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Susceptibility of the conventional criteria for mild cognitive impairment to false‐positive diagnostic errors
Author(s) -
Edmonds Emily C.,
DelanoWood Lisa,
Clark Lindsay R.,
Jak Amy J.,
Nation Daniel A.,
McDonald Carrie R.,
Libon David J.,
Au Rhoda,
Galasko Douglas,
Salmon David P.,
Bondi Mark W.
Publication year - 2015
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2014.03.005
Subject(s) - biomarker , dementia , neuropsychology , cognitive impairment , neuroimaging , medicine , cognition , psychology , alzheimer's disease neuroimaging initiative , cohort , cluster (spacecraft) , oncology , neuropsychological assessment , clinical psychology , disease , psychiatry , biology , biochemistry , computer science , programming language
Background We assessed whether mild cognitive impairment (MCI) subtypes could be empirically derived within the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort and examined associated biomarkers and clinical outcomes. Methods Cluster analysis was performed on neuropsychological data from 825 MCI ADNI participants. Results Four subtypes emerged: (1) dysnomic (n = 153), (2) dysexecutive (n = 102), (3) amnestic (n = 288), and (4) cluster‐derived normal (n = 282) who performed within normal limits on cognitive testing. The cluster‐derived normal group had significantly fewer APOE ε4 carriers and fewer who progressed to dementia compared with the other subtypes; they also evidenced cerebrospinal fluid Alzheimer's disease biomarker profiles that did not differ from the normative reference group. Conclusions Identification of empirically derived MCI subtypes demonstrates heterogeneity in MCI cognitive profiles that is not captured by conventional criteria. The large cluster‐derived normal group suggests that conventional diagnostic criteria are susceptible to false‐positive errors, with the result that prior MCI studies may be diluting important biomarker relationships.