Validation and comparison of cardiovascular risk prediction equations in Chinese patients with Type 2 diabetes.

Abstract

For patients with diabetes, the European guidelines updated the cardiovascular disease (CVD) risk prediction recommendations using diabetes-specific models with age-specific cut-offs, whereas American guidelines still advise models derived from the general population. We aimed to compare the performance of four cardiovascular risk models in diabetes populations. Patients with diabetes from the CHERRY study, an electronic health records-based cohort study in China, were identified. Five-year CVD risk was calculated using original and recalibrated diabetes-specific models [Action in Diabetes and Vascular disease: PreterAx and diamicroN-MR Controlled Evaluation (ADVANCE) and the Hong Kong cardiovascular risk model (HK)] and general population-based models [Pooled Cohort Equations (PCE) and Prediction for Atherosclerotic cardiovascular disease Risk in China (China-PAR)]. During a median 5.8-year follow-up, 46 558 patients had 2605 CVD events. C-statistics were 0.711 [95% confidence interval: 0.693-0.729] for ADVANCE and 0.701 (0.683-0.719) for HK in men, and 0.742 (0.725-0.759) and 0.732 (0.718-0.747) in women. C-statistics were worse in two general population-based models. Recalibrated ADVANCE underestimated risk by 1.2% and 16.8% in men and women, whereas PCE underestimated risk by 41.9% and 24.2% in men and women. With the age-specific cut-offs, the overlap of the high-risk patients selected by every model pair ranged from only 22.6% to 51.2%. When utilizing the fixed cut-off at 5%, the recalibrated ADVANCE selected similar high-risk patients in men (7400) as compared to the age-specific cut-offs (7102), whereas age-specific cut-offs exhibited a reduction in the selection of high-risk patients in women (2646 under age-specific cut-offs vs. 3647 under fixed cut-off). Diabetes-specific CVD risk prediction models showed better discrimination for patients with diabetes. High-risk patients selected by different models varied significantly. Age-specific cut-offs selected fewer patients at high CVD risk especially in women.