Sharmini Selvarajah1, Gurpreet Kaur2, Jamaiyah Haniff3, Kee Chee Cheong4, Tee Guat Hiong2, Yolanda van der Graaf5, Michiel L Bots5. 1. Clinical Research Centre, Kuala Lumpur Hospital, Jalan Pahang, 50586 Kuala Lumpur, Malaysia; Julius Centre University of Malaya, Department of Social and Preventive Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: s.selvarajah@umcutrecht.nl. 2. Institute for Public Health, Ministry of Health Malaysia, Jalan Bangsar, 50590 Kuala Lumpur, Malaysia. 3. Clinical Research Centre, Kuala Lumpur Hospital, Jalan Pahang, 50586 Kuala Lumpur, Malaysia. 4. Institute for Medical Research, Ministry of Health Malaysia, Jalan Pahang, 50588 Kuala Lumpur, Malaysia. 5. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
Abstract
BACKGROUND: Cardiovascular risk-prediction models are used in clinical practice to identify and treat high-risk populations, and to communicate risk effectively. We assessed the validity and utility of four cardiovascular risk-prediction models in an Asian population of a middle-income country. METHODS: Data from a national population-based survey of 14,863 participants aged 40 to 65 years, with a follow-up duration of 73,277 person-years was used. The Framingham Risk Score (FRS), SCORE (Systematic COronary Risk Evaluation)-high and -low cardiovascular-risk regions and the World Health Organization/International Society of Hypertension (WHO/ISH) models were assessed. The outcome of interest was 5-year cardiovascular mortality. Discrimination was assessed for all models and calibration for the SCORE models. RESULTS: Cardiovascular risk factors were highly prevalent; smoking 20%, obesity 32%, hypertension 55%, diabetes mellitus 18% and hypercholesterolemia 34%. The FRS and SCORE models showed good agreement in risk stratification. The FRS, SCORE-high and -low models showed good discrimination for cardiovascular mortality, areas under the ROC curve (AUC) were 0.768, 0.774 and 0.775 respectively. The WHO/ISH model showed poor discrimination, AUC=0.613. Calibration of the SCORE-high model was graphically and statistically acceptable for men (χ(2) goodness-of-fit, p=0.097). The SCORE-low model was statistically acceptable for men (χ(2) goodness-of-fit, p=0.067). Both SCORE-models underestimated risk in women (p<0.001). CONCLUSIONS: The FRS and SCORE-high models, but not the WHO/ISH model can be used to identify high cardiovascular risk in the Malaysian population. The SCORE-high model predicts risk accurately in men but underestimated it in women.
BACKGROUND: Cardiovascular risk-prediction models are used in clinical practice to identify and treat high-risk populations, and to communicate risk effectively. We assessed the validity and utility of four cardiovascular risk-prediction models in an Asian population of a middle-income country. METHODS: Data from a national population-based survey of 14,863 participants aged 40 to 65 years, with a follow-up duration of 73,277 person-years was used. The Framingham Risk Score (FRS), SCORE (Systematic COronary Risk Evaluation)-high and -low cardiovascular-risk regions and the World Health Organization/International Society of Hypertension (WHO/ISH) models were assessed. The outcome of interest was 5-year cardiovascular mortality. Discrimination was assessed for all models and calibration for the SCORE models. RESULTS: Cardiovascular risk factors were highly prevalent; smoking 20%, obesity 32%, hypertension 55%, diabetes mellitus 18% and hypercholesterolemia 34%. The FRS and SCORE models showed good agreement in risk stratification. The FRS, SCORE-high and -low models showed good discrimination for cardiovascular mortality, areas under the ROC curve (AUC) were 0.768, 0.774 and 0.775 respectively. The WHO/ISH model showed poor discrimination, AUC=0.613. Calibration of the SCORE-high model was graphically and statistically acceptable for men (χ(2) goodness-of-fit, p=0.097). The SCORE-low model was statistically acceptable for men (χ(2) goodness-of-fit, p=0.067). Both SCORE-models underestimated risk in women (p<0.001). CONCLUSIONS: The FRS and SCORE-high models, but not the WHO/ISH model can be used to identify high cardiovascular risk in the Malaysian population. The SCORE-high model predicts risk accurately in men but underestimated it in women.
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