BACKGROUND: Conceptualizing cognitive aging as a step-sequential process is useful in identifying particular stages of cognitive function and impairment. OBJECTIVE: We applied latent transition analysis (LTA) to determine 1) whether the underlying structure of cognitive profiles found at every measurement occasion are uniform across three waves of assessment, 2) whether class-instability is predictive of distal outcomes, and 3) whether class-reversions from impaired to non-impaired using latent modelling is lower than when using clinical criteria of mild cognitive impairment (MCI). METHODS: A mover-stayer LTA model with dementia as a distal outcome was specified to model transitions of ten neuropsychological measures over three annual waves in the Rush Memory and Aging Project (n = 1,661). The predictive validity of the mover-stayer status for incident Alzheimer's disease (AD) was then assessed. RESULTS: We identified a five-class model across the three time-points: Mixed-Domain Impairment, Memory-Specific Impairment, Frontal Impairment, Average, and Superior Cognition. None of the individuals in the Impairment classes reverted to the Average or Superior classes. Conventional MCI classification identified 26.4% and 14.1% at Times 1 and 2 as false-positive cases. "Movers" had 87% increased risk of developing dementia compared to those classified as "Stayers". CONCLUSION: Our findings support the use of latent variable modelling that incorporates comprehensive neuropsychological assessment to identify and classify cognitive impairment.
BACKGROUND: Conceptualizing cognitive aging as a step-sequential process is useful in identifying particular stages of cognitive function and impairment. OBJECTIVE: We applied latent transition analysis (LTA) to determine 1) whether the underlying structure of cognitive profiles found at every measurement occasion are uniform across three waves of assessment, 2) whether class-instability is predictive of distal outcomes, and 3) whether class-reversions from impaired to non-impaired using latent modelling is lower than when using clinical criteria of mild cognitive impairment (MCI). METHODS: A mover-stayer LTA model with dementia as a distal outcome was specified to model transitions of ten neuropsychological measures over three annual waves in the Rush Memory and Aging Project (n = 1,661). The predictive validity of the mover-stayer status for incident Alzheimer's disease (AD) was then assessed. RESULTS: We identified a five-class model across the three time-points: Mixed-Domain Impairment, Memory-Specific Impairment, Frontal Impairment, Average, and Superior Cognition. None of the individuals in the Impairment classes reverted to the Average or Superior classes. Conventional MCI classification identified 26.4% and 14.1% at Times 1 and 2 as false-positive cases. "Movers" had 87% increased risk of developing dementia compared to those classified as "Stayers". CONCLUSION: Our findings support the use of latent variable modelling that incorporates comprehensive neuropsychological assessment to identify and classify cognitive impairment.
Authors: Mark W Bondi; Amy J Jak; Lisa Delano-Wood; Mark W Jacobson; Dean C Delis; David P Salmon Journal: Neuropsychol Rev Date: 2008-03-18 Impact factor: 7.444
Authors: Andrea R Zammit; Charles B Hall; David A Bennett; Ali Ezzati; Mindy J Katz; Graciela Muniz-Terrera; Richard B Lipton Journal: Alzheimers Dement Date: 2019-08-13 Impact factor: 21.566
Authors: David A Bennett; Julie A Schneider; Aron S Buchman; Lisa L Barnes; Patricia A Boyle; Robert S Wilson Journal: Curr Alzheimer Res Date: 2012-07 Impact factor: 3.498
Authors: David A Bennett; Aron S Buchman; Patricia A Boyle; Lisa L Barnes; Robert S Wilson; Julie A Schneider Journal: J Alzheimers Dis Date: 2018 Impact factor: 4.472