A comparison of theoretical and statistically derived indices for predicting cognitive decline

Holly Wilhalme, Naira Goukasian, Fransia De Leon, Angie He, Kristy S. Hwang, Ellen Woo, David Elashoff, Yan Zhou, John M. Ringman, Liana G. Apostolova

Research output: Contribution to journalArticle

3 Scopus citations


Introduction 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.

Original languageEnglish (US)
Pages (from-to)171-181
Number of pages11
JournalAlzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
StatePublished - 2017


  • AD
  • Alzheimer's disease
  • Cognitive decline
  • Conversion
  • Executive decline
  • Factor analysis
  • MCI
  • Memory decline
  • Mild cognitive impairment
  • Neuropsychological test
  • Prognosis
  • Progression

ASJC Scopus subject areas

  • Clinical Neurology
  • Psychiatry and Mental health

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