Evaluation of Differential Diagnostics Potential of Uniform Data Set 2 Neuropsychology Battery Using Alzheimer’s Disease Biomarkers

• Published in: Archives of clinical neuropsychology Vol. 39; no. 7; pp. 839 - 848
• Main Authors: Čihák, Martin, Horáková, Hana, Vyhnálek, Martin, Veverová, Kateřina, Matušková, Veronika, Laczó, Jan, Hort, Jakub, Nikolai, Tomáš
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 06-04-2024
• Subjects: Original Empirical; Alzheimer’s disease; Mild cognitive impairment; Assessment
• ISSN: 1873-5843; 0887-6177; 1873-5843
• DOI: 10.1093/arclin/acae028

Abstract
Objective
This study aims to evaluate the efficacy of the Uniform Data Set (UDS) 2 battery in distinguishing between individuals with mild cognitive impairment (MCI) attributable to Alzheimer’s disease (MCI-AD) and those with MCI due to other causes (MCI-nonAD), based on contemporary AT(N) biomarker criteria. Despite the implementation of the novel UDS 3 battery, the UDS 2 battery is still used in several non-English-speaking countries.
Methods
We employed a cross-sectional design. A total of 113 Czech participants with MCI underwent a comprehensive diagnostic assessment, including cerebrospinal fluid biomarker evaluation, resulting in two groups: 45 individuals with prodromal AD (A+T+) and 68 participants with non-Alzheimer’s pathological changes or normal AD biomarkers (A−). Multivariable logistic regression analyses were employed with neuropsychological test scores and demographic variables as predictors and AD status as an outcome. Model 1 included UDS 2 scores that differed between AD and non-AD groups (Logical Memory delayed recall), Model 2 employed also Letter Fluency and Rey’s Auditory Verbal Learning Test (RAVLT). The two models were compared using area under the receiver operating characteristic curves. We also created separate logistic regression models for each of the UDS 2 scores.
Results
Worse performance in delayed recall of Logical Memory significantly predicted the presence of positive AD biomarkers. In addition, the inclusion of Letter Fluency RAVLT into the model significantly enhanced its discriminative capacity.
Conclusion
Our findings demonstrate that using Letter Fluency and RAVLT alongside the UDS 2 battery can enhance its potential for differential diagnostics.