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DOI: 10.1177/096228020000900303 Some statistical issues in the design of HIV-1 vaccine and treatment trialsDepartment of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA, pgilbert{at}hsph.harvard.edu This article summarizes material on statistical issues in the design of HIV-1 preventive vaccine trials and antiretroviral HIV-1 treatment trials that was presented at the first school on Modern Statistical Methods in Medical Research, held at the International Centre for Theoretical Physics in Trieste, in September 1999. Design issues for the two trial types are discussed separately and are compared, which highlights the relative complexity of vaccine trials. Vaccine trial designs for assessing various vaccine effects are considered, including classical double-blind individual-randomized designs for evaluating biological vaccine effects on susceptibility to infection, and augmented partners, cluster-randomized, and infant designs for evaluating biological vaccine effects on infectiousness as well as on susceptibility. Within these designs, covered topics include surrogate endpoints for measuring vaccine effects on secondary transmission and on HIV-1 disease progression, and exploratory and confirmatory methods for assessing host immune and viral genotypic or phenotypic correlates of vaccine protection against infection or disease. For antiretroviral trials, covered topics include endpoint selection and structured designs such as fractional factorial and Latin square designs for rapidly screening combination drug regimens and for identifying patterns of HIV-1 genomic evolution that predict loss of drug efficacy.
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