A Risk Prediction Equation for Cardiovascular Disease That Can Be Used in Different Countries | Journal Scan

Study Questions:

What is the utility of a risk prediction equation that can be recalibrated and updated for use in different countries with routinely available information?


The investigators used data from eight prospective cohort studies to estimate coefficients of the risk equation with proportional hazard regressions. The risk prediction equation included smoking, blood pressure, diabetes, and total cholesterol, and allowed the effects of sex and age on cardiovascular disease to vary between cohorts or countries. They developed risk equations for fatal cardiovascular disease and for fatal plus nonfatal cardiovascular disease. The authors validated the risk equations internally and also using data from three cohorts that were not used to create the equations. They then used the risk prediction equation and data from recent (2006 or later) national health surveys to estimate the proportion of the population at different levels of cardiovascular disease risk in 11 countries from different world regions (China, Czech Republic, Denmark, England, Iran, Japan, Malawi, Mexico, South Korea, Spain, and the United States).


The risk score discriminated well in internal and external validations, with C statistics generally 70% or more. At any age and risk factor level, the estimated 10-year fatal cardiovascular disease risk varied substantially between countries. The prevalence of people at high risk of fatal cardiovascular disease was lowest in South Korea, Spain, and Denmark, where only 5–10% of men and women had more than a 10% risk, and 62–77% of men and 79–82% of women had less than a 3% risk. Conversely, the proportion of people at high risk of fatal cardiovascular disease was largest in China and Mexico. In China, 33% of men and 28% of women had a 10-year risk of fatal cardiovascular disease of 10% or more, whereas in Mexico, the prevalence of this high risk was 16% for men and 11% for women. The prevalence of <3% risk was 37% for men and 42% for women in China, and 55% for men and 69% for women in Mexico.


The authors concluded that they have developed a cardiovascular disease risk equation that can be recalibrated for application in different countries with routinely available information.


This novel risk prediction equation for cardiovascular disease may fill the need for a unified risk score that can be used in different countries. The risk score can be recalibrated and updated for use in diverse populations and years with routinely available information, and allows for the effects of sex and age on cardiovascular risk to vary between countries. Overall, this risk prediction equation helps to overcome some barriers for global application of risk stratification and may allow coverage of risk-based treatment in different countries. The Globorisk score will complement the American College of Cardiology/American Heart Association pooled cohort risk equation and help identify high-risk individuals.

Clinical Topics: Dyslipidemia, Prevention, Lipid Metabolism, Nonstatins, Smoking

Keywords: Cardiovascular Diseases, Risk, Risk Factors, Blood Pressure, Cholesterol, Diabetes Mellitus, Smoking, Prevalence, Prospective Studies, Health Care Surveys, Mortality, Secondary Prevention

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