Cognitive and functional progression along the continuum from mild cognitive impairment (MCI) to Alzheimer's disease (AD): A latent class analysis using the U.S. National Alzheimer's Coordinating Center (NACC) data set: Epidemiology / Risk and protective factors in MCI and dementia. (7th December 2020)

• Record Type: Journal Article
• Authors: Mouchet, Julie; Betts, Keith A.; Ionescu‐Ittu, Raluca; Butler, Lesley M.; Delmar, Paul; Georgieva, Mihaela V.; Kulalert, Thomas; Desai, Urvi
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 10
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-07
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.040906
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: The trajectory of AD progression is heterogeneous between individuals, and the predictors of cognitive and functional decline associated with rapid progression remain poorly understood. Better understanding of the cognitive and functional trajectories and predictors of decline is critical for articulating the natural history of the disease, identifying subgroups of individuals with MCI at higher risk of developing dementia, and contextualizing clinical trial data for AD treatments. Method: Subjects newly diagnosed with MCI in the NACC uniform data set from September 2005 to February 2019 were identified. Cognition and function were measured by the Clinical Dementia Rating‐Sum of Boxes (CDR‐SB). CDR‐SB score trajectories were fitted using a linear multi‐step growth mixture model, which was then used to identify three latent classes of subjects based on the similarity of progression patterns. Multivariate multinomial logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for baseline predictors across the latent classes. Result: Of 830 subjects included in the study sample, 42% were male, and the median age was 79.0 years. Median CDR‐SB at the time of MCI diagnosis was 0.5 (interquartile range=0.5–1.0; Table). Average follow‐up after initial MCI diagnosis was 3.6 years (standard deviation=2.5). Subjects were classified in three latent classes with differing CDR‐SB trajectories: fast progressors (21% of sample; average CDR‐SB increase=1.87 points/year), slow progressors (22%; average CDR‐SB increase=0.51 points/year), and non‐progressors (57%; no CDR‐SB increase) (Figure). Independent factors at MCI diagnosis associated with fast progressors vs non‐progressors were: older age (OR 1.04, 95% CI 1.01–1.07), female sex (2.00, 1.23–3.23), one copy of apo ε4 (1.89, 1.18–3.02), higher baseline CDR‐SB score (3.20, 2.25–4.54), and lower baseline Mini Mental State Examination (MMSE) score (0.89, 0.81–0.98). Conclusion: In this NACC‐based study, three latent classes of subjects were identified based on CDR‐SB progression trajectories. Older age, female sex, one copy of apo ε4, and worse baseline cognitive scores (CDR‐SB and MMSE) were associated with faster progression on CDR‐SB.