Open AccessA comparison of theoretical and statistically derived indices for predicting cognitive decline
Author(s) -
Wilhalme Holly,
Goukasian Naira,
De Leon Fransia,
He Angie,
Hwang Kristy S.,
Woo Ellen,
Elashoff David,
Zhou Yan,
Ringman John M.,
Apostolova Liana G.
Publication year - 2016
Publication title -
alzheimer's and dementia: diagnosis, assessment and disease monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.497
H-Index - 37
ISSN - 2352-8729
DOI - 10.1016/j.dadm.2016.10.002
Subject(s) - cognition , logistic regression , exploratory factor analysis , cognitive decline , psychology , executive functions , clinical psychology , audiology , statistics , medicine , psychometrics , psychiatry , mathematics , dementia , disease
Both theoretical and statistically derived approaches have been used in research settings for predicting cognitive decline. Methods Fifty‐eight cognitively normal (NC) and 71 mild cognitive impairment (MCI) subjects completed a comprehensive cognitive battery for up to 5 years of follow‐up. Composite indices of cognitive function were derived using a classic theoretical approach and exploratory factor analysis (EFA). Cognitive variables comprising each factor were averaged to form the EFA composite indices. Logistic regression was used to investigate whether these cognitive composites can reliably predict cognitive outcomes. Results Neither method predicted decline in NC. The theoretical memory, executive, attention, and language composites and the EFA‐derived “attention/executive” and “verbal memory” composites were significant predictors of decline in MCI. The best models achieved an area under the curve of 0.94 in MCI. Conclusions The theoretical and the statistically derived cognitive composite approaches are useful in predicting decline in MCI but not in NC.