Can we individualize the ‘number needed to treat’? An empirical study of summary effect measures in meta-analyses | Zendy

Toshi A. Furukawa | Zendy; Gordon Guyatt | Zendy; Lauren E. Griffith | Zendy

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Can we individualize the ‘number needed to treat’? An empirical study of summary effect measures in meta-analyses

Author(s) -

Toshi A. Furukawa,

Gordon Guyatt,

Lauren E. Griffith

Publication year - 2002

Publication title -

international journal of epidemiology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.406

H-Index - 208

eISSN - 1464-3685

pISSN - 0300-5771

DOI - 10.1093/ije/31.1.72

Subject(s) - meta analysis , medicine , medline , biology , biochemistry

Meta-analyses summarize the magnitude of treatment effect using a number of measures of association, including the odds ratio (OR), risk ratio (RR), risk difference (RD) and/or number needed to treat (NNT). In applying the results of a meta-analysis to individual patients, some textbooks of evidence-based medicine advocate individualizing NNT, based on the RR and the patient's expected event rate (PEER). This approach assumes constant RR but no empirical study to date has examined the validity of this assumption.

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