Bocancea, DI;
Van Loenhoud, AC;
Groot, C;
Barkhof, F;
Van der Flier, WM;
Ossenkoppele, R;
(2021)
Measuring Resilience and Resistance in Aging and Alzheimer Disease Using Residual Methods: A Systematic Review and Meta-analysis.
Neurology
, 97
(10)
pp. 474-488.
10.1212/WNL.0000000000012499.
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Abstract
OBJECTIVE: There is currently a lack of consensus on how to optimally define and measure resistance and resilience in brain and cognitive aging. Residual methods use residuals from regression analysis to quantify the capacity to avoid (resistance) or cope (resilience) "better or worse than expected" given a certain level of risk or cerebral damage. We reviewed the rapidly growing literature on residual methods in the context of aging and Alzheimer's disease (AD) and performed meta-analyses to investigate associations of residual-method based resilience and resistance measures with longitudinal cognitive and clinical outcomes. METHODS: A systematic literature search of PubMed and Web-of-Science databases (consulted until March 2020) and subsequent screening led to 54 studies fulfilling eligibility criteria, including 10 studies suitable for the meta-analyses. RESULTS: We identified articles using residual methods aimed at quantifying resistance (n=33), cognitive resilience (n=23) and brain resilience (n=2). Critical examination of the literature revealed that there is considerable methodological variability in how the residual measures were derived and validated. Despite methodological differences across studies, meta-analytic assessments showed significant associations of levels of resistance (HR[95%CI]=1.12[1.07-1.17], p<0.0001) and levels of resilience (HR[95%CI]=0.46[0.32-0.68], p<0.001) with risk of progression to dementia/AD. Resilience was also associated with rate of cognitive decline (β[95%CI]=0.05[0.01-0.08], p<0.01). CONCLUSION: This review and meta-analysis supports the usefulness of residual methods as appropriate measures of resilience and resistance, as they capture clinically meaningful information in aging and AD. More rigorous methodological standardization is needed, however, to increase comparability across studies and, ultimately, application in clinical practice.
| Type: | Article |
|---|---|
| Title: | Measuring Resilience and Resistance in Aging and Alzheimer Disease Using Residual Methods: A Systematic Review and Meta-analysis |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1212/WNL.0000000000012499 |
| Publisher version: | https://doi.org/10.1212/WNL.0000000000012499 |
| Language: | English |
| Additional information: | Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | All Imaging, Alzheimer's disease, MRI, Cognitive aging, MCI (mild cognitive impairment) |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences 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 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 |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10131968 |
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