanassoulis; Karen Tu; Jacob A Udell; Harindra C Wijeysundera; Todd J Anderson Journal: CMAJ Date: 2020-04-27 Impact factor: 8.262
Authors: Donna K Arnett; Roger S Blumenthal; Michelle A Albert; Andrew B Buroker; Zachary D Goldberger; Ellen J Hahn; Cheryl Dennison Himmelfarb; Amit Khera; Donald Lloyd-Jones; J William McEvoy; Erin D Michos; Michael D Miedema; Daniel Muñoz; Sidney C Smith; Salim S Virani; Kim A Williams; Joseph Yeboah; Boback Ziaeian Journal: J Am Coll Cardiol Date: 2019-03-17 Impact factor: 24.094
Authors: Donna K Arnett; Roger S Blumenthal; Michelle A Albert; Andrew B Buroker; Zachary D Goldberger; Ellen J Hahn; Cheryl Dennison Himmelfarb; Amit Khera; Donald Lloyd-Jones; J William McEvoy; Erin D Michos; Michael D Miedema; Daniel Muñoz; Sidney C Smith; Salim S Virani; Kim A Williams; Joseph Yeboah; Boback Ziaeian Journal: Circulation Date: 2019-03-17 Impact factor: 29.690
Authors: Donald E Casey; Randal J Thomas; Vivek Bhalla; Yvonne Commodore-Mensah; Paul A Heidenreich; Dhaval Kolte; Paul Muntner; Sidney C Smith; John A Spertus; John R Windle; Gregory D Wozniak; Boback Ziaeian Journal: J Am Coll Cardiol Date: 2019-11-26 Impact factor: 24.094
Authors: Donald E Casey; Randal J Thomas; Vivek Bhalla; Yvonne Commodore-Mensah; Paul A Heidenreich; Dhaval Kolte; Paul Muntner; Sidney C Smith; John A Spertus; John R Windle; Gregory D Wozniak; Boback Ziaeian Journal: Circ Cardiovasc Qual Outcomes Date: 2019-11-12