Forecasting the Cognitive Status in an Aging Population

• Activity Number: 194
• Type: Contributed
• Date/Time: Monday, August 5, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Georgios Tripodis*+ and Nikolaos Zirogiannis
• Companies: Boston University and University of Massachusetts-Amherst
• Keywords: latent variables ; factor analysis ; Alzheimer's disease ; Kalman filter ; panel data

Abstract

The overall aim of this project is to advance techniques of forecasting the cognitive status of an aging population in high risk or with a diagnosis of Alzheimer's disease (AD). We focus on data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the National Alzheimer Coordinating Center (NACC). We estimate a trajectory of general cognitive performance based on measures of global cognition and domain-specific abilities. We apply a novel dynamic factor model that accounts for within-subject correlation across time and across different tests. We estimate the underlying cognitive index for subjects during the pre and post dementia stage and forecast their level of cognition. For participants with normal cognition or mild cognitive impairment we aim to predict conversion to AD using the estimated index of cognition. For participants with AD, we examine mediating factors that explain differences in the rate of decline. We will validate the cognitive index by measuring its association with the risk of developing dementia and its ability to differentiate participants with an AD profile of known biomarkers compared with people without that profile.