Evidence-Based Reviews

Can you interpret confidence intervals? It’s not that difficult

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NNT—medicine’s ‘secret stat’—offers infinite possibilities for clinical practice.


 

References

Number needed to treat (NNT) is a measure of clinical effect that has been called medicine’s “secret stat”(Box 1).1,2 By itself, however, the NNT provides no information about whether a trial result is probably true (statistical significance). If a NNT is statistically significant, the confidence interval (CI) can tell you the range of numbers within which the truth probably lies.

In the March 2007 issue of Current Psychiatry, we described how to use NNT to interpret and apply research data in daily practice.3 In this article, we explain the “secrets” of NNT and CI by providing sample calculations and several figures for visual learning. For illustration, we analyze data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) in schizophrenia, this time focusing on phase 2E—the efficacy pathway in which patients were randomly assigned to open-label clozapine or a double-blinded second-generation antipsychotic (SGA).4

Confidence intervals: Is the NNT statistically significant?

To find out a NNT’s statistical significance, you can examine the CI. A 95% CI means that the truth lies between the interval’s lower and upper bounds with a 95% probability.

Calculating CI. Although formulas to calculate the CI appear complicated,5 they are easily inserted into a Microsoft Excel-brand spreadsheet. Useful alternatives are online calculators (seeRelated Resources), which can be downloaded to your hand-held device or pocket PC.

Box 1

Number needed to treat: Not so secret anymore

Time magazine recently declared NNT as medicine’s “secret stat.”1 NNT allows us to place a number on how often we would see a difference between 2 interventions.

In a handbook on essentials of evidence-based clinical practice, Guyatt et al2 define NNT as “the number of patients who must receive an intervention of therapy during a specific period of time to prevent 1 adverse outcome or produce 1 positive outcome.”

If a difference in therapeutic outcome is seen once in every 5 patients treated with 1 intervention vs another (NNT of 5), it will likely influence day-to-day practice. However, if a therapeutic difference occurs in 1 of every 100 patients (NNT of 100), the difference between 2 treatments is not usually of great concern (except, for example, in assessing immunization against a rare but very dangerous illness).

A 95% CI of 5 to 15 means we are dealing with a NNT that with 95% probability falls between 5 and 15. However, if the NNT is not statistically significant, it becomes more difficult to describe the CI.6 A non-statistically significant NNT would have a CI that includes a negative number and a positive number: When comparing intervention A with intervention B, A might be better than B or B might be better than A. One bound of the CI may be a NNT of 10 and the other may be –10. It would be tempting to describe the CI as –10 to 10, but this would be misleading.

Attributable risk. NNT is calculated by taking the reciprocal of the difference between 2 rates for a particular outcome (Box 2). This difference is known as the attributable risk (AR). We can calculate a 95% CI for the AR, and the AR is considered statistically significant if both ends of the 95% CI are positive or both ends are negative.

If the 95% CI includes zero, then the AR is considered not statistically significant.

An AR value of zero means the rates of the outcome of interest are the same for the 2 interventions (there is no difference). Translating this to NNT would mean that no matter how many patients you treat with 1 intervention versus the other, you will not see a difference on the outcome of interest. The NNT would be “infinite” (represented by the symbol “∞”). Mathematically, if we tried to calculate the NNT when AR was zero, we would be trying to calculate the reciprocal of zero.

CI in CATIE’s efficacy phase

What do NNT and CI calculations tell us about data from clinical trials such as CATIE for schizophrenia? In CATIE, 1,493 patients were randomly assigned to 1 of 5 antipsychotics—perphenazine, olanzapine, quetiapine, risperidone, or ziprasidone—for up to 18 months. Patients who received an SGA and discontinued phase 1 before 18 months could participate in phase 2:

  • Those who discontinued because of poor symptom control were expected to enter the efficacy arm (2E) and receive open-label clozapine (n = 49) or an SGA not taken in phase 1 (n = 50).
  • Those who discontinued phase 1 because of poor tolerability (n = 444) were expected to enter the tolerability arm (2T), and receive an SGA they had not taken in phase 1.

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