TY - JOUR
T1 - Applying Exercise Capacity and Physical Activity as Single vs Composite Endpoints for Trials of Cardiac Rehabilitation Interventions
T2 - Rationale, Use-case, and a Blueprint Method for Sample Size Calculation
AU - Carrozzo, Anna Eleonora
AU - Cornelissen, Veronique
AU - Bathke, Arne C.
AU - Claes, Jomme
AU - Niebauer, Josef
AU - Zimmermann, Georg
AU - Treff, Gunnar
AU - Kulnik, Stefan Tino
N1 - Niebauer, Treff: Institute for Molecular Sportsand Rehabilitation Medicine, Paracelsus Medical University, Salzburg, Austria; Niebauer:University Institute of Sports Medicine, Prevention and Rehabilitation, Paracelsus Medical University, Salzburg, Austria; Zimmermann: Team Biostatistics and Big Medical Data, IDA Lab Salzburg, Paracelsus Medical University Salzburg, Salzburg, Austria;
Research Programme Biomedical Data Science, Paracelsus Medical University Salzburg, Salzburg, Austria
PY - 2024/8
Y1 - 2024/8
N2 - Objective: To conceptualize a composite primary endpoint for parallel-group RCTs of exercise-based cardiac rehabilitation (CR) interventions and to explore its application and statistical efficiency. Design: We conducted a statistical exploration of sample size requirements. We combined exercise capacity and physical activity for the composite endpoint (CE), both being directly related to reduced premature mortality in patients with cardiac diseases. Based on smallest detectable and minimal clinically important changes (change in exercise capacity of 15 W and change in physical activity of 10 min/day), the CE combines 2 dichotomous endpoints (achieved/not achieved). To examine statistical efficiency, we compared sample size requirements based on the CE to single endpoints using data from 2 completed CR trials. Setting: Cardiac rehabilitation phase III. Participants: Patients in cardiac rehabilitation. Interventions: Not applicable. Main Outcome Measure(s): Exercise capacity (P max assessed by incremental cycle ergometry) and physical activity (daily minutes of moderate to vigorous physical activity assessed by accelerometry). Results: Expecting, for example, a 10% between-group difference and improvement in the clinical outcome, the CE would increase sample size 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%. Conclusions: Trialists may consider the utility of the CE for future studies in exercise-based CR to 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. Archives of Physical Medicine and Rehabilitation 2024;105:1498-505 (c) 2024 by the American Congress of Rehabilitation Medicine.
AB - Objective: To conceptualize a composite primary endpoint for parallel-group RCTs of exercise-based cardiac rehabilitation (CR) interventions and to explore its application and statistical efficiency. Design: We conducted a statistical exploration of sample size requirements. We combined exercise capacity and physical activity for the composite endpoint (CE), both being directly related to reduced premature mortality in patients with cardiac diseases. Based on smallest detectable and minimal clinically important changes (change in exercise capacity of 15 W and change in physical activity of 10 min/day), the CE combines 2 dichotomous endpoints (achieved/not achieved). To examine statistical efficiency, we compared sample size requirements based on the CE to single endpoints using data from 2 completed CR trials. Setting: Cardiac rehabilitation phase III. Participants: Patients in cardiac rehabilitation. Interventions: Not applicable. Main Outcome Measure(s): Exercise capacity (P max assessed by incremental cycle ergometry) and physical activity (daily minutes of moderate to vigorous physical activity assessed by accelerometry). Results: Expecting, for example, a 10% between-group difference and improvement in the clinical outcome, the CE would increase sample size 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%. Conclusions: Trialists may consider the utility of the CE for future studies in exercise-based CR to 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. Archives of Physical Medicine and Rehabilitation 2024;105:1498-505 (c) 2024 by the American Congress of Rehabilitation Medicine.
KW - Cardiovascular diseases
KW - Clinical study
KW - Rehabilitation
KW - Sample size
KW - Treatment outcome
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=pmu_pure&SrcAuth=WosAPI&KeyUT=WOS:001286589600001&DestLinkType=FullRecord&DestApp=WOS_CPL
U2 - 10.1016/j.apmr.2024.04.004
DO - 10.1016/j.apmr.2024.04.004
M3 - Original Article (Journal)
C2 - 38621456
SN - 0003-9993
VL - 105
SP - 1498
EP - 1505
JO - ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
JF - ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
IS - 8
ER -