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A consumer's guide to subgroup analyses.

A D Oxman¹, G H Guyatt

¹McMaster University Health Sciences Centre, Hamilton, Ontario.

Annals of Internal Medicine

|January 1, 1992

Summary

This summary is machine-generated.

Clinicians face controversy interpreting subgroup analyses from randomized trials. This paper offers guidelines to assess subgroup findings, aiding treatment decisions based on evidence strength and consistency.

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Area of Science:

Clinical Trials Methodology
Biostatistics
Evidence-Based Medicine

Background:

Subgroup analyses in randomized controlled trials (RCTs) and meta-analyses are frequently used but their interpretation is debated.
Decisions on whether to act on subgroup findings can significantly impact patient care and treatment strategies.
Lack of clear guidelines complicates the clinical application of subgroup analyses.

Purpose of the Study:

To provide a framework for evaluating the credibility and clinical utility of subgroup analyses.
To guide clinicians in determining when to rely on subgroup-specific treatment effects versus overall trial results.
To enhance the rigorous interpretation of secondary findings from clinical research.

Main Methods:

Development of a set of criteria to assess the strength of inference for subgroup differences.
Consideration of factors including magnitude and statistical significance of differences, pre-specification of hypotheses, number of hypotheses tested, origin of comparisons (within vs. between studies), consistency, and supporting indirect evidence.
Application of these criteria to real-world clinical trial data (implicitly suggested by the context of clinician decision-making).

Main Results:

The strength of evidence for a treatment effect in a subgroup depends on multiple factors, not solely statistical significance.
Key factors influencing credibility include the magnitude of the effect, hypothesis pre-specification, and consistency across studies.
A systematic approach is necessary to differentiate potentially spurious findings from genuine subgroup effects.

Conclusions:

Clinicians should critically evaluate subgroup analyses using a structured set of guidelines.
These guidelines help determine whether treatment decisions should be based on overall study results or specific subgroup findings.
Adherence to these principles promotes more robust and evidence-based clinical practice regarding subgroup data.