Background: Forest plots are graphical displays of findings of systematic reviews and meta-analyses. Little is known about the style and content of these plots and whether published plots maximize the graphic's potential for information exchange. Methods: We examine the number, style and content of forest plots presented in a previously studied cross-sectional sample of 300 systematic reviews. We studied all forest plots in non-Cochrane reviews and a sample of forest plots in Cochrane reviews. Results: The database contained 129 Cochrane reviews and 171 non-Cochrane reviews. All the Cochrane reviews had forest plots (2197 in total), and a random sample of 500 of these plots were included. In total, 28 of the non-Cochrane reviews had forest plots (139 in total), all of which were included. Plots in Cochrane reviews were standardized but often contained little data (80% had three or fewer studies; 10% had no studies) and always presented studies in alphabetical order. Non-Cochrane plots depicted a larger number of studies (60% had four or more studies) and 59% ordered studies by a potentially meaningful characteristic, but important information was often missing. Of the 28 reviews that had a forest plots with at least 10 studies, 3 (11%) had funnel plots. Conclusions: Forest plots in Cochrane reviews were highly standardized but some of the standards do not optimize information exchange, and many of the plots had too little data to be useful. Forest plots in non-Cochrane reviews often omitted key elements but had more data and were often more thoughtfully constructed. © Published by Oxford University Press on behalf of the International Epidemiological Association. The Author 2010; all rights reserved.
CITATION STYLE
Schriger, D. L., Altman, D. G., Vetter, J. A., Heafner, T., & Moher, D. (2010). Forest plots in reports of systematic reviews: A cross-sectional study reviewing current practice. International Journal of Epidemiology, 39(2), 421–429. https://doi.org/10.1093/ije/dyp370
Mendeley helps you to discover research relevant for your work.