• A Gregory DiRienzo and Victor DeGruttola.
• Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. dirienzo@sdac.harvard.edu
• Control Clin Trials. 2003 Apr 1; 24 (2): 122-34.

AbstractThis paper investigates the use of a bivariate endpoint in clinical trials of antiretroviral drugs to treat infection with the HIV. While they provide the most reliable information about treatment effects, clinical events such AIDS or death are relatively rare among newly treated patients with HIV infection. As a result, surrogate endpoints, such as time to virological failure and time to regimen termination, are generally used in place of clinical endpoints in studies that enroll patients without previous treatment experience. Because no surrogate endpoint has been completely validated (i.e., shown to capture the full effect of treatment on clinical endpoint), it may be preferable to base treatment decisions on more than one surrogate. In this paper, we consider the bivariate endpoint of time to virological failure and time to regimen termination. Analysis of a bivariate endpoint requires appropriate statistical methods that maintain the experimentwise type I error rate when making simultaneous inference with respect to each endpoint. This article outlines such methods and compares their small sample properties using the simulation study that was executed for the purpose of designing a current AIDS clinical trial.

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