Measuring Resilience and Resistance in Aging and Alzheimer Disease Using Residual Methods: A Systematic Review and Meta-analysis.
Measuring Resilience and Resistance in Aging and Alzheimer Disease Using Residual Methods: A Systematic Review and Meta-analysis.
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DOI：
10.1212/wnl.0000000000012499
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发表时间：
2021-09-07
期刊：
影响因子：
9.9
通讯作者：
Ossenkoppele R
中科院分区：
文献类型：
--
作者：
Bocancea DI;van Loenhoud AC;Groot C;Barkhof F;van der Flier WM;Ossenkoppele R
对于如何最佳地定义和测量大脑和认知衰老的抵抗力和恢复力缺乏共识。残差方法使用回归分析的残差来量化在给定一定水平的风险或脑损伤的情况下避免（抵抗）或应对（弹性）“比预期更好或更差”的能力。我们回顾了关于衰老和阿尔茨海默病（AD）背景下残差方法的快速增长的文献，并进行荟萃分析，以研究基于残差方法的弹性和抵抗测量与纵向认知和临床结果的关联。对 PubMed 和 Web of Science 数据库进行系统文献检索（查阅至 2020 年 3 月）以及随后的筛选，得出 54 项符合资格标准的研究，其中包括 10 项适合荟萃分析的研究。我们使用残差方法识别了旨在量化阻力 (n = 33)、认知弹性 (n = 23) 和大脑弹性 (n = 2) 的文章。对文献的严格审查表明，残差测量的得出和验证方式存在相当大的方法学差异。尽管各研究之间存在方法学差异，但荟萃分析评估显示，抵抗水平（风险比 [HR] [95% 置信区间 (CI)] 1.12 [1.07–1.17]；p < 0.0001）和复原力水平（HR [95% CI] 0.46 [0.32–0.68]；p < 0.001）与进展为痴呆/AD 的风险存在显着相关性。复原力还与认知能力下降率相关（β [95% CI] 0.05 [0.01–0.08]；p < 0.01）。这项综述和荟萃分析支持残差方法作为弹性和抵抗力的适当衡量标准的有用性，因为它们捕获了衰老和 AD 方面具有临床意义的信息。需要更严格的方法标准化，以提高研究之间的可比性，并最终提高临床实践中的应用。
There is 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 disease (AD) and performed meta-analyses to investigate associations of residual method–based resilience and resistance measures with longitudinal cognitive and clinical outcomes. 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. 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 methodologic variability in how the residual measures were derived and validated. Despite methodologic differences across studies, meta-analytic assessments showed significant associations of levels of resistance (hazard ratio [HR] [95% confidence interval (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). 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 methodologic standardization is needed to increase comparability across studies and, ultimately, application in clinical practice.