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Interpreting measures of treatment effect

H T Davies1

  • 1Department of Management, University of St Andrews, Fife.

Hospital Medicine (London, England : 1998)
|October 17, 1998
PubMed
Summary

Understanding clinical trial effect sizes is crucial. This paper clarifies absolute and relative measures, emphasizing the importance of initial risk for accurate interpretation of study findings.

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Area of Science:

  • Clinical trials and systematic reviews
  • Biostatistics
  • Evidence-based medicine

Background:

  • Numerous effect size measures exist for clinical studies.
  • Absolute and relative measures can yield different numerical results and convey distinct messages.

Purpose of the Study:

  • To describe the role and meaning of various effect size measures.
  • To provide guidance on interpreting these measures.
  • To highlight the significance of baseline risk in effect size assessment.

Main Methods:

  • Literature review and conceptual analysis of statistical measures.
  • Explanation of absolute risk reduction (ARR) and number needed to treat (NNT).
  • Explanation of relative risk reduction (RRR), relative risk (RR), and odds ratio (OR).

Main Results:

  • Different effect size measures provide varying numerical outcomes.
  • Interpretation of measures is influenced by the choice of metric.
  • Initial risk significantly impacts the perception and understanding of treatment effects.

Conclusions:

  • Clear understanding of absolute and relative effect sizes is essential for evidence appraisal.
  • Consideration of baseline risk is critical for accurate interpretation of clinical trial results.
  • Standardized reporting and interpretation of effect sizes can improve clinical decision-making.

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