Demographically-corrected normative data for the RBANS learning ratio in a sample of older adults

Sensitivity of the African neuropsychology battery memory subtests and learning slopes in discriminating APOE 4 and amyloid pathology in adult individuals in the Democratic Republic of Congo

Background

The current study examined the sensitivity of two memory subtests and their corresponding learning slope metrics derived from the African Neuropsychology Battery (ANB) to detect amyloid pathology and APOEε4 status in adults from Kinshasa, the Democratic Republic of the Congo.

Methods

85 participants were classified for the presence of β-amyloid pathology and based on allelic presence of APOEε4 using Simoa. All participants were screened using CSID and AQ, underwent verbal and visuospatial memory testing from ANB, and provided blood samples for plasma Aβ42, Aβ40, and APOE proteotype. Pearson correlation, linear and logistic regression were conducted to compare amyloid pathology and APOEε4 status with derived learning scores, including initial learning, raw learning score, learning over trials, and learning ratio.

Results

Our sample included 35 amyloid positive and 44 amyloid negative individuals as well as 42 without and 39 with APOEε4. All ROC AUC ranges for the prediction of amyloid pathology based on learning scores were low, ranging between 0.56-0.70 (95% CI ranging from 0.44-0.82). The sensitivity of all the scores ranged between 54.3-88.6, with some learning metrics demonstrating good sensitivity. Regarding APOEε4 prediction, all AUC values ranged between 0.60-0.69, with all sensitivity measures ranging between 53.8-89.7. There were minimal differences in the AUC values across learning slope metrics, largely due to the lack of ceiling effects in this sample.

Discussion

This study demonstrates that some ANB memory subtests and learning slope metrics can discriminate those that are normal from those with amyloid pathology and those with and without APOEε4, consistent with findings reported in Western populations.

A quantitative review of competing learning slope metrics: effects of age, sex, and clinical diagnosis

INTRODUCTION

In learning and memory tests that involve multiple presentations of the same material, learning slope refers to the degree to which examinees improve performances over successive learning trials. We aimed to quantitatively review the traditional raw learning slope (RLS), and the newly created learning ratio (LR) to understand the effects of demographic variables and clinical diagnoses on learning slope (e.g., limited improvement over multiple trials), and to develop demographically sensitive norms.

METHOD

A systematic literature search was conducted to evaluate the potential for these aims to be examined across the most popular contemporary multi-trial learning tests. Two databases were searched. Following this, hierarchical linear modeling was used to examine how demographic variables predict learning slope indices. These results were in turn used to contrast the performance of clinical groups with the predicted performance of demographically similar healthy controls. Finally, preliminary normative estimates for learning slope indices were presented.

RESULTS

A total of 82 studies met criteria for inclusion in this study. However, the Rey Auditory Verbal Learning Test (RAVLT) was the only test to have sufficient trial-level learning and demographic data. Fifty-eight samples from 19 studies were quantitatively examined. Hierarchical linear models provided evidence of sex differences and a curvilinear decline in learning slope with age, with strongest and most consistent effects for LR relative to RLS. Regression-based norms for demographically corrected RLS and LR scores for the RAVLT are presented. The effect of clinical diagnoses was consistently stronger for LR, and Alzheimer's disease had the strongest effect, followed by invalid performances, severe traumatic brain injury, and seizures/epilepsy.

CONCLUSION

Overall, LR enjoys both conceptual and demonstrated psychometric advantages over RLS. Replication of these findings can be completed by reanalyzing existing datasets. Further work may focus on the utility of using LR in diagnosis and prediction of clinical prognosis.

Validation of and Demographically Adjusted Normative Data for the Learning Ratio Derived from the RAVLT in Robustly Intact Older Adults

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.