PROVICED. Our long-term goals are to contribute to the fight against HIV/AIDS by developing useful statistical methods for the design, conduct, and analysis of research studies aimed at the prevention of HIV infection, the treatment of personswith HIV, and better understanding the inter-relationship between HIV, the immune system, and therapeutic interventions. During the period of the proposed research, we will focus on the following specific aims: 1. To develop statistical methods for prevention studies, with special emphasis on (1.1) estimating the timing cf perinatal and vertical transmission of HIV based on diagnostic tests with imperfect specificity and time-dependent sensitivity, and (1.2) statistical methods for HIV preventive vaccine trials, especially in assessingvaccine efficacy and viral transmissibility in the presence of several viral subtypes; 2. To develop statistical methods for the analysis and design of structured interruption trials of host immune suppression, including: (2.1) estimation of the subdistribution of time to host immune suppression in the presence of incomplete foSlow-up of subjects in post-treatment evaluation phase, (2.2) methods for assessing the consequences of premature treatment interruption, including the time course of viral rebound, the probability of successful rechallenge, and in subjects who are successfully rechallenged, the distribution of time to host immune suppression, and (2.3) the design of structured interruption trials; 3. To develop statistical methods for analyzing HIV/AIDS data subject to interval and informatively missing observations, including (3.1) methods for assessing a primary response variable whose observation depends on the values of intermediate markers, (3.2) regression methods in the presence of interval-censored covariates, and (3.3) models for defining guidelines for the real-time monitoring of viral load for treatment failure, and methods for identifying factorsthat are associated with viral rebound; and 4. To develop methods for the analysis of Phase I studies, especially methods for designing and analyzing do:;e escalation studies for trials with bivariate outcome measures. PERFORMANCE SITI=(S) (organization, city, state) Harvard School of Public Health KEEY PERSONNEL. See instructions on Page 11. Name Stephen Lagakos Peter Gilbert Wenzheng Huang Michael Hughes Yougan Wang Meredith Goldwasser Use continuation pages as needed to provide the required information Organization Harvard School of Public Health Harvard School of Public Health Harvard School of Public Health Harvard School of Public Health Harvard School of Public Health in the format sihown below. Role on Project Co-Investigator Co-Investigator Co-Investigator Co-Investigator Research Assistant PUS 398 (REV. 4/98) Page 2 BB Number pages consecutively at the bottom throughout the application Do notuse suffixes such as 3a, 3b. Principal Investigated/Program Director (Last, first, middle}. LAGAKOS, STEPHEN. . Type the name of the principal investigator/program director at the top of each printed page and each continuation page. (For type specifications, see Specific Instructions on page 6.) RESEARCH GRANT TABLE OF CONTENTS Page Numbers Face Pago 1 Description,

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Method to Extend Research in Time (MERIT) Award (R37)
Project #
5R37AI024643-19
Application #
7174849
Study Section
Special Emphasis Panel (NSS)
Program Officer
Gezmu, Misrak
Project Start
1987-04-01
Project End
2011-01-31
Budget Start
2007-02-01
Budget End
2008-01-31
Support Year
19
Fiscal Year
2007
Total Cost
$318,488
Indirect Cost
Name
Harvard University
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
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
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
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
Novitsky, Vlad; Wang, Rui; Rossenkhan, Raabya et al. (2013) Intra-host evolutionary rates in HIV-1C env and gag during primary infection. Infect Genet Evol 19:361-8
Tate, Janet P; Justice, Amy C; Hughes, Michael D et al. (2013) An internationally generalizable risk index for mortality after one year of antiretroviral therapy. AIDS 27:563-72
Wang, Rui; Ware, James H (2013) Detecting moderator effects using subgroup analyses. Prev Sci 14:111-20
Novitsky, Vladimir; Bussmann, Hermann; Logan, Andrew et al. (2013) Phylogenetic relatedness of circulating HIV-1C variants in Mochudi, Botswana. PLoS One 8:e80589
Gomez, Guadalupe; Lagakos, Stephen W (2013) Statistical considerations when using a composite endpoint for comparing treatment groups. Stat Med 32:719-38
Noubary, Farzad; Hughes, Michael D (2012) Factors affecting timing of antiretroviral treatment initiation based on monitoring CD4 counts. J Acquir Immune Defic Syndr 61:326-33
Claggett, B; Lagakos, S W; Wang, R (2012) Augmented cross-sectional studies with abbreviated follow-up for estimating HIV incidence. Biometrics 68:62-74

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