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Subjective Cognitive Complaints Contribute to Misdiagnosis of Mild Cognitive Impairment

Published online by Cambridge University Press:  22 August 2014

Emily C. Edmonds ,
Lisa Delano-Wood ,
Douglas R. Galasko ,
David P. Salmon  and
Mark W. Bondi
Emily C. Edmonds
Affiliation:
Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, California
Lisa Delano-Wood
Affiliation:
Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, California Veterans Affairs San Diego Healthcare System, San Diego, California
Douglas R. Galasko
Affiliation:
Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, California Veterans Affairs San Diego Healthcare System, San Diego, California Department of Neurosciences, University of California San Diego, School of Medicine, La Jolla, California
David P. Salmon
Affiliation:
Department of Neurosciences, University of California San Diego, School of Medicine, La Jolla, California
Mark W. Bondi*
Affiliation:
Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, California Veterans Affairs San Diego Healthcare System, San Diego, California
*
Correspondence and reprint requests to: Mark W. Bondi, PhD, Psychology Service (116B), VA San Diego, Healthcare System, 3350 La Jolla Village Drive, San Diego, CA 92161. E-mail: [email protected]
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Abstract

Subjective cognitive complaints are a criterion for the diagnosis of mild cognitive impairment (MCI), despite their uncertain relationship to objective memory performance in MCI. We aimed to examine self-reported cognitive complaints in subgroups of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) MCI cohort to determine whether they are a valuable inclusion in the diagnosis of MCI or, alternatively, if they contribute to misdiagnosis. Subgroups of MCI were derived using cluster analysis of baseline neuropsychological test data from 448 ADNI MCI participants. Cognitive complaints were assessed via the Everyday Cognition (ECog) questionnaire, and discrepancy scores were calculated between self- and informant-report. Cluster analysis revealed Amnestic and Mixed cognitive phenotypes as well as a third Cluster-Derived Normal subgroup (41.3%), whose neuropsychological and cerebrospinal fluid (CSF) Alzheimer’s disease (AD) biomarker profiles did not differ from a “robust” normal control group. This cognitively intact phenotype of MCI participants overestimated their cognitive problems relative to their informant, whereas Amnestic MCI participants with objective memory impairment underestimated their cognitive problems. Underestimation of cognitive problems was associated with positive CSF AD biomarkers and progression to dementia. Overall, there was no relationship between self-reported cognitive complaints and objective cognitive functioning, but significant correlations were observed with depressive symptoms. The inclusion of self-reported complaints in MCI diagnostic criteria may cloud rather than clarify diagnosis and result in high rates of misclassification of MCI. Discrepancies between self- and informant-report demonstrate that overestimation of cognitive problems is characteristic of normal aging while underestimation may reflect greater risk for cognitive decline. (JINS, 2014, 20, 1–12)

Keywords

Mild cognitive impairmentAwarenessCluster analysisDiagnostic errorsNeuropsychologyDementiaAlzheimer disease
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 20 , Issue 8 , September 2014 , pp. 836 - 847
Copyright
Copyright © The International Neuropsychological Society 2014 

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Footnotes

*

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of the ADNI and/or provided data but did not participate in analysis or writing of this article. 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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