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Show me the evidence: using number needed to treat
1Department of Psychiatry, New York University School of Medicine, USA. citrome@nki.rfmh.org
Southern Medical Journal
|October 2, 2007
Summary
This review explains Number Needed to Treat (NNT) and Number Needed to Harm (NNH), essential evidence-based medicine tools. These metrics simplify understanding treatment benefits and risks from clinical trial data.
Area of Science:
- Evidence-Based Medicine
- Clinical Trial Analysis
- Biostatistics
Background:
- Number Needed to Treat (NNT) and Number Needed to Harm (NNH) are crucial metrics in evidence-based medicine.
- These tools help interpret binary outcomes from clinical studies, such as treatment efficacy and adverse event rates.
- Understanding NNT and NNH aids clinicians in making informed treatment decisions.
Purpose of the Study:
- To review the calculation and interpretation of NNT and NNH.
- To highlight the utility of these metrics in assessing treatment effects and potential harms.
- To demonstrate the application of NNT and NNH using a major clinical trial.
Main Methods:
- Discussion of absolute versus relative risk and P-values.
- Explanation of the mechanics for calculating NNT and NNH.
- Application of NNT and NNH to data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study.
Main Results:
- NNT and NNH provide a straightforward method for evaluating binary outcomes in medical literature.
- Online resources and calculators facilitate the determination of confidence intervals for NNT and NNH.
- The CATIE trial serves as a practical example for applying these statistical measures.
Conclusions:
- NNT and NNH are fundamental tools for evidence-based medical practice.
- These metrics enhance the clinical interpretation of treatment benefits and risks.
- The calculation and application of NNT and NNH are essential for evidence-based decision-making.
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