James R Moore1,2, Deborah J Donnell1, Marie-Claude Boily2,3, Kate M Mitchell2,3, Sinead Delany-Moretlwe4, Linda-Gail Bekker5, Nyaradzo M Mgodi6, Wafaa El-Sadr7, Myron S Cohen8, Connie L Celum9, Dobromir Dimitrov1,2,10. 1. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA. 2. HPTN Modelling Centre, Imperial College London, London, United Kingdom. 3. Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London United Kingdom. 4. Wits RHI, University of Witswatersrand, Johannesburg, South Africa. 5. Desmond Tutu HIV Foundation, University of Cape Town, Cape Town, South Africa. 6. University of Zimbabwe College of Health Sciences Clinical Trials Research Centre, Harare, Zimbabwe. 7. Mailman School of Public Health Columbia University, New York, NY. 8. Institute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, NC. 9. Global Health, Allergy and Infectious Diseases, University of Washington, Seattle, WA; and. 10. Department of Applied Mathematics, University of Washington, Seattle, WA.
Abstract
BACKGROUND: Pre-exposure prophylaxis (PrEP) with tenofovir disoproxil fumarate and emtricitabine has proven highly effective in preventing HIV acquisition and is therefore offered to all participants in the control group as part of the standard of care package in many new HIV prevention studies. We propose a methodology for predicting HIV incidence in a hypothetical "placebo arm" for open-label studies or clinical trials with active control among African women. We apply the method to an open-label PrEP study, HIV Prevention Trials Network 082, which tested strategies to improve PrEP adherence in young African women all of whom were offered PrEP. METHODS: Our model predicted HIV infection risk for female study cohorts in sub-Saharan Africa using baseline behavioral risk factors and contemporary HIV prevalence and viral suppression in the local male population. The model was calibrated to HIV incidence in the Vaginal and Oral Interventions to Control the Epidemic study. RESULTS: Our model reproduced the annual HIV incidence of 3.2%-4.8% observed over 1 year of follow-up in the placebo groups of 4 completed clinical studies. We predicted an annual HIV incidence of 3.7% (95% confidence interval: 3.2 to 4.2) among HIV Prevention Trials Network 082 participants in the absence of PrEP and other risk reduction interventions. CONCLUSIONS: We demonstrated the potential of the proposed methodology to provide HIV incidence predictions based on assessment of individual risk behaviors and community and time-specific HIV exposure risk using HIV treatment and viral suppression data. These estimates may serve as comparators in HIV prevention trials without a placebo group.
BACKGROUND: Pre-exposure prophylaxis (PrEP) with tenofovir disoproxil fumarate and emtricitabine has proven highly effective in preventing HIV acquisition and is therefore offered to all participants in the control group as part of the standard of care package in many new HIV prevention studies. We propose a methodology for predicting HIV incidence in a hypothetical "placebo arm" for open-label studies or clinical trials with active control among African women. We apply the method to an open-label PrEP study, HIV Prevention Trials Network 082, which tested strategies to improve PrEP adherence in young African women all of whom were offered PrEP. METHODS: Our model predicted HIV infection risk for female study cohorts in sub-Saharan Africa using baseline behavioral risk factors and contemporary HIV prevalence and viral suppression in the local male population. The model was calibrated to HIV incidence in the Vaginal and Oral Interventions to Control the Epidemic study. RESULTS: Our model reproduced the annual HIV incidence of 3.2%-4.8% observed over 1 year of follow-up in the placebo groups of 4 completed clinical studies. We predicted an annual HIV incidence of 3.7% (95% confidence interval: 3.2 to 4.2) among HIV Prevention Trials Network 082 participants in the absence of PrEP and other risk reduction interventions. CONCLUSIONS: We demonstrated the potential of the proposed methodology to provide HIV incidence predictions based on assessment of individual risk behaviors and community and time-specific HIV exposure risk using HIV treatment and viral suppression data. These estimates may serve as comparators in HIV prevention trials without a placebo group.
Authors: Jennifer Velloza; Deborah Donnell; Sybil Hosek; Peter L Anderson; Z Mike Chirenje; Nyaradzo Mgodi; Linda-Gail Bekker; Mark A Marzinke; Sinead Delany-Moretlwe; Connie Celum Journal: Lancet HIV Date: 2022-09-07 Impact factor: 16.070
Authors: Catherine A Koss; Diane V Havlir; James Ayieko; Dalsone Kwarisiima; Jane Kabami; Gabriel Chamie; Mucunguzi Atukunda; Yusuf Mwinike; Florence Mwangwa; Asiphas Owaraganise; James Peng; Winter Olilo; Katherine Snyman; Benard Awuonda; Tamara D Clark; Douglas Black; Joshua Nugent; Lillian B Brown; Carina Marquez; Hideaki Okochi; Kevin Zhang; Carol S Camlin; Vivek Jain; Monica Gandhi; Craig R Cohen; Elizabeth A Bukusi; Edwin D Charlebois; Maya L Petersen; Moses R Kamya; Laura B Balzer Journal: PLoS Med Date: 2021-02-09 Impact factor: 11.069
Authors: Katherine M Jia; Hallie Eilerts; Olanrewaju Edun; Kevin Lam; Adam Howes; Matthew L Thomas; Jeffrey W Eaton Journal: J Int AIDS Soc Date: 2022-01 Impact factor: 5.396