Key result
The Framingham and SCORE-Low risk models demonstrated good discrimination (AUC > 0.85) and calibration for predicting 10-year cardiovascular mortality risk in Australian women, though they overestimated risk by greater than 15%.
Why the study?
Do Framingham and SCORE risk models accurately predict 10-year cardiovascular mortality in Australian women without prior cardiovascular disease?
Cohort (n=4,487)
Yes
Do Framingham and SCORE risk models accurately predict 10-year cardiovascular mortality in Australian women without prior cardiovascular disease?
The Framingham and SCORE-Low risk models demonstrate good discrimination and calibration for predicting 10-year cardiovascular mortality in Australian women, though lower treatment thresholds are proposed to improve sensitivity.
Answers are grounded in this paper and cite their sources.
May inform risk stratification in Australian women; extends validation but leaves open recalibration needs due to overestimation.
BACKGROUND: We conducted an independent external validation of three cardiovascular risk score models (Framingham risk score model and SCORE risk charts developed for low-risk regions and high-risk regions in Europe) on a prospective cohort of 4487 Australian women with no previous history of heart disease, diabetes or stroke. External validation is an important step to evaluate the performance of risk score models using discrimination and calibration measures to ensure their applicability beyond the settings in which they were developed. METHODS: Ten year mortality follow-up of 4487 Australian adult women from the National Heart Foundation third Risk Factor Prevalence Study with no baseline history of heart disease, diabetes or stroke. The 10-year risk of cardiovascular mortality was calculated using the Framingham and SCORE models and the predictive accuracy of the three risk score models were assessed using both discrimination and calibration. RESULTS: The discriminative ability of the Framingham and SCORE models were good (area under the curve > 0.85). Although all models overestimated the number of cardiovascular deaths by greater than 15%, the Hosmer-Lemeshow test indicated that the Framingham and SCORE-Low models were calibrated and hence suitable for predicting the 10-year cardiovascular mortality risk in this Australian population. An assessment of the treatment thresholds for each of the three models in identifying participants recommended for treatment were found to be inadequate, with low sensitivity and high specificity resulting from the high recommended thresholds. Lower treatment thresholds of 8.7% for the Framingham model, 0.8% for the SCORE-Low model and 1.3% for the SCORE-High model were identified for each model using the Youden index, at greater than 78% sensitivity and 80% specificity. CONCLUSIONS: Framingham risk score model and SCORE risk chart for low-risk regions are recommended for use in the Australian women population for predicting the 10-year cardiovascular mortality risk. These models demonstrate good discrimination and calibration performance. Lower treatment thresholds are proposed for better identification of individuals for treatment.
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Goh et al. (2014) conducted a cohort in Cardiovascular disease risk prediction (n=4,487). Framingham and SCORE risk models vs. Observed mortality was evaluated on 10-year cardiovascular mortality risk discrimination (Framingham model) (AUC 0.858, 95% CI 0.786-0.929). The Framingham and SCORE-Low risk models demonstrated good discrimination (AUC > 0.85) and calibration for predicting 10-year cardiovascular mortality risk in Australian women, though they overestimated risk by greater than 15%.
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