External validation of three atherosclerotic cardiovascular disease risk equations in rural areas of Xinjiang, China

Yunxing Jiang,Shuxia Guo,Jia He,Mulatibieke Keerman,Jingyu Zhang,Jiaolong Ma,Xinping Wang,Rulin Ma,Xianghui Zhang,Yanpeng Song,Yizhong Yan,Kui Wang,Yunhua Hu,Heng Guo

doi:10.1186/s12889-020-09579-4

Abstract

BackgroundTo externally validate the Prediction for ASCVD Risk in China (PAR) risk equation for predicting the 5-year atherosclerotic cardiovascular disease (ASCVD) risk in the Uyghur and Kazakh populations from rural areas in northwestern China and compare its performance with those of the pooled cohort equations (PCE) and Framingham risk score (FRS).MethodsThe final analysis included 3347 subjects aged 40–74 years without CVD at baseline. The 5-year ASCVD risk was calculated using the PAR, PCE, and FRS. Discrimination, calibration, and clinical usefulness of the three equations in predicting the 5-year ASCVD risk were assessed before and after recalibration.ResultsOf 3347 included subjects, 1839 were female. We observed 286 ASCVD events in within 5-year follow-up. All three risk equations had moderate discrimination in both men and women. C-indices of PAR, PCE, and FRS were 0.727 (95% CI, 0.725–0.729), 0.727 (95% CI, 0.725–0.729), and 0.740 (95% CI, 0.738–0.742), respectively, in men; the corresponding C-indices were 0.738 (95% CI, 0.737–0.739), 0.731 (95% CI, 0.730–0.732), and 0.761 (95% CI, 0.760–0.762), respectively, in women. PCE, PAR and FRS substantially underestimated the 5-year ASCVD risk in women by 70, 23 and 51%, respectively. However, PAR and FRS fairly predicted the risk in men and PAR was well calibrated. The calibrations of the three risk equations could be changed by recalibration. The decision curve analyses demonstrated that at the threshold risk of 5%, PCE was the most clinically useful in both men and women after recalibration.ConclusionsAll three risk equations underestimated the 5-year ASCVD risk in women, while PAR and FRS fairly predicted that in men. However, the results of predictive performances for three risk equations are inconsistent, more accurate risk equations are required in the primary prevention of ASCVD aiming to this Uyghur and Kazakh populations.

Highlights

To externally validate the Prediction for ASCVD Risk in China (PAR) risk equation for predicting the 5-year atherosclerotic cardiovascular disease (ASCVD) risk in the Uyghur and Kazakh populations from rural areas in northwestern China and compare its performance with those of the pooled cohort equations (PCE) and Framingham risk score (FRS)
The PAR and FRS fairly predicted the risk in men with a Predicted events/Observed events (P/O) of 1.05 and 1.06, respectively, whereas the PCE underestimated it by nearly 50% and was poorly calibrated
A study [23] suggested that the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) could be strongly affected by miscalibration of a model, and the PCE and PAR in women and the PCE in men were still poorly calibrated after recalibration; the results may be affected

Summary

Introduction

To externally validate the Prediction for ASCVD Risk in China (PAR) risk equation for predicting the 5-year atherosclerotic cardiovascular disease (ASCVD) risk in the Uyghur and Kazakh populations from rural areas in northwestern China and compare its performance with those of the pooled cohort equations (PCE) and Framingham risk score (FRS). After the development of the PAR, it has been undergone an external validation in a rural northern Chinese population, the performance of the PAR in predicting 5-year ASCVD risk was just moderate [5]. It is crucial to identify high-risk individuals using ASCVD risk assessment tools in the prevention of ASCV D. There has not been an ASCVD risk prediction model specially targeted at this population

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