Abstract
BACKGROUND: To improve screening for atherosclerotic cardiovascular disease (ASCVD), we aimed to develop and temporally evaluate sex-specific models to predict 4-year ASCVD risk in South Limburg based on age and neighbourhood characteristics concerning home address. METHODS: We included 40- to 70-year-olds living in South Limburg on 1 January 2015 for model development, and 40- to 70-year-olds living in South Limburg on 1 January 2016 for model evaluation. We randomly sampled people selected in 1 year and in both years to create development and evaluation data sets. Follow-up of ASCVD and competing events (overall mortality excluding ASCVD) lasted until 31 December 2020. Candidate predictors were the individual's age, the neighbourhood's socio-economic status, and the neighbourhood's particulate matter concentration. Using the evaluation data sets, we compared two model types, subdistribution and cause-specific hazard models, and eight model structures. Discrimination was assessed by the area under the receiver operating characteristic curve (AUROC). Calibration was assessed by calculating overall expected-observed ratios (E/O). For the final models, calibration plots were made additionally. RESULTS: The development data sets consisted of 67,549 males (4-year cumulative ASCVD incidence: 3.08%) and 67,947 females (4-year cumulative ASCVD incidence: 1.50%). The evaluation data sets consisted of 66,068 males (4-year cumulative ASCVD incidence: 3.22%) and 66,231 females (4-year cumulative ASCVD incidence: 1.49%). For males, the AUROC of the final model equalled 0.6548. The E/O equalled 0.9466. For females, the AUROC equalled 0.6744. The E/O equalled 0.9838. CONCLUSIONS: The resulting model shows promise for further research. These models may be used for ASCVD screening in the future.