Predicting Brain Amyloid PET Positivity Using the Amyloid Beta Composite (ABC) Index in Patients With Cognitive...

Area of Science:

• Neurology
• Biomarkers
• Diagnostic Tools

Background:

• Amyloid positron emission tomography (PET) is vital for Alzheimer's disease (AD) diagnosis but faces cost and accessibility limitations.
• Predicting cerebral amyloid positivity is crucial for efficient AD patient management and research.

Purpose of the Study:

• To develop a practical composite index for predicting cerebral amyloid positivity in patients with cognitive impairment.
• To create a cost-effective screening tool to aid in selecting patients for amyloid PET and therapies.

Main Methods:

• A cohort of 223 patients with mild cognitive impairment or early AD underwent amyloid PET scans.
• Receiver operating characteristic analysis identified key predictors: MMSE, memory recall, CDR-SB, MTL atrophy, and APOE genotype.
• The Amyloid Beta Composite (ABC) index was developed using logistic regression and validated internally.

Main Results:

• The optimal model incorporating five variables achieved an AUC of 0.88 in the development group.
• The ABC index demonstrated good performance in the validation group with an AUC of 0.74, accuracy 0.70, sensitivity 0.63, and specificity 0.78.

Conclusions:

• The ABC index is a simple, practical tool for screening cerebral amyloid deposition using readily available clinical data.
• This index can assist in optimizing patient selection for amyloid PET, anti-amyloid treatments, and clinical trials, potentially reducing healthcare costs.