International Psychogeriatrics

Research Article

Trajectories of cognitive decline in Alzheimer's disease

Patricia A. Wilkosza1, Howard J. Seltmana3, Bernie Devlina1, Elise A. Weamera1a2, Oscar L. Lopeza1a2, Steven T. DeKoskya1a2 and Robert A. Sweeta1a2a4 c1

a1 Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, U.S.A.

a2 Department of Neurology, University of Pittsburgh, Pittsburgh, PA, U.S.A.

a3 Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, U.S.A.

a4 VISN 4 Mental Illness Research, Education and Clinical Center (MIRECC), VA Pittsburgh Healthcare System, Pittsburgh, PA, U.S.A.


Background: Late-onset Alzheimer disease (LOAD) is a clinically heterogeneous complex disease defined by progressively disabling cognitive impairment. Psychotic symptoms which affect approximately one-half of LOAD subjects have been associated with more rapid cognitive decline. However, the variety of cognitive trajectories in LOAD, and their correlates, have not been well defined. We therefore used latent class modeling to characterize trajectories of cognitive and behavioral decline in a cohort of AD subjects.

Methods: 201 Caucasian subjects with possible or probable Alzheimer's disease (AD) were evaluated for cognitive and psychotic symptoms at regular intervals for up to 13.5 years. Cognitive symptoms were evaluated serially with the Mini-mental State Examination (MMSE), and psychotic symptoms were rated using the CERAD behavioral rating scale (CBRS). Analyses undertaken were latent class mixture models of quadratic trajectories including a random intercept with initial MMSE score, age, gender, education, and APOE xs03F54 count modeled as concomitant variables. In a secondary analysis, psychosis status was also included.

Results: AD subjects showed six trajectories with significantly different courses and rates of cognitive decline. The concomitant variables included in the best latent class trajectory model were initial MMSE and age. Greater burden of psychotic symptoms increased the probability of following a trajectory of more rapid cognitive decline in all age and initial MMSE groups. APOE xs03F54 was not associated with any trajectory.

Conclusion: Trajectory modeling of longitudinal cognitive and behavioral data may provide enhanced resolution of phenotypic variation in AD.

(Received August 04 2008)

(Revised October 17 2008)

(Revised August 10 2009)

(Accepted August 11 2009)

(Online publication September 28 2009)


c1 Correspondence should be addressed to: Robert A. Sweet, M. D., Professor of Psychiatry and Neurology, University of Pittsburgh, Biomedical Science Tower, Rm W-1645, 3811 O'Hara Street, Pittsburgh, PA 15213–2593, U.S.A. Phone +1 412 383 8548; Fax +1 412 624 9910. Email: