Article

Longitudinal change in neuropsychological performance using latent growth models: A study of mild cognitive impairment

Department of Social and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA, .
Brain Imaging and Behavior (Impact Factor: 4.6). 05/2012; 6(4). DOI: 10.1007/s11682-012-9161-8
Source: PubMed

ABSTRACT The goal of the current study was to examine cognitive change in both healthy controls (n = 229) and individuals with mild cognitive impairment (MCI) (n = 397) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We applied latent growth modeling to examine baseline and longitudinal change over 36 months in five cognitive factors derived from the ADNI neuropsychological test battery (memory, executive function/processing speed, language, attention and visuospatial). At baseline, MCI patients demonstrated lower performance on all of the five cognitive factors when compared to controls. Both controls and MCI patients declined on memory over 36 months; however, the MCI patients declined at a significantly faster rate than controls. The MCI patients also declined over 36 months on the remaining four cognitive factors. In contrast, the controls did not exhibit significant change over 36 months on the non-memory cognitive factors. Within the MCI group, executive function declined faster than memory, while the other factor scores changed slower than memory over time. These findings suggest different patterns of cognitive change in healthy older adults and MCI patients. The findings also suggest that, when compared with memory, executive function declines faster than other cognitive factors in patients with MCI. Thus, decline in non-memory domains may be an important feature for distinguishing healthy older adults and persons with MCI.

0 Followers
 · 
109 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Recent changes in diagnostic criteria for Alzheimer's disease (AD) state that biomarkers can enhance certainty in a diagnosis of AD. In the present study, we combined cognitive function and brain morphology, a potential imaging biomarker, to predict conversion from mild cognitive impairment to AD. We identified four biomarkers, or cortical signatures of cognition (CSC), from regressions of cortical thickness on neuropsychological factors representing memory, executive function/processing speed, language, and visuospatial function among participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Neuropsychological factor scores were created from a previously validated multidimensional factor structure of the neuropsychological battery in ADNI. Mean thickness of each CSC at the baseline study visit was used to evaluate risk of conversion to clinical AD among participants with mild cognitive impairment (MCI) and rate of decline on the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) score. Of 307 MCI participants, 119 converted to AD. For all domain-specific CSC, a one standard deviation thinner cortical thickness was associated with an approximately 50 % higher hazard of conversion and an increase of approximately 0.30 points annually on the CDR-SB. In combined models with a domain-specific CSC and neuropsychological factor score, both CSC and factor scores predicted conversion to AD and increasing clinical severity. The present study indicated that factor scores and CSCs for memory and language both significantly predicted risk of conversion to AD and accelerated deterioration in dementia severity. We conclude that predictive models are best when they utilize both neuropsychological measures and imaging biomarkers.
    Brain Imaging and Behavior 06/2012; 6(4). DOI:10.1007/s11682-012-9180-5 · 4.60 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article summarizes a special series of articles from The Advanced Psychometric Methods in Cognitive Aging Research conference, held in June, 2011 at Friday Harbor, Washington. This conference used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to address cognitive change associated with Alzheimer's disease (AD) and how it related to neuroimaging, genetic, and cerebrospinal fluid biomarkers. The 13 articles in this series present innovative approaches to measuring cognition and studying determinants of cognitive decline in AD.
    Brain Imaging and Behavior 12/2012; 6(4). DOI:10.1007/s11682-012-9211-2 · 4.60 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The use of neuropsychological tests to detect cognitive decline in the initial phases of Alzheimer's disease (AD) has faced significant limitations, namely the fact that most cohort studies of conversion to dementia had relatively short follow-up periods. The aim of the present study is to assess the predictive value for future conversion to dementia of a comprehensive neuropsychological battery applied to a cohort of non-demented patients followed-up for 5 years. Participants (n = 250) were selected from the Cognitive Complaints Cohort (CCC) having cognitive complaints, assessment with a comprehensive neuropsychological battery, and a follow-up period of 5 years (unless patients have converted to dementia earlier). During the follow-up period (2.6 ± 1.8 years for converters and 6.1 ± 2.1 years for non-converters), 162 patients (64.8%) progressed to dementia (mostly AD), and 88 (35.2%) did not. A Linear Discriminant Analysis (LDA) model constituted by Digit Span backward, Semantic Fluency, Logical Memory (immediate recall), and Forgetting Index significantly discriminated converters from non-converters (λ Wilks = 0.64; χ2 (4) = 81.95; p < 0.001; RCanonical = 0.60). Logical Memory (immediate recall) was the strongest predictor with a standardized canonical discriminant function coefficient of 0.70. The LDA classificatory model showed good sensitivity, specificity and accuracy values (78.8%, 79.9% and 78.6%, respectively) of the neuropsychological tests to predict long-term conversion to dementia. The present results show that it is possible to predict, on the basis of the initial clinical and neuropsychological evaluation, whether non-demented patients with cognitive complaints will probably convert to dementia, or remain stable, at a reasonably long and clinically relevant term.
    Journal of Alzheimer's disease: JAD 12/2012; 34(3). DOI:10.3233/JAD-122098 · 4.15 Impact Factor
Show more