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In biomedical research, various longitudinal markers measuring different quantities are often collected over time. For example, repeated measures of psychometric scores are very informative about the degradation process toward dementia. These trajectories are generally nonlinear with an acceleration of the decline a few years before the diagnosis and a large heterogeneity between psychometric tests depending on the underlying cognitive function to be evaluated and the metrological properties of the test. Comparing the times of acceleration of the decline before diagnosis between cognitive tests is useful to better understand the natural history of the disease. Our objective is to propose a bivariate random changepoint model that allows for the comparison of the mean time of change between two markers. A frequentist approach is proposed that gives validated statistical tests to assess the temporal order of the changepoints. Using a spline transformation function, the model is designed to handle non-Gaussian data, that are common for cognitive scores which frequently exhibit a strong ceiling effect. The procedure is assessed through a simulation study and applied to a French cohort of elderly to identify the order of the decline of several cognitive scores. The whole methodology has been implemented in a R package freely available.

In line with declining trends in dementia incidence, we compared the cognitive and functional evolution of 2 "generations" of elderly individuals aged 78-88 years, who were included 10 years apart in the French Personnes Agées Quid cohort (n = 612 in 1991-1992 and n = 628 in 2001-2002) and followed-up for 12 years with assessments of cognition and disability. The impact of specific risk factors on this evolution was evaluated. Differences between the generations in baseline levels and decline over time were estimated using a joint model to account for differential attrition. Compared with the first generation, the second generation had higher performances at baseline on 4 cognitive tests (from P < 0.005). Differences in global cognition, verbal fluency, and processing speed, but not in working memory, were mostly explained by improvement in educational level. The second generation also exhibited less cognitive decline in verbal fluency and working memory. Progression of disability was less over the follow-up period for the second generation than for the first. The cognitive state of this elderly population improved, partially due to improvements in educational level.

Early detection of subjects at high risk of developing dementia is essential. By dealing with censoring and competing risk of death, we developed a score for predicting 10-year dementia risk by combining cognitive tests, and we assessed whether inclusion of cognitive change over the previous year increased its discrimination. Data came from the French prospective cohort study Personnes Agées QUID (PAQUID) and included 3,777 subjects aged 65 years or older (1988-1998). The combined prediction score was estimated by means of an illness-death model handling interval censoring and competing risk of death. Its predictive ability was measured using the receiver operating characteristic (ROC) curve, with 2 different definitions depending on the way subjects who died without a dementia diagnosis were considered. To account for right-censoring and interval censoring, we estimated the ROC curves by means of a weighting approach and a model-based imputation estimator. The combined score exhibited an area under the ROC curve (AUROC) of 0.81 for discriminating future demented subjects from subjects alive and nondemented 10 years later and an AUROC of 0.75 for discriminating future demented subjects from all other subjects (including deceased persons). Adjustment for cognitive change over the previous year did not improve prediction., (© The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Cognitive lifestyle measures such as education, occupation, and social engagement are commonly associated with late-life cognitive ability although their associations with cognitive decline tend to be mixed. However, longitudinal analyses of cognition rarely account for death and dropout, measurement error of the cognitive phenotype, and differing trajectories for different population sub-groups. This paper applies a joint latent class mixed model (and a multi-state model in a sensitivity analysis) that accounts for these issues to a large (n = 3,653), population-based cohort, Paquid, to model the relationship between cognitive lifestyle and cognitive decline. Cognition was assessed over a 20-year period using the Mini-Mental State Examination. Three cognitive lifestyle variables were assessed: education, mid-life occupation, and late-life social engagement. The analysis identified four latent sub-populations with class-specific longitudinal cognitive decline and mortality risk. Irrespective of the cognitive trajectory, increased social engagement was associated with a decreased mortality risk. High education was associated with the most favourable cognitive trajectory, and after adjusting for cognitive decline, with an increased mortality risk. Mid-life occupational complexity was also associated with more favourable trajectories but not with mortality risk. To realistically examine the link between cognitive lifestyle and cognitive decline, complex statistical models are required. This paper applies and compares in a sensitivity analysis two such models, and shows education to be linked to a compression of cognitive morbidity irrespective of cognitive trajectory. Furthermore, a potentially modifiable variable, late-life social engagement is associated with a decreased mortality risk in all of the population sub-groups.

Background: The Mini-Mental State Examination (MMSE) is widely used in population-based longitudinal studies to quantify cognitive change. However, its poor metrological properties, mainly ceiling/floor effects and varying sensitivity to change, have largely restricted its usefulness. We propose a normalizing transformation that corrects these properties, and makes possible the use of standard statistical methods to analyze change in MMSE scores., Methods: The normalizing transformation designed to correct at best the metrological properties of MMSE was estimated and validated on two population-based studies (n = 4,889, 20-year follow-up) by cross-validation. The transformation was also validated on two external studies with heterogeneous samples mixing normal and pathological aging, and samples including only demented subjects., Results: The normalizing transformation provided correct inference in contrast with models analyzing the change in crude MMSE that most often lead to biased estimates of risk factors and incorrect conclusions., Conclusions: Cognitive change can be easily and properly assessed with the normalized MMSE using standard statistical methods such as linear (mixed) models., (© 2014 S. Karger AG, Basel.)

In cognitive aging research, the study of a general cognitive factor has been shown to have a substantial explanatory power over the study of isolated tests. The authors aimed at differentiating the impact of gender and education on global cognitive change with age from their differential impact on 4 psychometric tests using a new latent process approach, which intermediates between a single-factor longitudinal model for sum scores and an item-response theory approach for longitudinal data. The analysis was conducted on a sample of 2,228 subjects from PAQUID, a population-based cohort of older adults followed for 13 years with repeated measures of cognition. Adjusted for vascular factors, the analysis confirmed that women performed better in tests involving verbal components, while men performed better in tests involving visuospatial skills. In addition, the model suggested that women had a slightly steeper global cognitive decline with oldest age than men, even after excluding incident dementia or death. Subjects with higher education exhibited a better mean score for the 4 tests, but this difference tended to attenuate with age for tests involving a speed component., ((c) 2008 APA, all rights reserved)

Choosing the measure of cognition in an epidemiologic study investigating cognitive changes over time is a challenging question. A powerful measure must be able to detect small cognitive changes in all the range of cognition observed in the target population. This work aims at comparing the sensitivity to detect cognitive changes in the observed range of cognition of four widely used psychometric tests in an aging-population-based study through a nonlinear latent process model, assuming that the psychometric tests are nonlinear noisy transformations of their common factor. With data from the French prospective cohort study PAQUID (1989-2001), the authors found that the Mini-Mental State Examination and the Benton Visual Retention Test exhibited a better sensitivity to cognitive changes in low levels of cognition, while the Digit Symbol Substitution Test was more sensitive to changes in high levels of cognition. In contrast, the Isaacs Set Test shortened at 15 seconds appeared to be sensitive to small changes in all the range of cognition and, thus, represents an appropriate measure of cognition in population-based studies including both highly normal and severely impaired subjects.

Cognition is not directly measurable. It is assessed using psychometric tests, which can be viewed as quantitative measures of cognition with error. The aim of this article is to propose a model to describe the evolution in continuous time of unobserved cognition in the elderly and assess the impact of covariates directly on it. The latent cognitive process is defined using a linear mixed model including a Brownian motion and time-dependent covariates. The observed psychometric tests are considered as the results of parameterized nonlinear transformations of the latent cognitive process at discrete occasions. Estimation of the parameters contained both in the transformations and in the linear mixed model is achieved by maximizing the observed likelihood and graphical methods are performed to assess the goodness of fit of the model. The method is applied to data from PAQUID, a French prospective cohort study of ageing.

Background: The aim of this study is to describe and compare the course of the score of two psychometric tests during a five-year period in a cohort of non-demented elderly subjects. We studied a timed test of simple logical reasoning (the Digit Symbol Substitution Test of Wechsler) and a test of short-term visual memory (the Benton Visual Retention Test). Then we compared the course of these two tests with the course of the Mini-Mental State Examination (MMSE) which evaluates the general cognitive functioning and which has been studied previously., Methods: The sample consisted of 2792 subjects aged 65 years and older living at home at the beginning of the study (the Paquid cohort in Gironde). Subjects were interviewed at home by a psychologist at the baseline visit and one year, 3 years and 5 years after the baseline visit. All subjects who were diagnosed as demented at any of the four examinations were excluded from this study (218 subjects). The statistical analysis was performed using a mixed effects linear model and an additional analysis was performed to study sensitivity of the results to hypotheses regarding missing data mechanism., Results: Among the three tests studied, only the score of the Digit Symbol Substitution Test declined over the five years (by -1.15 points for subjects aged 65 years to -3.4 points for subjects aged 85 years). We observed an improvement of the score between the first two visits which is sharper for the test of Benton and the MMSE than for the Digit Symbol Substitution Test and which reflects a stress effect at the baseline visit or a learning effect at the second visit. The difference between the cross-sectional measure of age effect and the longitudinal measure of time effect suggests either a cohort effect or a practice effect which would persist during the five years., Conclusions: The cognitive change in a non-demented elderly population is different according to the psychometric test used. Among the three tests studied, only the score of the Digit Symbol Substitution Test which has a a speed component declined over the five years.

The Mini-Mental State Examination (MMSE) measures global cognitive performance and is often used as a screening test for dementia. This paper presents a 5-year longitudinal study of the MMSE score in a sample of 2,537 non-demented French community residents aged 65 years and older who were participants in the Paquid Study in 1988-1992. Subjects were evaluated at the baseline visit (T0) and 1 year (T1), 3 years (T3), and 5 years (T5) later. Analyses performed with a random effects linear model showed that the score rose between T0 and T1 (by 0.60 points for subjects aged 65 years at T0 to 0.83 points for subjects aged 85 years at T0), then it decreased very slightly between T1 and T5 (by 0.02 points for subjects aged 65 years to 0.57 points for subjects aged 85 years). The improvement during the first year, which was larger for less educated subjects, may be explained by the stress due to the test situation at T0 or by a learning effect at T1. The decline during the last 4 years was more pronounced for older and less well educated subjects. The cross-sectional measure of age effect was larger than the longitudinal measure of time effect. This difference may be explained by a cohort effect or by a practice effect induced by repetition of the test. The authors conclude that the MMSE score declines very slightly in non-demented subjects, thus suggesting that the cognitive processes involved are spared by the aging process. These results may have implications for dementia screening.