The use of numbers needed to treat derived from systematic reviews and meta-analysis. Caveats and pitfalls.
Numbers needed to treat (NNTs) may be used to present the effects of treatment and are the reciprocal of the absolute difference between treatment and control groups in a randomized controlled trial. NNTs are sensitive to factors that change the baseline risk of trial participants: the outcome considered; characteristics of patients; secular trends in incidence and case-fatality; and clinical setting. NNTs derived from pooled absolute risk differences in meta-analyses are commonly presented and easily calculated by meta-analytic software but may be seriously misleading because of heterogeneity between trials included in meta-analyses. Meaningful NNTs are obtained by applying the pooled relative risk reductions calculated from meta-analyses or individual trials to the baseline risk relevant to specific patient groups. This process will give a range of NNTs depending on whether patients are at high, low, or intermediate levels of risk, rather than a potentially misleading single number.
Ebrahim
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University of Bristol.
D002986:Clinical Trials as Topic; D019317:Evidence-Based Medicine; D006801:Humans; D015201:Meta-Analysis as Topic; D008722:Methods; D016032:Randomized Controlled Trials as Topic; D018570:Risk Assessment; D016896:Treatment Outcome