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The number needed to treat—the number of patients who must be treated to prevent one adverse outcome—is a widely used measure. 1 2 It is increasingly being calculated by pooling absolute risk differences in trials included in meta-analyses. 3 4 This option is available in statistical software and the Cochrane Database of Systematic Reviews . 5 6 In this paper, we examine pooled numbers needed to treat derived from trials and meta-analyses of interventions to prevent cardiovascular disease. We show that a pooled number needed to treat may be misleading because of variation in the event rates in trials, differences in the outcomes considered, effects of secular trends on disease risk, and differences in clinical setting. The number needed to treat should be derived by applying the relative risk reductions from treatment which have been estimated by trials or meta-analysis to relevant baseline risks for different types of patients. This provides a range of possible numbers needed to treat in different patient groups. ### Summary points Numbers needed to treat are often used to summarise treatment effects in a clinically relevant way They are derived from the baseline risk without treatment and the reduction in risk achieved with treatment Numbers needed to treat are sensitive to factors that change the baseline risk such as the outcome considered, patients' characteristics, secular trends in incidence and case fatality, and the clinical setting Pooled numbers needed to treat derived from meta-analyses can be seriously misleading because the baseline risk often varies appreciably between the trials Applying the pooled relative risk reductions calculated from meta-analyses or individual trials to the baseline risk relevant to specific patient group produces a useful number needed to treat The interventions selected for study were use of statins for lowering cholesterol concentrations in primary and secondary prevention of coronary heart disease.7 …
Smeeth et al. (Sat,) studied this question.