Cognitive and functional progression in Alzheimer disease: A prediction model of latent classes

International Journal of Geriatric Psychiatry
Miriam L HaaksmaJeannie-Marie S Leoutsakos

Abstract

We sought to replicate a previously published prediction model for progression, developed in the Cache County Dementia Progression Study, using a clinical cohort from the National Alzheimer's Coordinating Center. We included 1120 incident Alzheimer disease (AD) cases with at least one assessment after diagnosis, originating from 31 AD centres from the United States. Trajectories of the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating sum of boxes (CDR-sb) were modelled jointly over time using parallel-process growth mixture models in order to identify latent classes of trajectories. Bias-corrected multinomial logistic regression was used to identify baseline predictors of class membership and compare these with the predictors found in the Cache County Dementia Progression Study. The best-fitting model contained 3 classes: Class 1 was the largest (63%) and showed the slowest progression on both MMSE and CDR-sb; classes 2 (22%) and 3 (15%) showed moderate and rapid worsening, respectively. Significant predictors of membership in classes 2 and 3, relative to class 1, were worse baseline MMSE and CDR-sb, higher education, and lack of hypertension. Combining all previously mentioned predictors yielded areas under th...Continue Reading

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Dec 18, 2018·Current Opinion in Psychiatry·René J F MelisGraciela Muniz-Terrera
Jul 19, 2019·International Journal of Geriatric Psychiatry·Yuwei WangRené J F Melis
Jul 6, 2019·International Journal of Geriatric Psychiatry·Jiyoung LyuGiyeon Kim
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May 22, 2019·Journal of the American Medical Directors Association·Miriam L HaaksmaAmaia Calderón-Larrañaga
Aug 24, 2021·International Psychogeriatrics·Luis Agüera-Ortiz

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