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35 The Effect of Diagnostic Method on Racial Disparities in Mild Cognitive Impairment and Dementia Diagnosis Using the NACC Database.

Published online by Cambridge University Press:  21 December 2023

Jennifer L Nosker*
Affiliation:
University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA.
Stephen L Aita
Affiliation:
Geisel School of Medicine at Dartmouth College, Hanover, NH, USA.
Nicholas C Borgogna
Affiliation:
Texas Tech University, Lubbock, TX, USA.
Tina Jimenez
Affiliation:
University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA.
Keenan A Walker
Affiliation:
National Institute on Aging, Baltimore, MD, USA.
Tasha Rhoads
Affiliation:
Rosalind Franklin University of Medicine & Science, North Chicago, IL, USA. Minneapolis VA Healthcare System, Minneapolis, MN, USA.
Janelle M Eloi
Affiliation:
Cogstate Ltd, New Haven, CT, USA.
Zachary J Resch
Affiliation:
University of Illinois at Chicago, Chicago, IL, USA.
Victor A Del Bene
Affiliation:
University of Alabama at Birmingham School of Medicine, Alabama, AL, USA
*
Correspondence: Jennifer Nosker, University of Alabama at Birmingham School of Medicine, [email protected]
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Abstract

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Objective:

Population studies have shown that Black individuals are at higher risk for MCI and dementia than White individuals but are more likely to be underdiagnosed or misdiagnosed. Although multiple contributory factors have been identified in relation to neurocognitive diagnostic disparities among persons of color, few studies have investigated race-associated differences in MCI and dementia classification across diagnostic methods. The current study examined the agreement of cognitive classification made via semi-structured interview and neuropsychological assessment.

Participants and Methods:

Only participants assigned normal cognitive status or cognitive impairment with presumed Alzheimer’s etiology were included in the study. Baseline visit data in the National Alzheimer’s Coordinating Center (NACC) dataset was collected to compare correspondence of cognitive classification (normal cognition, MCI, dementia) via semi-structured interview (Clinical Dementia Rating; CDR) with formal NACC diagnostic determination. NACC diagnostic determination was further separated by single clinician and consensus diagnostic methods. Inter-rater agreement was evaluated using chi-squared tests, and respective analyses were stratified for race (Black vs White), ethnicity (Hispanic vs Non-Hispanic), and education (<12 years vs. >12 years).

Results:

The sample size included 4,739 Black and 26,393 White participants across 43 Alzheimer’s Disease Research Centers (ADRCs). Inter-rater analyses between CDR (semi-structured interview) versus single-clinician and formal consensus NACC diagnostic methods showed strong (all (pc>.70) consistency in cognitive diagnoses overall, irrespective of race, ethnicity, and education. The percentage of agreement between diagnostic methods was nearly 100% for those categorized as cognitively normal or with dementia. However, the agreement for MCI was considerably lower (ranging from 28-74%) and revealed a disparity in diagnostic method between Black and White individuals. White individuals diagnosed with MCI via CDR (CDR total =0.5) were more likely to be labeled as having dementia regardless of NACC diagnostic method. However, Black individuals diagnosed with MCI via CDR were equally likely to be diagnosed as cognitively normal or with dementia via the formal consensus method.

Conclusions:

Irrespective of race and other demographic variables, diagnostic methods had high agreement for groups labeled with normal cognition and dementia. Agreement was consistently lower for the group labeled with MCI, with Black individuals having greater variability in diagnostic differentials when diagnosed via formal consensus method. The results of the study suggest that neuropsychological assessment continues to be an integral component of diagnosing individuals with MCI, reducing possible sources of bias.

Type
Poster Session 10: Late Breaking Science
Copyright
Copyright © INS. Published by Cambridge University Press, 2023