2.5 Statistical analysis
We performed meta-analysis of included studies using a random-effects
model and the generic inverse-variance method of Der Simonian and Laird
to calculate pooled HR [18]. We extracted from these studies the
freedom from AT rates and complications rates. For the analysis of
pooled recurrent rate, if the study does not provide HR, we manually
calculate HR with methods by Tierney et al. [16]. For the analysis
of adverse events, we calculate pooled OR, or OR if outcome was
available from one study only. The heterogeneity of effect size
estimates was assessed using forest plots to detect non-overlapping
confidence interval (CI), and then was calculated using the Q statistic
and I2 statistic. For the Q statistic, substantial
heterogeneity was defined as p< 0.10. 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 funnel plot and
Egger’s regression tests [19] (p< 0.05 was
considered significant). All statistical tests were performed using the
STATA 14.2 software (College Station, TX).