title: A comparison of theoretical and statistically derived indices for predicting cognitive decline.
abstract: BACKGROUND
  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.
authors.affiliation: Department of Medicine Statistics Core, University of California, Los Angeles, Los Angeles, CA, USA.
authors.forename: Holly
authors.initials: H
authors.lastname: Wilhalme
authors.affiliation: Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA.
authors.forename: Naira
authors.initials: N
authors.lastname: Goukasian
authors.affiliation: Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA.
authors.forename: Fransia
authors.initials: F
authors.lastname: De Leon
authors.affiliation: Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA.
authors.forename: Angie
authors.initials: A
authors.lastname: He
authors.affiliation: Oakland University, William Beaumont School of Medicine, Rochester, MI, USA.
authors.forename: Kristy S
authors.initials: KS
authors.lastname: Hwang
authors.affiliation: Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA.
authors.forename: Ellen
authors.initials: E
authors.lastname: Woo
authors.affiliation: Department of Medicine Statistics Core, University of California, Los Angeles, Los Angeles, CA, USA.
authors.forename: David
authors.initials: D
authors.lastname: Elashoff
authors.affiliation: Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA.
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhou
authors.affiliation: Department of Neurology, University of Southern California, Los Angeles, CA, USA.
authors.forename: John M
authors.initials: JM
authors.lastname: Ringman
authors.affiliation: Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA; Department of Neurology, Indiana University, Indianapolis, IN, USA; Department of Radiology, Indiana University, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, USA.
authors.forename: Liana G
authors.initials: LG
authors.lastname: Apostolova
keywords: AD; Alzheimer's disease; Cognitive decline; Conversion; Executive decline; Factor analysis; MCI; Memory decline; Mild cognitive impairment; Neuropsychological test; Prognosis; Progression