Mank, Arenda;
van Maurik, Ingrid S;
Rijnhart, Judith JM;
Bakker, Els D;
Bouteloup, Vincent;
Le Scouarnec, Lisa;
Teunissen, Charlotte E;
... van der Flier, Wiesje M; + view all
(2022)
Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer's disease.
Alzheimer's Research & Therapy
, 14
(1)
, Article 110. 10.1186/s13195-022-01053-0.
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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.
Type: | Article |
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Title: | Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer's disease |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1186/s13195-022-01053-0 |
Publisher version: | https://doi.org/10.1186/s13195-022-01053-0 |
Language: | English |
Additional information: | © 2022 BioMed Central Ltd. This article is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Alzheimer’s disease, Mild cognitive impairment, Subjective cognitive decline, Prognosis, Mortality, Institutionalization |
UCL classification: | UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Brain Repair and Rehabilitation UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology |
URI: | https://discovery.ucl.ac.uk/id/eprint/10154208 |
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