Abstract Details

Title Predicting Cognitive Decline Using Baseline Data in Cognitively Unimpaired Older Adults: Results from the A4 Trial

Topic Aging, Dementia, and Behavioral Neurology

Presentation(s) P2 - Poster Session 2 (8:00 AM-9:00 AM)

Poster/Presentation
Number 3-018

Objective To identify factors predicting cognitive/functional decline on the CDR over a 5-year period in cognitively unimpaired older adults.

Background The clinical and biological heterogeneity observed in Alzheimer’s disease makes the design of trials and inclusion of appropriate participants difficult. Identifying methods to discern more homogenous subgroups of participants can assist in enriching trials.

Design/Methods Participants included 1169 amyloid-positive participants enrolled in the A4 trial (receiving solanezumab, N=578, or placebo, N=591), and 538 amyloid-negative individuals enrolled in the LEARN observational study. We used multiple logistic regression models to examine the separate and joint predictive value of demographics, APOE4 genotype, neuropsychological tests, amyloid PET SUVR, and plasma phosphorylated tau 217 (P-tau217) levels in predicting individuals experiencing cognitive/functional decline (defined as an increase of 0.5 or more in the CDR-global score after 240 weeks).

Results

Participants had an average age of 70.5 ± 4.2 years, with 60.3% being female. The addition of P-tau217 and PACC to the base model (demographics and APOE4 status) significantly improved the predictive performance across all study arms. For the base model plus P-tau217, the AUC values were: Solanezumab (AUC = 0.81±0.11), Placebo (AUC = 0.78±0.11), and LEARN (AUC = 0.76±0.15). Similarly, for the base model plus PACC, the AUC values were: Solanezumab (AUC = 0.72±0.12), Placebo (AUC = 0.76±0.11), and LEARN (AUC = 0.74±0.15). The models that included all covariates achieved the highest predictive performance across the study arms, with AUC values of: Solanezumab (AUC = 0.82 ± 0.1), Placebo (AUC = 0.83 ± 0.1), and LEARN (AUC = 0.80 ± 0.13).

Conclusions

These findings underscore the importance of baseline neuropsychological scores and plasma P-tau217 in predicting cognitive decline. Predictive models using these practical measures can improve clinical trial design and optimize participant selection, enhancing the effectiveness of interventions.

Authors/Disclosures
Babak Khorsand, PhD PRESENTER	Dr. Khorsand has nothing to disclose.
Elham Ghanbarian, MD, PhD	Dr. Ghanbarian has nothing to disclose.
Laura Rabin, PhD	Prof. Rabin has nothing to disclose.
Ali Ezzati, MD (University of California, Irvine)	The institution of Dr. Ezzati has received research support from NIA. The institution of Dr. Ezzati has received research support from Alzheimer's Association. The institution of Dr. Ezzati has received research support from Cure Alzheimer's Fund.

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