Risk Prediction of Cardiovascular Disease in the Asia‑Pacific Region: The SCORE2 Asia-Pacific Model

Background and aims: To improve upon the estimation of 10-year cardiovascular disease (CVD) event risk for individuals without prior CVD or diabetes mellitus in the Asia-Pacific region by systematic recalibration of the SCORE2 risk algorithm. Methods: The sex-specific and competing risk-adjusted SCORE2 algorithms were systematically recalibrated to reflect CVD incidence observed in four Asia-Pacific risk regions, defined according to country-level WHO age- and sex-standardised CVD mortality rates. Using the same approach as applied for the original SCORE2 models, recalibration to each risk region was completed using expected CVD incidence and risk factor distributions from each region. Results: Risk region-specific CVD incidence was estimated using CVD mortality and incidence data on 8,405,574 individuals (556,421 CVD events). For external validation, data from 9 560 266 individuals without previous CVD or diabetes were analysed in 13 prospective studies from 12 countries (350,550 incident CVD events). The pooled C-index of the SCORE2 Asia-Pacific algorithms in the external validation datasets was 0.710 (95% CI [0.677–0.744]). Cohort-specific C-indices ranged from 0.605 (95% CI 0.597–0.613) to 0.840 (95% CI 0.771–0.909). Estimated CVD risk varied several-fold across Asia-Pacific risk regions. For example, the estimated 10-year CVD risk for a 50-year-old non-smoker, with a systolic blood pressure of 140 mmHg, total cholesterol of 5.5 mmol/l, and high-density lipoprotein cholesterol of 1.3 mmol/l, ranged from 7% for men in low-risk countries to 14% for men in very-high-risk countries, and from 3% for women in low-risk countries to 13% for women in very-high-risk countries. Conclusion: The SCORE2 Asia-Pacific algorithms have been calibrated to estimate 10-year risk of CVD for apparently healthy people in Asia and Oceania, thereby enhancing the identification of individuals at higher risk of developing CVD across the Asia-Pacific region.

Authors

Institutions

Publication Details

Journal
Journal of Asian Pacific Society of Cardiology
Published
2024-11-29
DOI
https://doi.org/10.15420/japsc.2024.49
Primary Topic
Lipoproteins and Cardiovascular Health
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Risk Prediction of Cardiovascular Disease in the Asia‑Pacific Region: The SCORE2 Asia-Pacific Model

Emanuele Di Angelantonio, Zijuan Huang, Hokyou Lee, Steven H J Hageman et al.
Journal of Asian Pacific Society of Cardiology
Lipoproteins and Cardiovascular Health
article

Risk Prediction of Cardiovascular Disease in the Asia‑Pacific Region: The SCORE2 Asia-Pacific Model

Emanuele Di Angelantonio, Zijuan Huang, Hokyou Lee, Steven H J Hageman, Lisa Pennells, Jannick A N Dorresteijn, Frank L.J. Visseren, Hyeon Chang Kim, Stephen Kaptoge, Sofian Johar
article en

Abstract

Background and aims: To improve upon the estimation of 10-year cardiovascular disease (CVD) event risk for individuals without prior CVD or diabetes mellitus in the Asia-Pacific region by systematic recalibration of the SCORE2 risk algorithm. Methods: The sex-specific and competing risk-adjusted SCORE2 algorithms were systematically recalibrated to reflect CVD incidence observed in four Asia-Pacific risk regions, defined according to country-level WHO age- and sex-standardised CVD mortality rates. Using the same approach as applied for the original SCORE2 models, recalibration to each risk region was completed using expected CVD incidence and risk factor distributions from each region. Results: Risk region-specific CVD incidence was estimated using CVD mortality and incidence data on 8,405,574 individuals (556,421 CVD events). For external validation, data from 9 560 266 individuals without previous CVD or diabetes were analysed in 13 prospective studies from 12 countries (350,550 incident CVD events). The pooled C-index of the SCORE2 Asia-Pacific algorithms in the external validation datasets was 0.710 (95% CI [0.677–0.744]). Cohort-specific C-indices ranged from 0.605 (95% CI 0.597–0.613) to 0.840 (95% CI 0.771–0.909). Estimated CVD risk varied several-fold across Asia-Pacific risk regions. For example, the estimated 10-year CVD risk for a 50-year-old non-smoker, with a systolic blood pressure of 140 mmHg, total cholesterol of 5.5 mmol/l, and high-density lipoprotein cholesterol of 1.3 mmol/l, ranged from 7% for men in low-risk countries to 14% for men in very-high-risk countries, and from 3% for women in low-risk countries to 13% for women in very-high-risk countries. Conclusion: The SCORE2 Asia-Pacific algorithms have been calibrated to estimate 10-year risk of CVD for apparently healthy people in Asia and Oceania, thereby enhancing the identification of individuals at higher risk of developing CVD across the Asia-Pacific region.

Journal of Asian Pacific Society of CardiologyVol. 3
Universiti Brunei Darussalam (BN), Yonsei University (KR), University of Cambridge (GB), University Medical Center Utrecht (NL), ORCID (US), National Heart Centre Singapore (SG)
Amgen, Bristol-Myers Squibb, Pfizer, AstraZeneca, Sanofi, Higher Education Research Promotion, Universiti Brunei Darussalam, Queensland Health, Iran University of Medical Sciences, Pratt Foundation, Australian Government, Kidney Health Australia, National Research Foundation, National University of Singapore, Trinity College Dublin, National Natural Science Foundation of China, National Research Foundation of Korea, Mahidol University, Novo Nordisk, Thailand Research Fund, Universiti Kebangsaan Malaysia, National Research Council of Thailand, University of Tokyo, State Government of Victoria, Electricity Generating Authority of Thailand, Peking University, University of Kelaniya, National University Health System, Menzies Institute for Medical Research, Ministry of Science and ICT, South Korea, Baker Heart and Diabetes Institute, Office of the Higher Education Commission, Amgen Australia, Medical Research Council, National Health and Medical Research Council, National Medical Research Council, Gastrointestinal and Liver Diseases Research Center, Philippine Council for Health Research and Development, National Key Research and Development Program of China, Biomedical Research Council, Peking University Health Science Center, Cilag
Good health and well-being
Openalex Percentile: Top 59%
Lipoproteins and Cardiovascular Health
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.