Simpson's paradox and calculation of number needed to treat from meta-analysis.
Simpson's paradox and calculation of number needed to treat from meta-analysis.
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DOI：
10.1186/1471-2288-2-1
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发表时间：
2002
影响因子：
4
通讯作者：
Cates CJ
中科院分区：
文献类型：
--
作者：
Cates CJ
从荟萃分析中计算需要治疗的人数（NNT）比从单一试验中计算更复杂。当试验组不平衡时，将数据视为来自一项试验可能会导致误导性结果。一个例子是从发表的科克伦审查，其中戒烟的护理干预的好处是由正式的荟萃分析的个人试验结果。然而，如果这些患者被加在一起，就好像他们都来自一个试验，效果的方向似乎是相反的（由于辛普森悖论）。虽然荟萃分析的NNT可以从汇总的风险差异中计算，但这不太可能是一种稳定的方法，除非对照组的事件发生率非常相似。由于在实践中事件发生率差异很大，因此提倡使用相对度量，如比值比或相对风险。这些可以应用于不同水平的基线风险，以生成用于治疗的风险特异性NNT。应明确说明从荟萃分析中计算NNT的方法，并应避免将来自单独试验的患者添加到一起，好像他们都来自一项试验。
Calculation of numbers needed to treat (NNT) is more complex from meta-analysis than from single trials. Treating the data as if it all came from one trial may lead to misleading results when the trial arms are imbalanced. An example is shown from a published Cochrane review in which the benefit of nursing intervention for smoking cessation is shown by formal meta-analysis of the individual trial results. However if these patients were added together as if they all came from one trial the direction of the effect appears to be reversed (due to Simpson's paradox). Whilst NNT from meta-analysis can be calculated from pooled Risk Differences, this is unlikely to be a stable method unless the event rates in the control groups are very similar. Since in practice event rates vary considerably, the use a relative measure, such as Odds Ratio or Relative Risk is advocated. These can be applied to different levels of baseline risk to generate a risk specific NNT for the treatment. The method used to calculate NNT from meta-analysis should be clearly stated, and adding the patients from separate trials as if they all came from one trial should be avoided.