Development and internal validation of a multivariable prediction model for 6-year risk of stroke: a cohort study in middle-aged and elderly Chinese population

• Published in: BMJ open 2021-07, Vol.11 (7), p.e048734-e048734
• Main Authors: Yu, Qi, Wu, Yuanzhe, Jin, Qingdong, Chen, Yanqing, Lin, Qingying, Liu, Xinru
• Format: Article
• Language: English
• Subjects: Blood pressure; Calibration; Cholesterol; Cohort analysis; Data collection; Diabetes; Epidemiology; Gender; Middle age; Nomograms; Nutrition; Older people; Optimism; Population; Regression analysis; Risk factors; risk management; Sample size; Stroke; Variables
• ISSN: 2044-6055; 2044-6055
• DOI: 10.1136/bmjopen-2021-048734

ObjectiveTo develop and internally validate a prediction model for 6-year risk of stroke and its primary subtypes in middle-aged and elderly Chinese population.DesignThis is a retrospective cohort study from a prospectively collected database.ParticipantsWe included a total 3124 adults aged 45–80 years, free of stroke or myocardial infarction at baseline in the 2009–2015 cohort of China Health and Nutrition Survey.Primary and secondary outcome measuresThe outcome of the prediction model was stroke. Investigated predictors were: age, gender, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), hypertension (HBP), drinking status, smoking status, diabetes and site. Stepwise multiple Cox regression was applied to identify independent predictors. A nomogram was constructed to predict 6-year risk of stroke based on the multiple analysis results. Bootstraps with 1000 resamples were applied to both C-index and calibration curve.ResultThe overall incidence of overall stroke was 2.98%. Age, gender, HBP and TC were found as significant risk predictors for overall stroke; age, gender, HBP and LDL-C were found as significant risk predictors for ischaemic stroke; age, gender, HBP, BMI and HDL-C were found as significant risk predictors for haemorrhagic stroke. The nomogram was constructed using significant variables included in the model, with a C-index of 0.74 (95% CI: 0.72 to 0.76), 0.74 (95% CI: 0.71 to 0.77), and 0.81 (95% CI: 0.78 to 0.84) for overall stroke, ischaemic stroke, and haemorrhagic stroke model, respectively. The calibration curves demonstrated the good agreements between predicted and observed 6-year risk probability.ConclusionOur nomogram could be convenient, easy to use and effective prognoses for predicting 6-year risk of stroke in middle-aged and elderly Chinese population.