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Combining hippocampal volume metrics to better understand Alzheimer’s disease progression in at-risk individuals
To date nearly all clinical trials of Alzheimer’s disease (AD) therapies have failed. These failures are, at least in part, attributable to poor endpoint choice and to inadequate recruitment criteria. Recently, focus has shifted to targeting at-risk populations in the preclinical stages of AD thus i...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6522521/ https://www.ncbi.nlm.nih.gov/pubmed/31097733 http://dx.doi.org/10.1038/s41598-019-42632-w |
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author | McRae-McKee, K. Evans, S. Hadjichrysanthou, C. Wong, M. M. de Wolf, F. Anderson, R. M. |
author_facet | McRae-McKee, K. Evans, S. Hadjichrysanthou, C. Wong, M. M. de Wolf, F. Anderson, R. M. |
author_sort | McRae-McKee, K. |
collection | PubMed |
description | To date nearly all clinical trials of Alzheimer’s disease (AD) therapies have failed. These failures are, at least in part, attributable to poor endpoint choice and to inadequate recruitment criteria. Recently, focus has shifted to targeting at-risk populations in the preclinical stages of AD thus improved predictive markers for identifying individuals likely to progress to AD are crucial to help inform the sample of individuals to be recruited into clinical trials. We focus on hippocampal volume (HV) and assess the added benefit of combining HV and rate of hippocampal atrophy over time in relation to disease progression. Following the cross-validation of previously published estimates of the predictive value of HV, we consider a series of combinations of HV metrics and show that a combination of HV and rate of hippocampal atrophy characterises disease progression better than either measure individually. Furthermore, we demonstrate that the risk of disease progression associated with HV metrics does not differ significantly between clinical states. HV and rate of hippocampal atrophy should therefore be used in tandem when describing AD progression in at-risk individuals. Analyses also suggest that the effects of HV metrics are constant across the continuum of the early stages of the disease. |
format | Online Article Text |
id | pubmed-6522521 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65225212019-05-28 Combining hippocampal volume metrics to better understand Alzheimer’s disease progression in at-risk individuals McRae-McKee, K. Evans, S. Hadjichrysanthou, C. Wong, M. M. de Wolf, F. Anderson, R. M. Sci Rep Article To date nearly all clinical trials of Alzheimer’s disease (AD) therapies have failed. These failures are, at least in part, attributable to poor endpoint choice and to inadequate recruitment criteria. Recently, focus has shifted to targeting at-risk populations in the preclinical stages of AD thus improved predictive markers for identifying individuals likely to progress to AD are crucial to help inform the sample of individuals to be recruited into clinical trials. We focus on hippocampal volume (HV) and assess the added benefit of combining HV and rate of hippocampal atrophy over time in relation to disease progression. Following the cross-validation of previously published estimates of the predictive value of HV, we consider a series of combinations of HV metrics and show that a combination of HV and rate of hippocampal atrophy characterises disease progression better than either measure individually. Furthermore, we demonstrate that the risk of disease progression associated with HV metrics does not differ significantly between clinical states. HV and rate of hippocampal atrophy should therefore be used in tandem when describing AD progression in at-risk individuals. Analyses also suggest that the effects of HV metrics are constant across the continuum of the early stages of the disease. Nature Publishing Group UK 2019-05-16 /pmc/articles/PMC6522521/ /pubmed/31097733 http://dx.doi.org/10.1038/s41598-019-42632-w Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article McRae-McKee, K. Evans, S. Hadjichrysanthou, C. Wong, M. M. de Wolf, F. Anderson, R. M. Combining hippocampal volume metrics to better understand Alzheimer’s disease progression in at-risk individuals |
title | Combining hippocampal volume metrics to better understand Alzheimer’s disease progression in at-risk individuals |
title_full | Combining hippocampal volume metrics to better understand Alzheimer’s disease progression in at-risk individuals |
title_fullStr | Combining hippocampal volume metrics to better understand Alzheimer’s disease progression in at-risk individuals |
title_full_unstemmed | Combining hippocampal volume metrics to better understand Alzheimer’s disease progression in at-risk individuals |
title_short | Combining hippocampal volume metrics to better understand Alzheimer’s disease progression in at-risk individuals |
title_sort | combining hippocampal volume metrics to better understand alzheimer’s disease progression in at-risk individuals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6522521/ https://www.ncbi.nlm.nih.gov/pubmed/31097733 http://dx.doi.org/10.1038/s41598-019-42632-w |
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