Prediction of 10-year atherosclerotic cardiovascular disease risk among community residents in Shanghai, China – a comparative analysis of risk algorithms

Abstract

Background and aimsThe accuracy of various 10-year atherosclerotic cardiovascular disease (ASCVD) risk models has been debatable. We compared two risk algorithms and explored clustering patterns across different risk stratifications among community residents in Shanghai. Methods and resultsA total of 28,201 residents (aged 40–74 years old) who were free of ASCVD were selected from the Shanghai Survey in China. The 10-year ASCVD risk was estimated by applying the 2013 Pooled Cohort Equations (PCEs) and Prediction for ASCVD Risk in China (China-PAR). The agreement was assessed between PCEs and China-PAR using Cohen's kappa statistics.The mean absolute 10-year ASCVD risk calculated by PCEs and China-PAR was about 10.0% and 6.0%, respectively. PCEs estimated that 44.9% of participants [with a 95% confidence interval (CI):44.0%–45.8%] were at high risk, while China-PAR estimated only 16.7% (95%CI:15.8%–18.0%) were at high risk. In both models, the percentage of high ASCVD risk was higher for participants who were older, men, less educated, current smokers, drinkers and manual workers. Among high-risk individuals, almost all participants (PCEs:90.5%; China-PAR:98.6%) had at least one risk factor; hypertension being the most prevalent. The concordance between PCEs and China-PAR was moderate (kappa:0.428, 95%CI: 0.420–0.434) with a better agreement for women (kappa:0.503,95%CI: 0.493–0.513) than for men (kappa:0.211,95%CI: 0.201–0.221). ConclusionThe proportion of participants with a 10-year ASCVD high risk predicted by China-PAR was lower than the results of the PCEs. The risk stratifications of the two algorithms were inconsistent in terms of demographic and life-behaviour characteristics.