Key result
China-PAR outperforms PCE in initial calibration for 5-year ASCVD risk, though both show good discrimination.
Why the study?
Guidelines recommend calculating ASCVD risk using the PCE or China-PAR models, but evidence on the performance of both models in Asian populations is limited.
Do the PCE and China-PAR models accurately predict 5-year ASCVD risk in a contemporary Chinese cohort?
Cohort (n=226,406)
Do the PCE and China-PAR models accurately predict 5-year ASCVD risk in a contemporary Chinese cohort?
Both PCE and China-PAR models show good discrimination for 5-year ASCVD risk in a Chinese population, though China-PAR offers better calibration prior to recalibration.
Answers are grounded in this paper and cite their sources.
May warrant recalibration of China-PAR for Chinese adults; extends validation to large contemporary cohorts.
Updated American or Chinese guidelines recommended calculating atherosclerotic cardiovascular disease (ASCVD) risk using the Pooled Cohort Equations (PCE) or Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) models; however, evidence on performance of both models in Asian populations is limited. The authors aimed to evaluate the accuracy of the PCE or China-PAR models in a Chinese contemporary cohort. Data were extracted from the CHERRY (CHinese Electronic health Records Research in Yinzhou) study. Participants aged 40 to 79 years without prior ASCVD at baseline from 2010 to 2016 were included. ASCVD was defined as nonfatal or fatal stroke, nonfatal myocardial infarction, and cardiovascular death. Models were assessed for discrimination and calibration. Among 226,406 participants, 5362 (2.37%) adults developed a first ASCVD event during a median of 4.60 years of follow-up. Both models had good discrimination: C-statistics in men were 0.763 (95% confidence interval [CI]: 0.754-0.773) for PCE and 0.758 (95% CI: 0.749-0.767) for China-PAR; C-statistics in women were 0.820 (95% CI: 0.812-0.829) for PCE and 0.811 (95% CI: 0.802-0.819) for China-PAR. The China-PAR model underpredicted risk by 20% in men and by 40% in women, especially in the highest-risk groups. However, PCE overestimated by 63% in men and inversely underestimated the risk by 34% in women with poor calibration (both P < 0.001). After recalibration, observed and predicted risks by recalibrated PCE were better aligned. In this large-scale population-based study, both PCE and China-PAR had good discrimination in 5-year ASCVD risk prediction. China-PAR outperformed PCE in calibration, whereas recalibration equalized the performance of PCE and China-PAR. Further specific models are needed to improve accuracy in the highest-risk groups.
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Liu et al. (2022) conducted a cohort in Atherosclerotic cardiovascular disease (n=226,406). Pooled Cohort Equations (PCE) and China-PAR models was evaluated on First ASCVD event (nonfatal or fatal stroke, nonfatal myocardial infarction, and cardiovascular death). Both the Pooled Cohort Equations and China-PAR models demonstrated good discrimination for 5-year ASCVD risk prediction, with China-PAR outperforming PCE in calibration prior to recalibration.
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