Date Approved
2025
Degree Type
Open Access Thesis
Degree Name
Master of Science (MS)
Department or School
Health Sciences
Committee Member
Michael Switzer, Ph.D.
Committee Member
Shannon Murray Diacono, MHS.
Abstract
Early-onset Alzheimer’s disease (EOAD), a progressive neurological condition, is often difficult to diagnose before substantial neuronal damage. Neuropsychological assessments offer a more cost-effective and accessible method for detecting early cognitive decline, yet limited research exists on optimal combinations for EOAD identification. This study analyzed data from 24 clinical studies to determine the diagnostic accuracy of FDA-approved EOAD assessments used in combination. No single combination was found to be superior across all diagnostic metrics. MMSE + MoCA + ADAS-Cog showed the highest sensitivity, MMSE + MoCA + RBANS the highest specificity, MMSE + RBANS the highest AUC value, and MMSE + MoCA the highest classification accuracy. These findings highlight the importance of aligning assessment selection with diagnostic goals: high-sensitivity combinations for early detection; high-specificity combinations for diagnosis confirmation; and high AUC or classification accuracy combinations for balanced decision-making, overall enhancing accuracy, consistency, and timeliness of EOAD identification.
Recommended Citation
Thomas, Elise, "Neuropsychological assessment accuracy in diagnosing early-onset Alzheimer’s disease" (2025). Master's Theses and Doctoral Dissertations. 1327.
https://commons.emich.edu/theses/1327