The long-term objectives of this proposal are to develop statistical models and methods to analyze various types of AIDS data and better understand the natural history and future spread of the epidemic.
The specific aims fall into four categories: (1) to develop statistical methods for estimating the distribution of the latency period between infection by the AIDS virus and the onset of AIDS, for assessing the effects of covariates (cofactors) on this distribution, and for estimating the infection rates over time, based on data from transfusion and pediatric AIDS cases; (2) to develop statistical methods for estimating the AIDS latency distribution, for assessing the role of covariates on this distribution, and for assessing the dependence between the latencies of infected persons and of those who infected them, based on certain types of 'screening' data; (3) to develop statistical models and methods for studying, in infected persons, the deterioration in immune system over time, and the role of cofactors on this deterioration, based on repeated serologic measures of immune function; and (4) to develop statistical models for the development and spread of infection with the AIDS virus in a heterogeneous population, and to implement these models in a computer program. Techniques of survival analysis and of more general stochastic processes will play a key role in the development of these methods.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI024643-03
Application #
3137773
Study Section
(SSS)
Project Start
1987-04-01
Project End
1990-06-30
Budget Start
1989-04-01
Budget End
1990-06-30
Support Year
3
Fiscal Year
1989
Total Cost
Indirect Cost
Name
Dana-Farber Cancer Institute
Department
Type
DUNS #
149617367
City
Boston
State
MA
Country
United States
Zip Code
02115
Lok, Judith J; Yang, Shu; Sharkey, Brian et al. (2018) Estimation of the cumulative incidence function under multiple dependent and independent censoring mechanisms. Lifetime Data Anal 24:201-223
Angelidou, Konstantia; Palumbo, Paul; Lindsey, Jane et al. (2018) Defining Study Outcomes That Better Reflect Individual Response to Treatment. Pediatr Infect Dis J 37:258-262
Harling, Guy; Wang, Rui; Onnela, Jukka-Pekka et al. (2017) Leveraging contact network structure in the design of cluster randomized trials. Clin Trials 14:37-47
Wang, Rui; De Gruttola, Victor (2017) The use of permutation tests for the analysis of parallel and stepped-wedge cluster-randomized trials. Stat Med 36:2831-2843
Li, Junlong; Zhao, Lihui; Tian, Lu et al. (2016) A predictive enrichment procedure to identify potential responders to a new therapy for randomized, comparative controlled clinical studies. Biometrics 72:877-87
Lok, Judith J; Hughes, Michael D (2016) Evaluating predictors of competing risk outcomes when censoring depends on time-dependent covariates, with application to safety and efficacy of HIV treatment. Stat Med 35:2183-94
Zhao, Lihui; Claggett, Brian; Tian, Lu et al. (2016) On the restricted mean survival time curve in survival analysis. Biometrics 72:215-21
Zhang, Yifan; Trippa, Lorenzo; Parmigiani, Giovanni (2016) Optimal Bayesian adaptive trials when treatment efficacy depends on biomarkers. Biometrics 72:414-21
Prague, Melanie; Wang, Rui; Stephens, Alisa et al. (2016) Accounting for interactions and complex inter-subject dependency in estimating treatment effect in cluster-randomized trials with missing outcomes. Biometrics 72:1066-1077
Claggett, Brian; Tian, Lu; Castagno, Davide et al. (2015) Treatment selections using risk-benefit profiles based on data from comparative randomized clinical trials with multiple endpoints. Biostatistics 16:60-72

Showing the most recent 10 out of 149 publications