Using Base Rate of Low Scores to Identify Progression from Amnestic Mild Cognitive Impairment to Alzheimer's Disease

Oltra-Cucarella, Javier; Sánchez‐SanSegundo, Miriam; Lipnicki, Darren M.; Sachdev, Perminder S.; Crawford, John D.; Pérez-Vicente, José Antonio; Cabello-Rodríguez, Luis; Ferrer‐Cascales, Rosario

doi:10.1111/jgs.15412

Cited by 35 publications

(53 citation statements)

References 44 publications

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“…Not surprisingly, our results are in line with those reported by Mitchell and Shiri-Feshki (2009), who found that amnestic MCI and mdMCI had a similar risk-AD (11.7% vs. 12.2%), both having a higher risk-AD compared to naMCI. One possible explanation is that severity of memory impairments, and not the number of tests, is related to the risk-AD, as has been suggested recently (Oltra-Cucarella et al, 2018).…”

Section: Discussionmentioning

confidence: 90%

“…A review by Binder et al (2009) showed that the probability of obtaining one or more low scores increased as the number of measures increased, with a percentage of up to 59% of participants having at least one score 1.5 standard deviations below the mean. Recently, Oltra-Cucarella et al (2018) reported that up to 90% of a sample of 280 individuals with normal cognition had up to two scores at least 1.5 standard deviations below the mean in a battery with 9 measures. These data suggest that increasing the number of tests in the neuropsychological battery increases the probability of false positive MCI cases, and also the probability of falsely being classified as having multiple-domain MCI if only two measures suffice for diagnosis in batteries with several measures.…”

Section: Discussionmentioning

confidence: 99%

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Risk of progression to Alzheimer’s disease for different neuropsychological Mild Cognitive Impairment subtypes: A hierarchical meta-analysis of longitudinal studies.

Oltra-Cucarella¹,

Ferrer‐Cascales²,

Alegret³

et al. 2018

Psychology and Aging

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Mild Cognitive Impairment (MCI) is a heterogeneous condition between normal aging and dementia. Upon neuropsychological testing, MCI can be divided into four groups: singledomain amnestic MCI (sd-aMCI), multiple-domain amnestic MCI (md-aMCI), single-and multiple-domain non-amnestic MCI (sd-naMCI, md-naMCI). Some controversy exists about whether the risk of progression to Alzheimer's disease (risk-AD) is increased in all MCI subtypes. We meta-analyzed the risk-AD for four MCI groups using random-effects metaregression with the Hierarchical Robust Variance Estimator and sample size, criterion for objective cognitive impairment, length of follow-up and source of recruitment as covariates. From a pool of 134 available studies, 81 groups from 33 studies (N = 4,907) were metaanalyzed. All the studies were rated as having a high risk of bias. aMCI is overrepresented in studies from memory clinics. Multivariate analyses showed that md-aMCI had a similar risk-AD relative to sd-aMCI, whereas both sd-naMCI and md-naMCI showed a lower risk-AD compared to sd-aMCI. The risk-AD was significantly associated with differences in sample sizes across studies and between groups within studies. md-aMCI had a similar risk-AD relative to sd-aMCI in studies from memory clinics and in studies in the community. Several potential sources of bias such as blindness of AD diagnosis, the MCI diagnosis approach and the reporting of demographics were associated with the risk-AD. This work provides important data for use in both clinical and research scenarios.

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Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Risk of progression to Alzheimer’s disease for different neuropsychological Mild Cognitive Impairment subtypes: A hierarchical meta-analysis of longitudinal studies.

Oltra-Cucarella¹,

Ferrer‐Cascales²,

Alegret³

et al. 2018

Psychology and Aging

Self Cite

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“…Also, the original ADNI MCI criteria used education-adjusted scores of WMS story recall, but scores adjusted for both age and education are likely to further improve MCI diagnosis. One study of ADNI participants categorized individuals with MCI based on the number of impaired tests and found that this criterion worked better than the original ADNI MCI classification or the Jak/Bondi actuarial approach in predicting progression from MCI to AD (Oltra-Cucarella et al 2018). This study used the average number of low scores in the worst performing 10% of ADNI CN participants as the basis for diagnosing MCI.…”

Section: Discussionmentioning

confidence: 99%

“…Out of 9 scores from 6 tests, the lowest 10% of CN participants had ≥3 low scores. The highest progression rate (43%) to AD in a 3year period was in those with single domain amnestic MCI (i.e., individuals who were ≥ 1.5 SD below the mean in Logical Memory delayed recall, AVLT delayed recall and AVLT recognition) (Oltra-Cucarella et al 2018). This rate was higher than the progression rate of 33% for multiple-domain amnestic MCI, probably because one could meet criteria for multiple-domain amnestic MCI with only one or two impaired memory scores but a single-domain diagnosis would require impairment on all three.…”

Section: Discussionmentioning

confidence: 99%

Modifying the minimum criteria for diagnosing amnestic MCI to improve prediction of brain atrophy and progression to Alzheimer’s disease

Vuoksimaa

McEvoy

Holland

et al. 2018

Brain Imaging and Behavior

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Mild cognitive impairment (MCI) is a heterogeneous condition with variable outcomes. Improving diagnosis to increase the likelihood that MCI reliably reflects prodromal Alzheimer's Disease (AD) would be of great benefit for clinical practice and intervention trials. In 230 cognitively normal (CN) and 394 MCI individuals from the Alzheimer's Disease Neuroimaging Initiative, we studied whether an MCI diagnostic requirement of impairment on at least two episodic memory tests improves 3-year prediction of medial temporal lobe atrophy and progression to AD. Based on external age-adjusted norms for delayed free recall on the Rey Auditory Verbal Learning Test (AVLT), MCI participants were further classified as having normal (AVLT+, above −1 SD, n = 121) or impaired (AVLT-, −1 SD or below, n = 273) AVLT performance. CN, AVLT+, and AVLT-groups differed significantly on baseline brain (hippocampus, entorhinal cortex) and cerebrospinal fluid (amyloid, tau, p-tau) biomarkers, with the AVLT-group being most abnormal. The AVLT-group had significantly more medial temporal atrophy and a substantially higher AD progression rate than the AVLT+ group (51% vs. 16%, p < 0.001). The AVLT+ group had similar medial temporal trajectories compared to CN individuals. Results were similar even when restricted to individuals with above average (based on the CN group mean) baseline medial temporal volume/thickness. Requiring impairment on at least two memory tests for MCI diagnosis can markedly improve prediction of medial temporal atrophy and conversion to AD, even in the absence of baseline medial temporal atrophy. This modification constitutes a practical and cost-effective approach for clinical and research settings.

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“…Pioneering work from Bondi and Jak in longitudinal aging cohorts rather consistently demonstrates that actuarial approaches that classify cognitive impairment using patterns and frequencies of low scores have led to modest rates of clinical reversion (mild cognitive impairment or "MCI" to "cognitively normal" at follow-up), improved characterization of risk of progression to dementia, and stronger associations with biologic disease markers than "single-test" methods Bondi & Smith, 2014;Jak et al, 2009;Jak et al, 2016;Petersen et al, 1999). Oltra-Cucarella et al (2018) recently showed that the number of low scores in a test battery predicted progression from MCI to dementia in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort with improved specificity (Oltra-Cucarella et al, 2018). Put simply, implementing these approaches increases a clinician's confidence about whether a patient's test scores reflect true cognitive changes versus normal performance variability unrelated to suspected underlying disease.…”

Section: Introductionmentioning

confidence: 99%

Discrepancy-Based Evidence for Loss of Thinking Abilities (DELTA): Development and Validation of a Novel Approach to Identifying Cognitive Changes

Asken

Thomas

Lee

et al. 2019

J Int Neuropsychol Soc

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Objective:To develop and validate the Discrepancy-based Evidence for Loss of Thinking Abilities (DELTA) score. The DELTA score characterizes the strength of evidence for cognitive decline on a continuous spectrum using well-established psychometric principles for improving detection of cognitive changes.Methods:DELTA score development used neuropsychological test scores from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort (two tests each from Memory, Executive Function, and Language domains). We derived regression-based normative reference scores using age, gender, years of education, and word-reading ability from robust cognitively normal ADNI participants. Discrepancies between predicted and observed scores were used for calculating the DELTA score (range 0–15). We validated DELTA scores primarily against longitudinal Clinical Dementia Rating-Sum of Boxes (CDR-SOB) and Functional Activities Questionnaire (FAQ) scores (baseline assessment through Year 3) using linear mixed models and secondarily against cross-sectional Alzheimer’s biomarkers.Results:There were 1359 ADNI participants with calculable baseline DELTA scores (age 73.7 ± 7.1 years, 55.4% female, 100% white/Caucasian). Higher baseline DELTA scores (stronger evidence of cognitive decline) predicted higher baseline CDR-SOB (ΔR2 = .318) and faster rates of CDR-SOB increase over time (ΔR2 = .209). Longitudinal changes in DELTA scores tracked closely and in the same direction as CDR-SOB scores (fixed and random effects of mean + mean-centered DELTA, ΔR2 > .7). Results were similar for FAQ scores. High DELTA scores predicted higher PET-Aβ SUVr (ρ = 324), higher CSF-pTau/CSF-Aβ ratio (ρ = .460), and demonstrated PPV > .9 for positive Alzheimer’s disease biomarker classification.Conclusions:Data support initial development and validation of the DELTA score through its associations with longitudinal functional changes and Alzheimer’s biomarkers. We provide several considerations for future research and include an automated scoring program for clinical use.

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Using Base Rate of Low Scores to Identify Progression from Amnestic Mild Cognitive Impairment to Alzheimer's Disease

Abstract: Considering normal variability in cognitive test performance when diagnosing MCI may help identify individuals at greatest risk of progression to AD with greater certainty.

Cited by 35 publications

References 44 publications

Risk of progression to Alzheimer’s disease for different neuropsychological Mild Cognitive Impairment subtypes: A hierarchical meta-analysis of longitudinal studies.

Risk of progression to Alzheimer’s disease for different neuropsychological Mild Cognitive Impairment subtypes: A hierarchical meta-analysis of longitudinal studies.

Modifying the minimum criteria for diagnosing amnestic MCI to improve prediction of brain atrophy and progression to Alzheimer’s disease

Discrepancy-Based Evidence for Loss of Thinking Abilities (DELTA): Development and Validation of a Novel Approach to Identifying Cognitive Changes

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