Dataset Information

Quantile regression with a change-point model for longitudinal data: An application to the study of cognitive changes in preclinical alzheimer's disease.

ABSTRACT: Progressive and insidious cognitive decline that interferes with daily life is the defining characteristic of Alzheimer's disease (AD). Epidemiological studies have found that the pathological process of AD begins years before a clinical diagnosis is made and can be highly variable within a given population. Characterizing cognitive decline in the preclinical phase of AD is critical for the development of early intervention strategies when disease-modifying therapies may be most effective. In the last decade, there has been an increased interest in the application of change-point models to longitudinal cognitive outcomes prior to and after diagnosis. Most of the proposed statistical methodology for describing decline relies upon distributional assumptions that may not hold. In this article, we introduce a quantile regression with a change-point model for longitudinal data of cognitive function in persons bound to develop AD. A change-point in our model reflects the transition from the cognitive decline due to normal aging to the accelerated decline due to disease progression. Quantile regression avoids common distributional assumptions on cognitive outcomes and allows the covariate effects and the change-point to vary for different quantiles of the response. We provided an approach for estimating the model parameters, including the change-point, and presented inferential procedures based on the asymptotic properties of the estimators. A simulation study showed that the estimation and inferential procedures perform reasonably well in finite samples. The practical use of our model was illustrated by an application to longitudinal episodic memory outcomes from two cohort studies of aging and AD.

SUBMITTER: Li C

PROVIDER: S-EPMC4575281 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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Quantile regression with a change-point model for longitudinal data: An application to the study of cognitive changes in preclinical alzheimer's disease.

Li Chenxi C Dowling N Maritza NM Chappell Rick R

Biometrics 20150417 3

Progressive and insidious cognitive decline that interferes with daily life is the defining characteristic of Alzheimer's disease (AD). Epidemiological studies have found that the pathological process of AD begins years before a clinical diagnosis is made and can be highly variable within a given population. Characterizing cognitive decline in the preclinical phase of AD is critical for the development of early intervention strategies when disease-modifying therapies may be most effective. In th ...[more]

PMID: 25892034

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Project description:Clinical trials testing treatments for Alzheimer disease (AD) are increasingly focused on cognitively normal individuals in the preclinical phase of the disease. To optimize observing a treatment effect, such trials need to enroll cognitively normal individuals likely to show cognitive decline over the duration of the trial.To identify which group of cognitively normal individuals shows the greatest cognitive decline over time based on their cerebrospinal fluid biomarker profile.In this cohort study, cognitively normal participants were classified into 1 of the following 4 hypothetical preclinical AD groups using baseline cerebrospinal fluid levels of A? and tau or A? and phosphorylated tau (p-tau): stage 0 (high A? and low tau), stage 1 (low A? and low tau), stage 2 (low A? and high tau), and suspected non-AD pathology (SNAP) (high A? and high tau). The data presented herein were collected between August 1995 and August 2014.An a priori cognitive composite score based on the following 4 tests previously shown to predict progression from normal cognition to symptom onset of mild cognitive impairment or dementia: Paired Associates immediate recall, Logical Memory delayed recall, Boston Naming, and Digit-Symbol Substitution. Linear mixed-effects models were used to compare the cognitive composite scores across the 4 groups over time, adjusting for baseline age, sex, education, and their interactions with time.Two hundred twenty-two cognitively normal participants were included in the analyses (mean follow-up, 11.0 years [range, 0-18.3 years] and mean baseline age, 56.9 years [range, 22.1-85.8 years]). Of these, 102 were stage 0, 46 were stage 1, 28 were stage 2, and 46 were SNAP. Individuals in stage 2 (low A? and high tau [or p-tau]) had lower baseline cognitive scores and a greater decline in the cognitive composite score relative to the other 3 groups (????-0.06 for all and P???.001 for the rate of decline for all). Individuals in stage 0, stage 1, and SNAP did not differ from one another in cognitive performance at baseline or over time (11.0 years) and showed practice-related improvement in performance. The APOE ?4 genotype was not associated with baseline cognitive composite score or the rate of change in the cognitive composite score.These results suggest that, to optimize observing a treatment effect, clinical trials enrolling cognitively normal individuals should selectively recruit participants with abnormal levels of both amyloid and tau (ie, stage 2) because this group would be expected to show the greatest cognitive decline over time if untreated.

Project description:A sensitive marker for monitoring progression of early Alzheimer's disease would help to develop and test new therapeutic strategies. The present study is aimed at investigating brain metabolism changes over time, as a potential monitoring marker, in patients with amnestic mild cognitive impairment, according to their clinical outcome (converters or non-converters), and in relation to their cognitive decline. Seventeen amnestic mild cognitive impairment patients underwent magnetic resonance imaging and 18FDG-positron emission tomography scans both at inclusion and 18 months later. Baseline and follow-up positron emission tomography data were corrected for partial volume effects and spatially normalized using magnetic resonance imaging data, scaled to the vermis and compared using SPM2. 'PET-PAC' maps reflecting metabolic per cent annual changes were created for correlation analyses with cognitive decline. In the whole sample, the greatest metabolic decrease concerned the posterior cingulate-precuneus area. Converters had significantly greater metabolic decrease than non-converters in two ventro-medial prefrontal areas, the subgenual (BA25) and anterior cingulate (BA24/32). PET-PAC in BA25 and BA24/32 combined allowed complete between-group discrimination. BA25 PET-PAC significantly correlated with both cognitive decline and PET-PAC in the hippocampal region and temporal pole, while BA24/32 PET-PAC correlated with posterior cingulate PET-PAC. Finally, the metabolic change in BA8/9/10 was inversely related to that in BA25 and showed relative increase with cognitive decline, suggesting that compensatory processes may occur in this dorso-medial prefrontal region. The observed ventro-medial prefrontal disruption is likely to reflect disconnection from the hippocampus, both indirectly through the cingulum bundle and posterior cingulate cortex for BA24/32, and directly through the uncinate fasciculus for BA25. Altogether, our findings emphasize the potential of 18FDG-positron emission tomography for monitoring early Alzheimer's disease progression.

Dataset Information

Quantile regression with a change-point model for longitudinal data: An application to the study of cognitive changes in preclinical alzheimer's disease.

Publications

Quantile regression with a change-point model for longitudinal data: An application to the study of cognitive changes in preclinical alzheimer's disease.

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