*2.5. Data Synthesis and Statistical Analysis*

The effect of selenium supplementation on relevant outcomes was assessed as the changes (mean ± standard deviation [SD]) before and after treatment in the experimental and the control groups. If the mean values of the changes before and after treatment were unreported, they were calculated by subtracting the mean at the baseline from the mean at the end of the follow-up. When the SDs of the changes before and after treatment were not reported, they were computed according to the number of patients, standard errors, 95% confidence interval (CI), interquartile ranges, or *p*-values. If the missing SDs were still unavailable, they were calculated using the correlation formula, and the correlation coefficient was cautiously assumed to be 0.5 [36,37]. For studies with multiple intervention groups, we combined relevant groups into a single treatment group. All related calculation formulas were referred to the Cochrane Handbook for Systematic Reviews of Intervention [38].

Data were evaluated using Review Manager version 5.3 and STATA version 17.0 for a more comprehensive assessment of outcomes. The heterogeneity between studies was assessed using Cochrane's Q test and was quantified by the *I* <sup>2</sup> test. Heterogeneity was rated as low, moderate, or high when the value of *I* <sup>2</sup> was <50%, 50–75%, or >75%, respectively [39]. When the heterogeneity was low (*I* <sup>2</sup> < 50%), data were pooled by applying the fixed-effects model; otherwise, the random-effects model was applied [40]. Effect sizes are presented as the standardized mean difference (SMD) with 95% CI. If sufficient studies (≥10) were included, funnel plots and Egger's test were applied to determine whether there was publication bias. A *p*-value of <0.05 was considered statistically significant.

### *2.6. Analysis of Subgroups or Subsets*

In cases where significant heterogeneity was noted among studies, sensitivity analysis or subgroup analyses were performed to identify its possible sources. Sensitivity analysis was performed by removing each study sequentially to evaluate the influence of each study on the overall effect size. Subgroup analysis was conducted according to the type of disease of the participants.
