Browsing by Author "Spencer, Robert J."

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    Demographically-corrected normative data for the RBANS Learning Ratio in a sample of older adults
    (Taylor & Francis, 2022) Hammers, Dustin B.; Duff, Kevin; Spencer, Robert J.; Neurology, School of Medicine
    Background: A novel learning slope score - the Learning Ratio (LR) - has recently been developed that appears to be sensitive to memory performance and AD pathology more optimally than traditional learning slope calculations. While promising, this research to date has been both experimental and based on group differences, and therefore does not aid in the interpretation of individual LR performance for either clinical or research settings. The objective of the current study was to develop demographically-corrected normative data on these LR learning slopes on verbal learning measures from the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Method: The current study examined the influence of age and education on LR metrics for the List Learning, Story Memory, and an Aggregated RBANS score in 200 cognitively intact adults aged 65 or older using linear regression. Results: Age and education correlated with most LR metrics, but no sex differences were observed. Linear regression permitted the prediction of LR values from age and education, which are then compared to observed LR values. The result is demographically-corrected T scores for these LR metrics. Conclusions: By comparing observed and predicted LR scores calculated from regression-based prediction equations, this represents the first step towards interpretation of individual performances on this metric for clinical decision making and treatment planning purposes. With future replication in diverse and heterogenous samples, we hope to offer a new clinical tool for the examination of learning slopes in older adults.
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    Relationship between a novel learning slope metric and Alzheimer’s disease biomarkers
    (Taylor & Francis, 2022) Hammers, Dustin B.; Suhrie, Kayla; Dixon, Ava; Gradwohl, Brian D.; Archibald, Zane G.; King, Jace B.; Spencer, Robert J.; Duff, Kevin; Hoffman, John M.; Neurology, School of Medicine
    The Learning Ratio (LR) is a novel learning score examining the proportion of information learned over successive learning trials relative to information available to be learned. Validation is warranted to understand LR's sensitivity to Alzheimer's disease (AD) pathology. One-hundred twenty-three participants across the AD continuum underwent memory assessment, quantitative brain imaging, and genetic analysis. LR scores were calculated from the HVLT-R, BVMT-R, RBANS List Learning, and RBANS Story Memory, and compared to total hippocampal volumes,18F-Flutemetamol composite SUVR uptake, and APOE ε4 status. Lower LR scores were consistently associated with smaller total hippocampal volumes, greater cerebral β-amyloid deposition, and APOE ε4 positivity. This LR score outperformed a traditional learning slope calculation in all analyses. LR is sensitive to AD pathology along the AD continuum - more so than a traditional raw learning score - and reducing the competition between the first trial and subsequent trials can better depict learning capacity.
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    Sensitivity of memory subtests and learning slopes from the ADAS-Cog to distinguish along the continuum of the NIA-AA Research Framework for Alzheimer’s Disease
    (Taylor & Francis, 2023) Hammers, Dustin B.; Kostadinova, Ralitsa V.; Spencer, Robert J.; Ikanga, Jean N.; Unverzagt, Frederick W.; Risacher, Shannon L.; Apostolova, Liana G.; Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of Medicine
    Despite extensive use of the Alzheimer's Disease (AD) Assessment Scale - Cognitive Subscale (ADAS-Cog) in AD research, exploration of memory subtests or process scores from the measure has been limited. The current study sought to establish validity for the ADAS-Cog Word Recall Immediate and Delayed Memory subtests and learning slope scores by showing that they are sensitive to AD biomarker status. Word Recall subtest and learning slope scores were calculated for 441 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90). All participants were categorized using the NIA-AA Research Framework - based on PET-imaging of β-amyloid (A) and tau (T) deposition - as Normal AD Biomarkers (A-T-), Alzheimer's Pathologic Change (A + T-), or Alzheimer's disease (A + T+). Memory subtest and learning slope performances were compared between biomarker status groups, and with regard to how well they discriminated samples with (A + T+) and without (A-T-) biomarkers. Lower Word Recall memory subtest scores - and scores for a particular learning slope calculation, the Learning Ratio - were observed for the AD (A + T+) group than the other biomarker groups. Memory subtest and Learning Ratio scores further displayed fair to good receiver operator characteristics when differentiating those with and without AD biomarkers. When comparing across learning slopes, the Learning Ratio metric consistently outperformed others. ADAS-Cog memory subtests and the Learning Ratio score are sensitive to AD biomarker status along the continuum of the NIA-AA Research Framework, and the results offer criterion validity for use of these subtests and process scores as unique markers of memory capacity.
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    The Relationship Between Learning Slopes and Alzheimer’s Disease Biomarkers in Cognitively Unimpaired Participants with and without Subjective Memory Concerns
    (Taylor & Francis, 2023) Hammers, Dustin B.; Pentchev, Julian V.; Kim, Hee Jin; Spencer, Robert J.; Apostolova, Liana G.; Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of Medicine
    Objective: Learning slopes represent serial acquisition of information during list-learning tasks. Although several calculations for learning slopes exist, the Learning Ratio (LR) has recently demonstrated the highest sensitivity toward changes in cognition and Alzheimer's disease (AD) biomarkers. However, investigation of learning slopes in cognitively unimpaired individuals with subjective memory concerns (SMC) has been limited. The current study examines the association of learning slopes to SMC, and the role of SMC in the relationship between learning slopes and AD biomarkers in cognitively unimpaired individuals. Method: Data from 950 cognitively unimpaired participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 89) were used to calculate learning slope metrics. Learning slopes among those with and without SMC were compared with demographic correction, and the relationships of learning slopes with AD biomarkers of bilateral hippocampal volume and β-amyloid pathology were determined. Results: Learning slopes were consistently predictive of hippocampal atrophy and β-amyloid deposition. Results were heightened for LR relative to the other learning slopes. Additionally, interaction analyses revealed different associations between learning slopes and hippocampal volume as a function of SMC status. Conclusions: Learning slopes appear to be sensitive to SMC and AD biomarkers, with SMC status influencing the relationship in cognitively unimpaired participants. These findings advance our knowledge of SMC, and suggest that LR - in particular - can be an important tool for the detection of AD pathology in both SMC and in AD clinical trials.
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    Validation of and Demographically Adjusted Normative Data for the Learning Ratio Derived from the RAVLT in Robustly Intact Older Adults
    (Oxford University Press, 2022) Hammers, Dustin B.; Spencer, Robert J.; Apostolova, Liana G.; Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of Medicine
    Background: The learning ratio (LR) is a novel learning slope score that was developed to identify learning more accurately by considering the proportion of information learned after the first trial of a multi-trial learning task. Specifically, LR is the number of items learned after trial one divided by the number of items yet to be learned. Although research on LR has been promising, convergent validation, clinical characterization, and demographic norming of this LR metric are warranted to understand its clinical utility when derived from the Rey Auditory Verbal Learning Test (RAVLT). Method: Data from 674 robustly cognitively intact older participants from the Alzheimer's Disease Neuroimaging Initiative (aged 54- 89) were used to calculate the LR metric. Comparison of LR's relationship with standard memory measures was undertaken relative to other traditional learning slope metrics. In addition, retest reliability at 6, 12, and 24 months was examined, and demographically adjusted normative comparisons were developed. Results: Lower LR scores were associated with poorer performances on memory measures, and LR scores outperformed traditional learning slope calculations across all analyses. Retest reliability exceeded acceptability thresholds across time, and demographically adjusted normative equations suggested better performance for cognitively intact participants than those with mild cognitive impairment. Conclusions: These results suggest that this LR score possesses sound retest reliability and can better reflect learning capacity than traditional learning slope calculations. With the added development and validation of regression-based normative comparisons, these findings support the use of the RAVLT LR as a clinical tool to inform clinical decision-making and treatment.