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On reporting of effect size in randomized clinical trials
George A Diamond1, Sanjay Kaul
1Division of Cardiology, Cedars-Sinai Medical Center and University of California, Los Angeles, California, USA. george.a.diamond@gmail.com
The American Journal of Cardiology
|December 4, 2012
Summary
Composite effect size measures better convey clinical importance in randomized trials than statistical significance (p values). Standard measures like relative risk reduction are often missing, while composite metrics offer clearer insights into treatment impact.
Area of Science:
- Biostatistics
- Clinical Trial Analysis
- Evidence-Based Medicine
Background:
- Randomized clinical trial reports often prioritize statistical significance (p-values) over effect size magnitude.
- Clinical importance of trial evidence is more dependent on effect size than statistical significance.
- Standard effect size measures include relative risk reduction and absolute risk reduction.
Purpose of the Study:
- To compare standard effect size measures (relative and absolute risk reduction) and novel composite measures with statistical significance.
- To evaluate the reporting frequency of different measures in high-impact medical journals.
- To assess how effectively different measures communicate clinical importance.
Main Methods:
- Analysis of 100 randomized clinical trials published in The New England Journal of Medicine.
- Comparison of reporting rates for p-values, relative risk reduction, and absolute risk reduction.
- Assessment of correlations between standard effect size measures, composite measures, and statistical significance.
Main Results:
- P-values were reported in 100% of trials, relative risk reduction in 89%, and absolute risk reduction in 39%.
- Only 35% of trials reported both standard measures; none reported composite measures.
- Composite measures showed high correlation (1.3% unexplained variance) but weak correlation with statistical significance (83% unexplained variance).
- 25% of statistically significant results were deemed clinically unimportant.
Conclusions:
- Composite measures of effect size are superior to conventional risk reduction assessments and statistical significance.
- Composite measures better communicate the clinical importance of randomized trial results.
- Current reporting practices in major journals inadequately convey the clinical impact of trial findings.
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