Evidence map›Paper›PMID 34266918›Full record

ArticleNeurology2021

Measuring Resilience and Resistance in Aging and Alzheimer Disease Using Residual Methods: A Systematic Review and Meta-analysis.

Diana I Bocancea, Anna C van Loenhoud, Colin Groot, Frederik Barkhof, Wiesje M van der Flier, Rik Ossenkoppele

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PubMed Full text at PMC Publisher
In one paragraph

Article in Neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

73 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  18. A novel approach to resilience and its links with education and Alzheimer's disease genetics.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
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13 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Diana I BocanceaFrom the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience (D.I.B., A.C.v.L., C.G., W.M.v.d.F., R.O.), and Department of Radiology and Nuclear Medicine (F.B.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; Department of Epidemiology and Biostatistics (W.M.v.d.F.), VU University Medical Center, Amsterdam, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.
Anna C van LoenhoudFrom the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience (D.I.B., A.C.v.L., C.G., W.M.v.d.F., R.O.), and Department of Radiology and Nuclear Medicine (F.B.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; Department of Epidemiology and Biostatistics (W.M.v.d.F.), VU University Medical Center, Amsterdam, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.
Colin GrootFrom the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience (D.I.B., A.C.v.L., C.G., W.M.v.d.F., R.O.), and Department of Radiology and Nuclear Medicine (F.B.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; Department of Epidemiology and Biostatistics (W.M.v.d.F.), VU University Medical Center, Amsterdam, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.
Frederik BarkhofFrom the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience (D.I.B., A.C.v.L., C.G., W.M.v.d.F., R.O.), and Department of Radiology and Nuclear Medicine (F.B.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; Department of Epidemiology and Biostatistics (W.M.v.d.F.), VU University Medical Center, Amsterdam, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.ORCID 0000-0003-3543-3706
Wiesje M van der FlierFrom the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience (D.I.B., A.C.v.L., C.G., W.M.v.d.F., R.O.), and Department of Radiology and Nuclear Medicine (F.B.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; Department of Epidemiology and Biostatistics (W.M.v.d.F.), VU University Medical Center, Amsterdam, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.ORCID 0000-0001-8766-6224
Rik OssenkoppeleFrom the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience (D.I.B., A.C.v.L., C.G., W.M.v.d.F., R.O.), and Department of Radiology and Nuclear Medicine (F.B.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; Department of Epidemiology and Biostatistics (W.M.v.d.F.), VU University Medical Center, Amsterdam, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveThere 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.

methodsA 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.

resultsWe 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]; DISCUSSION: 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.

Indexed as

Alzheimer DiseaseCognitive DysfunctionAgingBrainDisease ProgressionHumans

Identifiers

PMID34266918
PMCPMC8448552

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.