2.5 Statistical analysis
We performed a meta-analysis of the included studies using a random-effects model. Studies were excluded if they did not include an outcome in each intervention group, did not have enough information required for continuous data comparison, or shared the same patient population. Incidence rate ratios (IRR) of events were calculated by dividing the number of incident cases of events by the total number of person-years follow-up. IRR were pooled after applying the Freeman-Turkey double arcsine transformation to stabilize the variances (9). We pooled the point estimates of IRR, odds ratio, and incidence rate from each study using the generic inverse-variance method of Der Simonian and Laird (10). If no event was observed, pooled IRR were estimated using Poisson regression with random intervention effects (11). The heterogeneity of effect size estimates across these studies was quantified using the I2 statistic. The I2 statistic ranges in value from 0 to 100% (I2< 25%, low heterogeneity; I2= 25%–50%, moderate heterogeneity; and I2> 50%, substantial heterogeneity). A sensitivity analysis was performed to assess the influence of the individual studies on the overall results by omitting one study at a time. Publication bias was assessed using a funnel plot and the Egger’s regression test (12). (p< 0.05 was considered significant). All data analyses were performed using the STATA SE version 14.2.