Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer’s disease
Abstract Background Patients and caregivers express a desire for accurate prognostic information about time to institutionalization and mortality. Previous studies predicting institutionalization and mortality focused on the dementia stage. However, Alzheimer’s disease (AD) is characterized by a lon...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-08-01
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| Series: | Alzheimer’s Research & Therapy |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13195-022-01053-0 |
| _version_ | 1828149669675401216 |
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| author | Arenda Mank Ingrid S. van Maurik Judith J. M. Rijnhart Els D. bakker Vincent Bouteloup Lisa Le Scouarnec Charlotte E. Teunissen Frederik Barkhof Philip Scheltens Johannes Berkhof Wiesje M. van der Flier |
| author_facet | Arenda Mank Ingrid S. van Maurik Judith J. M. Rijnhart Els D. bakker Vincent Bouteloup Lisa Le Scouarnec Charlotte E. Teunissen Frederik Barkhof Philip Scheltens Johannes Berkhof Wiesje M. van der Flier |
| author_sort | Arenda Mank |
| collection | DOAJ |
| description | Abstract Background Patients and caregivers express a desire for accurate prognostic information about time to institutionalization and mortality. Previous studies predicting institutionalization and mortality focused on the dementia stage. However, Alzheimer’s disease (AD) is characterized by a long pre-dementia stage. Therefore, we developed prediction models to predict institutionalization and mortality along the AD continuum of cognitively normal to dementia. Methods This study included SCD/MCI patients (subjective cognitive decline (SCD) or mild cognitive impairment (MCI)) and patients with AD dementia from the Amsterdam Dementia Cohort. We developed internally and externally validated prediction models with biomarkers and without biomarkers, stratified by dementia status. Determinants were selected using backward selection (p<0.10). All models included age and sex. Discriminative performance of the models was assessed with Harrell’s C statistics. Results We included n=1418 SCD/MCI patients (n=123 died, n=74 were institutionalized) and n=1179 patients with AD dementia (n=413 died, n=453 were institutionalized). For both SCD/MCI and dementia stages, the models for institutionalization and mortality included after backward selection clinical characteristics, imaging, and cerebrospinal fluid (CSF) biomarkers. In SCD/MCI, the Harrell’s C-statistics of the models were 0.81 (model without biomarkers: 0.76) for institutionalization and 0.79 (model without biomarker: 0.76) for mortality. In AD-dementia, the Harrell’s C-statistics of the models were 0.68 (model without biomarkers: 0.67) for institutionalization and 0.65 (model without biomarker: 0.65) for mortality. Models based on data from amyloid-positive patients only had similar discrimination. Conclusions We constructed prediction models to predict institutionalization and mortality with good accuracy for SCD/MCI patients and moderate accuracy for patients with AD dementia. The developed prediction models can be used to provide patients and their caregivers with prognostic information on time to institutionalization and mortality along the cognitive continuum of AD. |
| first_indexed | 2024-04-11T21:33:40Z |
| format | Article |
| id | doaj.art-1a1160c2108245568ccdb44efb065220 |
| institution | Directory Open Access Journal |
| issn | 1758-9193 |
| language | English |
| last_indexed | 2024-04-11T21:33:40Z |
| publishDate | 2022-08-01 |
| publisher | BMC |
| record_format | Article |
| series | Alzheimer’s Research & Therapy |
| spelling | doaj.art-1a1160c2108245568ccdb44efb0652202022-12-22T04:01:50ZengBMCAlzheimer’s Research & Therapy1758-91932022-08-0114111210.1186/s13195-022-01053-0Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer’s diseaseArenda Mank0Ingrid S. van Maurik1Judith J. M. Rijnhart2Els D. bakker3Vincent Bouteloup4Lisa Le Scouarnec5Charlotte E. Teunissen6Frederik Barkhof7Philip Scheltens8Johannes Berkhof9Wiesje M. van der Flier10Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmcAlzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health InstituteAlzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmcUniversité Bordeaux, Inserm U1219, Institut de Santé Publique, d’Epidémiologie et de Développement (ISPED)Université Bordeaux, Inserm U1219, Institut de Santé Publique, d’Epidémiologie et de Développement (ISPED)Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam, The Netherlands Neuroscience, VU University Medical Center Amsterdam, Amsterdam UMCDepartment of Diagnostic Radiology, VU University Medical Center Amsterdam, Amsterdam UMCAlzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmcAmsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health InstituteAlzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmcAbstract Background Patients and caregivers express a desire for accurate prognostic information about time to institutionalization and mortality. Previous studies predicting institutionalization and mortality focused on the dementia stage. However, Alzheimer’s disease (AD) is characterized by a long pre-dementia stage. Therefore, we developed prediction models to predict institutionalization and mortality along the AD continuum of cognitively normal to dementia. Methods This study included SCD/MCI patients (subjective cognitive decline (SCD) or mild cognitive impairment (MCI)) and patients with AD dementia from the Amsterdam Dementia Cohort. We developed internally and externally validated prediction models with biomarkers and without biomarkers, stratified by dementia status. Determinants were selected using backward selection (p<0.10). All models included age and sex. Discriminative performance of the models was assessed with Harrell’s C statistics. Results We included n=1418 SCD/MCI patients (n=123 died, n=74 were institutionalized) and n=1179 patients with AD dementia (n=413 died, n=453 were institutionalized). For both SCD/MCI and dementia stages, the models for institutionalization and mortality included after backward selection clinical characteristics, imaging, and cerebrospinal fluid (CSF) biomarkers. In SCD/MCI, the Harrell’s C-statistics of the models were 0.81 (model without biomarkers: 0.76) for institutionalization and 0.79 (model without biomarker: 0.76) for mortality. In AD-dementia, the Harrell’s C-statistics of the models were 0.68 (model without biomarkers: 0.67) for institutionalization and 0.65 (model without biomarker: 0.65) for mortality. Models based on data from amyloid-positive patients only had similar discrimination. Conclusions We constructed prediction models to predict institutionalization and mortality with good accuracy for SCD/MCI patients and moderate accuracy for patients with AD dementia. The developed prediction models can be used to provide patients and their caregivers with prognostic information on time to institutionalization and mortality along the cognitive continuum of AD.https://doi.org/10.1186/s13195-022-01053-0Alzheimer’s diseaseMild cognitive impairmentSubjective cognitive declinePrognosisMortalityInstitutionalization |
| spellingShingle | Arenda Mank Ingrid S. van Maurik Judith J. M. Rijnhart Els D. bakker Vincent Bouteloup Lisa Le Scouarnec Charlotte E. Teunissen Frederik Barkhof Philip Scheltens Johannes Berkhof Wiesje M. van der Flier Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer’s disease Alzheimer’s Research & Therapy Alzheimer’s disease Mild cognitive impairment Subjective cognitive decline Prognosis Mortality Institutionalization |
| title | Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer’s disease |
| title_full | Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer’s disease |
| title_fullStr | Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer’s disease |
| title_full_unstemmed | Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer’s disease |
| title_short | Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer’s disease |
| title_sort | development of multivariable prediction models for institutionalization and mortality in the full spectrum of alzheimer s disease |
| topic | Alzheimer’s disease Mild cognitive impairment Subjective cognitive decline Prognosis Mortality Institutionalization |
| url | https://doi.org/10.1186/s13195-022-01053-0 |
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