to measure funnel plot asymmetry on the natural logarithm of the OR. The larger the deviation of each study from the funnel curve, the more pronounced the asymmetry. Results from small studies will scatter widely at the bottom of the graph, with the spread narrowing among larger studies. The significance of the intercept was evaluated using the T-test(Egger et al. 1997; Fan and Sklar 2005). For datasets with evidence for publication bias, the “Duval and Tweedie's Trim and Fill” procedure(Duval and Tweedie 2000) was used to impute the number of potentially-missing studies. In the absence of bias the funnel plot would be symmetric with respect to the summary effect. If there are more small studies on the right than on the left, some studies may be missing from the left. The Trim and Fill procedure imputes these missing studies, adds them to the analysis, and then re-computes the adjusted overall effect size.
