Predicting progression from mild cognitive impairment to Alzheimer's disease on an individual subject basis by applying the CARE index across different independent cohorts. Aging (Albany NY) 2019 Apr 30;11(8):2185-2201
Date
05/12/2019Pubmed ID
31078129Pubmed Central ID
PMC6520016DOI
10.18632/aging.101883Scopus ID
2-s2.0-85065784396 (requires institutional sign-in at Scopus site) 18 CitationsAbstract
The purposes of this study are to investigate whether the Characterizing Alzheimer's disease Risk Events (CARE) index can accurately predict progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) on an individual subject basis, and to investigate whether this model can be generalized to an independent cohort. Using an event-based probabilistic model approach to integrate widely available biomarkers from behavioral data and brain structural and functional imaging, we calculated the CARE index. We then applied the CARE index to identify which MCI individuals from the ADNI dataset progressed to AD during a three-year follow-up period. Subsequently, the CARE index was generalized to the prediction of MCI individuals from an independent Nanjing Aging and Dementia Study (NADS) dataset during the same time period. The CARE index achieved high prediction performance with 80.4% accuracy, 75% sensitivity, 82% specificity, and 0.809 area under the receiver operating characteristic (ROC) curve (AUC) on MCI subjects from the ADNI dataset over three years, and a highly validated prediction performance with 87.5% accuracy, 81% sensitivity, 90% specificity, and 0.861 AUC on MCI subjects from the NADS dataset. In conclusion, the CARE index is highly accurate, sufficiently robust, and generalized for predicting which MCI individuals will develop AD over a three-year period. This suggests that the CARE index can be usefully applied to select individuals with MCI for clinical trials and to identify which individuals will convert from MCI to AD for administration of early disease-modifying treatment.
Author List
Chen J, Chen G, Shu H, Chen G, Ward BD, Wang Z, Liu D, Antuono PG, Li SJ, Zhang Z, Alzheimer’s Disease Neuroimaging InitiativeAuthor
Piero G. Antuono MD Professor in the Neurology department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
AgedAged, 80 and over
Alzheimer Disease
Brain
Cognition
Cognitive Dysfunction
Disease Progression
Female
Humans
Individuality
Male
Middle Aged
Neuropsychological Tests
Prognosis
Risk Assessment
Sensitivity and Specificity
