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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.

SUBMITTER: Green C 

PROVIDER: S-EPMC5104191 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Predicting the progression of Alzheimer's disease dementia: A multidomain health policy model.

Green Colin C   Zhang Shenqiu S  

Alzheimer's & dementia : the journal of the Alzheimer's Association 20160324 7


<h4>Introduction</h4>We develop a multidomain model to predict progression of Alzheimer's disease dementia (AD).<h4>Methods</h4>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 progres  ...[more]

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