In this project, the researchers address important issues in the statistical analysis of data from trials of interventions for treatment or prevention of HIV infection, continuing work conducted during the current grant period on methods of clinical trials of AIDS therapeutics, and extending the work scope to the exploration of design and analysis issues arising in field trials of vaccines for prevention of HIV infection. The AIDS crisis has led to the urgent need for rapidly obtaining data about the efficacy and safety of therapeutic interventions. Efficiently designed clinical trials are the most reliable source of information on which valid assessments of treatment efficacy can be based. To improve the efficiency and reliability of trials, the Principal Investigator proposes to continue work on exploring methods to use surrogate endpoint information from biological markers, such as CD4 and RNA PCR profiles. He expects to explore approaches for determining long-term treatment effects when randomized clinical trials have been terminated early due to definitive evidence of short-term effects. Work will be continued on the development of important methods which are required to handle appropriately the type of outcome data which are multivariate or are subject to complicated censoring mechanisms and which arise frequently in AIDS cohort studies as well as in HIV clinical trials. Specifically, non- and semi-parametric methods will be developed for analyzing multivariate failure time data and statistical methods will be developed for the analysis of interval censored, doubly censored, and truncated failure time data. These methods will be assessed using data from HIV/AIDS clinical trials and cohort studies. Other features of HIV vaccine trials will also be addressed, including the effects of dependence and heterogeneity among vaccine trials participants on distributional properties of estimators of vaccine efficacy. New statistical methods will be developed and evaluated for the analysis of characteristics of viruses that impact HIV trial participants in order to make inferences regarding breadth of immunity conferred by the vaccine.
| Fleming, Thomas R; Ellenberg, Susan S; DeMets, David L (2018) Data Monitoring Committees: Current issues. Clin Trials 15:321-328 |
| Lyons, Vivian H; Li, Lingyu; Hughes, James P et al. (2017) Proposed variations of the stepped-wedge design can be used to accommodate multiple interventions. J Clin Epidemiol 86:160-167 |
| Fleming, Thomas R; DeMets, David L; Roe, Matthew T et al. (2017) Data monitoring committees: Promoting best practices to address emerging challenges. Clin Trials 14:115-123 |
| Fleming, Thomas R; DeMets, David L; Roe, Matthew T et al. (2017) Rejoinder. Clin Trials 14:126-127 |
| Fleming, Thomas R; Demets, David L; McShane, Lisa M (2017) Discussion: The role, position, and function of the FDA-The past, present, and future. Biostatistics 18:417-421 |
| Fleming, Thomas R; Ellenberg, Susan S (2016) Evaluating interventions for Ebola: The need for randomized trials. Clin Trials 13:6-9 |
| Dai, James Y; Hendrix, Craig W; Richardson, Barbra A et al. (2016) Pharmacological Measures of Treatment Adherence and Risk of HIV Infection in the VOICE Study. J Infect Dis 213:335-42 |
| Odem-Davis, K; Fleming, T R (2015) A simulation study evaluating bio-creep risk in serial non-inferiority clinical trials for preservation of effect. Stat Biopharm Res 7:12-24 |
| Hughes, James P; Granston, Tanya S; Heagerty, Patrick J (2015) Current issues in the design and analysis of stepped wedge trials. Contemp Clin Trials 45:55-60 |
| Cumberland, William N; Fong, Youyi; Yu, Xuesong et al. (2015) Nonlinear Calibration Model Choice between the Four and Five-Parameter Logistic Models. J Biopharm Stat 25:972-83 |
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