Elizabeth R Brown1, Clara P Dominguez Islas2, Jingyang Zhang3. 1. Fred Hutchinson Cancer Reseasrch Center, 1100 Fairview Avenue North, M2-C200, Seattle, WA, 98109-1024, USA. 2. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. 3. GRAIL, Inc., Menlo Park, CA, USA.
Abstract
OBJECTIVES: Using the MTN-020/ASPIRE HIV prevention trial as a motivating example, our objective is to construct a joint model for the HIV exposure process through vaginal intercourse and the time to HIV infection in a population of sexually active women. By modeling participants' HIV infection in terms of exposures, rather than time exposed, our aim is to obtain a valid estimate of the per-act efficacy of a preventive intervention. METHODS: Within the context of HIV prevention trials, in which the frequency of sex acts is self-reported periodically by the participants, we model the exposure process of the trial participants with a non-homogeneous Poisson process. This approach allows for variability in the rate of sexual contacts between participants as well as variability in the rate of sexual contacts over time. The time to HIV infection for each participant is modeled as the time to the exposure that results in HIV infection, based on the modeled sexual contact rate. We propose an empirical Bayes approach for estimation. RESULTS: We report the results of a simulation study where we evaluate the performance of our proposed approachandcompareittothetraditionalapproachofestimatingtheoverallreductioninHIVincidenceusing a Proportional Hazards Cox model. The proposed approach is also illustrated with data from the MTN-020/ASPIRE trial. CONCLUSIONS: The proposed joint modeling, along with the proposed empirical Bayes estimation approach, can provide valid estimation of the per-exposure efficacy of a preventive intervention.
OBJECTIVES: Using the MTN-020/ASPIRE HIV prevention trial as a motivating example, our objective is to construct a joint model for the HIV exposure process through vaginal intercourse and the time to HIV infection in a population of sexually active women. By modeling participants' HIV infection in terms of exposures, rather than time exposed, our aim is to obtain a valid estimate of the per-act efficacy of a preventive intervention. METHODS: Within the context of HIV prevention trials, in which the frequency of sex acts is self-reported periodically by the participants, we model the exposure process of the trial participants with a non-homogeneous Poisson process. This approach allows for variability in the rate of sexual contacts between participants as well as variability in the rate of sexual contacts over time. The time to HIV infection for each participant is modeled as the time to the exposure that results in HIV infection, based on the modeled sexual contact rate. We propose an empirical Bayes approach for estimation. RESULTS: We report the results of a simulation study where we evaluate the performance of our proposed approachandcompareittothetraditionalapproachofestimatingtheoverallreductioninHIVincidenceusing a Proportional Hazards Cox model. The proposed approach is also illustrated with data from the MTN-020/ASPIRE trial. CONCLUSIONS: The proposed joint modeling, along with the proposed empirical Bayes estimation approach, can provide valid estimation of the per-exposure efficacy of a preventive intervention.
Authors: Jared M Baeten; Thesla Palanee-Phillips; Elizabeth R Brown; Katie Schwartz; Lydia E Soto-Torres; Vaneshree Govender; Nyaradzo M Mgodi; Flavia Matovu Kiweewa; Gonasagrie Nair; Felix Mhlanga; Samantha Siva; Linda-Gail Bekker; Nitesha Jeenarain; Zakir Gaffoor; Francis Martinson; Bonus Makanani; Arendevi Pather; Logashvari Naidoo; Marla Husnik; Barbra A Richardson; Urvi M Parikh; John W Mellors; Mark A Marzinke; Craig W Hendrix; Ariane van der Straten; Gita Ramjee; Zvavahera M Chirenje; Clemensia Nakabiito; Taha E Taha; Judith Jones; Ashley Mayo; Rachel Scheckter; Jennifer Berthiaume; Edward Livant; Cindy Jacobson; Patrick Ndase; Rhonda White; Karen Patterson; Donna Germuga; Beth Galaska; Katherine Bunge; Devika Singh; Daniel W Szydlo; Elizabeth T Montgomery; Barbara S Mensch; Kristine Torjesen; Cynthia I Grossman; Nahida Chakhtoura; Annalene Nel; Zeda Rosenberg; Ian McGowan; Sharon Hillier Journal: N Engl J Med Date: 2016-02-22 Impact factor: 91.245
Authors: Lori L Heise; Charlotte Watts; Anna Foss; James Trussell; Peter Vickerman; Richard Hayes; Sheena McCormack Journal: Contraception Date: 2010-08-07 Impact factor: 3.375