title: Predicting the progression of Alzheimer's disease dementia: A multidomain health policy model.
abstract: We develop a multidomain model to predict progression of Alzheimer's disease dementia (AD).
  
  
  
  Data from the US National Alzheimer's Coordinating Center (n = 3009) are used to examine change in symptom status and to estimate transition probabilities between health states described using cognitive function, functional ability, and behavior. A model is used to predict progression and to assess a hypothetical treatment scenario that slows mild to moderate AD progression.
  
  
  
  More than 70% of participants moved state over 12 months. The majority moved in domains other than cognitive function. Over 5 years, of those alive more than half are in severe AD health states. Assessing an intervention scenario, we see fewer years in more severe health states and a potential impact (life years saved) due to mortality improvements.
  
  
  
  The model developed is exploratory and has limitations but illustrates the importance of using a multidomain approach when assessing impacts of AD and interventions.
authors.affiliation: Health Economics Group, Institute of Health Research, University of Exeter Medical School, University of Exeter, Exeter, UK; Collaboration for Leadership in Applied Health Research and Care South West Peninsula, University of Exeter Medical School, University of Exeter, Exeter, UK. Electronic address: c.green@exeter.ac.uk.
authors.forename: Colin
authors.initials: C
authors.lastname: Green
authors.affiliation: Health Economics Group, Institute of Health Research, University of Exeter Medical School, University of Exeter, Exeter, UK.
authors.forename: Shenqiu
authors.initials: S
authors.lastname: Zhang
mesh_terms: D000203:Activities of Daily Living; D000368:Aged; D000544:Alzheimer Disease / Q000175:diagnosis*; D003071:Cognition; D018450:Disease Progression; D005260:Female; D006291:Health Policy; D006801:Humans; D008297:Male; D015233:Models, Statistical
keywords: Alzheimer's disease; Decision analytic modelling; Health policy; Prediction; Progression