Disease progression model for cognitive deterioration from Alzheimer's Disease Neuroimaging Initiative database

Abstract

Background: A mathematical model was developed to describe the longitudinal response in Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) obtained from the Alzheimer's Disease Neuroimaging Initiative.

Methods: The model was fit to the longitudinal ADAS-cog scores from 817 patients. Risk factors (age, apolipoprotein ɛ4 [APOE ɛ4] genotype, gender, family history of AD, years of education) and baseline severity were tested as covariates.

Results: Rate of disease progression increased with baseline severity. Age, APOE ɛ4 genotype, and gender were identified as potential covariates influencing disease progression. The rate of disease progression in patients with mild to moderate AD was estimated as approximately 5.5 points/yr.

Conclusions: A disease progression model adequately described the natural decline of ADAS-cog observed in Alzheimer's Disease Neuroimaging Initiative. Baseline severity is an important covariate to predict a curvilinear rate of disease progression in normal elderly, mild cognitive impairment, and AD patients. Age, APOE ɛ4 genotype, and gender also influence the rate of disease progression.