AEGiS-14IAC: On the analysis of viral endpoints in HIV vaccine trials.

14th International AIDS Conference

Barcelona, Spain - July 7-12, 2002

On the analysis of viral endpoints in HIV vaccine trials.

Int Conf AIDS 2002 Jul 7-12; 14:(abstract no. WeOrD1298)

Hudgens MG, Hoering A, Self SG
Fred Hutchinson Cancer Research Center, Seattle, United States

BACKGROUND: Given that first generation HIV vaccines are not likely to provide complete protection from HIV--1 infection, it is important to assess a vaccine's effect on disease progression in an efficacy trial. Viral load in HIV--infected individuals correlates with disease progression and onset of AIDS in a natural history setting, and thus is a reasonable candidate for a surrogate outcome of disease progression. Therefore, we consider comparisons of viral load of infected vaccinees to those 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, i.e., a selection effect of the vaccine.

METHODS: We propose a model for the possible selective effects of a vaccine and develop several test statistics for assessing the consistency of data from a vaccine trial with this selection model. Finite sample properties of these tests are evaluated using computer simulations.

RESULTS: Simulation results show that the proposed testing procedures maintain proper false positive rates with sensitivity effected by the size of the trial, the magnitude of the shift in viral load, and the vaccine efficacy for susceptibility (VE). For VE less than or equal to 0.5, trial designs with as few as 45 expected infections within the control group will have adequate power (> 70%) to detect a 1/2 log shift in viral load distribution above the upper stochastic bound of the selection model. For VE=0.8, the trial size would need to be increased by about 50% to achieve comparable results.

CONCLUSIONS: Our analysis approach separates two components of a vaccine's effects while appropriately accommodating for potential selection bias due to the comparison of post-randomization subgroups.

Keywords: AEGIS, AIDS Vaccines, Viral Load, HIV Infections, HIV, Disease Progression, Treatment Outcome, HIV Antibodies, Anti-HIV Agents, Research Design, Acquired Immunodeficiency Syndrome, HIV Seronegativity, Control Groups, virology, immunology

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