Number needed to treat

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Overview

The number needed to treat (NNT) is an epidemiological measure that indicates how many patients would require treatment with a form of medication to reduce the expected number of cases of a defined endpoint by one. It is defined as the inverse of the absolute risk reduction. It was described in 1988.[1]

For example, consider a hypothetical drug which reduces the risk of colon cancer by 50%. Even without the drug, colon cancer is fairly rare, maybe 1 in 3,000 in every 5 year period. The NNT for a 5-year treatment with the drug is therefore 6,000: by treating 6,000 people with the drug, one can expect to reduce the number of colon cancer cases from 2 to 1.

In general, NNT is always computed with respect to two treatments A and B, with A typically a drug and B a placebo (in our example above, A is a 5-year treatment with the hypothetical drug, and B is no treatment). A defined endpoint has to be specified (in our example: the appearance of colon cancer in the 5 year period). If the probabilities pA and pB of this endpoint under treatments A and B, respectively, are known, then the NNT is computed as 1/(pB-pA).

The NNT is an important measure in pharmacoeconomics. If a clinical endpoint is devastating enough (e.g. death, heart attack), drugs with a high NNT may still be indicated in particular situations. If the endpoint is minor, health insurers may decline to reimburse drugs with a high NNT.

Worked example

Abbreviation Variable Equation Value
- subjects in control group - 250
- subjects in experimental group - 150
- events in control group - 100
- events in experimental group - 15
CER control event rate = events / subjects in control group 0.4, or 40%
EER experimental event rate = events / subjects in experimental group 0.1, or 10%
ARR absolute risk reduction (or increase) = CER - EER 0.3, or 30%
RRR relative risk reduction (or increase) = (CER - EER) / CER 0.75
NNT number needed to treat/number needed to harm = 1 / ARR 3.33
OR, RR odds ratio, relative risk (not really identical, but similar -- see articles for details) = CER / EER 4

See also

Reference

  1. Laupacis A, Sackett DL, Roberts RS. An assessment of clinically useful measures of the consequences of treatment. N Engl J Med 1988;318:1728-33. PMID 3374545.

External links


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Acknowledgement and Attribution Regarding Sources of Content

Some of the initial content on this page may be incorporated in part from copyleft sources in the public domain including wikis such as Wikipedia and AskDrWiki. Drug information for patients came from the The National Library of Medicine. Infectious disease information may have come from the Centers for Disease Control (CDC). Differential Diagnoses are drawn from clinicians as well as an amalgamation of 3 sources: 1.The Disease Database; 2. Kahan, Scott, Smith, Ellen G. In A Page: Signs and Symptoms. Malden, Massachusetts: Blackwell Publishing, 2004:3; 3. Sailer, Christian, Wasner, Susanne. Differential Diagnosis Pocket. Hermosa Beach, CA: Borm Bruckmeir Publishing LLC, 2002:7 .

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