Letters

Numbers needed to treat derived from meta-analysis

BMJ 1999; 319 doi: http://dx.doi.org/10.1136/bmj.319.7218.1199a (Published 30 October 1999) Cite this as: BMJ 1999;319:1199

Are an absurdity

  1. Bruce G Charlton, lecturer ([email protected])
  1. Department of Psychology, University of Newcastle upon Tyne, Newcastle upon Tyne NE1 7RU
  2. The Surgery, Leiston, Suffolk IP16 4ES
  3. The Surgery, Aldeburgh, Suffolk
  4. ICRF/NHS Centre for Statistics in Medicine, Institute of Health Sciences, Oxford OX3 7LF
  5. Pain Research, Churchill, Oxford OX3 7LJ

    EDITOR—Better late than never. Several years ago one group of epidemiologists put forward the number needed to treat (NNT) derived from megatrials and meta-analysis as a summary statistic suitable for expressing the effectiveness of medical interventions; now another group of epidemiologists has at long last realised that the NNT is seldom a valid measure.1

    Some of us came to the conclusion that NNTs were “not necessarily true” rather more rapidly, and without the need for three and a half pages of cumbersome and dubiously appropriate statistical analysis.2 The deep flaws in the NNT statistic can be understood by a straightforward act of inference based on an understanding of the relevant clinical science and guided by the principle of “garbage in, garbage out.”

    The spurious precision of the NNT is a statistical artefact which derives not from clinical knowledge but from the illegitimate pooling of the large amounts of qualitatively unlike and clinically irrelevant data that are incorporated in almost all megatrials and meta-analyses Unless trials incorporate patients with the same characteristics and the same prognosis and who are being given the same treatment as those to which the trial results will apply, then statistical summary is inevitably misleading.2

    It is somewhat galling that mega-epidemiologists and biostatisticians so routinely take credit for the act of creating spurious analytic tools, and then for belatedly dismantling them—but so it goes. The wheels of epidemiology grind exceedingly slow. At least Smeeth et al got there in the end.

    When clinical epidemiology gives up its grandiose and self awarded claim to be “evidence-based medicine” and once again becomes an activity based in clinical science, such absurdities may become a thing of the past I hope so.

    References

    1. 1.
    2. 2.

    Using patient years may also be misleading

    1. Kevork Hopayian, general practitioner ([email protected]),
    2. John McGough, general practitioner ([email protected])
    1. Department of Psychology, University of Newcastle upon Tyne, Newcastle upon Tyne NE1 7RU
    2. The Surgery, Leiston, Suffolk IP16 4ES
    3. The Surgery, Aldeburgh, Suffolk
    4. ICRF/NHS Centre for Statistics in Medicine, Institute of Health Sciences, Oxford OX3 7LF
    5. Pain Research, Churchill, Oxford OX3 7LJ

      EDITOR—Smeeth et al showed how inappropriate methods of calculating numbers needed to treat (NNTs) in systematic …

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