The DOI matches its Crossref record; 70 of the 70 references it cites were found in a registry or an index.
Neuropsychological Measures that Predict Progression from Mild Cognitive Impairment to Alzheimer's type dementia in Older Adults: a Systematic Review and Meta-Analysis
Open accessAbstract
This study aimed to determine the extent to which cognitive measures can predict progression from mild cognitive impairment (MCI) to Alzheimer's type dementia (AD), assess the predictive accuracy of different cognitive domain categories, and determine whether accuracy varies as a function of age and length of follow-up. We systematically reviewed and meta-analyzed data from longitudinal studies reporting sensitivity and specificity values for neuropsychological tests to identify individuals with MCI who will develop AD. We searched articles in Medline, Cochrane, EMBASE, PsycINFO, and the Web of Science. Methodological quality was assessed using the STARDem and QUADAS standards. Twenty-eight studies met the eligibility criteria (2365 participants) and reported predictive values from 61 neuropsychological tests with a 31-month mean follow-up. Values were pooled to provide combined accuracy for 14 cognitive domains. Many domains showed very good predictive accuracy with high sensitivity and specificity values (≥ 0.7). Verbal memory measures and many language tests yielded very high predictive accuracy. Other domains (e.g., executive functions, visual memory) showed better specificity than sensitivity. Predictive accuracy was highest when combining memory measures with a small set of other domains or when relying on broad cognitive batteries. Cognitive tests are excellent at predicting MCI individuals who will progress to dementia and should be a critical component of any toolkit intended to identify AD at the pre-dementia stage. Some tasks are remarkable as early indicators, whereas others might be used to suggest imminent progression.
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Cites
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Cited by
Alzheimer’s Disease: Epidemiology and Clinical Progression
Tahami Monfared, A. A., Byrnes, M. J., White, L. A., & Zhang, Q. (2022) · Neurology and Therapy · doi:10.1007/s40120-022-00338-8 · Cited by 629
A Guide to Conducting a Meta-Analysis with Non-Independent Effect Sizes
Cheung, M. W.-L. (2019) · Neuropsychology Review · doi:10.1007/s11065-019-09415-6 · Cited by 610
Dementia in Down syndrome: unique insights for Alzheimer disease research
Lott, I. T., & Head, E. (2019) · Nature Reviews Neurology · doi:10.1038/s41582-018-0132-6 · Cited by 383
Huang, L., Chen, K.-L., Lin, B.-Y., Tang, L., Zhao, Q.-H., Lv, Y.-R., & Guo, Q.-H. (2018) · Neuropsychiatric Disease and Treatment · doi:10.2147/ndt.s174293 · Cited by 112
Belloy, M. E., Napolioni, V., Han, S. S., Le Guen, Y., Greicius, M. D., & Initiative, F. T. A. D. N. (2020) · JAMA Neurology · doi:10.1001/jamaneurol.2020.0414 · Cited by 110
Metadata
- Authors
- Consortium for the Early Identification of Alzheimer’s disease-Quebec, Belleville, S., Fouquet, C., Hudon, C., Zomahoun, H. T. V., & Croteau, J.
- Venue
- Neuropsychology Review
- Published
- 2017-10-10
- Volume
- 27
- Issue
- 4
- Pages
- 328-353
- ISSN
- 1040-7308 (ISSN-L)
- 1573-6660
- OpenAlex
- W2763282512
- Cited by
- 308
- References
- 70
- FWCI
- 3.80
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Consortium for the Early Identification of Alzheimer’s disease-Quebec, Belleville, S., Fouquet, C., Hudon, C., Zomahoun, H. T. V., & Croteau, J. (2017). Neuropsychological Measures that Predict Progression from Mild Cognitive Impairment to Alzheimer's type dementia in Older Adults: a Systematic Review and Meta-Analysis. Neuropsychology Review. https://doi.org/10.1007/s11065-017-9361-5
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