Biomedical subjects

Daniel Commenges

Publications and source records attributed to Daniel Commenges.

16 recordsLinked to original sources

PubMed2007

Multiple imputation for interval censored data with auxiliary variables.

We propose a non-parametric multiple imputation scheme, NPMLE imputation, for the analysis of interval censored survival data. Features of the method are that it converts interval-censored data problems to complete data or right censored data problems to which many standard approaches can be used, and that measures of uncertainty are easily obtained. In addition to the event time of primary interest, there are frequently other auxiliary variables that are associated with the event time. For the goal of estimating the marginal survival distribution, these auxiliary variables may provide some additional information about the event time for the interval censored observations. We extend the imputation methods to incorporate information from auxiliary variables with potentially complex structures. To conduct the imputation, we use a working failure-time proportional hazards model to define an imputing risk set for each censored observation. The imputation schemes consist of using the data in the imputing risk sets to create an exact event time for each interval censored observation. In simulation studies we show that the use of multiple imputation methods can improve the efficiency of estimators and reduce the effect of missing visits when compared to simpler approaches. We apply the approach to cytomegalovirus shedding data from an AIDS clinical trial, in which CD4 count is the auxiliary variable.

CD4 Lymphocyte Count↗

PubMed2006

Survival analysis using auxiliary variables via non-parametric multiple imputation.

We develop an approach, based on multiple imputation, that estimates the marginal survival distribution in survival analysis using auxiliary variables to recover information for censored observations. To conduct the imputation, we use two working survival models to define a nearest neighbour imputing risk set. One model is for the event times and the other for the censoring times. Based on the imputing risk set, two non-parametric multiple imputation methods are considered: risk set imputation, and Kaplan-Meier imputation. For both methods a future event or censoring time is imputed for each censored observation. With a categorical auxiliary variable, we show that with a large number of imputes the estimates from the Kaplan-Meier imputation method correspond to the weighted Kaplan-Meier estimator. We also show that the Kaplan-Meier imputation method is robust to mis-specification of either one of the two working models. In a simulation study with time independent and time-dependent auxiliary variables, we compare the multiple imputation approaches with an inverse probability of censoring weighted method. We show that all approaches can reduce bias due to dependent censoring and improve the efficiency. We apply the approaches to AIDS clinical trial data comparing ZDV and placebo, in which CD4 count is the time-dependent auxiliary variable.

Biometry↗

PubMed2006

Estimation of dynamical model parameters taking into account undetectable marker values.

BACKGROUND: Mathematical models are widely used for studying the dynamic of infectious agents such as hepatitis C virus (HCV). Most often, model parameters are estimated using standard least-square procedures for each individual. Hierarchical models have been proposed in such applications. However, another issue is the left-censoring (undetectable values) of plasma viral load due to the lack of sensitivity of assays used for quantification. A method is proposed to take into account left-censored values for estimating parameters of non linear mixed models and its impact is demonstrated through a simulation study and an actual clinical trial of anti-HCV drugs. METHODS: The method consists in a full likelihood approach distinguishing the contribution of observed and left-censored measurements assuming a lognormal distribution of the outcome. Parameters of analytical solution of system of differential equations taking into account left-censoring are estimated using standard software. RESULTS: A simulation study with only 14% of measurements being left-censored showed that model parameters were largely biased (from -55% to +133% according to the parameter) with the exception of the estimate of initial outcome value when left-censored viral load values are replaced by the value of the threshold. When left-censoring was taken into account, the relative bias on fixed effects was equal or less than 2%. Then, parameters were estimated using the 100 measurements of HCV RNA available (with 12% of left-censored values) during the first 4 weeks following treatment initiation in the 17 patients included in the trial. Differences between estimates according to the method used were clinically significant, particularly on the death rate of infected cells. With the crude approach the estimate was 0.13 day-1 (95% confidence interval [CI]: 0.11; 0.17) compared to 0.19 day-1 (CI: 0.14; 0.26) when taking into account left-censoring. The relative differences between estimates of individual treatment efficacy according to the method used varied from 0.001% to 37%. CONCLUSION: We proposed a method that gives unbiased estimates if the assumed distribution is correct (e.g. lognormal) and that is easy to use with standard software.

AIDS-Related Opportunistic Infections↗

PubMed2006

Random change point model for joint modeling of cognitive decline and dementia.

We propose a joint model for cognitive decline and risk of dementia to describe the pre-diagnosis phase of dementia. We aim to estimate the time when the cognitive evolution of subjects in the pre-dementia phase becomes distinguishable from normal evolution and to study whether the shape of cognitive decline depends on educational level. The model combines a piecewise polynomial mixed model with a random change point for the evolution of the cognitive test and a log-normal model depending on the random change point for the time to dementia. Parameters are estimated by maximum likelihood using a Newton-Raphson-like algorithm. The expected cognitive evolution given age to dementia is then derived and the marginal distribution of dementia is estimated to check the log-normal assumption.

Algorithms↗

PubMed2006

A nonlinear model with latent process for cognitive evolution using multivariate longitudinal data.

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.

Aged↗

PubMed2006

Change in T-lymphocyte count after initiation of highly active antiretroviral therapy in HIV-infected patients with history of Mycobacterium avium complex infection.

OBJECTIVE: To compare changes in CD4+, CD8+ and total lymphocyte counts after initiation of highly active antiretroviral therapy (HAART) between HIV-infected patients with and without a recent history of Mycobacterium avium complex (MAC) infection. METHOD: Matched exposed-non-exposed retrospective cohort study. RESULTS: Fifty-one patients with a recent history of MAC infection (MAC+) started a combination of at least three antiretroviral drugs. They were individually matched to 145 patients without any history of MAC infection (MAC-) according to CD4+ T-cell count (+/- 30 cells/mm3), previous experience of antiretroviral treatment, AIDS clinical stage at the time of HAART initiation (baseline), age (+/- 10 years) and gender. MAC+ and MAC- patients presented comparable median levels of total lymphocytes (488 vs 688/mm3, P=0.09), CD4+ (11 vs 16/mm3, P=0.15), CD8+ count (359 vs 386/mm3, P=0.39) and plasma HIV RNA (5.3 vs 5.1 log10 copies/ml, P=0.22) at baseline. After 6 months on HAART, the median increase of CD4+ T-cell count was 28 cells/mm3 (interquartile range [IQR]: 1-63) in MAC+ and 72 cells/mm3 (IQR: 34-120) in MAC- patients (P<0.0001), whereas the percentage of CD4+ T cells was not significantly different between the two groups (P=0.13). Comparable differences were observed for total lymphocytes and CD8+ T cells (P<0.001). The 6 months decline of plasma HIV RNA was not significantly different according to MAC exposure (-1.6 in MAC+ vs -1.8 log10 copies/ml in MAC- patients, P=0.65). Results were confirmed after adjustment for other characteristics than the matching variables and after taking into account potential informative bias due to unbalanced number of deaths between the two groups. CONCLUSION: MAC infection at the time of HAART initiation is an important deleterious factor for immune reconstitution. A better understanding of the underlying mechanism and an evaluation of additional treatment strategies are necessary to help immune restoration in such circumstances.

AIDS-Related Opportunistic Infections↗

PubMed2005

Joint modelling of bivariate longitudinal data with informative dropout and left-censoring, with application to the evolution of CD4+ cell count and HIV RNA viral load in response to treatment of HIV infection.

Several methodological issues occur in the context of the longitudinal study of HIV markers evolution. Three of them are of particular importance: (i) correlation between CD4+ T lymphocytes (CD4+) and plasma HIV RNA; (ii) left-censoring of HIV RNA due to a lower quantification limit; (iii) and potential informative dropout. We propose a likelihood inference for a parametric joint model including a bivariate linear mixed model for the two markers and a lognormal survival model for the time to drop out. We apply the model to data from patients starting antiretroviral treatment in the CASCADE collaboration where all of the three issues needed to be addressed.

Anti-HIV Agents↗

PubMed2004

Estimating the expectation of the log-likelihood with censored data for estimator selection.

A criterion for choosing an estimator in a family of semi-parametric estimators from incomplete data is proposed. This criterion is the expected observed log-likelihood (ELL). Adapted versions of this criterion in case of censored data and in presence of explanatory variables are exhibited. We show that likelihood cross-validation (LCV) is an estimator of ELL and we exhibit three bootstrap estimators. A simulation study considering both families of kernel and penalized likelihood estimators of the hazard function (indexed on a smoothing parameter) demonstrates good results of LCV and a bootstrap estimator called ELL(bboot). We apply the ELL(bboot) criterion to compare the kernel and penalized likelihood estimators to estimate the risk of developing dementia for women using data from a large cohort study.

Bias↗

PubMed2003

Maximum penalized likelihood estimation in a gamma-frailty model.

The shared frailty models allow for unobserved heterogeneity or for statistical dependence between observed survival data. The most commonly used estimation procedure in frailty models is the EM algorithm, but this approach yields a discrete estimator of the distribution and consequently does not allow direct estimation of the hazard function. We show how maximum penalized likelihood estimation can be applied to nonparametric estimation of a continuous hazard function in a shared gamma-frailty model withright-censored and left-truncated data. We examine the problem of obtaining variance estimators for regression coefficients, the frailty parameter and baseline hazard functions. Some simulations for the proposed estimation procedure are presented. A prospective cohort (Paquid) with grouped survival data serves to illustrate the method which was used to analyze the relationship between environmental factors and the risk of dementia.

Algorithms↗

PubMed2003

Cardiovascular mortality and calcium and magnesium in drinking water: an ecological study in elderly people.

BACKGROUND: Previous studies found relations between cardiovascular mortality and minerals in drinking water, but the major works considered water hardness or neglected the differences between adults and elderly. Drinking water is an important source of calcium in the elderly particularly because of increased needs and decreased consumption of dairy products. METHODS: We collected informations about all deaths (14,311) occurring in 69 parishes of the South-West of France during 7 years (1990-1996). We obtained the causes of deaths from a special service of INSERM for each death, with age at death and sex. The exposure value was supplied by administrative source (DDASS) and by measurement surveys. We use an extra-Poisson variation model to take into account the heterogeneity of the population of these parishes. RESULTS: A significant relationship was observed between calcium and cardiovascular mortality with a RR: 0.90 for non-cerebrovascular causes and RR: 0.86 for cerebrovascular (when calcium is higher than the second tercile: 94 mg/l). We found a protective effect of magnesium concentrations between 4 and 11 mg/l with a RR: 0.92 for non-cerebrovascular and RR: 0.77 for cerebrovascular mortality, as compared to concentrations lower than 4 mg/l. CONCLUSIONS: These findings strongly suggest a potential protective dose-effect relation between calcium in drinking water and cardiovascular causes. For magnesium, a U-shape effect is possible, especially for cerebrovascular mortality.

Aged↗

PubMed2002

Endometrial vascularity and ongoing pregnancy after IVF.

BACKGROUND: Embryo transfer is prone to failure. AIM: To investigate whether endometrial vascularity influences in vitro fertilization (IVF) outcome. METHODS: Total 144 patients receiving IVF (conventional or microinjection) were assessed with color and power Doppler on the day of embryo transfer: age, IVF type, number and quality of embryos, endometrial thickness and aspect, mean uterine PI, uterine notch, type of endometrial vascularity (peripheral or sub- and intra-endometrial), and pregnancy involving second trimester were recorded. RESULTS: 27 (18.7%) pregnancies were obtained. By univariate analysis, two parameters were significant: high frequency of uterine notch (P = 0.03) and peri-endometrial vascularity (P = 0.012) in the group of failures. Multivariate analysis by logistic regression clearly showed that the absence of sub- and intra-endometrial color signal decreased the chances of pregnancy eight-fold odds ratio (OR) = 0.14 [CI: 0.029-0.68]. CONCLUSION: In this limited series, the presence of sub- and intra-endometrial vascularity on the day of transfer seemed to be mandatory for obtaining an ongoing pregnancy.

Adult↗

PubMed2002

Penalized likelihood approach to estimate a smooth mean curve on longitudinal data.

This paper aims to propose a penalized likelihood approach to estimate a smooth mean curve for the evolution with time of a Gaussian variable taking into account the correlation structure of longitudinal data. The model is an extension of the mixed effects linear model including an unspecified function of time f(t). The estimator (circumflex)f(t) is defined as the solution of the maximization of the penalized likelihood and is approximated on a basis of cubic M-spline with a reduced number of knots. We present modifications of four criteria (cross-validation, generalized cross-validation, T of Rice, Akaike's criterion) to estimate the smoothing parameter when data are correlated; these four criteria gave very similar results in the simulation study. The simulation study showed also the superiority of the Bayesian confidence bands of the mean curve over the frequentist ones. We develop empirical Bayes estimates of subject-specific deviations. This approach was applied to study the progression of CD4+ lymphocyte counts in a cohort of HIV patients treated with protease inhibitors.

Acquired Immunodeficiency Syndrome↗

PubMed2002

Recombinant follicle-stimulating hormone versus human menopausal gonadotropin in the late follicular phase during ovarian hyperstimulation for in vitro fertilization.

OBJECTIVE: To study the effect of exogenous LH in the late follicular phase on ongoing pregnancies and at the different stages of IVF-ET (stimulation, fertilization, and implantation) in patients with low endogenous LH. DESIGN: Retrospective cohort study with modeling of the different phases of IVF-ET. SETTING: IVF center of the teaching hospital in Bordeaux, France. PATIENT(S): Women undergoing IVF and ICSI treatment. INTERVENTION(S): One group received recombinant FSH alone (FSH group) and the other received recombinant FSH and hMG in the late follicular phase (i.e., when the largest follicle reached 14 mm) (FSH/hMG group). MAIN OUTCOME MEASURE(S): Ongoing pregnancy, number of oocytes, and number of embryos. RESULT(S): The FSH/hMG group had a higher probability of having at least one oocyte (odds ratio [OR] = 2.75 [1.11-6.80]), of having at least one embryo after oocyte retrieval (OR = 2.84 [1.33-6.07]), and of ongoing pregnancy after ET (OR = 2.04 [0.83-5.01]), and globally had a higher probability of ongoing pregnancy (OR = 2.83 [1.19-6.71]). CONCLUSION(S): In ovarian hyperstimulation for IVF-ET, LH supplementation in the late follicular phase of women with low endogenous LH is beneficial for ongoing pregnancy by increasing the rate of success of all stages of the treatment.

Adult↗

PubMed2002

Bivariate linear mixed models using SAS proc MIXED.

Bivariate linear mixed models are useful when analyzing longitudinal data of two associated markers. In this paper, we present a bivariate linear mixed model including random effects or first-order auto-regressive process and independent measurement error for both markers. Codes and tricks to fit these models using SAS Proc MIXED are provided. Limitations of this program are discussed and an example in the field of HIV infection is shown. Despite some limitations, SAS Proc MIXED is a useful tool that may be easily extendable to multivariate response in longitudinal studies.

Antiretroviral Therapy, Highly Active↗

PubMed2002

Correction of the p-value after multiple tests in a Cox proportional hazard model.

We consider a situation which is common in epidemiology, in which several transformations of an explanatory variable are tried in a Cox model and the most significant test is retained. The p-value should then be corrected to take account of the multiplicity of tests. Bonferroni method is often too conservative because the tests may be highly positively correlated. We propose an asymptotically exact correction of the p-value. The method uses the fact that the tests are asymptotically normal to compute numerically the distribution of the maximum of several tests. Counting processes theory is used to derive estimators of the correlations between tests. The method is illustrated by a simulation and an analysis of the relation between concentration of aluminum in drinking water and risk of dementia.

Aluminum↗

PubMed2002

A penalized likelihood approach for an illness-death model with interval-censored data: application to age-specific incidence of dementia.

We consider the problem of estimating the intensity functions for a continuous time 'illness-death' model with intermittently observed data. In such a case, it may happen that a subject becomes diseased between two visits and dies without being observed. Consequently, there is an uncertainty about the precise number of transitions. Estimating the intensity of transition from health to illness by survival analysis (treating death as censoring) is biased downwards. Furthermore, the dates of transitions between states are not known exactly. We propose to estimate the intensity functions by maximizing a penalized likelihood. The method yields smooth estimates without parametric assumptions. This is illustrated using data from a large cohort study on cerebral ageing. The age-specific incidence of dementia is estimated using an illness-death approach and a survival approach.

Journal Article↗