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Difficulty: EasyMeasures of Disease Frequency and Association

A clinical study evaluates a novel prophylactic drug for episodic tension-type headaches among 200 adult participants over a 6-month period. Participants are equally divided into two groups. In the group receiving the standard placebo, 30 out of 100 participants experience a severe headache episode. In the group receiving the novel prophylactic drug, 10 out of 100 participants experience a severe headache episode. Based on these findings, what is the number needed to treat (NNT) to prevent one severe headache episode?

Answer: 5 patients

Answer

5
The Number Needed to Treat (NNT) is the number of patients who must receive a particular therapy for one additional patient to benefit. It is calculated as 1 divided by the Absolute Risk Reduction (ARR). In this study, the ARR is the difference between the control event rate (30%) and the experimental event rate (10%), which equals 20% (0.20). Therefore, the NNT is 10.20=5\frac{1}{0.20} = 5.

Step-by-Step Solution

1
Calculate the event rate in the control (placebo) group.
CER=30100=0.30CER = \frac{30}{100} = 0.30
This establishes the baseline risk of the outcome without the intervention.
2
Calculate the event rate in the experimental (drug) group.
EER=10100=0.10EER = \frac{10}{100} = 0.10
This establishes the risk of the outcome with the intervention.
3
Calculate the Absolute Risk Reduction (ARR).
ARR=CER−EER=0.30−0.10=0.20ARR = CER - EER = 0.30 - 0.10 = 0.20
ARR represents the absolute difference in risk between the two groups.
4
Calculate the Number Needed to Treat (NNT).
NNT=1ARR=10.20=5NNT = \frac{1}{ARR} = \frac{1}{0.20} = 5
NNT is the inverse of the ARR, representing the number of patients who need to receive the treatment to prevent one additional negative outcome.

Key Concept

The Number Needed to Treat (NNT) is calculated as the inverse of the Absolute Risk Reduction (NNT=1ARRNNT = \frac{1}{ARR}), representing the number of patients that must be treated to prevent one additional adverse outcome.
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Topics

Measures of Disease Frequency and Association

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