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Predicting Long-Term Cognitive Outcome with New Regression Models in Donepezil-Treated Alzheimer Patients in a Naturalistic Setting.

Wattmo, Carina LU ; Hansson, Oskar LU ; Wallin, Åsa LU ; Londos, Elisabet LU and Minthon, Lennart LU (2008) In Dementia and Geriatric Cognitive Disorders 26(3). p.203-211
Abstract
Background/Aims: To build and analyze regression models predicting (1) the long-term cognitive outcome in donepezil-treated patients with Alzheimer's disease, and (2) the short-term (6 months) cognitive impact of treatment depending on cognitive severity at baseline. Methods: The Swedish Alzheimer Treatment Study (SATS) is an open-label, non-randomized, 3-year, multicentre study in a routine clinical setting. A total of 435 patients, mostly in the mild and moderate stages of Alzheimer's disease, received the cholinesterase inhibitor donepezil. They were assessed with the Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog) at baseline and every 6 months for a total period of 3 years.... (More)
Background/Aims: To build and analyze regression models predicting (1) the long-term cognitive outcome in donepezil-treated patients with Alzheimer's disease, and (2) the short-term (6 months) cognitive impact of treatment depending on cognitive severity at baseline. Methods: The Swedish Alzheimer Treatment Study (SATS) is an open-label, non-randomized, 3-year, multicentre study in a routine clinical setting. A total of 435 patients, mostly in the mild and moderate stages of Alzheimer's disease, received the cholinesterase inhibitor donepezil. They were assessed with the Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog) at baseline and every 6 months for a total period of 3 years. Regression models were fitted from the actual scores at different intervals for the prediction of the cognitive outcome. Results: The ADAS-cog and MMSE scores during the 3-year treatment period could be predicted with a high degree of explanation using regression models (p < 0.001). Moreover, there was a significant relation between the mean cognitive change after 6 months of treatment and the baseline scores on MMSE (p < 0.01) and ADAS-cog (p < 0.001), respectively. Conclusion: Statistical models can be used to predict cognitive outcome in donepezil-treated cohorts of AD patients. These models can be clinically valuable, for example when assessing the efficacy of new therapies when added to cholinesterase inhibitor treatment. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Alzheimer disease, longitudinal studies, cholinesterase inhibitors, donepezil, disease progression, severity of illness index, statistical models, regression analysis, psychiatric status rating scales.
in
Dementia and Geriatric Cognitive Disorders
volume
26
issue
3
pages
203 - 211
publisher
Karger
external identifiers
  • wos:000259876400003
  • pmid:18769065
  • scopus:50649100384
ISSN
1420-8008
DOI
10.1159/000152911
language
English
LU publication?
yes
id
d62c58a9-b87d-45fc-99d5-a4ce6d41fdae (old id 1243434)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/18769065?dopt=Abstract
date added to LUP
2008-10-03 16:08:25
date last changed
2017-05-21 03:40:45
@article{d62c58a9-b87d-45fc-99d5-a4ce6d41fdae,
  abstract     = {Background/Aims: To build and analyze regression models predicting (1) the long-term cognitive outcome in donepezil-treated patients with Alzheimer's disease, and (2) the short-term (6 months) cognitive impact of treatment depending on cognitive severity at baseline. Methods: The Swedish Alzheimer Treatment Study (SATS) is an open-label, non-randomized, 3-year, multicentre study in a routine clinical setting. A total of 435 patients, mostly in the mild and moderate stages of Alzheimer's disease, received the cholinesterase inhibitor donepezil. They were assessed with the Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog) at baseline and every 6 months for a total period of 3 years. Regression models were fitted from the actual scores at different intervals for the prediction of the cognitive outcome. Results: The ADAS-cog and MMSE scores during the 3-year treatment period could be predicted with a high degree of explanation using regression models (p &lt; 0.001). Moreover, there was a significant relation between the mean cognitive change after 6 months of treatment and the baseline scores on MMSE (p &lt; 0.01) and ADAS-cog (p &lt; 0.001), respectively. Conclusion: Statistical models can be used to predict cognitive outcome in donepezil-treated cohorts of AD patients. These models can be clinically valuable, for example when assessing the efficacy of new therapies when added to cholinesterase inhibitor treatment.},
  author       = {Wattmo, Carina and Hansson, Oskar and Wallin, Åsa and Londos, Elisabet and Minthon, Lennart},
  issn         = {1420-8008},
  keyword      = {Alzheimer disease,longitudinal studies,cholinesterase inhibitors,donepezil,disease progression,severity of illness index,statistical models,regression analysis,psychiatric status rating scales.},
  language     = {eng},
  number       = {3},
  pages        = {203--211},
  publisher    = {Karger},
  series       = {Dementia and Geriatric Cognitive Disorders},
  title        = {Predicting Long-Term Cognitive Outcome with New Regression Models in Donepezil-Treated Alzheimer Patients in a Naturalistic Setting.},
  url          = {http://dx.doi.org/10.1159/000152911},
  volume       = {26},
  year         = {2008},
}