The authors examined associations between exposure to aluminum or silica from drinking water and risk of cognitive decline, dementia, and Alzheimer's disease among elderly subjects followed for 15 ...years (1988–2003). They actively searched for incident cases of dementia among persons aged 65 years or over living in 91 civil drinking-water areas in southern France. Two measures of exposure to aluminum were assessed: geographic exposure and individual exposure, taking into account daily consumption of tap water and bottled water. A total of 1,925 subjects who were free of dementia at baseline and had reliable water assessment data were analyzed. Using random-effects models, the authors found that cognitive decline with time was greater in subjects with a higher daily intake of aluminum from drinking water (≥0.1 mg/day, P = 0.005) or higher geographic exposure to aluminum. Using a Cox model, a high daily intake of aluminum was significantly associated with increased risk of dementia. Conversely, an increase of 10 mg/day in silica intake was associated with a reduced risk of dementia (adjusted relative risk = 0.89, P = 0.036). However, geographic exposure to aluminum or silica from tap water was not associated with dementia. High consumption of aluminum from drinking water may be a risk factor for Alzheimer's disease.
Mechanistic models, based on ordinary differential equation systems, can exhibit very good predictive abilities that will be useful to build treatment monitoring strategies. In this review, we ...present the potential and the limitations of such models for guiding treatment (monitoring and optimizing) in HIV-infected patients. In the context of antiretroviral therapy, several biological processes should be considered in addition to the interaction between viruses and the host immune system: the mechanisms of action of the drugs, their pharmacokinetics and pharmacodynamics, as well as the viral and host characteristics. Another important aspect to take into account is clinical progression, although its implementation in such modelling approaches is not easy. Finally, the control theory and the use of intrinsic properties of mechanistic models make them very relevant for dynamic treatment adaptation. Their implementation would nevertheless require their evaluation through clinical trials.
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The study of dynamical models of HIV infection, based on a system of nonlinear ordinary differential equations (ODE), has considerably improved the knowledge of its pathogenesis. While the first ...models used simplified ODE systems and analyzed each patient separately, recent works dealt with inference in non-simplified models borrowing strength from the whole sample. The complexity of these models leads to great difficulties for inference and only the Bayesian approach has been attempted by now. We propose a full likelihood inference, adapting a Newton-like algorithm for these particular models. We consider a relatively complex ODE model for HIV infection and a model for the observations including the issue of detection limits. We apply this approach to the analysis of a clinical trial of antiretroviral therapy (ALBI ANRS 070) and we show that the whole algorithm works well in a simulation study.
I first discuss the main assumptions which can be made for multi-state models: the time-homogeneity and semi-Markov assumptions, the problem of choice of the time scale, the assumption of homogeneity ...of the population and also assumptions about the way the observations are incomplete, leading to truncation and censoring. The influence of covariates and different durations and time-dependent variables are synthesized using explanatory processes, and a general additive model for transition intensities presented. Different inference approaches, including penalized likelihood, are considered. Finally three examples of application in epidemiology are presented and some references to other works are given.
Clinical statuses of subjects are often observed at a finite number of visits. This leads to interval-censored observations of times of transition from one state to another. The likelihood can still ...easily be written in terms of both transition probabilities and transition intensities. In homogeneous Markov models, transition probabilities can be expressed simply in terms of transition intensities, but this is not the case in more general multi-state models. In addition, inference in homogeneous Markov models is easy because these are parametric models. Non-parametric approaches to non-homogeneous Markov models may follow two paths: one is the completely non-parametric approach and can be seen as a generalisation of the Turnbull approach; the other implies a restriction to smooth intensities models. In particular, the penalized likelihood method has been applied to this problem. This paper gives a review of these topics.
Despite the magnitude of the problem, little is known about the duration of dementia. Survival and risk factors of mortality with dementia and the impact of dementia on the risk of death were ...investigated using the Personnes Agées Quid (PAQUID) prospective population-based cohort study between 1988 and 1998. Statistical models dealing with interval censoring were performed. Among 3,675 participants aged 65 years or older and initially nondemented, 2,923 have been followed up for 8 years. Of these, 281 persons with incident dementia were actively diagnosed. The mean age of onset of dementia was 82.3 years. In the total population, the relative risk of dying after developing dementia was estimated to be 1.82 (95% confidence interval (CI): 1.77, 2.68) when adjusted for sociodemographic variables and comorbidity. Deaths from cerebrovascular diseases and respiratory diseases were particularly increased among persons with dementia, compared with those without. The median survival time of the persons with dementia was estimated to be 4.5 years. Women with dementia had a longer survival than did men with dementia, particularly for Alzheimer-type dementia (relative risk = 0.47, 95% CI: 0.27, 0.83). Educational level was not significantly associated with survival in persons with dementia. These results provide further evidence of the malignancy of dementia, which will be a challenge for the 21st century.
It has been postulated that oxidative stress may play a key role in dementia. This is substantiated by the recent discovery of the protective effect of wine. In wine, the flavonoids - powerful ...antioxidant substances also contained in tea, fruits and vegetables - have been thought to offer such protection. We investigated whether flavonoid intake could be associated with a lower incidence of dementia in a cohort of 1367 subjects above 65 years of age (Paquid). A questionnaire was used to evaluate their intake of flavonoids and subjects were followed-up for 5 years between 1991 and 1996: 66 incident cases of dementia were observed. We estimated the relative risk (RR) of dementia according to tertiles of flavonoid intake using a Cox model. The age-adjusted RR of dementia was 0.55 for the two highest tertiles compared to the lowest (95% CI: 0.34-0.90; p = 0.02). After additional adjustment for gender, education, weight and vitamin C intake, the RR was 0.49 (95% CI: 0.26-0.92; p = 0.04). We conclude that the intake of antioxidant flavonoids is inversely related to the risk of incident dementia.
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 (TO) 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 TO and T1 (by 0.60 points for subjects aged 65 years at TO to 0.83 points for subjects aged 85 years at TO), 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 TO 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. Am J Epidemiol 1997;145:49–506.
We study the practical identifiability of parameters, i.e., the accuracy of the estimation that can be hoped, in a model of HIV dynamics based on a system of non-linear Ordinary Differential ...Equations (ODE). This depends on the available information such as the schedule of the measurements, the observed components, and the measurement precision. The number of patients is another way to increase it by introducing an appropriate statistical "population" framework. The impact of each improvement of the experimental condition is not known in advance but it can be evaluated via the Fisher Information Matrix (FIM). If the non-linearity of the biological model, as well as the complex statistical framework makes computation of the FIM challenging, we show that the particular structure of these models enables to compute it as precisely as wanted. In the HIV model, measuring HIV viral load and total CD4+ count were not enough to achieve identifiability of all the parameters involved. However, we show that an appropriate statistical approach together with the availability of additional markers such as infected cells or activated cells should considerably improve the identifiability and thus the usefulness of dynamical models of HIV.
In the last decade, interest has been focused on human immunodeficiency virus (HIV) antibody assays and testing strategies that could distinguish recent infections from established infection in a ...single serum sample. Incidence estimates are obtained by using the relationship between prevalence, incidence, and duration of recent infection (window period). However, recent works demonstrated limitations of this approach due to the use of an estimated mean "window period." We propose an alternative approach that consists in estimating the distribution of infection times based on serological marker values at the moment when the infection is first discovered. We propose a model based on the repeated measurements of virological markers of seroconversion for the marker trajectory. The parameters of the model are estimated using data from a cohort of HIV-infected patients enrolled during primary infection. This model can be used for estimating the distribution of infection times for newly HIV diagnosed subjects reported in a HIV surveillance system. An approach is proposed for estimating HIV incidence from these results.
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