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Numbers needed to treat derived from meta-analysis: a word of caution
  1. Arthur Marx, MD, MPH,
  2. Heiner C Bucher, MD, MPH
  1. Basel Institute for Clinical Epidemiology, Basel, Switzerland

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    In clinical trials, treatment effects from binary outcomes, such as “alive” or “dead”, can be presented in various ways (eg, relative risk reduction [RRR] and absolute risk reduction [ARR]).1–2 (See glossary for definitions and calculations). Alternatively, the number needed to treat (NNT) is an expression of the number of patients who need to be treated to prevent one additional adverse event.2–4 Mathematically, the NNT equals the reciprocal of the ARR. Many journals now report results from clinical trials using the NNT, along with 95% confidence intervals (CIs).5

    Since its introduction,3 a debate has ensued whether reporting NNTs from meta-analyses is misleading.4,6,7 ACP Journal Club and Evidence-Based Medicine have devoted attention to this debate, and methodological questions have been raised in various review discussions and commentaries.8–9 The objective of this editorial is to provide Evidence-Based Medicine readers with caveats and suggestions when applying NNTs from a meta-analysis to an individual patient. We highlight 2 problems. Firstly, NNTs from a meta-analysis are subject to variation in risk differences among the studies included in the meta-analysis as well as in baseline risks. Secondly, applying NNTs to an individual requires adjustment for their baseline risk.

    NNTs derived from meta-analyses are affected …

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