Data synthesis and statistical analyses
The meta-analysis was conducted using R Statistical Software (v3.5.1, Boston, MA, USA) with the ‘meta’ and ‘metafor’ packages for analysis, and RevMan (Review Manager Version 5.1, The Cochrane Collaboration, Copenhagen, Denmark). A two-tailed p-value of < 0.05 was considered statistically significant. Summary statistics are presented as weighted mean differences (WMD) with 95% confidence intervals (CIs). Mean and standard deviation (SD) values were estimated based on the method described by Hozo et al. [20]. A random-effects model (Der Simonian and Laird method) was used to estimate the pooled prevalence of adverse events across studies. The 95% CIs for the prevalence of adverse events were calculated using the binomial exact method (Clopper-Pearson) based on the proportion of cases and sample size. Inverse variance weighting was applied to each study in the meta-analysis. Results are illustrated in forest plots, the standard way of presenting individual study and meta-analysis outcomes. Sub-analyses were conducted to evaluate the effect of different types of lipid-lowering therapy (LLT) on lipid profiles and safety parameters. Meta-analyses were performed using the random-effects model. Heterogeneity across studies was assessed using the Cochrane Q test and the I² index, with I² < 25% indicating low, 25-50% moderate, and >50% high heterogeneity. The reduced maximum likelihood method (tau²) was used to incorporate residual heterogeneity in the analysis [21]. Publication bias was assessed through visual inspection of funnel plots and Egger’s test.