How much can the Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS‐Cog) tell us? Insights from a latent state‐trait auto‐regressive (LST‐AR) model: Neuropsychology/Neuropsychological profiles of dementia: Valid biomarkers?. (7th December 2020)

• Record Type: Journal Article
• Authors: Cogo‐Moreira, Hugo; Krance, Saffire H.; Rabin, Jennifer S.; Lanctot, Krista L.; Herrmann, Nathan; Macintosh, Bradley J.; Black, Sandra E.; Eid, Michael; Swardfager, Walter
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 6
• 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.041582
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: The ADAS‐Cog assesses several cognitive domains and is the international gold standard for monitoring cognitive decline in clinical trials for Alzheimer's disease (AD) dementia. These manifold cognitive deficits can progress differently and therefore, individual ADAS‐Cog items may contain different sources of information: some predictable based on the baseline score (i.e. trait), and some based on progression from one occasion to the next (i.e. accumulated or "autoregressive" effects), while some reflects unpredictable "occasion specific" fluctuations in symptoms (i.e state). Method: Over multiple occasions of measurement, latent state‐trait autoregressive (LST‐AR) models can be used to decompose each item into reliable consistent information (composed of trait information and accumulated effects), reliable occasion‐specific information (i.e. state effects), and unreliable information (i.e. measurement error). Thus, consistency (trait + accumulated effects) and reliability (consistency + occasion specificity) can be determined for each item, at each assessment. The LST‐AR model was fit to four waves of data assessments (baseline, 6, 12 and 24 months) among 341 mild AD patients that participated in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. Result: The reliabilities of the memory (43.4%‐80.1%) and language (63.8%‐92.5%) items were generally greater than those of the praxis (average of 65.6%) and orientation (average of 60.8%) items. At the last assessment, all of the memory and language items had more consistency (ranging from 63.4% for comprehension of spoken language to 88.2% for word recognition) than occasion specificity. Disentangling the consistency into traits and accumulated effects, the items most reflective of traits were word recognition (79.4%) and commands (64.1%). Word recall, orientation and naming tasks contained roughly equal amounts of trait and accumulated information. Scores on comprehension of spoken language and spoken language ability were mainly related to accumulated effects (71.4% and 64.7%, respectively). Conclusion: In mild AD, most individual ADAS‐Cog memory and language items were reliable over time. Moreover, the scale captured additional information about the state, trait and accumulated effects of AD; the memory items tended to be more reflective of trait differences between subjects, whereas the language items tended to reflect effects that accumulated from one visit to the next, consistent with the typical progression of AD.