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Improving CSF Biomarkers’ Performance for Predicting Progression from Mild Cognitive Impairment to Alzheimer’s Disease by Considering Different Confounding Factors: A Meta-Analysis
Background: Cerebrospinal fluid (CSF) biomarkers’ performance for predicting conversion from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) is still suboptimal. Objective: By considering several confounding factors we aimed to identify in which situations these CSF biomarkers can be use...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4199277/ https://www.ncbi.nlm.nih.gov/pubmed/25360114 http://dx.doi.org/10.3389/fnagi.2014.00287 |
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author | Ferreira, Daniel Rivero-Santana, Amado Perestelo-Pérez, Lilisbeth Westman, Eric Wahlund, Lars-Olof Sarría, Antonio Serrano-Aguilar, Pedro |
author_facet | Ferreira, Daniel Rivero-Santana, Amado Perestelo-Pérez, Lilisbeth Westman, Eric Wahlund, Lars-Olof Sarría, Antonio Serrano-Aguilar, Pedro |
author_sort | Ferreira, Daniel |
collection | PubMed |
description | Background: Cerebrospinal fluid (CSF) biomarkers’ performance for predicting conversion from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) is still suboptimal. Objective: By considering several confounding factors we aimed to identify in which situations these CSF biomarkers can be useful. Data Sources: A systematic review was conducted on MEDLINE, PreMedline, EMBASE, PsycInfo, CINAHL, Cochrane, and CRD (1990–2013). Eligibility Criteria: (1) Prospective studies of CSF biomarkers’ performance for predicting conversion from MCI to AD/dementia; (2) inclusion of Aβ42 and T-tau and/or p-tau. Several meta-analyses were performed. Results: Aβ42/p-tau ratio had high capacity to predict conversion to AD in MCI patients younger than 70 years. The p-tau had high capacity to identify MCI cases converting to AD in ≤24 months. Conclusions: Explaining how different confounding factors influence CSF biomarkers’ predictive performance is mandatory to elaborate a definitive map of situations, where these CSF biomarkers are useful both in clinics and research. |
format | Online Article Text |
id | pubmed-4199277 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-41992772014-10-30 Improving CSF Biomarkers’ Performance for Predicting Progression from Mild Cognitive Impairment to Alzheimer’s Disease by Considering Different Confounding Factors: A Meta-Analysis Ferreira, Daniel Rivero-Santana, Amado Perestelo-Pérez, Lilisbeth Westman, Eric Wahlund, Lars-Olof Sarría, Antonio Serrano-Aguilar, Pedro Front Aging Neurosci Neuroscience Background: Cerebrospinal fluid (CSF) biomarkers’ performance for predicting conversion from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) is still suboptimal. Objective: By considering several confounding factors we aimed to identify in which situations these CSF biomarkers can be useful. Data Sources: A systematic review was conducted on MEDLINE, PreMedline, EMBASE, PsycInfo, CINAHL, Cochrane, and CRD (1990–2013). Eligibility Criteria: (1) Prospective studies of CSF biomarkers’ performance for predicting conversion from MCI to AD/dementia; (2) inclusion of Aβ42 and T-tau and/or p-tau. Several meta-analyses were performed. Results: Aβ42/p-tau ratio had high capacity to predict conversion to AD in MCI patients younger than 70 years. The p-tau had high capacity to identify MCI cases converting to AD in ≤24 months. Conclusions: Explaining how different confounding factors influence CSF biomarkers’ predictive performance is mandatory to elaborate a definitive map of situations, where these CSF biomarkers are useful both in clinics and research. Frontiers Media S.A. 2014-10-16 /pmc/articles/PMC4199277/ /pubmed/25360114 http://dx.doi.org/10.3389/fnagi.2014.00287 Text en Copyright © 2014 Ferreira, Rivero-Santana, Perestelo-Pérez, Westman, Wahlund, Sarría and Serrano-Aguilar. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Ferreira, Daniel Rivero-Santana, Amado Perestelo-Pérez, Lilisbeth Westman, Eric Wahlund, Lars-Olof Sarría, Antonio Serrano-Aguilar, Pedro Improving CSF Biomarkers’ Performance for Predicting Progression from Mild Cognitive Impairment to Alzheimer’s Disease by Considering Different Confounding Factors: A Meta-Analysis |
title | Improving CSF Biomarkers’ Performance for Predicting Progression from Mild Cognitive Impairment to Alzheimer’s Disease by Considering Different Confounding Factors: A Meta-Analysis |
title_full | Improving CSF Biomarkers’ Performance for Predicting Progression from Mild Cognitive Impairment to Alzheimer’s Disease by Considering Different Confounding Factors: A Meta-Analysis |
title_fullStr | Improving CSF Biomarkers’ Performance for Predicting Progression from Mild Cognitive Impairment to Alzheimer’s Disease by Considering Different Confounding Factors: A Meta-Analysis |
title_full_unstemmed | Improving CSF Biomarkers’ Performance for Predicting Progression from Mild Cognitive Impairment to Alzheimer’s Disease by Considering Different Confounding Factors: A Meta-Analysis |
title_short | Improving CSF Biomarkers’ Performance for Predicting Progression from Mild Cognitive Impairment to Alzheimer’s Disease by Considering Different Confounding Factors: A Meta-Analysis |
title_sort | improving csf biomarkers’ performance for predicting progression from mild cognitive impairment to alzheimer’s disease by considering different confounding factors: a meta-analysis |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4199277/ https://www.ncbi.nlm.nih.gov/pubmed/25360114 http://dx.doi.org/10.3389/fnagi.2014.00287 |
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