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Power Calculations for Clinical Trials in Alzheimer's Disease

Overview
Publisher Sage Publications
Specialties Geriatrics
Neurology
Date 2011 Oct 6
PMID 21971476
Citations 45
Authors
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Abstract

The Alzheimer research community is actively pursuing novel biomarker and other biologic measures to characterize disease progression or to use as outcome measures in clinical trials. One product of these efforts has been a large literature reporting power calculations and estimates of sample size for planning future clinical trials and cohort studies with longitudinal rate of change outcome measures. Sample size estimates reported in this literature vary greatly depending on a variety of factors, including the statistical methods and model assumptions used in their calculation. We review this literature and suggest standards for reporting power calculation results. Regardless of the statistical methods used, studies consistently find that volumetric neuroimaging measures of regions of interest, such as hippocampal volume, outperform global cognitive scales traditionally used in clinical treatment trials in terms of the number of subjects required to detect a fixed percentage slowing of the rate of change observed in demented and cognitively impaired populations. However, statistical methods, model assumptions, and parameter estimates used in power calculations are often not reported in sufficient detail to be of maximum utility. We review the factors that influence sample size estimates, and discuss outstanding issues relevant to planning longitudinal studies of Alzheimer's disease.

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References
1.
Nestor S, Rupsingh R, Borrie M, Smith M, Accomazzi V, Wells J . Ventricular enlargement as a possible measure of Alzheimer's disease progression validated using the Alzheimer's disease neuroimaging initiative database. Brain. 2008; 131(Pt 9):2443-54. PMC: 2724905. DOI: 10.1093/brain/awn146. View

2.
Stein J, Hua X, Lee S, Ho A, Leow A, Toga A . Voxelwise genome-wide association study (vGWAS). Neuroimage. 2010; 53(3):1160-74. PMC: 2900429. DOI: 10.1016/j.neuroimage.2010.02.032. View

3.
ROSEN W, Mohs R, Davis K . A new rating scale for Alzheimer's disease. Am J Psychiatry. 1984; 141(11):1356-64. DOI: 10.1176/ajp.141.11.1356. View

4.
Ho A, Stein J, Hua X, Lee S, Hibar D, Leow A . A commonly carried allele of the obesity-related FTO gene is associated with reduced brain volume in the healthy elderly. Proc Natl Acad Sci U S A. 2010; 107(18):8404-9. PMC: 2889537. DOI: 10.1073/pnas.0910878107. View

5.
Schlesselman J . Planning a longitudinal study. II. Frequency of measurement and study duration. J Chronic Dis. 1973; 26(9):561-70. DOI: 10.1016/0021-9681(73)90061-1. View