Neuropsychological Measures that Predict Progression from Mild Cognitive Impairment to Alzheimer's type dementia in Older Adults: a Systematic Review and Meta-Analysis.

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Tytuł:: Neuropsychological Measures that Predict Progression from Mild Cognitive Impairment to Alzheimer's type dementia in Older Adults: a Systematic Review and Meta-Analysis.
Autorzy:: Belleville S; Research Center of the Institut Universitaire de Gériatrie de Montréal, 4565 Chemin Queen Mary, Montréal, Québec, H3W 1W5, Canada. .; Université de Montréal, CP 6128 Succ. Centre Ville, Montréal, Québec, H3C-1J7, Canada. .
Fouquet C; Research Center of the Institut Universitaire de Gériatrie de Montréal, 4565 Chemin Queen Mary, Montréal, Québec, H3W 1W5, Canada.
Hudon C; Université Laval, Pavillon Félix-Antoine-Savard, 2325, rue des Bibliothèques, Local 1546, Québec, Québec, G1V 0A6, Canada.; CERVO Brain Research Center, 2601, de la Canardiere, Québec, Québec, G1J 2G3, Canada.
Zomahoun HTV; Health and Social Services Systems, Knowledge Translation and Implementation component of the Quebec SPOR-SUPPORT Unit, Université Laval, Québec, Québec, G1L 2E8, Canada.; Population Health and Practice-Changing Research Group, Research Centre of CHU de Québec- Université Laval, Québec, Québec, G1L 2E8, Canada.
Croteau J; Health and Social Services Systems, Knowledge Translation and Implementation component of the Quebec SPOR-SUPPORT Unit, Université Laval, Québec, Québec, G1L 2E8, Canada.; Population Health and Practice-Changing Research Group, Research Centre of CHU de Québec- Université Laval, Québec, Québec, G1L 2E8, Canada.
Corporate Authors:: Consortium for the Early Identification of Alzheimer’s disease-Quebec
Źródło:: Neuropsychology review [Neuropsychol Rev] 2017 Dec; Vol. 27 (4), pp. 328-353. Date of Electronic Publication: 2017 Oct 10.
Typ publikacji:: Journal Article; Meta-Analysis; Research Support, Non-U.S. Gov't; Systematic Review
Język:: English
Imprint Name(s):: Publication: 1999- : New York, NY : Kluwer Academic/Plenum Publishers
Original Publication: New York : Plenum Press, c1990-
MeSH Terms:: Neuropsychological Tests*
Alzheimer Disease/*diagnosis
Cognitive Dysfunction/*diagnosis
Alzheimer Disease/physiopathology ; Alzheimer Disease/psychology ; Cognitive Dysfunction/physiopathology ; Cognitive Dysfunction/psychology ; Disease Progression ; Humans ; Prognosis
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Grant Information:: 27239 International Fonds d'Innovation Pfizer-FRQS of the Fonds de Recherche du Québec-Santé
Contributed Indexing:: Keywords: Alzheimer’s disease; Cognitive tests; Diagnosis; Mild cognitive impairment; Neuropsychology; Predictive accuracy
Entry Date(s):: Date Created: 20171012 Date Completed: 20190122 Latest Revision: 20220408
Update Code:: 20240105
PubMed Central ID:: PMC5754432
DOI:: 10.1007/s11065-017-9361-5
PMID:: 29019061
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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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