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E Le Corfec

Publications and source records attributed to E Le Corfec.

7 recordsLinked to original sources
PubMed2000

Factors associated with clinical and virological failure in patients receiving a triple therapy including a protease inhibitor.

OBJECTIVE: To determine the predictors of virological and clinical failure in patients receiving a protease inhibitor as part of triple therapy. METHODS: From the French Hospital Database on HIV, 1402 protease inhibitor-naive patients starting a highly active antiretroviral therapy regimen with ritonavir, saquinavir-hard gel capsule (hgc) or indinavir between July 1996 and March 1997, and with measured HIV RNA at baseline and at 12 months, were studied for progression to a new AIDS-defining event (ADE) or death. Virological failure was defined as plasma HIV RNA > 1000 copies/ml at 12 months. Multivariate analyses were performed using Cox models for clinical outcomes and logistic regression for virological outcomes. RESULTS: During a median follow-up of 14.1 months, 94 (6.7%) patients experienced an ADE or died. At 12 months, 700 patients (49.9%) had virological failure. In the multivariate analysis, baseline CD4 cell count and viral load were found to be independent predictors of both virological and clinical failure. Neither the type of the first protease inhibitor taken nor previous antiretroviral therapy experience was associated with risk of clinical progression. For virological failure, the use of saquinavir-hgc was associated with a significant 1.96-fold increase in risk compared with indinavir; pre-treated patients were at higher risk than antiretroviral therapy-naive patients. CONCLUSION: In this study with large samples of patients, the use of saquinavir-hgc was associated with higher risk of virological failure at 12 months than were ritonavir and indinavir; no differences between protease inhibitors were found for clinical progression. As biases cannot be excluded, a longer duration of follow-up will be necessary to answer the question of whether the results are really discrepant or simply reflect the delay between virological failure and clinical manifestations.

Adult↗
PubMed2000

[HIV-1 quantitative dynamics in vivo: a review of mathematical models].

Over the last years, mathematical models have been applied in HIV infection to investigate the population dynamics of HIV-1 and cells of the immune system in infected hosts. They have contributed to a better understanding of the pathogenesis of AIDS. Among the model-based works, the quantitative studies carried out by two teams, during the years 1995, 1996 and 1997, have brought important results on HIV infection dynamics, reminding that HIV belonged to the lentivirus family, which had not been integrated in research of the previous years. In the studies on HIV dynamics, solutions of mathematical models were fitted to viral and/or immunological markers data in order to estimate the parameters of the viral and cellular production kinetics in infected patients. The present paper is a critical review of these studies. The methods and the most important results are presented. We explain why their impact was so considerable, but also show how the simplicity of modelling could result in conceptual errors. We finally discuss the contribution and the limits of mathematical models in the analysis of experimental data.

Acquired Immunodeficiency Syndrome↗
PubMed1999

Visit-driven endpoints in randomized HIV/AIDS clinical trials: impact of missing data on treatment difference measured on summary statistics.

In randomized HIV/AIDS clinical trials, CD4 lymphocyte counts and plasma HIV-1 RNA measurements are often used as endpoints. The comparison between treatment groups is mainly based on a summary measure of outcome, so-called summary statistic. Such analyses are often complicated by missing data occurring as drop-outs. For the most currently used summary statistics in these trials, we examined the impact of missing data occurring as drop-outs on test size, in order to help choosing between these statistics. A simulation of missing-data patterns was performed, using HIV-1 plasma RNA measurements as the main endpoint, to compare the effect of three plausible informative patterns, depending on treatment group, and on baseline or current plasma viral load, on eight different summary statistics. Missing data resulted in test sizes over the nominal value for the area under the curve minus baseline, the least-squares slope, the slope estimated with use of a mixed effects linear model, assuming a linear trend over the entire study, the difference between baseline and nadir, and the difference between baseline and week 24. The difference between baseline and week 8 was an acceptable summary with respect to the test size, but did not reflect accurately the durability of the effect of treatment. Two criteria appeared as the best summary statistics: the slope estimated by a mixed effects model, with a change of slope after two weeks of treatment, and to a lesser degree, the area under the curve after carrying forward the last observation.

Acquired Immunodeficiency Syndrome↗
PubMed1999

Direct HIV testing in blood donations: variation of the yield with detection threshold and pool size.

BACKGROUND: This study was designed to evaluate the potential yield of introducing nucleic acid amplification testing (NAT) in blood donation, according to the detection threshold and the pool size. STUDY DESIGN AND METHODS: A mathematical model of early HIV-1 population dynamics in blood has been developed and is used to predict the window period for NAT, according to the detection threshold and the pool size. The corresponding number of undetected, infected blood donations and the residual risk are estimated by using a previously published simulation model for the United States (9.96 million blood donations from regular donors, and an observed rate of HIV antibody-positive blood donations of 3.18/100,000) and for France (2.32 million blood donations, and a rate of antibody-positive donations of 0.9/100,000). RESULTS: The average window period from infection predicted by the mathematical model for NAT ranges from 8.4 to 15.6 days, according to the detection threshold and the pool size. The maximum yield of adding NAT to the current antibody tests is estimated at 14 donations for the United States and 2 for France. The maximum yield of adding NAT to the newly developed combined HIV antibody and p24 antigen tests is 7 donations for the United States and 1 for France. CONCLUSION: NAT at blood donation could reduce the HIV-1 window period to a minimal value of 8 days without pooling the blood samples, but the yield of NAT would be close to that of combined HIV antibody and p24 antigen tests for high values of the detection threshold and the pool size.

Blood Donors↗
PubMed1998

A stochastic model for early HIV-1 population dynamics.

A simple stochastic mathematical model is developed and investigated for early human immunodeficiency virus type-1 (HIV-1) population dynamics. The model, which is a multi-dimensional diffusion process, includes activated uninfected CD4(+)T cells, latently and actively infected CD4(+)T cells and free virions occurring in plasma. Stochastic effects are assumed to arise in the process of infection of CD4(+)T cells and transitions may occur from uninfected to latently or actively infected cells by chance mechanisms. Using the best currently available parameter values, the intrinsic variability in response to a given initial infection is examined by solving the stochastic system numerically. We estimate the statistical distributions of the time of occurrence and the magnitude of the early peak in viral concentration. The maximum of the viral load has a value in the experimental range and its time of occurrence has a 95% confidence interval from 19.4 to 25.1 days. The stochastic nature of the growth of viral density is extremely pronounced in the first few days after initial infection. Threshold effects are noted at virion levels of about 3-5x10(-5) mm-3. In addition to modeling the intrinsic variability in HIV-1 growth, we have explored the effects of perturbations in the parameter values in order to assess the additional stochastic effects of between-patient variability. We found that changes in the initial number of virions or dose size, the rate at which latently infected CD4(+)T cells are converted to the actively infected form and the fraction of latent cells has only minor effects on the size, speed and variability of the response. In contrast, decreased speed and magnitude but greater variability in response were obtained when the death rate of uninfected CD4(+) T cells, the death rate of actively infected cells and the clearance rate of the virus were increased or when the appearance rate of uninfected CD4(+)T cells, the number of virions produced by infected cells, the infection rate of CD4(+)T cells and the initial number of uninfected activated CD4(+)T cells were decreased. We also determined the distribution of the time to reach a given virion density. From this distribution the probability of detection of the virus as a function of time can be estimated. The numerical results obtained are in the range of experimental values and are discussed in relation to recently proposed detection and testing procedures.

CD4-Positive T-Lymphocytes↗