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Forest Plot Interpretation Guide

Jun 18, 2025

Overview

This lecture explains how to interpret forest plots, commonly used in systematic reviews and meta-analyses, by breaking down their descriptive, graphical, and statistical components.

Components of a Forest Plot

  • Each study in a systematic review is represented by a single line in the forest plot.
  • The left zone displays descriptive information about each study, including summary data.
  • The right (graphical) zone presents study results visually.
  • The bottom left area summarizes the statistical results for all studies combined.

Interpreting Study Data

  • Raw data from each study (e.g., intervention vs. control groups) is summarized in the left zone.
  • Study results are commonly shown as risk ratios, with point estimates and 95% confidence intervals.
  • Both the numerical results and graphical representations display these key figures for each study.

Weighting of Studies

  • Each study’s contribution to the meta-analysis is weighted, usually based on the inverse of variance.
  • Larger studies typically have greater weight, represented by larger boxes in the graphical area.
  • The size of each study’s box corresponds to its weight, and horizontal lines show confidence intervals.

Understanding the Graphical Area

  • The middle vertical line is the "line of no effect" (value = 1 for risk ratios, 0 for mean differences).
  • Labels at the bottom indicate which direction favors the experimental or control group.
  • The position of each box and its confidence interval relative to the line of no effect indicate statistical significance.

Meta-analytic Summary

  • The overall meta-analytic estimate is shown as a diamond, with its width representing the confidence interval.
  • If the diamond crosses the line of no effect, the result is not statistically significant.
  • The summary table includes total weights, event rates, combined effect estimate, and confidence interval.

Heterogeneity

  • Tests for heterogeneity assess consistency among study results and are typically shown in a separate section.
  • Results of heterogeneity tests are given, but details are not covered in this lecture.

Key Terms & Definitions

  • Forest Plot — A graphical summary of individual study results within a meta-analysis.
  • Meta-analysis — A statistical method for combining results from multiple studies.
  • Risk Ratio — The ratio of the probability of an event occurring in the intervention group versus the control group.
  • Confidence Interval — A range that estimates the true effect size with a specified probability (usually 95%).
  • Line of No Effect — The value where the intervention has no difference from control (e.g., risk ratio = 1).
  • Heterogeneity — Variation in study outcomes beyond chance.

Action Items / Next Steps

  • Watch the separate video on heterogeneity for further understanding.
  • Contact the instructor with questions via the course website or blog contact section.