John A Kairalla1, Christopher S Coffey2, Mitchell A Thomann2, Ronald I Shorr3, Keith E Muller4. 1. Department of Biostatistics, University of Florida, Gainesville, FL, USA. 2. Department of Biostatistics, University of Iowa, Iowa City, IA, USA. 3. Department of Epidemiology, University of Florida, Gainesville, FL, USA; Geriatric Research Education and Clinical Center (GRECC), Malcom Randall Veterans Affairs Medical Center, Gainesville, FL, USA. 4. Department of Health Outcomes and Policy, University of Florida, Gainesville, FL, USA.
Abstract
CONTEXT: Medical and health policy decision makers require improved design and analysis methods for comparative effectiveness research (CER) trials. In CER trials, there may be limited information to guide initial design choices. In general settings, adaptive designs (ADs) have effectively overcome limits on initial information. However, CER trials have fundamental differences from standard clinical trials including population heterogeneity and a vaguer concept of a "minimum clinically meaningful difference". OBJECTIVE: To explore the use of a particular form of ADs for comparing treatments within the CER trial context. METHODS: We review the current state of clinical CER, identify areas of CER as particularly strong candidates for application of novel ADs, and illustrate potential usefulness of the designs and methods for two group comparisons. RESULTS: ADs can stabilize power. The designs ensure adequate power for true effects are at least at clinically significant preplanned effect size, or when variability is larger than expected. The designs allow for sample size savings when the true effect is larger or when variability is smaller than planned. CONCLUSION: ADs in CER have great potential to allow trials to successfully and efficiently make important comparisons.
CONTEXT: Medical and health policy decision makers require improved design and analysis methods for comparative effectiveness research (CER) trials. In CER trials, there may be limited information to guide initial design choices. In general settings, adaptive designs (ADs) have effectively overcome limits on initial information. However, CER trials have fundamental differences from standard clinical trials including population heterogeneity and a vaguer concept of a "minimum clinically meaningful difference". OBJECTIVE: To explore the use of a particular form of ADs for comparing treatments within the CER trial context. METHODS: We review the current state of clinical CER, identify areas of CER as particularly strong candidates for application of novel ADs, and illustrate potential usefulness of the designs and methods for two group comparisons. RESULTS: ADs can stabilize power. The designs ensure adequate power for true effects are at least at clinically significant preplanned effect size, or when variability is larger than expected. The designs allow for sample size savings when the true effect is larger or when variability is smaller than planned. CONCLUSION: ADs in CER have great potential to allow trials to successfully and efficiently make important comparisons.
Authors: Kevin E Thorpe; Merrick Zwarenstein; Andrew D Oxman; Shaun Treweek; Curt D Furberg; Douglas G Altman; Sean Tunis; Eduardo Bergel; Ian Harvey; David J Magid; Kalipso Chalkidou Journal: J Clin Epidemiol Date: 2009-05 Impact factor: 6.437