Jul 11, 2016 · Understand how to read a forest plot and what the results displayed mean both at the level of individual studies and the averaged result; Understand why forest plots look different depending on the statistics being analysed; Understand the importance of heterogeneity within forest plots and how it affects interpretation

A forest plot, also known as a blobbogram, is a graphical display of estimated results from a number of scientific studies, number of end points and number of subgroups addressing the same question, along with the overall results.

Forest plots have become common in the pharmaceutical industry as a way of comparing the relative strength of treatment effect by providing a visual representation of the amount of variation between different groups.

Apr 2, 2023 · Click "Generate Forest Plot" to create a forest plot based on the input data. Click "Download Forest Plot" to download the generated forest plot as a PNG image. Pooled Risk Ratio: The weighted average of the risk ratios from all studies. 95% CI: The 95% confidence interval for the pooled risk ratio.

A forest plot is a useful graphical display of findings from a meta-analysis. It provides essential information to inform our interpretation of the results. Typically, a forest plot contains 6 basic “columns”, though additional columns can be added to provide more information.

Forest plots (FPs) are graphical displays originally developed for meta-analyses to present results obtained from multiple clinical trials addressing the same question or endpoint.1,2,10 Today FPs are considered one of the “gold standard” tools for the publication and presentation of meta-analyses of randomized controlled clinical trials.

Mar 10, 2025 · Learn to interpret forest plots effectively by understanding key components, effect sizes, confidence intervals, and data variation for accurate analysis. Forest plots are essential tools in meta-analyses, offering a visual summary of results from multiple studies.

Jan 5, 2022 · In this editorial, we start with introducing the anatomy of a forest plot and present 5 tips for understanding the results of a meta-analysis. We demonstrate the components of a typical...

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 heterogeneous and is referred to as the heterogeneity of the data—such data is less conclusive.

Dec 7, 2012 · The primary outcome measure was the presence of complications, including wound infection, perforated appendicitis, or peritonitis. Four randomised controlled trials were identified. 1 The results of the meta-analysis for complications were presented in a forest plot. ⇓