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Updated: Mar 14, 2026
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Using baseline cognitive severity for enriching Alzheimer's disease clinical trials: How does Mini-Mental State
Richard E Kennedy1, Gary R Cutter1, Guoqiao Wang1
1University of Alabama, Birmingham, Birmingham, Alabama.
Background:
Post hoc analyses from clinical trials in Alzheimer's disease suggest more cognitively impaired participants respond differently from less impaired on cognitive outcomes. We examined pooled clinical trials data to assess the utility of enriching trials using baseline cognition.
Methods:
We included 2,882 participants with mild to moderate AD in 7 studies from a meta-database. We used mixed effects models to estimate rate of decline in ADAS-cog scores among MMSE groups.
Findings:
Baseline MMSE category was associated with baseline scores and rate of decline on the ADAS-cog, adjusting for age and education (both p<0.001). Greater baseline cognitive impairment was associated with more rapid progression.
Interpretations:
Although we found significant differences in rate of decline, the majority of differences between individuals were from baseline ADAS-cog values. Enrichment based on MMSE would reduce the recruitment pool while adding only slightly to detecting differences in rate of progression and is not advised.
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