Development of a Model to Predict 10-Year Risk of Ischemic and Hemorrhagic Stroke and Ischemic Heart Disease Using the China Kadoorie Biobank.

Neurology

From the Department of Epidemiology & Biostatistics (S.Y., Y.H., C.Y., Y.P., D.S., J.L., L.L.), School of Public Health, Peking University; Peking University Center for Public Health and Epidemic Preparedness & Response (C.Y., J.L., L.L.); Fuwai Hospital Chinese Academy of Medical Sciences (Y.G.); Chinese Academy of Medical Sciences (P.P.), Beijing, China; Medical Research Council Population Health Research Unit at the University of Oxford (L.Y., Y.C., H.D.); Clinical Trial Service Unit & Epidemiological Studies Unit (L.Y., Y.C., H.D., M.S.M., D.B., R.C., Z.C.), Nuffield Department of Population Health, University of Oxford, UK; NCDs Prevention and Control Department (H.W.), Zhejiang CDC, Hangzhou; China National Center for Food Safety Risk Assessment (J.C.); and Key Laboratory of Molecular Cardiovascular Sciences (Peking University) (J.L.), Ministry of Education, Beijing, China.

Published: June 2022

Background And Objectives: Contemporary cardiovascular disease (CVD) risk prediction models are rarely applied in routine clinical practice in China due to substantial regional differences in absolute risks of major CVD types within China. Moreover, the inclusion of blood lipids in most risk prediction models also limits their use in the Chinese population. We developed 10-year CVD risk prediction models excluding blood lipids that may be applicable to diverse regions of China.

Methods: We derived sex-specific models separately for ischemic heart disease (IHD), ischemic stroke (IS), and hemorrhagic stroke (HS) in addition to total CVD in the China Kadoorie Biobank. Participants were age 30-79 years without CVD at baseline. Predictors included age, systolic and diastolic blood pressure, use of blood pressure-lowering treatment, current daily smoking, diabetes, and waist circumference. Total CVD risks were combined in terms of conditional probability using the predicted risks of 3 submodels. Risk models were recalibrated in each region by 2 methods (practical and ideal) and risk prediction was estimated before and after recalibration.

Results: Model derivation involved 489,596 individuals, including 45,947 IHD, 43,647 IS, and 11,168 HS cases during 11 years of follow-up. In women, the Harrell C was 0.732 (95% CI 0.706-0.758), 0.759 (0.738-0.779), and 0.803 (0.778-0.827) for IHD, IS, and HS, respectively. The Harrell C for total CVD was 0.734 (0.732-0.736), 0.754 (0.752-0.756), and 0.774 (0.772-0.776) for models before recalibration, after practical recalibration, and after ideal recalibration. The calibration performances improved after recalibration, with models after ideal recalibration showing the best model performances. The results for men were comparable to those for women.

Discussion: Our CVD risk prediction models yielded good discrimination of IHD and stroke subtypes in addition to total CVD without including blood lipids. Flexible recalibration of our models for different regions could enable more widespread use using resident health records covering the overall Chinese population.

Classification Of Evidence: This study provides Class I evidence that a prediction model incorporating accessible clinical variables predicts 10-year risk of IHD, IS, and HS in the Chinese population age 30-79 years.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202526PMC
http://dx.doi.org/10.1212/WNL.0000000000200139DOI Listing

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