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Epidemiology:
doi: 10.1097/EDE.0b013e318225ba48
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Forest Plot Viewer: A New Graphing Tool

Boyles, Abee L.; Harris, Shawn F.; Rooney, Andrew A.; Thayer, Kristina A.

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Office of Health Assessment and Translation, National Toxicology Program, National Institute of Environmental Health Sciences, Durham, NC, boylesa@niehs.nih.gov (Boyles)

SRA International, Inc., Durham, NC (Harris)

Office of Health Assessment and Translation, National Toxicology Program, National Institute of Environmental Health Sciences, Durham, NC (Rooney, Thayer)

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To the Editor:

We would like to introduce the Forest Plot Viewer—a free program that creates figures to display point-estimate data with multiple columns of descriptive text that can be rapidly modified to display subsets of data based on filtering criteria. Figures in this format are called “forest plots” for reasons that remain somewhat obscure—perhaps because the figure summarizes a large amount of data that allows the reader to see the overall “forest” as well as the individual trees. This graphical format can be used to summarize results from several studies, or to present sets of results from a single study (for example, to show the effect of sequential adjustments1).

The most common use of forest plots is to present data in systematic reviews or meta-analyses. Several software programs can generate such plots (eg, Comprehensive Meta-Analysis, RevMan, GraphPad, and R). In general, these programs are relatively inflexible, limiting the amount of accompanying text or requiring coding skills. The National Toxicology Program needed a more flexible and user-friendly interface to create figures with multiple columns of accompanying text. We developed such a tool (Forest Plot Viewer) in collaboration with SRA International. The text-based columns allow us to concisely present important study details that are not captured in point estimates (eg, study-population specifics, basis for disease diagnosis, exposure details, key adjustment factors) and to filter the display to include subsets of a larger data file.

Forest Plot Viewer horizontally plots a point estimate, confidence interval, and up to 15 columns of text for multiple rows of data (Figure). The shape, size, color, and fill of the point estimates can be modified to indicate groups or relative weights of results. One or 2 vertical reference lines can be included to indicate the deviation of the results from the null hypothesis or a meta-analysis result. A filtering function is available to select a subset of results for display from the larger set contained in the spreadsheet (eg, allowing the user to plot only prospective studies or only those with a particular exposure). The text and figures are automatically resized to fill the window space as settings are changed. Settings files can be saved for application to other datasets, or to create several displays from the same spreadsheet. Forest Plot Viewer does not perform a formal meta-analysis, but the results of a meta-analysis can be plotted with the program.

FIGURE. Studies of P...
FIGURE. Studies of P...
Image Tools

The program is freely available for download (http://ntp.niehs.nih.gov/go/tools_forestplotviewer) along with a user manual, example data, and example-settings files. Java version 5.0 or later is required to run the program (http://www.java.com). The data file is created by the user in a spreadsheet program such as Excel, or as a text file. Images from Forest Plot Viewer can be saved as standard image (GIF, PNG, BMP, JPG), scalable vector (SVG, EMF), or PDF files for use in presentations or publications.

The National Toxicology Program relied on this program during our January 2011 Workshop on the Role of Environmental Chemicals in the Development of Diabetes and Obesity to examine the role of persistent organic pollutants in diabetes and related health outcomes.2 Experts who reviewed this literature found the software tool (and it ability to sort subcategories of studies easily during presentation) to be of great utility in evaluating a complex literature of almost 100 studies. One of the example datasets included is a subset of the studies considered during the workshop. The Figure displays studies of PCBs and diabetes related outcomes. Full references are available in the workshop materials.3

Abee L. Boyles

Office of Health Assessment and Translation, National Toxicology Program

National Institute of Environmental Health Sciences

Durham, NC

boylesa@niehs.nih.gov

Shawn F. Harris

SRA International, Inc.

Durham, NC

Andrew A. Rooney

Kristina A. Thayer

Office of Health Assessment and Translation, National Toxicology Program

National Institute of Environmental Health Sciences

Durham, NC

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REFERENCES

1.Baird DD, Travlos G, Wilson R, et al. Uterine leiomyomata in relation to insulin-like growth factor-I, insulin, and diabetes. Epidemiology. 2009;20:604–610.

2.NTP Workshop: Role of Environmental Chemicals in the Development of Diabetes and Obesity Breakout Group on Persistent Organic Pollutants (POPs). Available at: http://cerhr.niehs.nih.gov/evals/diabetesobesity/presentations/POPsFinal_508.pdf. Accessed May 18, 2011.

3.Appendix Table for Epidemiology Studies of Persistent Organic Pollutants (POPs). Available at: http://cerhr.niehs.nih.gov/evals/diabetesobesity/presentations/POPsFinal_508.pdf. Accessed May 18, 2011.

4.Uemura H, Arisawa K, Hiyoshi M, et al. Associations of environmental exposure to dioxins with prevalent diabetes among general inhabitants in Japan. Environ Res. 2008;108:63–68.

5.Jorgensen ME, Borch-Johnsen K, Bjerregaard P. A cross-sectional study of the association between persistent organic pollutants and glucose intolerance among Greenland Inuit. Diabetologia. 2008;51:1416–1422.

6.Uemura H, Arisawa K, Hiyoshi M, et al. Prevalence of metabolic syndrome associated with body burden levels of dioxin and related compounds among Japan's general population. Environ Health Perspect. 2009;117:568–573.

7.Lee DH, Lee IK, Jin SH, Steffes M, Jacobs DR Jr. Association between serum concentrations of persistent organic pollutants and insulin resistance among nondiabetic adults: results from the National Health and Nutrition Examination Survey 1999–2002. Diabetes Care. 2007;30:622–628.

8.Lee DH, Lee IK, Porta M, Steffes M, Jacobs DR Jr. Relationship between serum concentrations of persistent organic pollutants and the prevalence of metabolic syndrome among non-diabetic adults: results from the National Health and Nutrition Examination Survey 1999–2002. Diabetologia. 2007;50:1841–1851.

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© 2011 Lippincott Williams & Wilkins, Inc.

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