Step 1 | Calculate and report the P-values and the 95% confidence intervals from all fixed-effect and random-effects meta-analyses. The most conservative result should be the main result. |
Step 2 | Explore the reasons behind substantial statistical heterogeneity by performing subgroup analyses and sensitivity analyses (see step 6). |
Step 3 | Adjust the thresholds for significance (P-values and the confidence intervals from the meta-analyses and the risks of type I error in the trial sequential analysis) according to the number of primary outcome comparisons. |
Step 4 | Calculate and report a realistic diversity-adjusted required information size and analyse all of the outcomes with trial sequential analysis. Report if the trial sequential monitoring boundaries for benefit, harm, or futility are crossed. |
Step 5 | Calculate and report Bayes factor for the primary outcome/s based on the anticipated intervention effect used to estimate the required information size (http://www.ctu.dk/tools-and-links/bayes-factor-calculation.aspx). A Bayes factor less than 0.1 (a ten-fold higher likelihood of compatibility with the alternative hypothesis than with the null hypothesis) may be chosen as threshold for significance. |
Step 6 | Use subgroup analysis and sensitivity analyses to assess the potential impact of systematic errors (‘bias’). |
Step 7 | Assess the risk of publication bias. |
Step 8 | Assess clinical significance of the review results if the prior seven steps have shown statistically significant results. |