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Operationalizing Impaired Performance in Neuropsychological Assessment: A Comparison of the Use of Published Versus Sample-Based Normative Data for the Prediction of Dementia

Published online by Cambridge University Press:  11 December 2019

Brandy L. Callahan Open the ORCID record for Brandy L. Callahan [Opens in a new window]  and
for the Alzheimer’s Disease Neuroimaging Initiative
Brandy L. Callahan*
Affiliation:
Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada Hotchkiss Brain Institute, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada Mathison Centre for Mental Health Research & Education, 3280 Hospital Drive NW, Calgary, Alberta T2N 4Z6, Canada
for the Alzheimer’s Disease Neuroimaging Initiative
Affiliation:
Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada Hotchkiss Brain Institute, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada Mathison Centre for Mental Health Research & Education, 3280 Hospital Drive NW, Calgary, Alberta T2N 4Z6, Canada
*
Correspondence and reprint requests to: Brandy L. Callahan, Department of Psychology, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada. Phone: +1 403 220 7291. E-mail: brandy.callahan@ucalgary.ca
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Abstract

Objectives:

To compare the sensitivity, specificity, and predictive value of published versus sample-based norms to detect early dementia in the Uniform Data Set (UDS).

Methods:

The UDS was administered to 526 nondemented participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Baseline scores were standardized using published norms and healthy control data from ADNI corrected for age, education, and sex. Subjects obtaining two scores < −1 SD (determined separately using published and sample norms) were labeled “at risk for dementia.” Both methods were compared on sensitivity, specificity, and positive/negative predictive value (PPV/NPV) for dementia at follow-up.

Results:

Risk scores derived from published data had 86.1% sensitivity, 62.0% specificity, 68.6% accuracy, 46.1% PPV, and 92.2% NPV. Those from sample norms were more sensitive (91.0%), less specific (52.9%), and less accurate (63.3%), with worse PPV (42.1%) and similar NPV (94.0%). Sample norms were better at identifying incident dementia cases with relatively lower education than those with higher education. Discrepancies between both methods were more common in women.

Conclusions:

Sample norms are marginally more sensitive than published norms for predicting dementia, while published norms are slightly more accurate. Accuracy of risk estimates for women and those with lower education may be increased using locally generated norms.

Keywords

Uniform Data SetDementia risk predictionOlder peopleCognitiveSensitivitySpecificityAccuracyAlzheimer
Type
Brief Communication
Information
Journal of the International Neuropsychological Society , Volume 26 , Issue 6 , July 2020 , pp. 624 - 631
Copyright
Copyright © INS. Published by Cambridge University Press, 2019

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Footnotes

*

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

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