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Obtaining data from randomised controlled trials: how much do we need for reliable and informative meta-analyses?
1Clinical Trial Service Unit, Radcliffe Infirmary, Oxford.
BMJ (Clinical Research Ed.)
|October 15, 1994
Summary
Synthesizing evidence from randomized controlled trials is crucial for assessing moderate treatment effects. Meta-analysis of individual patient data offers a robust method, minimizing bias and enhancing analytical power for clinical importance.
Area of Science:
- Clinical Trials Methodology
- Evidence Synthesis
- Biostatistics
Background:
- Randomized controlled trials (RCTs) often yield moderate treatment differences that are clinically significant but difficult to assess.
- Reliable assessment of these moderate differences necessitates substantial amounts of randomized evidence.
Purpose of the Study:
- To outline methods for reliably assessing clinically important, moderate differences in treatment outcomes from randomized controlled trials.
- To highlight the advantages of meta-analysis of individual patient data (IPD) for evidence synthesis.
Main Methods:
- Discusses the use of large prospective randomized trials and meta-analysis of past trial results.
- Emphasizes minimizing bias by including all available randomized evidence, both trials and participants.
- Proposes meta-analysis of individual patient data (IPD) as the optimal approach.
Main Results:
- Meta-analysis of IPD overcomes limitations of published data and aggregate data.
- IPD meta-analysis allows for more comprehensive and robust analyses.
- This approach requires significant time and effort but yields high-quality evidence.
Conclusions:
- Meta-analysis of individual patient data is the gold standard for assessing moderate treatment effects.
- Comprehensive evidence synthesis, including all IPD, is essential for reliable clinical decision-making.
- While resource-intensive, IPD meta-analysis provides superior insights into treatment efficacy.