Presentation of clinical data can have a profound effect on treatment decisions, and there is a need for measures that are objective, have clinical relevance, and are easily interpreted. Relative risk is often used to summarize treatment comparisons, but does not account for variations in baseline risk profiles and does not convey information on absolute sizes of treatment effects. Absolute risk reduction gives this information, but the data are dimensionless and abstract, and lack a direct connection with the clinical environment.The number needed to treat, or NNT, has been developed to address this issue. NNT is the reciprocal of the absolute risk reduction associated with an intervention, and may also be calculated as 100 divided by the absolute risk reduction expressed as a percentage. The result is the number of patients who would have to receive treatment for one of them to benefit or to avoid an adverse outcome over a given period of time. Since its introduction, the concept of NNT has been expanded to include number needed to harm (NNH), which illustrates adverse events or other undesirable outcomes associated with treatment, and the epidemiologic tool of number needed to screen.NNT has been used to describe treatment effects from many clinical trials. A recent example illustrates benefit of inhaler therapy combining a long-acting beta(2)-agonist (LABA) and corticosteroid for COPD over treatment with LABA alone. NNT has also been extended to systematic reviews and meta-analyses, where it has been used to rank different treatments where baseline profiles, treatment outcomes and time periods under examination are similar.NNT is therefore a concise and easily understood tool for quantifying treatment efficacy, particularly when applying trial results to the clinic setting.