Abstract
Aim: To identify the optimal Aβ PET/MMSE combination for predicting progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia.
Methods: 686 MCI participants with Clinical Dementia Rating (CDR) score of 0.5 were followed for up to 7 years. Harmonized data from AIBL (n = 166) and ADNI (n = 520) were analysed using Cox proportional-hazards models, adjusted for age, sex, and APOE4 status, with the event of interest being progression to mild dementia due to AD (CDR = 1 and Aβ>20 CL). Optimal thresholds for MMSE (27) and Aβ (44 CL) were selected to maximize hazard ratios (HR) at 3 years. Combination of both MMSE and Aβ cut-offs provided four groups 1) high-cognition, low-Aβ (reference group), 2) low-cognition, low-Aβ, 3) high-cognition, high-Aβ, and 4) low-cognition, high-Aβ. Cognitive trajectories over time were modelled by harmonized Preclinical Alzheimer's Cognitive Composite (PACC) scores using linear mixed models, stratified by combined groups and adjusted for age, sex, education and APOE status.
Results: Both 44 CL and MMSE = 27 thresholds showed comparable hazard ratios (HR = 1.50 and 1.49, respectively; Figure 1). However, the MCI high-cognition group had higher progression risk (risk probability (RP) = 1-survival probability = 0.17±0.05) than MCI low-Aβ (RP = 0.01±0.01). Combining both cutoffs improved risk stratification: 75 out of 135 MCI low-cognition, high-Aβ progressed to AD within 3 years (30% survival probability, HR=2.9), while only 1 of 308 of the MCI high-cognition low-Aβ progressed to AD (RP = 0.04±0.03). The Linear mixed-effect models indicated that the low-cognition high-Aβ MCIs group showed the fastest decline with an effect size of 0.75, compared to the high-cognition, low-Aβ group.
Conclusion: Cognitive performance alone is not a sufficient substitute for Aβ cutoffs in predicting MCI-to-AD progression. However, binary classification based on Aβ can be improved by combining Aβ with MMSE to further stratify the risk of progression, providing greater prognostic information on an individual level and aiding in the design of clinical trials and therapeutic interventions for prodromal AD.
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