Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease-informed machine-learning.
Alzheimer's disease
MRI
PET
autosomal-dominant Alzheimer's disease
biomarkers
machine learning
progression prediction
risk enrichment
Journal
Alzheimer's & dementia : the journal of the Alzheimer's Association
ISSN: 1552-5279
Titre abrégé: Alzheimers Dement
Pays: United States
ID NLM: 101231978
Informations de publication
Date de publication:
03 2020
03 2020
Historique:
received:
06
09
2019
revised:
21
10
2019
accepted:
25
11
2019
pubmed:
12
2
2020
medline:
27
11
2020
entrez:
12
2
2020
Statut:
ppublish
Résumé
Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge. We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid-PET and fluorodeoxyglucose positron-emission tomography (FDG-PET) to predict rates of cognitive decline. Prediction models were trained in autosomal-dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross-validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model-based risk enrichment was estimated. A model combining all biomarker modalities and established in ADAD predicted the 4-year rate of decline in global cognition (R Our independently validated machine-learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD.
Identifiants
pubmed: 32043733
doi: 10.1002/alz.12032
pmc: PMC7222030
mid: NIHMS1565951
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
501-511Subventions
Organisme : NIA NIH HHS
ID : U01 AG024904
Pays : United States
Organisme : NIA NIH HHS
ID : K01 AG053474
Pays : United States
Organisme : NIA NIH HHS
ID : U19 AG024904
Pays : United States
Organisme : NIA NIH HHS
ID : UF1 AG032438
Pays : United States
Organisme : NIA NIH HHS
ID : U19 AG032438
Pays : United States
Informations de copyright
© 2020 The Authors. Alzheimer's & Dementia published by Wiley Periodicals, Inc. on behalf of Alzheimer's Association.
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