Estimating Transition Probabilities Across the Alzheimer’s Disease Continuum Using a Nationally Representative Real-World Database in the United States
Abstract 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 diseas...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Adis, Springer Healthcare
2023-05-01
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| Series: | Neurology and Therapy |
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| Online Access: | https://doi.org/10.1007/s40120-023-00498-1 |
| _version_ | 1797555531116707840 |
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| author | Amir Abbas Tahami Monfared Shuai Fu Noemi Hummel Luyuan Qi Aastha Chandak Raymond Zhang Quanwu Zhang |
| author_facet | Amir Abbas Tahami Monfared Shuai Fu Noemi Hummel Luyuan Qi Aastha Chandak Raymond Zhang Quanwu Zhang |
| author_sort | Amir Abbas Tahami Monfared |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-10T16:49:53Z |
| format | Article |
| id | doaj.art-7710e9f88ab940b99a24539ccd7e6330 |
| institution | Directory Open Access Journal |
| issn | 2193-8253 2193-6536 |
| language | English |
| last_indexed | 2024-03-10T16:49:53Z |
| publishDate | 2023-05-01 |
| publisher | Adis, Springer Healthcare |
| record_format | Article |
| series | Neurology and Therapy |
| spelling | doaj.art-7710e9f88ab940b99a24539ccd7e63302023-11-20T11:21:41ZengAdis, Springer HealthcareNeurology and Therapy2193-82532193-65362023-05-011241235125510.1007/s40120-023-00498-1Estimating Transition Probabilities Across the Alzheimer’s Disease Continuum Using a Nationally Representative Real-World Database in the United StatesAmir Abbas Tahami Monfared0Shuai Fu1Noemi Hummel2Luyuan Qi3Aastha Chandak4Raymond Zhang5Quanwu Zhang6Eisai Inc.Certara, Integrated Drug DevelopmentCertara GmbHCertara SarlCertara Inc.Eisai Inc.Eisai Inc.Abstract 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.https://doi.org/10.1007/s40120-023-00498-1Alzheimer’s diseaseDisease progressionMixed-effects modelMulti-state Markov modelTICS-mTransition probability |
| spellingShingle | Amir Abbas Tahami Monfared Shuai Fu Noemi Hummel Luyuan Qi Aastha Chandak Raymond Zhang Quanwu Zhang Estimating Transition Probabilities Across the Alzheimer’s Disease Continuum Using a Nationally Representative Real-World Database in the United States Neurology and Therapy Alzheimer’s disease Disease progression Mixed-effects model Multi-state Markov model TICS-m Transition probability |
| 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 | Alzheimer’s disease Disease progression Mixed-effects model Multi-state Markov model TICS-m Transition probability |
| url | https://doi.org/10.1007/s40120-023-00498-1 |
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