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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

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The number needed to harm: is it too optimistic?

¹Department of Medicine, University of Western Ontario, London, Canada. dmassel@lhsc.on.ca

The Canadian Journal of Cardiology

|February 5, 2004

Summary

This summary is machine-generated.

The number needed to treat (NNT) and number needed to harm (NNH) help interpret clinical trial outcomes. NNH quantifies patient harm from treatments, but may underestimate true risks.

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Area of Science:

Clinical research methodology
Medical statistics
Pharmacovigilance

Background:

Clinical trials assess therapeutic benefits and risks.
Interpreting treatment outcomes requires understanding both positive and negative effects.
Existing metrics like NNT focus on benefits, necessitating complementary harm assessment.

Purpose of the Study:

To introduce and define the number needed to harm (NNH) as a measure for adverse outcomes in clinical trials.
To highlight the relationship between NNH and the absolute risk increase.
To discuss the potential limitations of NNH in reflecting true therapeutic risks.

Main Methods:

Conceptual definition of NNH based on absolute risk increase.
Comparison of NNH with the number needed to treat (NNT).
Discussion of the interpretation of NNH in the context of experimental vs. control treatments.

Main Results:

NNH is defined as the reciprocal of the absolute risk increase.
NNH represents the number of patients exposed to an experimental treatment for one additional harm event.
NNH may present an optimistic view of treatment-related risks.

Conclusions:

NNH is a valuable metric for quantifying patient harm in clinical studies.
Understanding NNH is crucial for a balanced interpretation of treatment efficacy and safety.
Further consideration is needed to address the potential underestimation of risks by NNH.