Abstract
Introduction: Cardiovascular diseases (CVDs) are the leading cause of death in India. The CVD risk approach is a cost-effective way to identify those at high risk, especially in a low resource setting. As there is no validated prognostic model for an Indian urban population, we have re-calibrated the original Framingham model using data from two urban Indian studies. Methods: We have estimated three risk score equations using three different models. The first model was based on Framingham original model; the second and third are the recalibrated models using risk factor prevalence from CARRS (Centre for cArdiometabolic Risk Reduction in South-Asia) and ICMR (Indian Council of Medical Research) studies, and estimated survival from WHO 2012 data for India. We applied these three risk scores to the CARRS and ICMR participants and estimated the proportion of those at high-risk (>30% 10 years CVD risk) who would be eligible to receive preventive treatment such as statins. Results: In the CARRS study, the proportion of men with 10 years CVD risk > 30% (and therefore eligible for statin treatment) was 13.3%, 21%, and 13.6% using Framingham, CARRS and ICMR risk models, respectively. The corresponding proportions of women were 3.5%, 16.4%, and 11.6%. In the ICMR study the corresponding proportions of men were 16.3%, 24.2%, and 16.5% and for women, these were 5.6%, 20.5%, and 15.3%. Conclusion: Although the recalibrated model based on local population can improve the validity of CVD risk scores our study exemplifies the variation between recalibrated models using different data from the same country. Considering the growing burden of cardiovascular diseases in India, and the impact that the risk approach has on influencing cardiovascular prevention treatment, such as statins, it is essential to develop high quality and well powered local cohorts (with outcome data) to develop local prognostic models.
Highlights
Cardiovascular diseases (CVDs) account for twothirds of the total non-communicable disease (NCD) burden in India[1]
Indians are affected by CVDs at a younger age compared to their European counterparts, with more than 50% CVDs deaths occurring before the age of 704–6
CVDs risk approach is a cost-effective means to identify those at high risk so that immediate short and long-term preventive steps can be followed to mitigate the risk[8]
Summary
Cardiovascular diseases (CVDs) account for twothirds of the total non-communicable disease (NCD) burden in India[1]. According to the 2016 Global Burden of Disease study, ischemic heart disease was the leading cause of the Disabilityadjusted life years (DALYs), measured to be 3062 per 100,000 population in India[2]. Risk factor effect can be similar across populations, the estimated cardiovascular disease risk from risk models differs substantially across populations. Another study from the United Kingdom has shown the CVD risk prediction model to be inaccurate in the South Asian group as compared to white Europeans[11]. Recalibrating a risk equation to a new population involves estimating the average values of the risk factors and the average risk of CVD. We report the Framingham model recalibration to an Indian urban population using data from two studies: CARRS (Centre for cArdiometabolic Risk Reduction in South-Asia), and ICMR (Indian Council of Medical Research). We compare the 10-year predictions of CVD fatal and nonfatal events produced by the original Framingham model and the recalibrated models and describe the potential impact of the recalibration on the proportion of the population eligible for treatment as recommended by current WHO guidelines
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