Validation of the general Framingham Risk Score (FRS), SCORE2, revised PCE and WHO CVD risk scores in an Asian population
Background: Cardiovascular risk prediction models incorporate myriad CVD risk factors. Current prediction models are developed from non-Asian populations, and their utility in other parts of the world is unknown. We validated and compared the performance of CVD risk prediction models in an Asian pop...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Elsevier
2023
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| Subjects: | |
| Online Access: | http://eprints.sunway.edu.my/2725/1/Chia%20Yook%20Chin_Validation%20of%20the%20general%20Framingham%20Risk%20Score.pdf http://eprints.sunway.edu.my/2725/ https://doi.org/10.1016/j.lanwpc.2023.100742 |
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| Summary: | Background: Cardiovascular risk prediction models incorporate myriad CVD risk factors. Current prediction models are developed from non-Asian populations, and their utility in other parts of the world is unknown. We validated and compared the performance of CVD risk prediction models in an Asian population.
Methods: Four validation groups were extracted from a longitudinal community-based study dataset of 12,573 participants aged ≥18 years to validate the Framingham Risk Score (FRS), Systematic Coronary Risk Evaluation 2 (SCORE2), Revised Pooled Cohort Equations (RPCE), and World Health Organization cardiovascular disease (WHO CVD) models. Two measures of validation are examined: discrimination and calibration. Outcome of interest was 10-year risk of CVD events (fatal and non-fatal). SCORE2 and RPCE performances were compared to SCORE and PCE, respectively.
Findings: FRS (AUC = 0.750) and RPCE (AUC = 0.752) showed good discrimination in CVD risk prediction. Although FRS and RPCE have poor calibration, FRS demonstrates smaller discordance for FRS vs. RPCE (298% vs. 733% in men, 146% vs. 391% in women). Other models had reasonable discrimination (AUC = 0.706-0.732). Only SCORE2-Low, -Moderate and -High (aged <50) had good calibration (X2 goodness-of-fit, P-value = 0.514, 0.189, 0.129, respectively). SCORE2 and RPCE showed improvements compared to SCORE (AUC = 0.755 vs. 0.747, P-value <0.001) and PCE (AUC = 0.752 vs. 0.546, P-value <0.001), respectively. Almost all risk models overestimated 10-year CVD risk by 3%-1430%.
Interpretation: In Malaysians, RPCE are evaluated be the most clinically useful to predict CVD risk. Additionally, SCORE2 and RPCE outperformed SCORE and PCE, respectively.
Funding: This work was supported by the Malaysian Ministry of Science, Technology, and Innovation (MOSTI) (Grant No: TDF03211036). |
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