Subgroups, treatment effects, and baseline risks: some lessons from major cardiovascular trials

Area of Science:

• Cardiovascular Medicine
• Clinical Trials Methodology
• Statistical Analysis

Background:

• Subgroup analyses are frequently employed in large cardiovascular pharmacotherapy trials.
• The methods and rigor of these subgroup analyses have not been consistently evaluated.

Purpose of the Study:

• To assess the methodology of subgroup analyses in large randomized cardiovascular pharmacotherapy trials.
• To identify common practices and potential limitations in reporting subgroup effects.

Main Methods:

• A systematic review of 67 large randomized controlled trials (RCTs) in cardiovascular pharmacotherapy (≥1000 patients) published between 1980-1997.
• Focus on trials with clinical outcomes as primary endpoints, including unstable angina, myocardial infarction, left ventricular dysfunction, and heart failure.

Main Results:

• 43 of 67 trials reported on 5 or more subgroups, while 31 lacked formal statistical tests for treatment-subgroup interactions.
• A clear rationale for subgroup selection was often missing in the published reports.
• Most analyses focused on single-factor subgroups, with limited exploration of multifactorial prognostic subgroups.

Conclusions:

• Ideally, subgroup analyses should be pre-specified, based on biological plausibility for single-factor subgroups or baseline risk for prognostic subgroups.
• Current practices often lack a supporting rationale and formal interaction testing, necessitating skepticism.
• Clinicians should critically evaluate subgroup-specific treatment effects, demanding a prespecified rationale and significant interaction for reliable interpretation.