The use of numbers needed to treat derived from systematic reviews and meta-analysis. Caveats and pitfalls

Eval Health Prof. 2001 Jun;24(2):152-64. doi: 10.1177/01632780122034858.

Abstract

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.

MeSH terms

  • Clinical Trials as Topic
  • Evidence-Based Medicine
  • Humans
  • Meta-Analysis as Topic*
  • Methods
  • Randomized Controlled Trials as Topic
  • Risk Assessment
  • Treatment Outcome