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Covariate Adjustment in Cardiovascular Randomized Controlled Trials: Its Value, Current Practice, and Need for
Leah Pirondini1, John Gregson1, Ruth Owen1
1Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom.
JACC. Heart Failure
|April 28, 2022
Summary
Many cardiovascular trials miss opportunities by not using covariate adjustment. More frequent use of covariate adjustment in randomized controlled trials can improve statistical power and trial efficiency.
Area of Science:
- Clinical Trials
- Biostatistics
- Cardiovascular Medicine
Background:
- Patient characteristics are usually balanced in randomized controlled trials (RCTs).
- However, adjusting for prognostic characteristics can increase statistical power.
- Previous reviews indicate that many RCTs do not use adjusted analyses.
Purpose of the Study:
- To review current practices of covariate adjustment in cardiovascular RCTs.
- To identify trials where covariate adjustment altered conclusions.
- To demonstrate the benefits and pitfalls of covariate adjustment using case studies and simulations.
Main Methods:
- Systematic review of 84 cardiovascular RCTs published in major medical journals in 2019.
- Analysis of case studies from identified trials.
- Utilized data from the CHARM trial and simulation studies.
Main Results:
- Contemporary cardiovascular trials underutilize covariate adjustment.
- Covariate adjustment can change trial conclusions and offers statistical power benefits.
- Complexities include covariate selection, modeling, missing data, and regulatory views.
Conclusions:
- There is a need for more frequent and appropriate use of covariate adjustment in cardiovascular trials.
- Optimizing covariate adjustment can enhance the efficiency and reliability of future clinical trials.
- Addressing complexities in covariate adjustment is crucial for improving trial methodology.
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