title: How well do MCI criteria predict progression to severe cognitive impairment and dementia?
abstract: BACKGROUND
  The International Working Group (IWG) criteria for mild cognitive impairment have variable utility in predicting progression to dementia, partly depending on the setting. We explored an empiric approach to optimize the criteria and cutoff points in a population study.
  
  
  METHODS
  In a cohort of adults aged 65 years or older, we identified 1129 individuals with normal or only mildly impaired cognition by cognitive classification, and 1146 individuals without dementia (Clinical Dementia Rating <1). Operationally defining the IWG criterion set, we examined its sensitivity and specificity for the development of severe cognitive impairment and dementia (Clinical Dementia Rating ≥1) over 4 years. We then disaggregated the criteria and used Classification and Regression Tree analyses to identify the optimal predictive model.
  
  
  RESULTS
  The operational IWG criteria had 49% sensitivity and 86% specificity for the outcome of severe cognitive impairment, and 40% sensitivity and 84% specificity for the outcome of dementia. Classification and Regression Tree modeling improved sensitivity to 82% for the cognitive outcome and 76% for the dementia outcome; specificity remained high. Memory scores were the most important predictors for both outcomes. The optimal cutoff points were around 1.0 SD below the age-education mean. The best fit was observed when prediction was modeled separately for each age-education group.
  
  
  CONCLUSIONS
  Objective cognitive measurements contributed more to the prediction of dementia than subjective and functional measures. Those with less education only required memory testing, whereas those with more education required assessment of several cognitive domains. In cases in which only overall norms are available, the appropriate threshold will vary according to the individual's age and education.
authors: Departments of *Psychiatry †Neurology §Medicine, University of Pittsburgh School of Medicine Departments of ‡Epidemiology ∥Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA.
authors: Mary
authors: M
authors: Ganguli
authors: Ching-Wen
authors: CW
authors: Lee
authors: Beth E
authors: BE
authors: Snitz
authors: Tiffany F
authors: TF
authors: Hughes
authors: Eric M
authors: EM
authors: McDade
authors: Chung-Chou H
authors: CC
authors: Chang
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D060825:Cognitive Dysfunction / Q000175:diagnosis*; D015331:Cohort Studies; D003704:Dementia / Q000175:diagnosis*; D018450:Disease Progression; D005260:Female; D006801:Humans; D008297:Male; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D012044:Regression Analysis; D018570:Risk Assessment; D012307:Risk Factors; D012680:Sensitivity and Specificity