Predicting the 10-Year Risks of Atherosclerotic Cardiovascular Disease in Chinese Population

TLDR

Accurate individual risk assessment is valuable for ASCVD prevention, yet existing prediction models are largely derived from white populations. The China‑PAR project aims to develop and validate 10‑year ASCVD risk equations tailored to Chinese cohorts. Using a derivation cohort of 21,320 Chinese participants followed for 12 years (1,048 events) and two independent validation cohorts (14,123 and 70,838 participants), the study compared its equations with the Pooled Cohort Equations. The sex‑specific equations achieved C statistics of 0.794 for men and 0.811 for women, showed good calibration, and outperformed the Pooled Cohort Equations, demonstrating effective tools for 10‑year ASCVD risk prediction in China.

Abstract

The accurate assessment of individual risk can be of great value to guiding and facilitating the prevention of atherosclerotic cardiovascular disease (ASCVD). However, prediction models in common use were formulated primarily in white populations. The China-PAR project (Prediction for ASCVD Risk in China) is aimed at developing and validating 10-year risk prediction equations for ASCVD from 4 contemporary Chinese cohorts.Two prospective studies followed up together with a unified protocol were used as the derivation cohort to develop 10-year ASCVD risk equations in 21 320 Chinese participants. The external validation was evaluated in 2 independent Chinese cohorts with 14 123 and 70 838 participants. Furthermore, model performance was compared with the Pooled Cohort Equations reported in the American College of Cardiology/American Heart Association guideline.Over 12 years of follow-up in the derivation cohort with 21 320 Chinese participants, 1048 subjects developed a first ASCVD event. Sex-specific equations had C statistics of 0.794 (95% confidence interval, 0.775-0.814) for men and 0.811 (95% confidence interval, 0.787-0.835) for women. The predicted rates were similar to the observed rates, as indicated by a calibration χ2 of 13.1 for men (P=0.16) and 12.8 for women (P=0.17). Good internal and external validations of our equations were achieved in subsequent analyses. Compared with the Chinese equations, the Pooled Cohort Equations had lower C statistics and much higher calibration χ2 values in men.Our project developed effective tools with good performance for 10-year ASCVD risk prediction among a Chinese population that will help to improve the primary prevention and management of cardiovascular disease.