The combination of apolipoprotein E4, age and Alzheimer's Disease Assessment Scale - Cognitive Subscale improves the prediction of amyloid positron emission tomography status in clinically diagnosed mild cognitive impairment

Background and purpose Randomized clinical trials involving anti-amyloid interventions focus on the early stages of Alzheimer's disease (AD) with proven amyloid pathology, using amyloid positron emission tomography (amyloid-PET) imaging or cerebrospinal fluid analysis. However, these investigations are either expensive or invasive and are not readily available in resource-limited centres. Hence, the identification of cost-effective clinical alternatives to amyloid-PET is highly desirable. This study aimed to investigate the accuracy of combined clinical markers in predicting amyloid-PET status in mild cognitive impairment (MCI) individuals. Methods In all, 406 MCI participants from the Alzheimer's Disease Neuroimaging Initiative database were dichotomized into amyloid-PET(+) and amyloid-PET(-) using a cut-off of >1.11. The accuracies of single clinical markers [apolipoprotein E4 (ApoE4) genotype, demographics, cognitive measures and cerebrospinal fluid analysis] in predicting amyloid-PET status were evaluated using receiver operating characteristic curve analysis. A logistic regression model was then used to determine the optimal model with combined clinical markers to predict amyloid-PET status. Results Cerebrospinal fluid amyloid-beta (A beta) showed the best predictive accuracy of amyloid-PET status [area under the curve (AUC) = 0.927]. Whilst ApoE4 genotype (AUC = 0.737) and Alzheimer's Disease Assessment Scale - Cognitive Subscale (ADAS-Cog) 13 (AUC = 0.724) independently discriminated amyloid-PET(+) and amyloid-PET(-) MCI individuals, the combination of clinical markers (ApoE4 carrier, age >60 years and ADAS-Cog 13 > 13.5) improved the predictive accuracy of amyloid-PET status (AUC = 0.827, P < 0.001). Conclusions Cerebrospinal fluid A beta, which is an invasive procedure, is most accurate in predicting amyloid-PET status in MCI individuals. The combination of ApoE4, age and ADAS-Cog 13 also accurately predicts amyloid-PET status. As this combination of clinical markers is cheap, non-invasive and readily available, it offers an attractive surrogate assessment for amyloid status amongst MCI individuals in resource-limited settings.