Forrest plots or caterpillar plots?

Abstract

The recent tutorial by Li et al. [[1]Li G. Zeng J. Tian J. Levine M.A. Thabane L. Multiple uses of forest plots in presenting analysis results in health research.J Clin Epidemiol. 2020; 117: 89-98Abstract Full Text Full Text PDF PubMed Scopus (7) Google Scholar] is of great interest. They describe the multiple ways of using a forest plot to enhance the ability to make comparisons between data items. May I suggest one slight variation to this end? The caterpillar plot. The only difference with the forest plot is that for a caterpillar plot, the items (usually individual studies) are sorted in order of increasing effect size. The effect of this sort in order of effect size is illustrated in Fig. 1. In this plot it is clear how each individual study effect size (in this case a bacteremia incidence) relates not only to the summary effect, but also to a central reference line. Moreover, the relationship of effect size and the degree of overlap of the caterpillar legs (the 95% confidence intervals of the studies) is more clearly apparent than is the case within a forest plot. This facilitates the visualization of heterogeneity “at a glance”. Download .xml (.0 MB) Help with xml files Data Profile Multiple uses of forest plots in presenting analysis results in health research: A TutorialJournal of Clinical EpidemiologyVol. 117PreviewForest plots are an important graphical method in meta-analyses used to show results from individual studies and pooled analyses. Forest plots are easy and straightforward to understand because they provide tabular and graphical information about estimates of comparisons or associations, corresponding precision, and statistical significance. This visual representation also makes it easier to see variations between individual study results. Forest plots are widely used in not only systematic reviews and meta-analyses but also observational studies and clinical trials. Full-Text PDF Reply to letter to the editor “Forrest plots or caterpillar plots?”Journal of Clinical EpidemiologyVol. 121PreviewWe thank Dr Hurley's comment [1] on our tutorial [2]. A caterpillar plot is essentially a slight modification to a forest plot, with the point estimates ordered by their magnitudes. We agree with Dr Hurley that sorting the point estimates could (1) aid in the easy visualization of heterogeneity for effect sizes among the included individual studies and (2) help readers with quick intake of the 95% confidence intervals of individual studies by presenting the caterpillar legs. This type of modification to a forest plot can be especially helpful when the number of included individual studies is large and when the focus is on investigation of the general pattern of point estimates among the included studies. Full-Text PDF

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