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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
Author(s) -
Ba M.,
Ng K. P.,
Gao X.,
Kong M.,
Guan L.,
Yu L.
Publication year - 2019
Publication title -
european journal of neurology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.881
H-Index - 124
eISSN - 1468-1331
pISSN - 1351-5101
DOI - 10.1111/ene.13881
Subject(s) - medicine , positron emission tomography , pittsburgh compound b , amyloid (mycology) , receiver operating characteristic , cerebrospinal fluid , area under the curve , apolipoprotein e , neuroimaging , alzheimer's disease , pathology , oncology , disease , nuclear medicine , psychiatry
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‐β (Aβ) 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 Aβ, 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.