imported>OAbot: Open access bot: hdl updated in citation with #oabot.

2025-03-03T03:26:14Z

Open access bot: hdl updated in citation with #oabot.

New page

{{Short description|Graphical display of scientific results}}
{{For|private plots producing forest products|Woodlot}}
[[Image:Generic_forest_plot.png|thumb|300px|alt=Generic forest plot diagram|An example forest plot of five [[odds ratios]] (squares, proportional to [[Weighting|weights]] used in meta-analysis), with the summary measure (centre line of diamond) and associated confidence intervals (lateral tips of diamond), and solid vertical line of no effect. Names of (fictional) studies are shown on the left, odds ratios and confidence intervals on the right.]]
{{Commons category|Forest plots}}

A '''forest plot''', also known as a '''blobbogram''', is a graphical display of estimated results from a number of scientific studies addressing the same question, along with the overall results.<ref>{{cite journal|title=Statistics V: Introduction to clinical trials and systematic reviews |journal=Continuing Education in Anaesthesia, Critical Care & Pain |volume=8 |issue=4 |pages=143–146 |last=Lalkhen|first=AG|doi=10.1093/bjaceaccp/mkn023 |year=2008 |doi-access=free }}</ref> It was developed for use in medical research as a means of graphically representing a [[meta-analysis]] of the results of [[randomized controlled trials]]. In the last twenty years, similar meta-analytical techniques have been applied in observational studies (e.g. [[environmental epidemiology]]) and forest plots are often used in presenting the results of such studies also.

Although forest plots can take several forms, they are commonly presented with two columns. The left-hand column lists the names of the studies (frequently [[randomized controlled trial]]s or [[epidemiology|epidemiological studies]]), commonly in chronological order from the top downwards. The right-hand column is a plot of the measure of effect (''e.g.'' an [[odds ratio]]) for each of these studies (often represented by a square) incorporating [[confidence interval]]s represented by horizontal lines. The graph may be plotted on a [[natural logarithm|natural logarithmic scale]] when using odds ratios or other ratio-based effect measures, so that the confidence intervals are symmetrical about the means from each study and to ensure undue emphasis is not given to odds ratios greater than 1 when compared to those less than 1. The area of each square is proportional to the study's weight in the meta-analysis. The overall meta-analysed measure of effect is often represented on the plot as a dashed vertical line. This meta-analysed measure of effect is commonly plotted as a diamond, the lateral points of which indicate confidence intervals for this estimate.

A vertical line representing no effect is also plotted. If the confidence intervals for individual studies overlap with this line, it demonstrates that at the given level of confidence their effect sizes do not differ from no effect for the individual study. The same applies for the meta-analysed measure of effect: if the points of the diamond overlap the line of no effect the overall meta-analysed result cannot be said to differ from no effect at the given level of confidence.

Forest plots date back to at least the 1970s. One plot is shown in a 1985 book about meta-analysis.<ref name="HedgesL1985Statistical">{{Cite book
| author = [[Larry V. Hedges]] and [[Ingram Olkin]]
| title = Statistical Methods for Meta-Analysis
| publisher = [[Academic Press]]
| year = 1985
| location = Orlando
| isbn = 978-0-12-336380-0
}}</ref>{{rp|252}}
The first use in print of the expression "forest plot" may be in an abstract for a poster at the Pittsburgh (US) meeting of the [[Society for Clinical Trials]] in May 1996.<ref>Bijnens L, Collette L, Ivanov A, Hoctin Boes G, Sylvester R (1996). Can the forest plot be simplified without losing relevant information in meta-analyses? Communication at the meeting of the SCT, Pittsburgh, Pennsylvania, 5–8 May 1996. Controlled Clinical Trials 17(2S): 124.</ref> An informative investigation on the origin of the notion "forest plot" was published in 2001.<ref name=lewisclarke>{{Cite journal
| author = [[Steff Lewis]] & Mike Clarke
| journal = [[BMJ]]
|date=June 2001
| volume = 322
| pages = 1479–1480
| title = Forest plots: trying to see the wood and the trees
| doi = 10.1136/bmj.322.7300.1479
| pmid = 11408310
| issue = 7300
| pmc = 1120528
}}</ref>
The name refers to the forest of lines produced. In September 1990, [[Richard Peto]] joked that the plot was named after a breast cancer researcher called Pat Forrest and as a result the name has sometimes been spelled "'''forrest plot'''".<ref name=lewisclarke/>

==Example==
[[File:Pre-term corticosteroid data.svg|thumb|500px|This blobbogram uses seven studies to show that corticosteroids can hasten lung development in pregnancies where a baby is likely to be [[premature birth|born prematurely]]. An [[odds ratio]] (OR) of one indicates no effect; studies with [[confidence intervals]] (horizontal lines) crossing one (vertical line) are inconclusive. Powerful studies (here, those with [[sample size|more participants]]) have narrower (shorter) confidence intervals. A study with an odds ratio of one and a very narrow confidence interval would indicate no significant effect. Here the summary and the Auckland study have narrow confidence intervals that do not cross one, indicating that these studies would be judged [[statistical significance|statistically significant]].]]

This blobbogram is from an iconic [[systematic review]]; it shows [[clinical trial]]s of the [[Preterm birth#Steroids|use of corticosteroids to hasten lung development]] in pregnancies where a baby is likely to be [[premature birth|born prematurely]]. Long ''after'' there was enough evidence to show that this treatment saved babies' lives, the evidence was not widely known and the treatment was not widely used. After a systematic review made the evidence better-known, the treatment was used more, preventing thousands of pre-term babies from dying of [[infant respiratory distress syndrome]]. However, when the treatment was rolled out in lower- and middle-income countries, it was found that more pre-term babies died. It is thought that this may be because of the higher risk of infection, which is more likely to kill a baby in places with lower-quality medical care.<ref name="Chalmers">{{cite web |url=http://www.evidentlycochrane.net/cochrane-logo-health-warning/ |title=Should the Cochrane logo be accompanied by a health warning? |author=Iain Chalmers |work=Evidently Cochrane |date=October 4, 2016}}</ref> A 2017 systematic review states that there is "little need" for further research into the usefulness of the treatment in higher-income countries, but further research is needed on how best to treat lower-income and higher-risk mothers, and optimal dosage.<ref>{{cite journal |last1=Roberts |first1=Devender |last2=Brown |first2=Julie |last3=Medley |first3=Nancy |last4=Dalziel |first4=Stuart R |title=Antenatal corticosteroids for accelerating fetal lung maturation for women at risk of preterm birth |journal=Cochrane Database of Systematic Reviews |date=21 March 2017 |doi=10.1002/14651858.CD004454.pub3|hdl=2292/34738 |hdl-access=free }}</ref>

==Reading a forest plot==
===Study identities===
Studies included in the meta-analysis and incorporated into the forest plot will generally be identified in [[chronological order]] on the left hand side by author and date. There is no significance given to the vertical position assumed by a particular study.

===Standardized mean difference===
The chart portion of the forest plot will be on the right hand side and will indicate the mean difference in effect between the [[scientific control|test and control groups]] in the studies. A more precise rendering of the data shows up in number form in the text of each line, while a somewhat less precise graphic representation shows up in chart form on the right. The vertical line ([[y-axis]]) indicates no effect. The horizontal distance of a box from the y-axis demonstrates the difference between the test and control (the experimental data with control data subtracted out) in relation to no observable effect, otherwise known as the magnitude of the experimental effect.

====Confidence interval whiskers====
The thin horizontal lines—sometimes referred to as whiskers—emerging from the box indicate the magnitude of the [[confidence interval]]. The longer the lines, the wider the confidence interval, and the less reliable the data. The shorter the lines, the narrower the confidence interval and the more reliable the data.

If either the box or the confidence interval whiskers pass through the y-axis of no effect, the study data is said to be [[statistical significance|statistically insignificant]].

====Weight====
The meaningfulness of the study data, or [[statistical power|power]], is indicated by the weight (size) of the box. More meaningful data, such as those from studies with greater [[Sample size determination|sample sizes]] and smaller confidence intervals, is indicated by a larger sized box than data from less meaningful studies, and they contribute to the pooled result to a greater degree.

===Heterogeneity===
The forest plot is able to demonstrate the degree to which data from multiple studies observing the same effect overlap with one another. Results that fail to overlap well are termed [[homogeneity (statistics)|heterogeneous]] and is referred to as the [[homogeneity (statistics)|heterogeneity]] of the data—such data is less conclusive. If the results are similar between various studies, the data is said to be [[homogeneity (statistics)|homogeneous]], and the tendency is for these data to be more conclusive.

The heterogeneity is indicated by the I<sup>2</sup>. A heterogeneity of less than 50% is termed low, and indicates a greater degree of similarity between study data than an I<sup>2</sup> value above 50%, which indicates more dissimilarity.

== See also ==
* [[Galbraith plot]]
* [[Funnel plot]]
* The [[Cochrane (organisation)]] logo is a forest plot
* A forest plot helps determine whether [[further research is needed]]

== References ==
{{Reflist}}

== External links ==
*[http://www.meta-analysis-made-easy.com MIX 2.0] – software to perform meta-analysis and create forest plots in Excel.
*[http://www.epigear.com MetaXL] – Software that can create forest plots and run bias adjusted meta-analyses

{{Statistics|descriptive}}

[[Category:Meta-analysis]]
[[Category:Statistical charts and diagrams]]
[[Category:Systematic review]]

Forest plot - Revision history

imported>OAbot: Open access bot: hdl updated in citation with #oabot.