In this paper , the statistic significance and clinical application of forest plots in a meta-analysis have been fully discussed. If the horizontal line represents the 95% confidence interval of the indexes including odds ratio, relative risk, weighted mean difference, and standard mean difference crosses the vertical line, the effect of test group is not signficant with that of control group; if the horizontal line lies to the right of the vertical line, it indicates that the test group is significantly effctive. If the horizontal line lies to the left of the vertical line, it indicates that the control group is more effective. In addition, it doesn’t mean that clinical application is more beneficial, if the treatment study has more effect, because experimental factor can be positive or negative.
With the rapidly growing literature across the surgical disciplines, there is a corresponding need to critically appraise and summarize the currently available evidence so they can be applied appropriately to patient care. The interpretation of systematic reviews is particularly challenging in cases where few robust clinical trials have been performed to address a particular question. However, risk of bias can be minimized and potentially useful conclusions can be drawn if strict review methodology is adhered to, including an exhaustive literature search, quality appraisal of primary studies, appropriate statistical methodology, assessment of confidence in estimates and risk of bias. Therefore, the following article aims to: (Ⅰ) summarize to the important features of a thorough and rigorous systematic review or meta-analysis for the surgical literature; (Ⅱ) highlight several underused statistical approaches which may yield further interesting insights compared to conventional pair-wise data synthesis techniques; and (Ⅲ) propose a guide for thorough analysis and presentation of results.