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CERAD practice effects and attrition bias in a dementia prevention trial

Published online by Cambridge University Press:  10 April 2013

Melissa Mathews ,
Erin Abner ,
Allison Caban-Holt ,
Richard Kryscio  and
Frederick Schmitt
Melissa Mathews
Affiliation:
Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA
Erin Abner
Affiliation:
Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA Department of Statistics and Biostatistics, University of Kentucky, Lexington, Kentucky, USA
Allison Caban-Holt
Affiliation:
Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA Department of Behavioral Science, University of Kentucky, Lexington, Kentucky, USA
Richard Kryscio
Affiliation:
Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA Department of Statistics and Biostatistics, University of Kentucky, Lexington, Kentucky, USA
Frederick Schmitt*
Affiliation:
Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA Department of Behavioral Science, University of Kentucky, Lexington, Kentucky, USA Department of Neurology, University of Kentucky, Lexington, Kentucky, USA
*
Correspondence should be addressed to: Frederick Schmitt, PhD, 303 Sanders-Brown Center on Aging, University of Kentucky, 800 S. Limestone Street, Lexington, KY 40536-023, USA. Phone: +1-859-218-5051; Fax: +1-859-323-1772. Email: fascom@uky.edu.
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Abstract

Background: The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) set of tests is frequently used for tracking cognition longitudinally in both clinical and research settings. Repeated cognitive assessments are an important component in measuring such changes; however, practice effects and attrition bias may obscure significant clinical change over time. The current study sought to examine the presence and magnitude of practice effects and the role of attrition bias in a sample of cognitively normal older men enrolled in a prevention trial.

Method: Participants were grouped according to whether they completed five years of follow-up (n = 182) or less (n = 126). Practice effects were examined in these participants as a whole (n = 308) and by group.

Results: Findings indicate that moderate practice effects exist in both groups on the CERAD T-score and that attrition bias likely does not play a contributing role in improved scores over time.

Conclusion: The current study provides additional evidence and support for previous findings that repeated cognitive assessment results in rising test scores in longitudinally collected data and demonstrates that these findings are unlikely to be due to attrition.

Keywords

practice effectsCERADattrition biasaging
Type
Research Article
Information
International Psychogeriatrics , Volume 25 , Issue 7 , July 2013 , pp. 1115 - 1123
Copyright
Copyright © International Psychogeriatric Association 2013 

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References

Boekamp, J. R., Strauss, M. E. and Adams, N. (1995). Estimating premorbid intelligence in African-American and white elderly Veterans using the American version of the National Adult Reading Test. Journal of Clinical and Experimental Neuropsychology, 17, 645–653.CrossRefGoogle ScholarPubMed
Burkhart, C. S.et al. (2011). Evaluation of a summary score of cognitive performance for use in trials in perioperative and critical care. Dementia and Geriatric Cognitive Disorders, 31, 451–459.CrossRefGoogle ScholarPubMed
Caban-Holt, A., Bottiggi, K. and Schmitt, F. A. (2005). Measuring treatment response in Alzheimer's disease clinical trials. Geriatrics, 60, Supplement, 3–8.Google Scholar
Caban-Holt, A.et al. (2006). Studying the effects of vitamin E and selenium for Alzheimer's disease prevention: the PREADViSE model. In Vellas, B., Fitten, L., Winblad, B., Feldman, H., Grundman, M., Giacobini, E. and Kurz, A. (eds.) Research and Practice in Alzheimer's Disese (pp. 124–130). Paris, France: Serdi.Google Scholar
Calamia, M., Markon, K. and Tranel, D. (2012). Scoring higher the second time around: meta-analyses of practice effects in neuropsychological assessment. Clinical Neuropsychologist, 26, 543–570.CrossRefGoogle ScholarPubMed
Chandler, M. J.et al. (2005). A total score for the CERAD neuropsychological battery. Neurology, 65, 102–106.CrossRefGoogle ScholarPubMed
Chang, C. C. H., Yang, H. C., Tang, G. and Ganguli, M. (2009). Minimizing attrition bias: a longitudinal study of depressive symptoms in an elderly cohort. International Psychogeriatrics, 21, 869–878.CrossRefGoogle Scholar
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159.CrossRefGoogle ScholarPubMed
Cooper, D. B.et al. (2001). Effects of practice on category fluency in Alzheimer's disease. Clinical Neuropsychologist, 15, 125–128.CrossRefGoogle ScholarPubMed
Cooper, D. B., Lacritz, L. H., Weiner, M. F., Rosenberg, R. N. and Cullum, C. M. (2004). Category fluency in mild cognitive impairment – reduced effect of practice in test–retest conditions. Alzheimer Disease & Associated Disorders, 18, 120–122.CrossRefGoogle ScholarPubMed
Ferris, S. H.et al. (1997). A multicenter evaluation of new treatment efficacy instruments for Alzheimer's disease clinical trials: overview and general results. Alzheimer Disease & Associated Disorders, 11, S1–S12.Google ScholarPubMed
Fillenbaum, G. G.et al. (2008). Consortium to establish a registry for Alzheimer's disease (CERAD): the first twenty years. Alzheimer's and Dementia, 4, 96–109.CrossRefGoogle ScholarPubMed
Galvin, J. E.et al. (2005). Predictors of preclinical Alzheimer's disease and dementia – a clinicopathologic study. Archives of Neurology, 62, 758–765.CrossRefGoogle ScholarPubMed
Hickman, S. E., Howieson, D. B., Dame, A., Sexton, G. and Kaye, J. (2000). Longitudinal analysis of the effects of the aging process on neuropsychological test performance in the healthy young-old and oldest-old. Developmental Neuropsychology, 17, 323–337.CrossRefGoogle ScholarPubMed
Jessen, F.et al. (2011). Prediction of dementia in primary care patients. PLoS One, 6, e16852. doi:10.1371/journal.pone.0016852.CrossRefGoogle ScholarPubMed
Klein, E. A.et al. (2003). The selenium and vitamin E cancer prevention trial. World Journal of Urology, 21, 21–27.CrossRefGoogle ScholarPubMed
Kryscio, R. J., Mendiondo, M. S., Schmitt, F. A. and Markesbery, W. R. (2004). Designing a large prevention trial: statistical issues. Statistics in Medicine, 23, 285–296.CrossRefGoogle ScholarPubMed
Morris, J. C.et al. (1989). The Consortium to Establish a Registry for Alzheimer's Disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer's disease. Neurology, 39, 1159–1165.Google Scholar
Rosen, W. G., Mohs, R. C. and Davis, K. L. (1984). A new rating-scale for Alzheimer's disease. American Journal of Psychiatry, 141, 1356–1364.Google ScholarPubMed
Rosetti, H., Cullum, C., Hynan, L. and Lacritz, L. (2010). The CERAD neuropsychological battery total score and the progression of Alzheimer disease. Alzheimer Disease & Associated Disorders, 24, 138–142.CrossRefGoogle Scholar
Stein, J.et al. (2012). The assessment of changes in cognitive functioning: age, education, and gender-specific reliable change indices for older adults tested on the CERAD-NP battery: results of the German study on ageing, cognition, and dementia in primary care patients (AgeCoDe). American Journal of Geriatric Psychiatry, 20, 84–97.CrossRefGoogle Scholar
Tierney, M. C., Yao, C., Kiss, A. and McDowell, I. (2005). Neuropsychological tests accurately predict incident Alzheimer's disease after 5 and 10 years. Neurology, 64, 1853–1859.CrossRefGoogle ScholarPubMed
Welsh, K. A.et al. (1994). The Consortium-to-Establish-a-Registry-for-Alzheimers-Disease (CERAD). 5. A normative study of the neuropsychological battery. Neurology, 44, 609–614.CrossRefGoogle Scholar
Zehnder, A., Blasi, S., Berres, M., Spiegel, R. and Monsch, A. (2007). Lack of practice effects on neuropsychological tests as early cognitive markers of Alzheimer disease? American Journal of Alzheimers Disease and Other Dementias, 22, 416–426.CrossRefGoogle ScholarPubMed
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