The goal of the project is to develop statistical methods for the design and analysis of preventive HIV vaccine efficacy trials and repeated low-dose non-human primate (NHP) challenge trials. Specifically the methods are for (1) Sieve Analysis: Assessing the impact of HIV genotypic and phenotypic variation on HIV vaccine efficacy; (2) Post-infection Vaccine Efficacy: Assessing HIV vaccine effects on post-HIV infection disease progression; and (3) Correlates/Surrogates of Protective Immunity: Assessing correlations of immunological measurements with risk of HIV/SIV infection rate and of post-infection outcomes, and evaluating whether and to what extent the correlations are causative.
Aim 1 will develop a model for studying the relationship between vaccine efficacy and multivariate summary measures of distance of an exposing virus to the immunogen, accounting for subject characteristics including their immune responses to vaccination, and will develop high-dimensional data methods for relating HIV amino acid sequences in breakthrough infections with viral load and other post-infection endpoints.
Aim 2 will develop methods for studying durability of vaccine effects on viral load over time, tackling the problems of selection bias that may arise because the analyzed groups are selected after randomization, and """"""""missing"""""""" viral loads that may arise because infected subjects initiate antiretro viral therapy.
Aim 3 will develop methods for assessing correlates/surrogates of protection in efficacy trials and in NHP trials.
The aims are complementary and integrated, with HIV sequence, immunological, and viral load data used for each aim. The methods will be applied to analyze several HIV vaccine efficacy trial and NHP challenge trial datasets. Primary goals of HIV vaccine research include developing a vaccine that protects broadly against many HIV strains and that can durably suppress viremia, and developing a correlate of protective immunity, which would streamline vaccine development and provide the basis for bridging efficacy of a vaccine observed in a Phase 3 trial to a new setting. By improving the design and analysis of efficacy and NHP trials for addressing these areas, the project will benefit public health. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI054165-05
Application #
7222794
Study Section
Special Emphasis Panel (ZRG1-AARR-A (06))
Program Officer
Gezmu, Misrak
Project Start
2003-04-01
Project End
2010-03-31
Budget Start
2007-04-01
Budget End
2008-03-31
Support Year
5
Fiscal Year
2007
Total Cost
$235,258
Indirect Cost
Name
Fred Hutchinson Cancer Research Center
Department
Type
DUNS #
078200995
City
Seattle
State
WA
Country
United States
Zip Code
98109
Dai, James Y; Li, Shuying S; Gilbert, Peter B (2014) Case-only method for cause-specific hazards models with application to assessing differential vaccine efficacy by viral and host genetics. Biostatistics 15:196-203
Rolland, Morgane; Edlefsen, Paul T; Larsen, Brendan B et al. (2012) Increased HIV-1 vaccine efficacy against viruses with genetic signatures in Env V2. Nature 490:417-20
Huang, Ying; Gilbert, Peter B (2011) Comparing biomarkers as principal surrogate endpoints. Biometrics 67:1442-51
Winstone, Nicola; Wilson, Aaron J; Morrow, Gavin et al. (2011) Enhanced control of pathogenic Simian immunodeficiency virus SIVmac239 replication in macaques immunized with an interleukin-12 plasmid and a DNA prime-viral vector boost vaccine regimen. J Virol 85:9578-87
Gilbert, Peter B (2010) Some design issues in phase 2B vs phase 3 prevention trials for testing efficacy of products or concepts. Stat Med 29:1061-71
Zhang, Min; Gilbert, Peter B (2010) Increasing the Efficiency of Prevention Trials by Incorporating Baseline Covariates. Stat Commun Infect Dis 2:
Scheike, Thomas H; Sun, Yanqing; Zhang, Mei-Jie et al. (2010) A semiparametric random effects model for multivariate competing risks data. Biometrika 97:133-145
Sun, Yanqing (2010) Estimation of semiparametric regression model with longitudinal data. Lifetime Data Anal 16:271-98
Gilbert, Peter B; Jin, Yuying (2010) Semiparametric estimation of the average causal effect of treatment on an outcome measured after a postrandomization event, with missing outcome data. Biostatistics 11:34-47
Wolfson, Julian; Gilbert, Peter (2010) Statistical identifiability and the surrogate endpoint problem, with application to vaccine trials. Biometrics 66:1153-61

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