Document Detail


Improving CSF biomarker accuracy in predicting prevalent and incident Alzheimer disease.
MedLine Citation:
PMID:  21228296     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
OBJECTIVE: To investigate factors, including cognitive and brain reserve, which may independently predict prevalent and incident dementia of the Alzheimer type (DAT) and to determine whether inclusion of identified factors increases the predictive accuracy of the CSF biomarkers Aβ(42), tau, ptau(181), tau/Aβ(42), and ptau(181)/Aβ(42).
METHODS: Logistic regression identified variables that predicted prevalent DAT when considered together with each CSF biomarker in a cross-sectional sample of 201 participants with normal cognition and 46 with DAT. The area under the receiver operating characteristic curve (AUC) from the resulting model was compared with the AUC generated using the biomarker alone. In a second sample with normal cognition at baseline and longitudinal data available (n = 213), Cox proportional hazards models identified variables that predicted incident DAT together with each biomarker, and the models' concordance probability estimate (CPE), which was compared to the CPE generated using the biomarker alone.
RESULTS: APOE genotype including an ε4 allele, male gender, and smaller normalized whole brain volumes (nWBV) were cross-sectionally associated with DAT when considered together with every biomarker. In the longitudinal sample (mean follow-up = 3.2 years), 14 participants (6.6%) developed DAT. Older age predicted a faster time to DAT in every model, and greater education predicted a slower time in 4 of 5 models. Inclusion of ancillary variables resulted in better cross-sectional prediction of DAT for all biomarkers (p < 0.0021), and better longitudinal prediction for 4 of 5 biomarkers (p < 0.0022).
CONCLUSIONS: The predictive accuracy of CSF biomarkers is improved by including age, education, and nWBV in analyses.
Authors:
C M Roe; A M Fagan; M M Williams; N Ghoshal; M Aeschleman; E A Grant; D S Marcus; M A Mintun; D M Holtzman; J C Morris
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Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, N.I.H., Extramural     Date:  2011-01-12
Journal Detail:
Title:  Neurology     Volume:  76     ISSN:  1526-632X     ISO Abbreviation:  Neurology     Publication Date:  2011 Feb 
Date Detail:
Created Date:  2011-02-08     Completed Date:  2011-03-23     Revised Date:  2013-07-02    
Medline Journal Info:
Nlm Unique ID:  0401060     Medline TA:  Neurology     Country:  United States    
Other Details:
Languages:  eng     Pagination:  501-10     Citation Subset:  AIM; IM    
Affiliation:
Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA. cathyr@wustl.edu
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MeSH Terms
Descriptor/Qualifier:
Age Factors
Aged
Aged, 80 and over
Alzheimer Disease / cerebrospinal fluid*,  diagnosis,  epidemiology*
Apolipoprotein E4 / cerebrospinal fluid
Biological Markers / cerebrospinal fluid
Cross-Sectional Studies
Female
Follow-Up Studies
Humans
Incidence
Longitudinal Studies
Male
Middle Aged
Predictive Value of Tests
Prevalence
Prospective Studies
tau Proteins / cerebrospinal fluid
Grant Support
ID/Acronym/Agency:
UL1 RR024992/RR/NCRR NIH HHS
Chemical
Reg. No./Substance:
0/Apolipoprotein E4; 0/Biological Markers; 0/tau Proteins
Comments/Corrections
Comment In:
Neurology. 2011 Feb 8;76(6):496-7   [PMID:  21228299 ]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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