Literature DB >> 12854093

On the analysis of viral load endpoints in HIV vaccine trials.

Michael G Hudgens1, Antje Hoering, Steven G Self.   

Abstract

First generation HIV vaccines are not likely to provide complete protection from HIV-1 infection. Therefore, it is important to assess a vaccine's effect on disease progression and infectiousness of infected vaccinees in an efficacy trial; however, direct assessment of such vaccine effects is not feasible within current trial designs. Viral load in HIV-infected individuals correlates with infectiousness and disease progression in a natural history setting, and thus is a reasonable candidate for a surrogate outcome in vaccine efficacy trials. We consider comparisons of viral load of infected vaccinees to that of infected trial participants in the control group. Dramatic differences in viral loads between these groups would suggest a vaccine effect on disease progression. However, modest differences, even if statistically significant, could be consistent with an imperfect vaccine effect on susceptibility to infection and not an effect on disease progression, that is, a selection effect of the vaccine. Thus, the usual statistical tests for no difference between groups do not test the biologically and clinically relevant hypothesis. We propose a model for the possible selective effects of a vaccine and develop several test statistics for assessing a direct effect of the vaccine on viral load given this selection model. Finite sample properties of these tests are evaluated using computer simulations. Copyright 2003 John Wiley & Sons, Ltd.

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Year:  2003        PMID: 12854093     DOI: 10.1002/sim.1394

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  24 in total

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4.  Nonparametric Bounds and Sensitivity Analysis of Treatment Effects.

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5.  Causal Vaccine Effects on Binary Postinfection Outcomes.

Authors:  Michael G Hudgens; M Elizabeth Halloran
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6.  Semiparametric estimation of the average causal effect of treatment on an outcome measured after a postrandomization event, with missing outcome data.

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7.  Semiparametric estimation of treatment effects given base-line covariates on an outcome measured after a post-randomization event occurs.

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8.  Principal stratification--uses and limitations.

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Journal:  Int J Biostat       Date:  2011-07-11       Impact factor: 0.968

9.  Does Finasteride Affect the Severity of Prostate Cancer? A Causal Sensitivity Analysis.

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10.  Endpoints and regulatory issues in HIV vaccine clinical trials: lessons from a workshop.

Authors:  Dean Follmann; Ann Duerr; Stephen Tabet; Peter Gilbert; Zoe Moodie; Patricia Fast; Massimo Cardinali; Steve Self
Journal:  J Acquir Immune Defic Syndr       Date:  2007-01-01       Impact factor: 3.731

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