The “Small” Clinical Trial: Methods, Analysis, and Interpretation in Acute Care Cardiology

Clinical trials in acute care settings, particularly those involving small populations or high mortality rates, face unique challenges in design and analysis. Co-authored by Drs. Fernando Zampieri and Justin Ezekowitz (University of Alberta), this review highlights innovative statistical methods and strategies to address these challenges, with an emphasis on cardiovascular therapies. The authors aim to guide researchers and clinicians in choosing trial designs and analytical strategies that enhance the quality, efficiency, and clarity of evidence in acute care cardiology.

The review explores the limitations associated with small sample sizes in clinical trials, and evaluates the impact of analytical frameworks on result interpretation and reproducibility. They analyse endpoints, including “days alive and free specific to disease state,” which combines mortality and morbidity measures, the win ratio for a hierarchical approach, and ordinal scales that capture detailed patient outcomes. These methods offer greater statistical power and provide more clinically relevant insights than traditional binary outcomes. Longitudinal ordinal models are highlighted for their ability to track complex patient trajectories over time, providing in-depth insights into treatment effects across various disease stages. Meanwhile, adaptive platform trials are recommended for rare conditions, maximizing the potential of limited patient populations.

The authors emphasize the crucial role of trial design and statistical methods in shaping both the execution of trials and the interpretation of their results. Challenges associated with smaller sample sizes will persist in many areas until larger platforms are established. While the statistical approaches discussed can be tailored to specific environments, the authors stress that selection should be driven by prior data, desired outcomes, data simulations, and input from patients, clinicians, and health systems, rather than relying on the appeal of methods popularized by recent trials.