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Predicting cognitive decline and conversion to Alzheimer’s disease in older adults using the NAB List Learning test

Published online by Cambridge University Press:  07 April 2010

BRANDON E. GAVETT ,
AL OZONOFF ,
VLADA DOKTOR ,
JOSEPH PALMISANO ,
ANIL K. NAIR ,
ROBERT C. GREEN ,
ANGELA L. JEFFERSON  and
ROBERT A. STERN
BRANDON E. GAVETT*
Affiliation:
Department of Neurology, Boston University School of Medicine, Boston, Massachusetts Boston University Alzheimer’s Disease Center, Boston, Massachusetts Center for the Study of Traumatic Encephalopathy, Boston University, Boston, Massachusetts
AL OZONOFF
Affiliation:
Boston University Alzheimer’s Disease Center, Boston, Massachusetts Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
VLADA DOKTOR
Affiliation:
Boston University Alzheimer’s Disease Center, Boston, Massachusetts
JOSEPH PALMISANO
Affiliation:
Boston University Alzheimer’s Disease Center, Boston, Massachusetts Data Coordinating Center, Boston University School of Public Health, Boston, Massachusetts
ANIL K. NAIR
Affiliation:
Department of Neurology, Boston University School of Medicine, Boston, Massachusetts Boston University Alzheimer’s Disease Center, Boston, Massachusetts
ROBERT C. GREEN
Affiliation:
Department of Neurology, Boston University School of Medicine, Boston, Massachusetts Boston University Alzheimer’s Disease Center, Boston, Massachusetts Department of Medicine (Genetics), Boston University School of Medicine, Boston, Massachusetts Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
ANGELA L. JEFFERSON
Affiliation:
Department of Neurology, Boston University School of Medicine, Boston, Massachusetts Boston University Alzheimer’s Disease Center, Boston, Massachusetts Department of Medicine (Geriatrics), Boston University School of Medicine, Boston, Massachusetts Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, Massachusetts
ROBERT A. STERN
Affiliation:
Department of Neurology, Boston University School of Medicine, Boston, Massachusetts Boston University Alzheimer’s Disease Center, Boston, Massachusetts Center for the Study of Traumatic Encephalopathy, Boston University, Boston, Massachusetts
*
*Correspondence and reprint requests to: Brandon E. Gavett, Instructor of Neurology, Boston University School of Medicine, 72 East Concord Street B-7800, Boston, MA 02118-2526. E-mail: begavett@bu.edu
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Abstract

To validate the Neuropsychological Assessment Battery (NAB) List Learning test as a predictor of future multi-domain cognitive decline and conversion to Alzheimer’s disease (AD), participants from a longitudinal research registry at a national AD Center were, at baseline, assigned to one of three groups (control, mild cognitive impairment [MCI], or AD), based solely on a diagnostic algorithm for the NAB List Learning test (Gavett et al., 2009), and followed for 1–3 years. Rate of change on common neuropsychological tests and time to convert to a consensus diagnosis of AD were evaluated to test the hypothesis that these outcomes would differ between groups (AD>MCI>control). Hypotheses were tested using linear regression models (n = 251) and Cox proportional hazards models (n = 265). The AD group declined significantly more rapidly than controls on Mini-Mental Status Examination (MMSE), animal fluency, and Digit Symbol; and more rapidly than the MCI group on MMSE and Hooper Visual Organization Test. The MCI group declined more rapidly than controls on animal fluency and CERAD Trial 3. The MCI and AD groups had significantly shorter time to conversion to a consensus diagnosis of AD than controls. The predictive validity of the NAB List Learning algorithm makes it a clinically useful tool for the assessment of older adults. (JINS, 2010, 16, 651–660.)

Keywords

MemoryDementiaDifferential diagnosisAgingNeuropsychologyNeuropsychological tests
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 16 , Issue 4 , July 2010 , pp. 651 - 660
Copyright
Copyright © The International Neuropsychological Society 2010

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References

REFERENCES

Andel, R., Vigen, C., Mack, W., Clark, L.J., & Gatz, M. (2006). The effect of education and occupational complexity on rate of cognitive decline in Alzheimer’s patients. Journal of the International Neuropsychological Society, 12, 147–152.CrossRefGoogle ScholarPubMed
Andersson, C., Lindau, M., Almkvist, O., Engfeldt, P., Johansson, S.-E., & Jonhagen, M. (2006). Identifying patients at high and low risk of cognitive decline using Rey Auditory Verbal Learning Test among middle-aged memory clinic outpatients. Dementia and Geriatric Cognitive Disorders, 21, 251–259.CrossRefGoogle ScholarPubMed
Arriagada, P.V., Growdon, J.H., Hedley-Whyte, E.T., & Hyman, B.T. (1992). Neurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimer’s disease. Neurology, 42, 631–639.CrossRefGoogle ScholarPubMed
Budson, A.E., & Price, B.H. (2005). Memory dysfunction. New England Journal of Medicine, 352, 692–699.CrossRefGoogle ScholarPubMed
Dubois, B., Feldman, H.H., Jacova, C., DeKosky, S.T., Barberger-Gateau, P., Cummings, J., et al. . (2007). Research criteria for the diagnosis of Alzheimer’s disease: Revising the NINCDS-ADRDA criteria. Lancet Neurology, 6, 734–746.CrossRefGoogle ScholarPubMed
Folstein, M., Folstein, S.E., & McHugh, P.R. (1975). “Mini-Mental State.” A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.CrossRefGoogle ScholarPubMed
Gavett, B.E., Poon, S.J., Ozonoff, A., Jefferson, A.L., Nair, A.K., Green, R.C., et al. . (2009). Diagnostic utility of the NAB List Learning test in Alzheimer’s disease and amnestic mild cognitive impairment. Journal of the International Neuropsychological Society, 15, 121–129.CrossRefGoogle ScholarPubMed
Guillozet, A.L., Weintraub, S., Mash, D.C., & Mesulam, M.-M. (2003). Neurofibrillary tangles, amyloid, and memory in aging and mild cognitive impairment. Archives of Neurology, 60, 729–736.CrossRefGoogle ScholarPubMed
Hall, C.B., Derby, C., LeValley, A., Katz, M.J., Verghese, J., & Lipton, R.B. (2007). Education delays accelerated decline on a memory test in persons who develop dementia. Neurology, 69, 1657–1664.CrossRefGoogle ScholarPubMed
Hamilton, J.M., Salmon, D.P., Galasko, D., Raman, R., Emond, J., Hansen, L.A., et al. . (2008). Visuospatial deficits predict rate of cognitive decline in autopsy-verified dementia with Lewy bodies. Neuropsychology, 22, 729–737.CrossRefGoogle ScholarPubMed
Hooper, H. (1983). Hooper Visual Organization Test (HVOT). Los Angeles: Western Psychological Services.Google Scholar
Jacobs, D., Sano, M., Marder, K., Bell, K., Bylsma, F., Lafleche, G., et al. . (1994). Age at onset of Alzheimer’s disease: Relation to pattern of cognitive dysfunction and rate of decline. Neurology, 44, 1215–1220.CrossRefGoogle ScholarPubMed
Jefferson, A.L., Wong, S., Bolen, E., Ozonoff, A., Green, R.C., & Stern, R.A. (2006). Cognitive correlates of HVOT performance differ between individuals with mild cognitive impairment and normal controls. Archives of Clinical Neuropsychology, 21, 405–412.CrossRefGoogle ScholarPubMed
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E.M. (1984). Clinical diagnosis of Alzheimer’s disease: Report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology, 34, 939–944.CrossRefGoogle ScholarPubMed
Morris, J.C. (2006). Mild cognitive impairment is early-stage Alzheimer disease: Time to revise diagnostic criteria. Archives of Neurology, 63, 15–16.CrossRefGoogle ScholarPubMed
Morris, J.C., Heyman, A., Mohs, R.C., Hughes, J.P., van Belle, G., Fillenbaum, G., 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
Mungas, D., Reed, B.R., Ellis, W.G., & Jagust, W.J. (2001). The effects of age on rate of progression of Alzheimer disease and dementia with associated cerebrovascular disease. Archives of Neurology, 58, 1243–1247.CrossRefGoogle ScholarPubMed
Murphy, K.J., Rich, J.B., & Troyer, A.K. (2006). Verbal fluency patterns in amnestic mild cognitive impairment are characteristic of Alzheimer’s type dementia. Journal of the International Neuropsychological Society, 12, 570–574.CrossRefGoogle ScholarPubMed
Reitan, R.M., & Wolfson, D. (1993). The Halstead-Reitan neuropsychological test battery: Theory and clinical interpretation (2nd ed.). Tuscon, AZ: Neuropsychology Press.Google Scholar
Royall, D. (2006). Mild cognitive impairment and functional status. Journal of the American Geriatrics Society, 54, 163–165.CrossRefGoogle ScholarPubMed
Salloway, S., Mintzer, J., Weiner, M.F., & Cummings, J.L. (2008). Disease-modifying therapies in Alzheimer’s disease. Alzheimer’s & Dementia, 4, 65–79.CrossRefGoogle ScholarPubMed
Stern, R.A., & White, T. (2003) Neuropsychological Assessment Battery. Lutz, FL: Psychological Assessment Resources.Google Scholar
Wechsler, D. (1981). WAIS-R manual. New York: The Psychological Corporation.Google Scholar
Wechsler, D. (1987). Wechsler Memory Scale-Revised. San Antonio, TX: The Psychological Corporation.Google Scholar
Weintraub, S., Salmon, D., Mercaldo, N., Ferris, S., Graff-Radford, N.R., Chui, H., et al. . (2009). The Alzheimer’s Disease Centers’ Uniform Data Set (UDS): The neuropsychologic test battery. Alzheimer Disease and Associated Disorders, 23, 91–101.CrossRefGoogle ScholarPubMed
Wilcock, G.K., & Esiri, M.M. (1982). Plaques, tangles and dementia. A quantitative study. Journal of the Neurological Sciences, 56, 343–356.CrossRefGoogle ScholarPubMed
Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L.O., et al. . (2004). Mild cognitive impairment – beyond controversies, towards a consensus: Report of the International Working Group on Mild Cognitive Impairment. Journal of Internal Medicine, 256, 240–246.CrossRefGoogle Scholar
Yaari, R., & Corey-Bloom, J. (2007). Alzheimer’s disease. Seminars in Neurology, 27, 32–41.CrossRefGoogle ScholarPubMed