Proof of concept demonstration of optimal composite MRI endpoints for clinical trials

Alzheimer's and Dementia: Translational Research and Clinical Interventions - Tập 2 - Trang 177-181 - 2016
Steven D. Edland1,2, M. Colin Ard2, Jaiashre Sridhar3, Derin Cobia4, Adam Martersteck3,5, M.-Marsel Mesulam3,6, Emily J. Rogalski3
1Division of Biostatistics, Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA, USA
2Department of Neurosciences, University of California–San Diego, La Jolla, CA, USA;
3Cognitive Neurology and Alzheimer’s Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
4Department of Psychiatry and Behavioral Sciences, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA
5Department of Radiology Northwestern University Feinberg School of medicine, Chicago, IL, USA
6Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

Tóm tắt

AbstractIntroductionAtrophy measures derived from structural MRI are promising outcome measures for early phase clinical trials, especially for rare diseases such as primary progressive aphasia (PPA), where the small available subject pool limits our ability to perform meaningfully powered trials with traditional cognitive and functional outcome measures.MethodsWe investigated a composite atrophy index in 26 PPA participants with longitudinal MRIs separated by 2 years. Rogalski et al. [5] previously demonstrated that atrophy of the left perisylvian temporal cortex (PSTC) is a highly sensitive measure of disease progression in this population and a promising endpoint for clinical trials. Using methods described by Ard et al. [1], we constructed a composite atrophy index composed of a weighted sum of volumetric measures of 10 regions of interest within the left perisylvian cortex using weights that maximize signal‐to‐noise and minimize sample size required of trials using the resulting score. Sample size required to detect a fixed percentage slowing in atrophy in a 2‐year clinical trial with equal allocation of subjects across arms and 90% power was calculated for the PSTC and optimal composite surrogate biomarker endpoints.ResultsThe optimal composite endpoint required 38% fewer subjects to detect the same percent slowing in atrophy than required by the left PSTC endpoint.ConclusionsOptimal composites can increase the power of clinical trials and increase the probability that smaller trials are informative, an observation especially relevant for PPA but also for related neurodegenerative disorders including Alzheimer's disease.

Tài liệu tham khảo

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Alzheimer's and Dementia: Translational Research and Clinical Interventions

Tập 2

177-181

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