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July 5, 2026Scientific ReportsOpen Access

External validation of American heart association predicting risk of cardiovascular disease EVENTs (PREVENT) equations in a Chinese population

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Why the study?

Does the AHA PREVENT equation accurately predict CVD risk in a middle-aged and elderly Chinese population?

Population

10,068 participants aged ≥ 45 years from the nationwide China Health and Retirement Longitudinal Study

Comparison

American Heart Association Predicting Risk of… vs China-PAR risk prediction model

Design

Cohort

Follow-up

2011-2018

Key result

The PREVENT equations exhibited poor discrimination for predicting cardiovascular disease in a Chinese population, with an AUC of 0.61 in males and 0.62 in females, despite higher scores being significantly associated with increased CVD risk.

Authors

WFWan-Qiu FanYHYiwen HuCYChun-Yu Yu

Discussion

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Overview

Supports PREVENT evaluation for CVD risk stratification; hypothesis-generating and requires prospective validation before practice change.

Key Points

  • This study aims to validate the AHA PREVENT equations for predicting cardiovascular disease (CVD) risk in a Chinese population.
  • Analyzed data from 10,068 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study (CHARLS)
  • Evaluated CVD risk using univariate and multivariate logistic regression, ROC curves, and calibration analysis
  • Compared PREVENT scores with China-PAR for predicting CVD risk using AUC and Delong test.
  • Each 1% increase in PREVENT scores correlates with a higher risk of CVD (OR for males: 1.05, 95% CI 1.04-1.07; females: OR 1.06, 95% CI 1.05-1.07)
  • AUC for CVD prediction was 0.61 for males and 0.62 for females, indicating low predictive performance
  • PREVENT showed better discrimination than China-PAR (AUC: 0.52, P < 0.001), but overall net benefit was marginal.

Study Design

Type

Cohort (n=10,068)

Multicenter

Yes

Structured PICO

Does the AHA PREVENT equation accurately predict CVD risk in a middle-aged and elderly Chinese population?

P
Population
10,068 middle-aged and elderly Chinese adults aged 45 to 79 years without baseline cardiovascular disease were followed for 7 years to externally validate the PREVENT risk equations.
E
Exposure
American Heart Association (AHA) Predicting Risk of Cardiovascular Disease Events (PREVENT) equations
C
Comparator
China-PAR risk prediction model
O
Outcome
Cardiovascular disease (CVD), including heart disease and strokecomposite

Main Result

Odds Ratio: 1.05 (95% CI 1.04–1.07)

The AHA PREVENT equations exhibit reduced discrimination for CVD prediction in middle-aged and elderly Chinese individuals compared to US populations, suggesting the need for statistical recalibration before clinical application.

Limitations

  • Family history of ASCVD was unavailable in the CHARLS cohort, preventing the evaluation of the China-PAR model in males.
  • Tracking data from wave 5 (2020) was not utilized due to simplified handling during the COVID-19 pandemic, which could introduce information bias.
  • Retrospective study design.

Cite This Study

Fan et al. (2026) conducted a cohort in Cardiovascular disease (n=10,068). PREVENT equations was evaluated on Cardiovascular disease (CVD) events, including heart disease and stroke (OR 1.05, 95% CI 1.04-1.07). The PREVENT equations exhibited poor discrimination for predicting cardiovascular disease in a Chinese population, with an AUC of 0.61 in males and 0.62 in females, despite higher scores being significantly associated with increased CVD risk.

synapsesocial.com/papers/6a49f36ff5d1d45b287ff90ehttps://doi.org/10.1038/s41598-026-60494-x
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