Journal
NEUROBIOLOGY OF AGING
Volume 33, Issue 7, Pages 1203-+Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.neurobiolaging.2010.10.019
Keywords
Alzheimer's disease; Dementia; Mild cognitive impairment; Mild cognitive impairment (MCI); Autopsy-confirmation; Biomarkers; Early detection; Cerebrospinal fluid; Cerebrospinal fluid (CSF); A beta(1-42); Tau; p-tau; MRI; Hippocampus; Volumetry; Entorhinal cortex; Prodromal; ADNI
Categories
Funding
- Science Foundation Ireland (SFI) [08/IN.1/B1846]
- National Institute on Aging [AG19610, AG024904, AG025526, AG11378]
- NIH Foundation
- Evelyn F. McKnight Brain Institute of the University of Arizona
- state of Arizona
- Mayo Clinic
- Pfizer
- Eisai
- Novartis
- Lilly
- AstraZeneca
- Sanofi
- NIH
- CIHR
- Alzheimer Society of Canada
- Michael Smith Health Research Foundation
- NIA [UO1 AG-024904]
- Janssen
- Arizona Department of Health Services
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The current study tested the accuracy of primary MRI and cerebrospinal fluid (CSF) biomarker candidates and neuropsychological tests for predicting the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia. In a cross-validation paradigm, predictor models were estimated in the training set of AD (N = 81) and elderly control subjects (N = 101). A combination of CSF t-tau/A beta(1-4) ratio and MRI biomarkers or neuropsychological tests (free recall and trail making test B (TMT-B)) showed the best statistical fit in the AD vs. HC comparison, reaching a classification accuracy of up to 64% when applied to the prediction of MCI conversion (3.3-year observation interval, mean = 2.3 years). However, several single-predictor models showed a predictive accuracy of MCI conversion comparable to that of any multipredictor model. The best single predictors were right entorhinal cortex (prediction accuracy - 68.5% (95% CI (59.5, 77.4))) and TMT-B test (prediction accuracy 64.6% (95% CI (55.5, 73.4%))). In conclusion, short-term conversion to AD is predicted by single marker models to a comparable degree as by multimarker models in amnestic MCI subjects. (C) 2012 Elsevier Inc. All rights reserved.
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