Number Needed to Treat
Chart overview
Number Needed to Treat plots translate absolute risk reduction into clinically intuitive NNT and NNH values, showing how many patients must be treated to achieve one additional benefit or cause one additional harm.
Key points
- Evidence-based medicine practitioners and clinical pharmacologists use NNT visualizations to communicate treatment effect magnitude in a patient-centered way, especially when comparing interventions across multiple outcomes in systematic reviews.
Example Visualization
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"Create a number needed to treat (NNT/NNH) plot from my data. Display each outcome as a horizontal bar centered at the NNT or NNH value with confidence interval whiskers. Use a diverging layout with NNT benefit values plotted in one direction and NNH harm values in the opposite direction. Label each outcome on the y-axis and add a vertical reference line at the origin. Use journal formatting with Arial font and no top or right spines."
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Python Code Example
Console Output
Figure saved: plotivy-number-needed-to-treat.png
Common Use Cases
- 1Summarizing absolute treatment effects across multiple outcomes for clinical guidelines panels
- 2Comparing NNT values across competing pharmacological interventions in formulary decisions
- 3Communicating treatment benefits and harms simultaneously for patient decision aids
- 4Presenting subgroup NNT analyses in randomized controlled trial publications
Pro Tips
Use a log scale for the NNT axis when values span a wide range to maintain visual proportion
Distinguish NNT from NNH with contrasting colors such as green and red consistently
Annotate any infinite NNT (no significant absolute risk reduction) with a special symbol
Include absolute risk difference and event rates in a supplementary table linked to each NNT estimate
Scientific Chart Selection Cheat Sheet
Not sure whether to use a Violin Plot, Box Plot, or Ridge Plot? Download our single-page reference mapping the most-used scientific chart types, exactly when to use them, and the core Matplotlib/Seaborn functions.