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Cardiovascular Risk/Epidemiology
Validation of Risk Prediction Models for Atherosclerotic Cardiovascular Disease in a Prospective Korean Community-Based Cohort
Jae Hyun Bae, Min Kyong Moon, Sohee Oh, Bo Kyung Koo, Nam Han Cho, Moon-Kyu Lee
Diabetes Metab J. 2020;44(3):458-469.   Published online January 13, 2020
DOI: https://doi.org/10.4093/dmj.2019.0061
  • 7,317 View
  • 236 Download
  • 16 Web of Science
  • 16 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

To investigate the performance of the 2013 American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) in a large, prospective, community-based cohort in Korea and to compare it with that of the Framingham Global Cardiovascular Disease Risk Score (FRS-CVD) and the Korean Risk Prediction Model (KRPM).

Methods

In the Korean Genome and Epidemiology Study (KOGES)-Ansan and Ansung study, we evaluated calibration and discrimination of the PCE for non-Hispanic whites (PCE-WH) and for African Americans (PCE-AA) and compared their predictive abilities with the FRS-CVD and the KRPM.

Results

The present study included 7,932 individuals (3,778 men and 4,154 women). The PCE-WH and PCE-AA moderately overestimated the risk of atherosclerotic cardiovascular disease (ASCVD) for men (6% and 13%, respectively) but underestimated the risk for women (−49% and −25%, respectively). The FRS-CVD overestimated ASCVD risk for men (91%) but provided a good risk prediction for women (3%). The KRPM underestimated ASCVD risk for men (−31%) and women (−31%). All the risk prediction models showed good discrimination in both men (C-statistic 0.730 to 0.735) and women (C-statistic 0.726 to 0.732). Recalibration of the PCE using data from the KOGES-Ansan and Ansung study substantially improved the predictive accuracy in men.

Conclusion

In the KOGES-Ansan and Ansung study, the PCE overestimated ASCVD risk for men and underestimated the risk for women. The PCE-WH and the FRS-CVD provided an accurate prediction of ASCVD in men and women, respectively.

Citations

Citations to this article as recorded by  
  • Risk Factors for Infertility in Korean Women
    Juyeon Lee, Chang-Woo Choo, Kyoung Yong Moon, Sang Woo Lyu, Hoon Kim, Joong Yeup Lee, Jung Ryeol Lee, Byung Chul Jee, Kyungjoo Hwang, Seok Hyun Kim, Sue K. Park
    Journal of Korean Medical Science.2024;[Epub]     CrossRef
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    Frontiers in Genetics.2024;[Epub]     CrossRef
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    Journal of Clinical Medicine.2024; 13(9): 2563.     CrossRef
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    Kayoung Lee
    International Journal of Behavioral Medicine.2023; 30(1): 89.     CrossRef
  • Validation of the general Framingham Risk Score (FRS), SCORE2, revised PCE and WHO CVD risk scores in an Asian population
    Sazzli Shahlan Kasim, Nurulain Ibrahim, Sorayya Malek, Khairul Shafiq Ibrahim, Muhammad Firdaus Aziz, Cheen Song, Yook Chin Chia, Anis Safura Ramli, Kazuaki Negishi, Nafiza Mat Nasir
    The Lancet Regional Health - Western Pacific.2023; 35: 100742.     CrossRef
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    F. O. Ushanova, T. Yu. Demidova, T. N. Korotkova
    FOCUS. Endocrinology.2023; 4(2): 19.     CrossRef
  • Prediction of the 10-year risk of atherosclerotic cardiovascular disease in the Korean population
    Sangwoo Park, Yong-Giun Kim, Soe Hee Ann, Young-Rak Cho, Shin-Jae Kim, Seungbong Han, Gyung-Min Park
    Epidemiology and Health.2023; : e2023052.     CrossRef
  • Triglyceride-Glucose Index Predicts Future Atherosclerotic Cardiovascular Diseases: A 16-Year Follow-up in a Prospective, Community-Dwelling Cohort Study
    Joon Ho Moon, Yongkang Kim, Tae Jung Oh, Jae Hoon Moon, Soo Heon Kwak, Kyong Soo Park, Hak Chul Jang, Sung Hee Choi, Nam H. Cho
    Endocrinology and Metabolism.2023; 38(4): 406.     CrossRef
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    Mahin Nomali, Davood Khalili, Mehdi Yaseri, Mohammad Ali Mansournia, Aryan Ayati, Hossein Navid, Saharnaz Nedjat, Hean Teik Ong
    PLOS ONE.2023; 18(11): e0292396.     CrossRef
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    Kyung-Soo Kim, Sangmo Hong, Kyungdo Han, Cheol-Young Park
    Journal of Lipid and Atherosclerosis.2022; 11(1): 73.     CrossRef
  • Mediation of Grip Strength on the Association Between Self-Rated Health and Estimated Cardiovascular Disease Risk
    Kayoung Lee
    Metabolic Syndrome and Related Disorders.2022; 20(6): 344.     CrossRef
  • Implications of the heterogeneity between guideline recommendations for the use of low dose aspirin in primary prevention of cardiovascular disease
    Xiao-Ying Li, Li Li, Sang-Hoon Na, Francesca Santilli, Zhongwei Shi, Michael Blaha
    American Journal of Preventive Cardiology.2022; 11: 100363.     CrossRef
  • The Risk of Cardiovascular Disease According to Chewing Status Could Be Modulated by Healthy Diet in Middle-Aged Koreans
    Hyejin Chun, Jongchul Oh, Miae Doo
    Nutrients.2022; 14(18): 3849.     CrossRef
  • Management of Cardiovascular Risk in Perimenopausal Women with Diabetes
    Catherine Kim
    Diabetes & Metabolism Journal.2021; 45(4): 492.     CrossRef
  • Comparative performance of the two pooled cohort equations for predicting atherosclerotic cardiovascular disease
    Alessandra M. Campos-Staffico, David Cordwin, Venkatesh L. Murthy, Michael P. Dorsch, Jasmine A. Luzum
    Atherosclerosis.2021; 334: 23.     CrossRef
  • Usefulness of Relative Handgrip Strength as a Simple Indicator of Cardiovascular Risk in Middle-Aged Koreans
    Won Bin Kim, Jun-Bean Park, Yong-Jin Kim
    The American Journal of the Medical Sciences.2021; 362(5): 486.     CrossRef
Clinical Diabetes and Therapeutics
Hospital-Based Korean Diabetes Prevention Study: A Prospective, Multi-Center, Randomized, Open-Label Controlled Study
Sang Youl Rhee, Suk Chon, Kyu Jeung Ahn, Jeong-Taek Woo
Diabetes Metab J. 2019;43(1):49-58.   Published online November 2, 2018
DOI: https://doi.org/10.4093/dmj.2018.0033
  • 5,689 View
  • 138 Download
  • 11 Web of Science
  • 13 Crossref
AbstractAbstract PDFPubReader   
Background

The prevalence of diabetes mellitus (DM) continues to increase, and the disease burden is the highest of any medical condition in Korea. However, large-scale clinical studies have not yet conducted to establish the basis for diabetes prevention in Korea.

Methods

The hospital-based Korean Diabetes Prevention Study (H-KDPS) is a prospective, multi-center, randomized, open-label controlled study conducted at university hospitals for the purpose of gathering data to help in efforts to prevent type 2 DM. Ten university hospitals are participating, and 744 subjects will be recruited. The subjects are randomly assigned to the standard care group, lifestyle modification group, or metformin group, and their clinical course will be observed for 36 months.

Results

All intervention methodologies were developed, validated, and approved by Korean Diabetes Association (KDA) multi-disciplinary team members. The standard control group will engage in individual education based on the current KDA guidelines, and the lifestyle modification group will participate in a professionally guided healthcare intervention aiming for ≥5% weight loss. The metformin group will begin dosing at 250 mg/day, increasing to a maximum of 1,000 mg/day. The primary endpoint of this study is the cumulative incidence of DM during the 3 years after randomization.

Conclusion

The H-KDPS study is the first large-scale clinical study to establish evidence-based interventions for the prevention of type 2 DM in Koreans. The evidence gathered by this study will be useful for enhancing the health of Koreans and improving the stability of the Korean healthcare system (Trial registration: CRIS KCT0002260, NCT02981121).

Citations

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    Joon Ha, Stephanie T. Chung, Max Springer, Joon Young Kim, Phil Chen, Aaryan Chhabra, Melanie G. Cree, Cecilia Diniz Behn, Anne E. Sumner, Silva A. Arslanian, Arthur S. Sherman
    American Journal of Physiology-Endocrinology and Metabolism.2024; 326(4): E454.     CrossRef
  • Development and Adaptability of Smartphone-based Dietary Coaching Program for Patients Undergoing Diabetes and Prediabetes with Continuous Glucose Monitoring Device
    Myoung Soo Kim, Jung Mi Ryu, Minkyeong Kang, Jiwon Park, Yeh Chan Ahn, Yang Seok Kim
    Journal of Health Informatics and Statistics.2023; 48(1): 36.     CrossRef
  • Improving Machine Learning Diabetes Prediction Models for the Utmost Clinical Effectiveness
    Juyoung Shin, Joonyub Lee, Taehoon Ko, Kanghyuck Lee, Yera Choi, Hun-Sung Kim
    Journal of Personalized Medicine.2022; 12(11): 1899.     CrossRef
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    Jin-Hee Lee, Suk Chon, Seon-Ah Cha, Sun-Young Lim, Kook-Rye Kim, Jae-Seung Yun, Sang Youl Rhee, Kun-Ho Yoon, Yu-Bae Ahn, Jeong-Taek Woo, Seung-Hyun Ko
    The Korean Journal of Internal Medicine.2021; 36(2): 382.     CrossRef
  • Development and Validation of a Deep Learning Based Diabetes Prediction System Using a Nationwide Population-Based Cohort
    Sang Youl Rhee, Ji Min Sung, Sunhee Kim, In-Jeong Cho, Sang-Eun Lee, Hyuk-Jae Chang
    Diabetes & Metabolism Journal.2021; 45(4): 515.     CrossRef
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    Kyu Yeon Hur, Min Kyong Moon, Jong Suk Park, Soo-Kyung Kim, Seung-Hwan Lee, Jae-Seung Yun, Jong Ha Baek, Junghyun Noh, Byung-Wan Lee, Tae Jung Oh, Suk Chon, Ye Seul Yang, Jang Won Son, Jong Han Choi, Kee Ho Song, Nam Hoon Kim, Sang Yong Kim, Jin Wha Kim,
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    Jin-Hee Lee, Sun-Young Lim, Seon-Ah Cha, Chan-Jung Han, Ah Reum Jung, Kook-Rye Kim, Kun-Ho Yoon, Seung-Hyun Ko
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