Applying Exercise Capacity and Physical Activity as Single vs Composite Endpoints for Trials of Cardiac Rehabilitation Interventions: Rationale, Use-case, and a Blueprint Method for Sample Size Calculation
Male
Cardiac Rehabilitation
Exercise Tolerance
Endpoint Determination
Research Design
Sample Size
Accelerometry
Humans
Exercise
Exercise Therapy
Randomized Controlled Trials as Topic
DOI:
10.1016/j.apmr.2024.04.004
Publication Date:
2024-04-14T01:39:29Z
AUTHORS (8)
ABSTRACT
Abstract Objective To conceptualise a composite primary endpoint (CE) for parallel-group RCTs of exercise-based cardiac rehabilitation (CR) interventions, and to explore its application and statistical efficiency. Study design and setting We combined exercise capacity and physical activity for the CE, both being directly related to reduced premature mortality in cardiac patients. Based on smallest detectable and smallest clinically important changes (Δ exercise capacity of 15 W and Δ physical activity of 10 min/day), the CE combines two dichotomous endpoints (achieved/not achieved). To examine statistical efficiency, we compared sample size requirements based on the CE to single endpoints using data from two completed CR trials. Results Expecting, e.g., a 10% between-group difference and improvement in the clinical outcome, the CE would require a sample size increase by up to 21% or 61%, depending on the dataset. When expecting a 10% difference and designing an intervention with the aim of non-deterioration,the CE would allow to reduce the sample size by up to 55% or 70%. Conclusion Trialists may consider the utility of the CE for future studies in exercise-based CR, which could reduce sample size requirements. However, perhaps surprisingly at first, the CE could also lead to an increased sample size needed, depending on the observed baseline proportions in the trial population and the aim of the intervention.
SUPPLEMENTAL MATERIAL
Coming soon ....
REFERENCES (34)
CITATIONS (0)
EXTERNAL LINKS
PlumX Metrics
RECOMMENDATIONS
FAIR ASSESSMENT
Coming soon ....
JUPYTER LAB
Coming soon ....