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Victor G DeGruttola

Publications and source records attributed to Victor G DeGruttola.

3 recordsLinked to original sources

What constitutes efficacy for a human immunodeficiency virus vaccine that ameliorates viremia: issues involving surrogate end points in phase 3 trials.

Initial human immunodeficiency virus (HIV) vaccines are unlikely to prevent acquisition of HIV in all recipients. Moreover, several HIV vaccines are under evaluation that are designed to reduce viremia after acquisition of infection. Such vaccines could provide important benefits to delay HIV progression and to reduce transmission. The decision to license a vaccine on the basis of observed effects on virus load and other postinfection surrogate end points in an efficacy trial is complicated by uncertainty about whether the vaccine effects will persist and reliably predict clinical effects, and by the challenge in interpreting the data posed by treatment of some seroconverters with antiretroviral drugs. Here, we evaluate how analyses of certain surrogate end points can be used for inferring clinically significant vaccine effects and propose end points that could be evaluated in efficacy trials to support licensure. The assessment suggests that a vaccine demonstrating moderately durable effects to delay therapy and to ameliorate viremia merits consideration for licensure.

AIDS Vaccines↗

Baseline predictors of CD4 T-lymphocyte recovery with combination antiretroviral therapy.

CD4 T-cell recovery with potent antiretroviral therapy varies considerably among HIV-1-infected patients. Data from two studies that enrolled subjects at different stages of disease progression were retrospectively combined. This analysis assessed the association between patient-specific factors and three measures of CD4 T-cell recovery after the initiation of triple-drug therapy: overall changes in CD4 cell counts; changes in CD4 cell counts during the first 8 weeks (phase I); and changes in CD4 cell counts during weeks 8-24 (phase II). Higher initial HIV-1 RNA values corresponded to greater increases in overall and phase I changes in mean CD4 cell counts, particularly among subjects with less advanced disease. In the overall and phase II cases, those subjects with suppressed HIV RNA levels had consistently higher increases in mean CD4 cell counts across both baseline HIV-1 RNA levels and CD4 cell counts than did the respective unsuppressed group. Based on a multivariate model, increases in mean phase I CD4 cell counts corresponded to higher log baseline HIV-1 RNA levels (p =.0001) and log changes in HIV-1 RNA levels at week 4 (p =.03). Patients with earlier stages of disease (p =.0001) and females (p =.01) had higher increases in phase I changes. Phase II CD4 cell counts did not depend solely on baseline HIV-1 RNA levels and CD4 cell counts but on their interaction (p =.0001) as well as on achieving virologic suppression (p =.0009).

Acquired Immunodeficiency Syndrome↗

Modelling HIV viral rebound using non-linear mixed effects models.

Individuals infected with the human immunodeficiency virus type 1 (HIV-1) who initiate antiretroviral therapy typically experience a marked decline in concentrations of HIV-1 RNA in plasma. Often, however, viral rebound occurs within the first year of treatment and this rebound may be associated with resistance to antiretroviral therapy. For this reason, it is important to study the patterns of virological response of HIV-1 RNA to treatment. In particular, there is interest in the relationship between the lowest level of plasma HIV-1 RNA attained after initiation of therapy (nadir value) and the time until rebound. To investigate this question, we implement a simple and flexible non-linear mixed effects model for the trajectory of the HIV-1 RNA until rebound. This model is also consistent with biological insights into the effects of treatment. We also show how the problem of censoring of HIV-1 RNA values at the lower limit of assay quantification can be addressed using a multiple imputation scheme. The algorithm is simple to implement and is based on accessible software. Our application makes use of data from clinical trial 315 conducted by the AIDS Clinical Trials Group (ACTG 315). We find a strong relationship between HIV-1 RNA nadir and time to rebound, with potentially important consequences for the management of HIV-infected individuals.

Adolescent↗