Statistical Model of Dynamic Markers of the Alzheimer's Pathological Cascade. (5th May 2018)

• Record Type: Journal Article
• Authors: Balsis, Steve; Geraci, Lisa; Benge, Jared; Lowe, Deborah A; Choudhury, Tabina K; Tirso, Robert; Doody, Rachelle S
• Is Part Of: Journals of gerontology. Volume 73:Number 6(2018)
• Page Start: 964
• Page End: 973
• Publication Date: 2018-05-05
• Subjects: Alzheimer's disease -- Brain -- Biomarkers -- Cognition -- Dementia -- Item response theory -- Magnetic resonance imaging -- Model -- Psychometrics -- Statistics; Geriatrics -- Periodicals; Gerontology -- Periodicals; Aged -- Periodicals; Aging -- Periodicals; Psychology, Social -- Periodicals; 305.26
• DOI: 10.1093/geronb/gbx156
• Languages: English
• ISSNs: 1079-5014

Abstract

Abstract: Objectives: Alzheimer's disease (AD) is a progressive disease reflected in markers across assessment modalities, including neuroimaging, cognitive testing, and evaluation of adaptive function. Identifying a single continuum of decline across assessment modalities in a single sample is statistically challenging because of the multivariate nature of the data. To address this challenge, we implemented advanced statistical analyses designed specifically to model complex data across a single continuum. Method: We analyzed data from the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 1, 056), focusing on indicators from the assessments of magnetic resonance imaging (MRI) volume, fluorodeoxyglucose positron emission tomography (FDG-PET) metabolic activity, cognitive performance, and adaptive function. Item response theory was used to identify the continuum of decline. Then, through a process of statistical scaling, indicators across all modalities were linked to that continuum and analyzed. Results: Findings revealed that measures of MRI volume, FDG-PET metabolic activity, and adaptive function added measurement precision beyond that provided by cognitive measures, particularly in the relatively mild range of disease severity. More specifically, MRI volume, and FDG-PET metabolic activity become compromised in the very mild range of severity, followed by cognitive performance and finally adaptive function. Conclusion: Our statistically derived models of the AD pathological cascade are consistent with existing theoretical models.