Cardiovascular disease (CVD) is the most common noncommunicable disease and the leading cause of death globally.1 It has resulted in enormous economic and social burdens, while posing a great challenge for the prevention and control of CVD worldwide, especially in China. Assessment and management of cardiovascular risk is the foundation of CVD prevention, and is strongly recommended by guidelines.2-4 Additionally, it can help screen the target population who would benefit most from the lower-cost intervention, while informing them the cardiovascular risk, which will help in promoting self-management. It can also guide doctors in making logical management decisions, and implement precision prevention and treatment strategies to reduce the CVD burden.2, 4 Therefore, it is a key approach in achieving the goals of “Good Health and Well-being” in the United Nations and “Healthy China 2030” in China. Here, we briefly highlight several advances in cardiovascular risk assessments.
The Framingham Heart Study introduced the term “risk factor” in 1961, and identified a series of risk factors of CVD subsequently, such as cholesterol, blood pressure, glucose, and obesity.5 By integrating multiple conventional risk factors, a general cardiovascular risk instrument was further developed to assist in identifying and treating individuals at high risk.6 Since the concept of cardiovascular risk assessment and stratification was adopted by the third Adult Treatment Panel of the National Cholesterol Education Program in 2001, it has led to the development of effective treatment and preventive strategies in clinical practice.
A systematic approach to cardiovascular risk assessment includes the collection of information to calculate the cardiovascular risk, identification of the target high-risk population, and implementation of individual management according to the risk level. Therefore, risk-prediction models are major components of risk-based CVD prevention and control efforts. Several cardiovascular risk models have been developed using conventional risk factors to assist in clinical practice, such as the Reynolds Risk Score7, 8 and the Pooled Cohort Equations (PCE)9 in the United States, the QRISK in the United Kingdom,10 the ASSIGN Score in Scotland,11 the Systematic Coronary Risk Evaluation (SCORE) model in Europe,12 and the Prediction for Atherosclerotic CVD Risk in China (China-PAR) equations.13 In addition, World Health Organization has derived the risk prediction charts for 21 Global Burden of Disease regions to facilitate the risk-based CVD prevention in low- and middle-income countries.4 These models, taking account of balance between good performance and ac