Objective: Previous research by Royall and colleagues has identified and longitudinally validated a latent dementia phenotype, δ, that estimates dementia severity and represents the concomitant cognitive and functional changes of dementia. There is evidence that the phenotype can classify patients according to their cognitive status, but it has not yet been investigated for its efficacy in differentiating dementing disorders. This study evaluates the effectiveness of δ for the differential diagnosis of Alzheimer's disease (AD) and Dementia with Lewy Bodies (DLB) within a sample of participants taken from the National Alzheimer's Coordinating Center (NACC). Method: This analysis utilized a subset of the NACC sample for whom clinical diagnosis was available at baseline assessment and was either AD or DLB. Given the disparity in sample size between the two diagnostic groups, matched samples of equal size were created by matching participants in each diagnostic group on the following: sex, race, education, age, propensity scores, and the Clinical Dementia Rating (CDR) global score. Results: A logistic regression model predicting diagnosis of AD using Logical Memory, Boston Naming Test, Functional Assessment Questionnaire, and δ scores as predictors was significant, χ2 (5, N = 487) = 143.52, p < .001, and predicted approximately 21.26% of the variance, correctly classifying 72.7% of cases. All predictors were statistically significant (p < .001) with δ score predicting the greatest level of AD risk (OR = 3.86). Conclusion: Results of the analysis suggest that δ score may be useful in differential diagnosis of dementia, above and beyond the contribution of cognitive test scores.
Use of the Latent Dementia Phenotype for Differential Diagnosis in the NACC UDS
Arch Clin Neuropsychol (2015) 30 (6): 524.
25 August 2015
S John, A Gurnani, B Gavett; B-08
Use of the Latent Dementia Phenotype for Differential Diagnosis in the NACC UDS. Arch Clin Neuropsychol 2015; 30 (6): 524. doi: 10.1093/arclin/acv047.104
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