A simple graphical test can detect bias in meta-analyses. The study examined funnel plots, which plot effect estimates against sample size, to assess asymmetry and its relation to bias. Eight pairs of meta-analyses and large trials were analyzed, with four showing concordant results and four discordant. Discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but not in concordant ones. In 38% of journal meta-analyses and 13% of Cochrane reviews, funnel plot asymmetry indicated bias. The study concluded that funnel plot asymmetry can be a useful indicator of potential bias in meta-analyses, but caution is needed as the method's effectiveness is limited when meta-analyses are based on a small number of trials. The study also identified various sources of funnel plot asymmetry, including publication bias, language bias, citation bias, and true heterogeneity. The results suggest that bias may be present in a small proportion of meta-analyses published in the Cochrane Database of Systematic Reviews, but may be more common in meta-analyses published in leading general medicine journals. The study emphasizes the importance of critically examining systematic reviews for publication and related biases as a routine procedure.A simple graphical test can detect bias in meta-analyses. The study examined funnel plots, which plot effect estimates against sample size, to assess asymmetry and its relation to bias. Eight pairs of meta-analyses and large trials were analyzed, with four showing concordant results and four discordant. Discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but not in concordant ones. In 38% of journal meta-analyses and 13% of Cochrane reviews, funnel plot asymmetry indicated bias. The study concluded that funnel plot asymmetry can be a useful indicator of potential bias in meta-analyses, but caution is needed as the method's effectiveness is limited when meta-analyses are based on a small number of trials. The study also identified various sources of funnel plot asymmetry, including publication bias, language bias, citation bias, and true heterogeneity. The results suggest that bias may be present in a small proportion of meta-analyses published in the Cochrane Database of Systematic Reviews, but may be more common in meta-analyses published in leading general medicine journals. The study emphasizes the importance of critically examining systematic reviews for publication and related biases as a routine procedure.