Predicting Alzheimer's disease development : a comparison of cognitive criteria and associated neuroimaging biomarkers

Élément Dublin CoreValeurLangue
dc.contributor.authorCallahan, Brandy-
dc.contributor.authorDuchesne, Simon-
dc.description.abstractIntroduction: The definition of “objective cognitive impairment” in current criteria for mild cognitive impairment (MCI) varies considerably between research groups and clinics. This study aims to compare different methods of defining memory impairment to improve prediction models for the development of Alzheimer’s disease (AD) from baseline to 24 months. Methods: The sensitivity and specificity of six methods of defining episodic memory impairment (< −1, −1.5 or −2 standard deviations [SD] on one or two memory tests) were compared in 494 non-demented seniors from the Alzheimer’s Disease Neuroimaging Initiative using the area under the curve (AUC) for receiver operating characteristic analysis. The added value of non-memory measures (language and executive function) and biomarkers (hippocampal and white-matter hyperintensity volume, brain parenchymal fraction [BPF], and APOEε4 status) was investigated using logistic regression. Results: Baseline scores < −1 SD on two memory tests predicted AD with 75.91 % accuracy (AUC = 0.80). Only APOE ε4 status further improved prediction (B = 1.10, SE = 0.45, p = .016). A < −1.5 SD cut-off on one test had 66.60 % accuracy (AUC = 0.77). Prediction was further improved using Trails B/A ratio (B = 0.27, SE = 0.13, p = .033), BPF (B = −15.97, SE = 7.58, p = .035), and APOEε4 status (B = 1.08, SE = 0.45, p = .017). A cut-off of < −2 SD on one memory test (AUC = 0.77, SE = 0.03, 95 % CI 0.72-0.82) had 76.52 % accuracy in predicting AD. Trails B/A ratio (B = 0.31, SE = 0.13, p = .017) and APOE ε4 status (B = 1.07, SE = 0.46, p = .019) improved predictive accuracy. Conclusions: Episodic memory impairment in MCI should be defined as scores < −1 SD below normative references on at least two measures. Clinicians or researchers who administer a single test should opt for a more stringent cut-off and collect and analyze whole-brain volume. When feasible, ascertaining APOE ε4 status can further improve
dc.publisherBioMed Central
dc.titlePredicting Alzheimer's disease development : a comparison of cognitive criteria and associated neuroimaging biomarkersfr
dc.typeCOAR1_1::Texte::Périodique::Revue::Contribution à un journal::Article::Article de recherchefr
dcterms.bibliographicCitationAlzheimer's research and therapy, Vol. 7 (1), (2015)fr
dc.subject.rvmMaladie d'Alzheimerfr
dc.subject.rvmTroubles de la mémoirefr
dc.subject.rvmTrouble cognitif légerfr
dc.subject.rvmMarqueurs biologiquesfr
rioxxterms.versionVersion of Recordfr
rioxxterms.project125740; 13129;m W81XWH-12-2-0012fr
rioxxterms.project.funder_nameCanadian Institutes of Health Researchfr
rioxxterms.project.funder_nameLinda C. Campbell Foundationfr
rioxxterms.project.funder_nameHeart and Stroke Foundation of Canadafr
rioxxterms.project.funder_nameL’Oréal Canada for Women in Science Research Excellence Fellowshipfr
rioxxterms.project.funder_nameCanadian Vascular Networkfr
rioxxterms.project.funder_nameFonds de Recherche du Québec - Santéfr
rioxxterms.project.funder_nameAlzheimer’s Disease Neuroimaging Initiativefr
rioxxterms.project.funder_nameDOD ADNI (Department of Defense award number )fr
rioxxterms.project.funder_nameSunnybrook Research Institutefr
rioxxterms.project.funder_nameNational Institute on Agingfr
rioxxterms.project.funder_nameNational Institute of Biomedical Imaging and Bioengineeringfr
ali.license_refAttribution CC BYfr
bul.rights.periodeEmbargo0 moisfr
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