The relative efficiency of time-to-progression and continuous measures of cognition in presymptomatic Alzheimer’s disease
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Date
2019-07-18
Journal Title
Journal ISSN
Volume Title
Publisher
Alzheimer's & Dementia: Translational Research & Clinical Interventions
Abstract
Introduction: Clinical trials on preclinical Alzheimer’s disease are challenging because of the slow
rate of disease progression.We use a simulation study to demonstrate that models of repeated cognitive
assessments detect treatment effects more efficiently than models of time to progression.
Methods: Multivariate continuous data are simulated from a Bayesian joint mixed-effects model fit to
data from the Alzheimer’s Disease Neuroimaging Initiative. Simulated progression events are algorithmically
derived from the continuous assessments using a random forest model fit to the same data.
Results: We find that power is approximately doubled with models of repeated continuous outcomes
compared with the time-to-progression analysis. The simulations also demonstrate that a plausible
informative missing data pattern can induce a bias that inflates treatment effects, yet 5% type I error
is maintained.
Discussion: Given the relative inefficiency of time to progression, it should be avoided as a primary
analysis approach in clinical trials of preclinical Alzheimer’s disease.
Description
Research Article
Keywords
Clinical trial simulations, Alzheimer’s disease, Cox proportional hazards model, Longitudinal data, Mixed model of repeated measures (MMRM)