2.6 Statistical Methods

All data analyses were performed using MedCalc (version 15.2.2; MedCalc Software, Mariakerke, Belgium) and R (version 3.2.4; R Foundation for Statistical Computing, Vienna, Austria). A p value 0.05 (two-tailed) was considered significant. The ANOVA or Mann–Whitney U test was used to evaluate the differences in continuous variables as appropriate. The χ² test or Fisher’s exact test was used to evaluate the differences in the categorical variables as appropriate. The discrimination and calibration of the CACS-CL model were assessed by the area under receiver operating characteristic curve (AUC) and Hosmer–Lemeshow goodness-of-fit statistic (H-L χ²) [21]. Net reclassification improvement (NRI) was assessed in a reclassification table and used to determine how strategies using different CACS-CL cutoffs reclassified patients into various risk groups compared with each other [21]. The cumulative MACE-free survivals were estimated using Kaplan–Meier curves and were compared by the log-rank test. We used Cox proportional hazard regression models to calculate the adjusted hazard ratios (HRs) and 95% confidence intervals (CIs), which assessed the association of risk groups to the onset of the first MACE. The models were adjusted for age, sex, cardiovascular risk factors (diabetes, hypertension, hyperlipidemia, smoking, family history of CAD), symptoms, and CACS.