Variation in Variables That Predict Progression from MCI to AD Dementia over Duration of Follow-up

The purpose of this paper is to investigate the relative utility of using neuroimaging, genetic, cerebrospinal fluid (CSF), and cognitive measures to predict progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia over a follow-up period. The studied subjects were 139 persons with MCI enrolled in the Alzheimer's Disease Neuroimaging Initiative. Predictors of progression to AD included brain volume, ventricular volume, hippocampal volume, APOE ε4 two alleles, Aβ, p-tau, p-tau/Aβ, memory, language, and executive function. We employ a combination of Cox regression analyses and time-dependent receiver operating characteristic (ROC) methods to assess the prognostic utility and performance stability of candidate biomarkers. In a demographic-adjusted multivariable Cox model, seven measures- brain volume, hippocampal volume, ventricular volume, APOE ε4 two alleles, Aβ, Memory composite, Executive function composite - predicted progression to AD. Time-dependent ROC revealed that this multivariable model had an area under the curve of 0.832, 0.788, 0.794, and 0.757 at 12, 18, 24, and 36 months respectively. Supplemental Cox models with time of origin set differentially at 12, 18, 24 and 36 months showed that six measures were significant predictors at 12 months whereas only memory and executive function predicted progression to AD at 18 and 24 months. The authors concluded that baseline volumetric MRI and cognitive measures selectively predict progression from MCI to AD, with cognitive measures remaining predictive even late in the follow-up period. These findings may inform case selection for AD clinical trials.