Neuropsychological tests accurately predict incident Alzheimer disease after 5 and 10 years
Abstract
OBJECTIVE: To determine whether neuropsychological tests accurately predict incident Alzheimer disease (AD) after 5 and 10 years in participants of the Canadian Study of Health and Aging (CSHA) who were initially nondemented. METHODS: The CSHA was conducted in three waves: CSHA-1 (1991 to 1992), CSHA-2 (1996 to 1997), and CSHA-3 (2001 to 2002). The 10-year prediction study included those who completed neuropsychological testing at CSHA-1 and received a diagnostic assessment at CSHA-3 (n = 263). The 5-year prediction study included those who completed neuropsychological testing at CSHA-2 and received a diagnostic assessment at CSHA-3 (n = 551). The diagnostic workup for dementia at CSHA-3 was formulated without knowledge of neuropsychological test performance at CSHA-1 or CSHA-2. The authors excluded cases with a baseline diagnosis of dementia or a prior history of any condition likely to affect the brain. Age and education were included in all analyses as covariates. RESULTS: In the 10-year follow-up study, only one test (short delayed verbal recall) emerged from the forward regression analyses. The model with this test and two covariates was significant, chi2 (3) = 31.61, p < 0.0001 (sensitivity = 73%, specificity = 70%). In the 5-year follow-up study, three tests (short delayed verbal recall, animal fluency, and information) emerged from the forward logistic regression analyses. The model was significant, chi2 (5) = 91.34, p < 0.0001 (sensitivity = 74%, specificity = 83%). Both models were supported with bootstrapping estimates. CONCLUSIONS: In a large epidemiologic sample of nondemented participants, neuropsychological tests accurately predicted conversion to Alzheimer disease after 5 and 10 years.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Story recall may be less sensitive to MCI or an evolving dementia than tests of verbal list learning or visual memory.
“Second, story recall may be less sensitive to MCI or an evolving dementia than tests of verbal list learning [11–16] or perhaps visual memory [17].”
From Neuropsychological Criteria for Mild Cognitive Impairment Improves Diagnostic Precision, Biomarker Associations, and Progression Rates (2014) · cites this paper as [16]
Cites
Visual memory predicts Alzheimer's disease more than a decade before diagnosis
Kawas, C. H., Corrada, M. M., Brookmeyer, R., Morrison, A., Resnick, S. M., Zonderman, A. B., & Arenberg, D. (2003) · Neurology · doi:10.1212/01.wnl.0000055813.36504.bf · Cited by 247 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria
Dubois, B., Feldman, H. H., Jacova, C., DeKosky, S. T., Barberger-Gateau, P., Cummings, J., Delacourte, A., Galasko, D., Gauthier, S., Jicha, G., et al. (2007) · The Lancet Neurology · doi:10.1016/s1474-4422(07)70178-3 · Cited by 4,411 · see citing works
Bondi, M. W., Initiative, F. T. A. D. N., Edmonds, E. C., Jak, A. J., Clark, L. R., Delano-Wood, L., McDonald, C. R., Nation, D. A., Libon, D. J., Au, R., et al. (2014) · Journal of Alzheimer's Disease · doi:10.3233/jad-140276 · Cited by 750 · see citing works
Prodromal Alzheimer's disease: successive emergence of the clinical symptoms
Amieva, H., Le Goff, M., Millet, X., Orgogozo, J. M., Pérès, K., Barberger‐Gateau, P., Jacqmin‐Gadda, H., & Dartigues, J. F. (2008) · Annals of Neurology · doi:10.1002/ana.21509 · Cited by 737 · see citing works
Neuropathology of nondemented aging: presumptive evidence for preclinical Alzheimer disease
Price, J. L., McKeel, D. W., Buckles, V. D., Roe, C. M., Xiong, C., Grundman, M., Hansen, L. A., Petersen, R. C., Parisi, J. E., Dickson, D. W., et al. (2009) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2009.04.002 · Cited by 661 · see citing works
Comparing predictors of conversion and decline in mild cognitive impairment
Landau, S. M., Harvey, D., Madison, C. M., Reiman, E. M., Foster, N. L., Aisen, P. S., Petersen, R. C., Shaw, L. M., Trojanowski, J. Q., Jack, C. R., et al. (2010) · Neurology · doi:10.1212/wnl.0b013e3181e8e8b8 · Cited by 616 · see citing works
Longitudinal Verbal Fluency in Normal Aging, Preclinical, and Prevalent Alzheimer’s Disease
Clark, L. J., Gatz, M., Zheng, L., Chen, Y.-L., McCleary, C., & Mack, W. J. (2009) · American Journal of Alzheimer's Disease & Other Dementias® · doi:10.1177/1533317509345154 · Cited by 318 · see citing works
Brain aging, Alzheimer's disease, and mitochondria
Swerdlow, R. H. (2011) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2011.08.012 · Cited by 306 · see citing works
“Over time, cognitive decline in those with AAMI and AACD tends to progress, the line from no dementia to dementia is frequently crossed, and AD is often diagnosed [3,22 – 31].”
BackgroundRabin, L. A., Paré, N., Saykin, A. J., Brown, M. J., Wishart, H. A., Flashman, L. A., & Santulli, R. B. (2009) · Aging, Neuropsychology, and Cognition · doi:10.1080/13825580902825220 · Cited by 256 · see citing works
Subjective Cognitive Complaints Contribute to Misdiagnosis of Mild Cognitive Impairment
Edmonds, E. C., Delano-Wood, L., Galasko, D. R., Salmon, D. P., & Bondi, M. W. (2014) · Journal of the International Neuropsychological Society · doi:10.1017/s135561771400068x · Cited by 249 · see citing works
Verbal fluency performance in amnestic MCI and older adults with cognitive complaints
NUTTERUPHAM, K., SAYKIN, A., RABIN, L., ROTH, R., WISHART, H., PARE, N., & FLASHMAN, L. (2008) · Archives of Clinical Neuropsychology · doi:10.1016/j.acn.2008.01.005 · Cited by 238 · see citing works
Nontraditional risk factors combine to predict Alzheimer disease and dementia
Song, X., Mitnitski, A., & Rockwood, K. (2011) · Neurology · doi:10.1212/wnl.0b013e318225c6bc · Cited by 220 · see citing works
Resnick, S. M., Matsumoto, A. M., Stephens-Shields, A. J., Ellenberg, S. S., Gill, T. M., Shumaker, S. A., Pleasants, D. D., Barrett-Connor, E., Bhasin, S., Cauley, J. A., et al. (2017) · JAMA · doi:10.1001/jama.2016.21044 · Cited by 220 · see citing works
FDG-PET as an independent biomarker for Alzheimer’s biological diagnosis: A longitudinal study
Initiative, O. B. O. A. D. N., Ou, Y.-N., Xu, W., Li, J.-Q., Guo, Y., Cui, M., Chen, K.-L., Huang, Y.-Y., Dong, Q., Tan, L., et al. (2019) · Alzheimer's Research & Therapy · doi:10.1186/s13195-019-0512-1 · Cited by 155 · see citing works
Bellassen, V., Iglói, K., de Souza, L. C., Dubois, B., & Rondi-Reig, L. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.4556-11.2012 · Cited by 93 · see citing works
Effect of a Computerized Brain Exercise Program on Cognitive Performance in Older Adults
Miller, K. J., Dye, R. V., Kim, J., Jennings, J. L., O'Toole, E., Wong, J., & Siddarth, P. (2013) · The American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2013.01.077 · Cited by 90 · see citing works
Preclinical AD Workgroup staging: Pathological correlates and potential challenges
Jicha, G. A., Abner, E. L., Schmitt, F. A., Kryscio, R. J., Riley, K. P., Cooper, G. E., Stiles, N., Mendiondo, M. S., Smith, C. D., Van Eldik, L. J., et al. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2011.02.018 · Cited by 71 · see citing works
Trajectories of Alzheimer disease‐related cognitive measures in a longitudinal sample
Bilgel, M., An, Y., Lang, A., Prince, J., Ferrucci, L., Jedynak, B., & Resnick, S. M. (2014) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2014.04.520 · Cited by 65 · see citing works
White matter degeneration in subjective cognitive decline: a diffusion tensor imaging study
Li, X.-Y., Tang, Z.-C., Sun, Y., Tian, J., Liu, Z.-Y., & Han, Y. (2016) · Oncotarget · doi:10.18632/oncotarget.10091 · Cited by 65 · see citing works
Wouters, H., van Gool, W. A., Schmand, B., Zwinderman, A. H., & Lindeboom, R. (2010) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.2402 · Cited by 43 · see citing works
- Authors
- Tierney, M. C., Yao, C., Kiss, A., & McDowell, I.
- Affiliations
- Sunnybrook Health Science Centre (CA)
- Venue
- Neurology
- Published
- 2005-06-14
- Volume
- 64
- Issue
- 11
- Pages
- 1853-1859
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- OpenAlex
- W1969713976
- Cited by
- 274
- References
- 1
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 6 · 2023: 3 · 2022: 9 · 2021: 13 · 2020: 12 · 2019: 12 · 2018: 9 · 2017: 12 · 2016: 16 · 2015: 14 · 2014: 20 · 2013: 15 · 2012: 14
- FWCI
- 9.20
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neurology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
- Social Sciences › Psychology › Clinical Psychology › Historical and Modern Theater Studies
- Keywords
- Alzheimer's disease, neuropsychological assessment, conversion to dementia, animal fluency, Canadian Study of Health and Aging, non-demented elderly, sensitivity and specificity
- MeSH terms
- Age Factors, Aged, Aged, 80 and over, Alzheimer Disease, Canada, Dementia, Educational Status, Female, Genetic Testing, Genotype, Health Surveys, Humans, Male, Memory Disorders, Neuropsychological Tests, Predictive Value of Tests, Risk Factors, Sex Factors, Reproducibility of Results, Cohort Studies, Genetic Predisposition to Disease
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review