Meta-analysis: The fashion of summing-up evidence. Part II: Interpretations and uses

R. D. Gelber, A. S. Coates, A. Goldhirsch

Research output: Contribution to journalArticle

Abstract

In this commentary, we use evidence produced by the Early Breast Cancer Trialists' Collaborative Group (EBCTCG) ten-year update of a meta-analysis of trials of adjuvant therapies for early breast cancer which started prior to 1985 to illustrate aspects of interpretations and uses of meta-analysis results. The following issues are discussed: i) The meta-analysis provides an average summary for the effect of a treatment. Greater statistical power is obtained by increasing the number of events contributing to the analysis. However, summing up the results of various trials necessitates the loss of individual information concerning the magnitude of treatment effects which depend on tumor- and patient-related factors. Subgroup analyses within the meta-analysis process allow some recovery of such features; ii) The absolute benefit obtained from an effective treatment depends not only on the relative benefit of the treatment but also on the prognosis of the individual patients; iii) The results are more immediately applicable if less reliance is placed on the arithmetic construct inherent in the overview, using instead unconfounded information about the value of treatments actually administered. This avoids the need to extrapolate the effect for one component of the therapy by assuming a lack of interaction with its other components; iv) Although indirect comparisons between different meta-analyses are regularly made to pick the 'winner' from among tested treatment modalities, it is unlikely that the optimal therapeutic regimen can be defined via such indirect comparisons, though such comparisons may raise interesting, testable hypotheses.

Original languageEnglish
Pages (from-to)683-691
Number of pages9
JournalAnnals of Oncology
Volume3
Issue number9
Publication statusPublished - 1992

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ASJC Scopus subject areas

  • Cancer Research
  • Oncology
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Public Health, Environmental and Occupational Health
  • Neuropsychology and Physiological Psychology
  • Hematology

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