Validation of a Multivariate Prediction Model of the Clinical Progression of Alzheimer’s Disease in a Community-Dwelling Multiethnic Cohort

Author:

Stallard Eric1,Kociolek Anton2,Jin Zhezhen3,Ryu Hyunnam2,Lee Seonjoo45,Cosentino Stephanie2,Zhu Carolyn67,Gu Yian2,Fernandez Kayri2,Hernandez Michelle2,Kinosian Bruce8,Stern Yaakov2

Affiliation:

1. Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA

2. Cognitive Neuroscience Division of the Department of Neurology and Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA

3. Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA

4. Division of Biostatistics, New York State Psychiatric Institute, New York, NY, USA

5. Department of Psychiatry, Columbia University, New York, NY, USA

6. Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA

7. James J. Peters VA Medical Center, Bronx, NY, USA

8. Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

Abstract

Background: The major aims of the three Predictors Studies have been to further our understanding of Alzheimer’s disease (AD) progression sufficiently to predict the length of time from disease onset to major disease outcomes in individual patients with AD. Objectives: To validate a longitudinal Grade of Membership (L-GoM) prediction algorithm developed using clinic-based, mainly white patients from the Predictors 2 Study in a statistically representative community-based sample of Hispanic (N = 211) and non-Hispanic (N = 62) older adults (with 60 males and 213 females) from the Predictors 3 Study and extend the algorithm to mild cognitive impairment (MCI). Methods: The L-GoM model was applied to data collected at the initial Predictors 3 visit for 150 subjects with AD and 123 with MCI. Participants were followed annually for up to seven years. Observed rates of survival and need for full-time care (FTC) were compared to those predicted by the algorithm. Results: Initial MCI/AD severity in Predictors 3 was substantially higher than among clinic-based AD patients enrolled at the specialized Alzheimer’s centers in Predictors 2. The observed survival and need for FTC followed the L-GoM model trajectories in individuals with MCI or AD, except for N = 32 subjects who were initially diagnosed with AD but reverted to a non-AD diagnosis on follow-up. Conclusion: These findings indicate that the L-GoM model is applicable to community-dwelling, multiethnic older adults with AD. They extend the use of the model to the prediction of outcomes for MCI. They also justify release of our L-GoM calculator at this time.

Publisher

IOS Press

Subject

Psychiatry and Mental health,Geriatrics and Gerontology,Clinical Psychology,General Medicine,General Neuroscience

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