Abstract
Background: The societal costs of Alzheimer’s Disease (AD) are enormous and pose a great challenge for the health and social care in any society. It is of vital importance to develop and identify cost effective treatment. The aim of the study was to present a hypothetical economic model of Disease Modifying Treatment (DMT) in AD.
Methods: A 20 year Markov cohort model of DMT was constructed, based on Swedish care conditions. States and progression were defined according to the Mini Mental State Examination (MMSE). Epidemiological studies of incidence of dementia, prevalence and costs of Mild Cognitive Impairment (MCI) and AD as well as conversion studies of MCI and demographic statistics were used as inputs in the model. Results: Total costs were 113,797 million SEK for patients treated with DMT vs 88,562 million SEK for untreated patients. The corresponding gained QALYs were 529,945 and 450,307 respectively, giving an incremental cost effectiveness ratio of 293,002 SEK/QALY in the base option. Survival in the model was 8.72 years with DMT and 7.77 years for untreated. With an assumed Willingness to pay (WTP) of 600,000 SEK (about 86,200 US$ and 62,000 €) per gained QALY, the model indicated cost effectiveness with DMT. The sensitivity analysis implied no cost savings with DMT, but most options indicated cost effectiveness vs. the chosen WTP. Conclusion: The main reasons for the higher costs with DMT were the costs of DMT itself and the prolonged survival with DMT. Even if costs increase with DMT, the model indicates cost effectiveness.Keywords: Alzheimer’s disease, dementia, cholinesterase inhibitors, mortality
Current Alzheimer Research
Title:Mortality and Treatment Costs have a Great Impact on the Cost- Effectiveness of Disease Modifying Treatment in Alzheimer’s Disease - A Simulation Study
Volume: 10 Issue: 2
Author(s): Anders Skoldunger, Kristina Johnell, Bengt Winblad and Anders Wimo
Affiliation:
Keywords: Alzheimer’s disease, dementia, cholinesterase inhibitors, mortality
Abstract: Background: The societal costs of Alzheimer’s Disease (AD) are enormous and pose a great challenge for the health and social care in any society. It is of vital importance to develop and identify cost effective treatment. The aim of the study was to present a hypothetical economic model of Disease Modifying Treatment (DMT) in AD.
Methods: A 20 year Markov cohort model of DMT was constructed, based on Swedish care conditions. States and progression were defined according to the Mini Mental State Examination (MMSE). Epidemiological studies of incidence of dementia, prevalence and costs of Mild Cognitive Impairment (MCI) and AD as well as conversion studies of MCI and demographic statistics were used as inputs in the model. Results: Total costs were 113,797 million SEK for patients treated with DMT vs 88,562 million SEK for untreated patients. The corresponding gained QALYs were 529,945 and 450,307 respectively, giving an incremental cost effectiveness ratio of 293,002 SEK/QALY in the base option. Survival in the model was 8.72 years with DMT and 7.77 years for untreated. With an assumed Willingness to pay (WTP) of 600,000 SEK (about 86,200 US$ and 62,000 €) per gained QALY, the model indicated cost effectiveness with DMT. The sensitivity analysis implied no cost savings with DMT, but most options indicated cost effectiveness vs. the chosen WTP. Conclusion: The main reasons for the higher costs with DMT were the costs of DMT itself and the prolonged survival with DMT. Even if costs increase with DMT, the model indicates cost effectiveness.Export Options
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Cite this article as:
Skoldunger Anders, Johnell Kristina, Winblad Bengt and Wimo Anders, Mortality and Treatment Costs have a Great Impact on the Cost- Effectiveness of Disease Modifying Treatment in Alzheimer’s Disease - A Simulation Study, Current Alzheimer Research 2013; 10 (2) . https://dx.doi.org/10.2174/1567205011310020011
DOI https://dx.doi.org/10.2174/1567205011310020011 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
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Alzheimer's disease (AD) poses a significant global health challenge, with an increasing number of individuals affected yearly. Deep learning, a subfield of artificial intelligence, has shown immense potential in various domains, including healthcare. This thematic issue of Current Alzheimer Research explores the application of deep learning techniques in advancing our ...read more
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