Abstract

ObjectivesEstimating the total risk of cardiovascular disease (CVD) using risk prediction models represents a huge improvement in identifying and treating each of the risk factors. The objective of this study was to evaluate the effectiveness of the China-PAR (Prediction of atherosclerotic CVD risk in China) and Framingham risk score (FRS) in predicting the 10-year risk of CVD in Chinese hypertensive patients. The results of the study can be used to design health promotion strategies. Study designA large cohort study was used to assess the validity of models by comparing model predictions with actual incidence rates. MethodsIn total, 10,498 hypertensive patients aged 30–70 years in Jiangsu Province, China, participated in the baseline survey that took place between January and December 2010 and were followed up to May 2020. China-PAR and FRS were used to calculate the predicted 10-year risk of CVD. The 10-year observed incidence of new cardiovascular events was adjusted by the Kaplan–Meier method. The ratio of the predicted risk to the actual incidence was calculated to evaluate the effectiveness of the model. The discrimination Harrell's C statistics and calibration Chi-square value were used to evaluate the predictive reliability of the models. ResultsOf the 10,498 participants, 4411 (42.02%) were male. During the mean follow-up of 8.30 ± 1.45 years, a total of 693 new cardiovascular events occurred. Both models overestimated the risk of morbidity to varying degrees, and the FRS overestimated to a greater extent. After adjustment for covariates, the results of Cox proportional hazards regression showed that the risk of CVD in the high-risk group was higher than in low-risk group. The degree of discrimination in both models was approximately 0.6, which showed that discrimination was not ideal in the models. In addition, Chi-square calibrations of the two models were <20 in males, which showed that calibration of the models was better for men than women. ConclusionsThe China-PAR and FRS models overestimated the risk of CVD for participants in this study. In addition, the degree of discrimination was not ideal, and both models performed better in males than in females in terms of calibration. The results of this study suggest that a more suitable risk prediction model should be established according to the characteristics of the hypertensive population in Jiangsu Province.

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