Calculating confidence intervals for the number needed to treat

The number needed to treat (NNT) has gained much attention in the past years as a useful way of reporting the results of randomized controlled trials with a binary outcome. Defined as the reciprocal of the absolute risk reduction (ARR), NNT is the estimated average number of patients needed to be treated to prevent an adverse outcome in one additional patient. As with other estimated effect measures, it is important to document the uncertainty of the estimation by means of an appropriate confidence interval. Confidence intervals for NNT can be obtained by inverting and exchanging the confidence limits for the ARR provided that the NNT scale ranging from 1 through infinity to -1 is taken into account. Unfortunately, the only method used in practice to calculate confidence intervals for ARR seems to be the simple Wald method, which yields too short confidence intervals in many cases. In this paper it is shown that the application of the Wilson score method improves the calculation and presentation of confidence intervals for the number needed to treat. (C) Elsevier Science Inc. 2001.