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Estimating Transition Probabilities Across the Alzheimer’s Disease Continuum Using a Nationally Representative Real-World Database in the United States

INTRODUCTION: Clinical Alzheimer’s disease (AD) begins with mild cognitive impairment (MCI) and progresses to mild, moderate, or severe dementia, constituting a disease continuum that eventually leads to death. This study aimed to estimate the probabilities of transitions across those disease states...

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Autores principales: Tahami Monfared, Amir Abbas, Fu, Shuai, Hummel, Noemi, Qi, Luyuan, Chandak, Aastha, Zhang, Raymond, Zhang, Quanwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10310620/
https://www.ncbi.nlm.nih.gov/pubmed/37256433
http://dx.doi.org/10.1007/s40120-023-00498-1
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author Tahami Monfared, Amir Abbas
Fu, Shuai
Hummel, Noemi
Qi, Luyuan
Chandak, Aastha
Zhang, Raymond
Zhang, Quanwu
author_facet Tahami Monfared, Amir Abbas
Fu, Shuai
Hummel, Noemi
Qi, Luyuan
Chandak, Aastha
Zhang, Raymond
Zhang, Quanwu
author_sort Tahami Monfared, Amir Abbas
collection PubMed
description INTRODUCTION: Clinical Alzheimer’s disease (AD) begins with mild cognitive impairment (MCI) and progresses to mild, moderate, or severe dementia, constituting a disease continuum that eventually leads to death. This study aimed to estimate the probabilities of transitions across those disease states. METHODS: We developed a mixed-effects multi-state Markov model to estimate the transition probabilities, adjusted for 5 baseline covariates, using the Health and Retirement Study (HRS) database. HRS surveys older adults in the United States bi-annually. Alzheimer states were defined using the modified Telephone Interview of Cognitive Status (TICS-m). RESULTS: A total of 11,292 AD patients were analyzed. Patients were 70.8 ± 9.0 years old, 54.9% female, and with 12.0 ± 3.3 years of education. Within 1 year from the initial state, the model estimated a higher probability of transition to the next AD state in earlier disease: 12.8% from MCI to mild AD and 5.0% from mild to moderate AD, but < 1% from moderate to severe AD. After 10 years, the probability of transition to the next state was markedly higher for all states, but still higher in earlier disease: 29.8% from MCI to mild AD, 23.5% from mild to moderate AD, and 5.7% from moderate to severe AD. Across all AD states, the probability of transition to death was < 5% after 1 year and > 15% after 10 years. Older age, fewer years of education, unemployment, and nursing home stay were associated with a higher risk of disease progression (p < 0.01). CONCLUSIONS: This analysis shows that the risk of progression is greater in earlier AD states, increases over time, and is higher in patients who are older, with fewer years of education, unemployed, or in a nursing home at baseline. The estimated transition probabilities can provide guidance for future disease management and clinical trial design optimization, and can be used to refine existing cost-effectiveness frameworks. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40120-023-00498-1.
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spelling pubmed-103106202023-07-01 Estimating Transition Probabilities Across the Alzheimer’s Disease Continuum Using a Nationally Representative Real-World Database in the United States Tahami Monfared, Amir Abbas Fu, Shuai Hummel, Noemi Qi, Luyuan Chandak, Aastha Zhang, Raymond Zhang, Quanwu Neurol Ther Original Research INTRODUCTION: Clinical Alzheimer’s disease (AD) begins with mild cognitive impairment (MCI) and progresses to mild, moderate, or severe dementia, constituting a disease continuum that eventually leads to death. This study aimed to estimate the probabilities of transitions across those disease states. METHODS: We developed a mixed-effects multi-state Markov model to estimate the transition probabilities, adjusted for 5 baseline covariates, using the Health and Retirement Study (HRS) database. HRS surveys older adults in the United States bi-annually. Alzheimer states were defined using the modified Telephone Interview of Cognitive Status (TICS-m). RESULTS: A total of 11,292 AD patients were analyzed. Patients were 70.8 ± 9.0 years old, 54.9% female, and with 12.0 ± 3.3 years of education. Within 1 year from the initial state, the model estimated a higher probability of transition to the next AD state in earlier disease: 12.8% from MCI to mild AD and 5.0% from mild to moderate AD, but < 1% from moderate to severe AD. After 10 years, the probability of transition to the next state was markedly higher for all states, but still higher in earlier disease: 29.8% from MCI to mild AD, 23.5% from mild to moderate AD, and 5.7% from moderate to severe AD. Across all AD states, the probability of transition to death was < 5% after 1 year and > 15% after 10 years. Older age, fewer years of education, unemployment, and nursing home stay were associated with a higher risk of disease progression (p < 0.01). CONCLUSIONS: This analysis shows that the risk of progression is greater in earlier AD states, increases over time, and is higher in patients who are older, with fewer years of education, unemployed, or in a nursing home at baseline. The estimated transition probabilities can provide guidance for future disease management and clinical trial design optimization, and can be used to refine existing cost-effectiveness frameworks. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40120-023-00498-1. Springer Healthcare 2023-05-31 /pmc/articles/PMC10310620/ /pubmed/37256433 http://dx.doi.org/10.1007/s40120-023-00498-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Tahami Monfared, Amir Abbas
Fu, Shuai
Hummel, Noemi
Qi, Luyuan
Chandak, Aastha
Zhang, Raymond
Zhang, Quanwu
Estimating Transition Probabilities Across the Alzheimer’s Disease Continuum Using a Nationally Representative Real-World Database in the United States
title Estimating Transition Probabilities Across the Alzheimer’s Disease Continuum Using a Nationally Representative Real-World Database in the United States
title_full Estimating Transition Probabilities Across the Alzheimer’s Disease Continuum Using a Nationally Representative Real-World Database in the United States
title_fullStr Estimating Transition Probabilities Across the Alzheimer’s Disease Continuum Using a Nationally Representative Real-World Database in the United States
title_full_unstemmed Estimating Transition Probabilities Across the Alzheimer’s Disease Continuum Using a Nationally Representative Real-World Database in the United States
title_short Estimating Transition Probabilities Across the Alzheimer’s Disease Continuum Using a Nationally Representative Real-World Database in the United States
title_sort estimating transition probabilities across the alzheimer’s disease continuum using a nationally representative real-world database in the united states
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10310620/
https://www.ncbi.nlm.nih.gov/pubmed/37256433
http://dx.doi.org/10.1007/s40120-023-00498-1
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