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. 2011 Apr 19;6(4):e16973.
doi: 10.1371/journal.pone.0016973.

Intra-individual variability in Alzheimer's disease and cognitive aging: definitions, context, and effect sizes

Rochelle E Tractenberg  1 , Robert H Pietrzak
Affiliations

Intra-individual variability in Alzheimer's disease and cognitive aging: definitions, context, and effect sizes

Rochelle E Tractenberg et al. PLoS One. .

Abstract

Background/aims: To explore different definitions of intra-individual variability (IIV) to summarize performance on commonly utilized cognitive tests (Mini Mental State Exam; Clock Drawing Test); compare them and their potential to differentiate clinically-defined populations; and to examine their utility in predicting clinical change in individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

Methods: Sample statistics were computed from ADNI cohorts with no cognitive diagnosis, a diagnosis of mild cognitive impairment (MCI), and a diagnosis of possible or probable Alzheimer's disease (AD). Nine different definitions of IIV were computed for each sample, and standardized effect sizes (Cohen's d) were computed for each of these definitions in 500 simulated replicates using scores on the Mini Mental State Exam and Clock Drawing Test. IIV was computed based on test items separately ('within test' IIV) and the two tests together ('across test' IIV). The best performing definition was then used to compute IIV for a third test, the Alzheimer's Disease Assessment Scale-Cognitive, and the simulations and effect sizes were again computed. All effect size estimates based on simulated data were compared to those computed based on the total scores in the observed data. Association between total score and IIV summaries of the tests and the Clinician's Dementia Rating were estimated to test the utility of IIV in predicting clinically meaningful changes in the cohorts over 12- and 24-month intervals.

Results: ES estimates differed substantially depending on the definition of IIV and the test(s) on which IIV was based. IIV (coefficient of variation) summaries of MMSE and Clock-Drawing performed similarly to their total scores, the ADAS total performed better than its IIV summary.

Conclusion: IIV can be computed within (items) or across (totals) items on commonly-utilized cognitive tests, and may provide a useful additional summary measure of neuropsychological test performance.

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Conflict of interest statement

Competing Interests: RET is an academic editor at PLoS ONE. RHP declares no competing interests. ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics, Johnson and Johnson, Eli Lilly and Co., Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer Inc, F. Hoffman-La Roche, Schering-Plough, Synarc, Inc., and Wyeth, as well as non-profit partners the Alzheimer's Association and Alzheimer's Drug Discovery Foundation, with participation from the U.S. Food and Drug Administration. Private sector contributions to ADNI are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro-Imaging at the University of California, Los Angeles. This does not alter the authors' adherence to all the PLoS ONE policies on sharing data and materials.

Figures

Figure 1
Figure 1. Mean effect sizes based on 500 replications of simulating 500 “observations” for the nine IIV formulations outlined in the text.
Reference effect size (ES) values are shown giving the value obtained from the observed data for the total test score (flat lines) (Figure 1A: N vs MCI; Figure 1B: MCI vs AD).
See this image and copyright information in PMC

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References

    1. Hultsch DF, MacDonald SWS, Hunter MA, Levy-Bencheton J, Strauss E. Intraindividual variability in cognitive performance in older adults: comparison of adults with mild dementia, adults with arthritis, and healthy adults. Neuropsychology. 2000;14(4):588–598. - PubMed
    1. Christensen H, Dear KBG, Anstey KJ, Parslow RA, Sachdev P, et al. Within-Occasion Intraindividual Variability and Preclinical Diagnostic Status: Is Intraindividual Variability an Indicator of Mild Cognitive Impairment? Neuropsychology. 2005;19(3):309–317. - PubMed
    1. Hultsch DF, Strauss E, Hunter MA, MacDonald SWS. Intraindividual variability, cognition, and aging. In: Craik FIM, Salthouse TA, editors. The Handbook of Aging and Cognition, 3E. New York, NY: Psychology Press; 2008. pp. 491–556.
    1. Hultsch DF, MacDonald SWS. Intraindividual variability in performance as a theoretical window onto cognitive aging. In: Dixon RA, Backman L, Nilsson L-G, editors. New Frontiers in Cognitive Aging. New York: Oxford University Press; 2004. pp. 65–88.
    1. Nesselroade JR, Salthouse TA. Methodological and theoretical implications of intraindividual variability in perceptual-motor performance. Journal of Gerontolology, B Psychological Science and Social Science. 2004;59(2):P49–P55. - PubMed

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