title: Forest plots.
abstract: Forest plots are frequently used in meta-analysis to present the results graphically. Without specific knowledge of statistics, a visual assessment of heterogeneity appears to be valid and reproducible. Possible causes of heterogeneity can be explored in modified forest plots. Forest plots in meta-analyses appear to be a valid and useful tool to quickly and efficiently scan and interpret the evidence. The expression ‘a picture is worth a thousand words’ certainly expresses the value of forest plots.
authors.affiliation: Department of General Practice, Erasmus Medical Centre University, Rotterdam, The Netherlands.
authors.forename: Arianne P
authors.initials: AP
authors.lastname: Verhagen
authors.affiliation: Musculoskeletal Division, The George Institute for Global Health, Sydney, Australia.
authors.forename: Manuela L
authors.initials: ML
authors.lastname: Ferreira
mesh_terms: D003627:Data Interpretation, Statistical; D006801:Humans; D055641:Mathematical Concepts; D015201:Meta-Analysis as Topic; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012680:Sensitivity and Specificity; D016896:Treatment Outcome