title: Proof of concept demonstration of optimal composite MRI endpoints for clinical trials.
abstract: BACKGROUND
  Atrophy 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.
  
  
  METHODS
  We investigated a composite atrophy index in 26 PPA participants with longitudinal MRIs separated by two years. Rogalskiet al. [Neurology2014;83:1184-1191] 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 Ardet al. [Pharmaceutical Statistics2015;14:418-426], 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 two-year clinical trial with equal allocation of subjects across arms and 90% power was calculated for the PSTC and optimal composite surrogate biomarker endpoints.
  
  
  RESULTS
  The optimal composite endpoint required 38% fewer subjects to detect the same percent slowing in atrophy than required by the left PSTC endpoint.
  
  
  CONCLUSIONS
  Optimal 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.
authors.affiliation: Division of Biostatistics, Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.
authors.forename: Steven D
authors.initials: SD
authors.lastname: Edland
authors.affiliation: Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.
authors.forename: M Colin
authors.initials: MC
authors.lastname: Ard
authors.affiliation: Northwestern University Feinberg School of Medicine, Cognitive Neurology and Alzheimer's Disease Center, Chicago, IL, USA.
authors.forename: Jaiashre
authors.initials: J
authors.lastname: Sridhar
authors.affiliation: Northwestern University Feinberg School of Medicine, Department of Psychiatry and Behavioral Sciences, Chicago, IL, USA.
authors.forename: Derin
authors.initials: D
authors.lastname: Cobia
authors.affiliation: Northwestern University Feinberg School of Medicine, Cognitive Neurology and Alzheimer's Disease Center, Chicago, IL, USA; Northwestern University Feinberg School of Medicine, Department of Radiology, Chicago, IL, USA.
authors.forename: Adam
authors.initials: A
authors.lastname: Martersteck
authors.affiliation: Northwestern University Feinberg School of Medicine, Cognitive Neurology and Alzheimer's Disease Center, Chicago, IL, USA; Northwestern University Feinberg School of Medicine, Department of Neurology, Chicago, IL, USA.
authors.forename: M Marsel
authors.initials: MM
authors.lastname: Mesulam
authors.affiliation: Northwestern University Feinberg School of Medicine, Cognitive Neurology and Alzheimer's Disease Center, Chicago, IL, USA.
authors.forename: Emily J
authors.initials: EJ
authors.lastname: Rogalski
keywords: Alzheimer’s Disease; Clinical Trial; Composite Endpoint; MRI; PPA; Power Calculations; Primary Progressive Aphasia; Region of Interest; Sample Size; Structural Magnetic Resonance Imaging