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Describing the Sequence of Cognitive Decline in Alzheimer's Disease Patients: Results from an Observational Study.

ABSTRACT: Improved understanding of the pattern of cognitive decline in Alzheimer's disease (AD) would be useful to assist primary care physicians in explaining AD progression to patients and caregivers.To identify the sequence in which cognitive abilities decline in community-dwelling patients with AD.Baseline data were analyzed from 1,495 patients diagnosed with probable AD and a Mini-Mental State Examination (MMSE) score ? 26 enrolled in the 18-month observational GERAS study. Proportional odds logistic regression models were applied to model MMSE subscores (orientation, registration, attention and concentration, recall, language, and drawing) and the corresponding subscores of the cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-cog), using MMSE total score as the index of disease progression. Probabilities of impairment start and full impairment were estimated at each MMSE total score level.From the estimated probabilities for each MMSE subscore as a function of the MMSE total score, the first aspect of cognition to start being impaired was recall, followed by orientation in time, attention and concentration, orientation in place, language, drawing, and registration. For full impairment in subscores, the sequence was recall, drawing, attention and concentration, orientation in time, orientation in place, registration, and language. The sequence of cognitive decline for the corresponding ADAS-cog subscores was remarkably consistent with this pattern.The sequence of cognitive decline in AD can be visualized in an animation using probability estimates for key aspects of cognition. This might be useful for clinicians to set expectations on disease progression for patients and caregivers.

SUBMITTER: Henneges C

PROVIDER: S-EPMC4927893 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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Describing the Sequence of Cognitive Decline in Alzheimer's Disease Patients: Results from an Observational Study.

Henneges Carsten C Reed Catherine C Chen Yun-Fei YF Dell'Agnello Grazia G Lebrec Jeremie J

Journal of Alzheimer's disease : JAD 20160101 3

<h4>Background</h4>Improved understanding of the pattern of cognitive decline in Alzheimer's disease (AD) would be useful to assist primary care physicians in explaining AD progression to patients and caregivers.<h4>Objective</h4>To identify the sequence in which cognitive abilities decline in community-dwelling patients with AD.<h4>Methods</h4>Baseline data were analyzed from 1,495 patients diagnosed with probable AD and a Mini-Mental State Examination (MMSE) score ≤ 26 enrolled in the 18-month ...[more]

PMID: 27079700

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Project description:BackgroundIn Alzheimer's disease, amyloid- β (A β) peptides aggregate in the lowering CSF amyloid levels - a key pathological hallmark of the disease. However, lowered CSF amyloid levels may also be present in cognitively unimpaired elderly individuals. Therefore, it is of great value to explain the variance in disease progression among patients with A β pathology.MethodsA cohort of n=2293 participants, of whom n=749 were A β positive, was selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to study heterogeneity in disease progression for individuals with A β pathology. The analysis used baseline clinical variables including demographics, genetic markers, and neuropsychological data to predict how the cognitive ability and AD diagnosis of subjects progressed using statistical models and machine learning. Due to the relatively low prevalence of A β pathology, models fit only to A β-positive subjects were compared to models fit to an extended cohort including subjects without established A β pathology, adjusting for covariate differences between the cohorts.ResultsA β pathology status was determined based on the A β42/A β40 ratio. The best predictive model of change in cognitive test scores for A β-positive subjects at the 2-year follow-up achieved an R2 score of 0.388 while the best model predicting adverse changes in diagnosis achieved a weighted F1 score of 0.791. A β-positive subjects declined faster on average than those without A β pathology, but the specific level of CSF A β was not predictive of progression rate. When predicting cognitive score change 4 years after baseline, the best model achieved an R2 score of 0.325 and it was found that fitting models to the extended cohort improved performance. Moreover, using all clinical variables outperformed the best model based only on a suite of cognitive test scores which achieved an R2 score of 0.228.ConclusionOur analysis shows that CSF levels of A β are not strong predictors of the rate of cognitive decline in A β-positive subjects when adjusting for other variables. Baseline assessments of cognitive function accounts for the majority of variance explained in the prediction of 2-year decline but is insufficient for achieving optimal results in longer-term predictions. Predicting changes both in cognitive test scores and in diagnosis provides multiple perspectives of the progression of potential AD subjects.

Project description:IntroductionThe objective of this study was to determine the factors including neuropsychological test performances and cerebrospinal fluid (CSF) biomarkers which can predict disease progression of early Alzheimer's disease (AD) in a Japanese population.MethodsThe group classification on early AD population in both Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) and North American ADNI (NA-ADNI) was performed using the inclusion criteria including brain amyloid positivity on positron emission tomography or CSF. Participants with early AD from each cohort were stratified into two groups based on a cutoff 1.0 of Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) change at month 24 (m24): participants in "progress group" have CDR-SB change ≥ 1.0 and participants in "stable group" have CDR-SB change < 1.0. Then, we performed identification of prognostic factors from baseline items including neuropsychological scores (Assessment Scale-Cognitive Subscale[ADAS-cog 13], Mini-Mental State Examination (MMSE), CDR, FAQ, and Geriatric Depression Scale ), CSF markers (t-tau, p-tau, and beta-amyloid 1-42), vital signs (body weight, pulse rate, etc.,), by using two statistical approaches, Welch's t-test and simple linear regression by ordinary least squares. Comparisons between participants with J-ADNI and participants with NA-ADNI were also performed.ResultsTrends of CDR-SB changes were very similar between J-ADNI and NA-ADNI early AD population enrolled in this study. Baseline levels of CSF t-tau, p-tau, Mini-Mental State Examination, FAQ, and ADAS-cog13 were identified as prognostic factors in both J-ADNI and NA-ADNI. Based on a detailed subscale analysis on ADAS-cog13, four subscales (Q1: word recall, Q3: construction, Q4: delayed word recall, and Q8: word recognition) were identified as prognostic factors in both J-ADNI and NA-ADNI.DiscussionCharacterizing population with early AD can provide benefits for promoting efficiency in conducting AD clinical trials for disease-modifying treatments. Thus, implementing these prognostic factors into clinical trials may be potentially a good method to enrich participants with early AD who are suitable for evaluating treatment effects.

Dataset Information

Describing the Sequence of Cognitive Decline in Alzheimer's Disease Patients: Results from an Observational Study.

Publications

Describing the Sequence of Cognitive Decline in Alzheimer's Disease Patients: Results from an Observational Study.

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