Beatriz Grinsztejn1, Michael D Hughes2, Justin Ritz2, Robert Salata3, Peter Mugyenyi4, Evelyn Hogg5, Linda Wieclaw6, Robert Gross7, Catherine Godfrey8, Sandra W Cardoso9, Aggrey Bukuru4, Mumbi Makanga10, Sharlaa Faesen11, Vidya Mave12, Beatrice Wangari Ndege13, Sandy Nerette Fontain14, Wadzanai Samaneka15, Rode Secours14, Marije van Schalkwyk16, Rosie Mngqibisa17, Lerato Mohapi18, Javier Valencia19, Patcharaphan Sugandhavesa20, Esmelda Montalban21, Anchalee Avihingsanon22, Breno R Santos23, Nagalingeswaran Kumarasamy24, Cecilia Kanyama25, Robert T Schooley26, John W Mellors27, Carole L Wallis28, Ann C Collier29. 1. Instituto Nacional de Infectologia Evandro Chagas, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil. Electronic address: beatriz.grinsztejn@gmail.com. 2. Harvard T H Chan School of Public Health, Boston, MA, USA. 3. Department of Medicine, Case Western Reserve University, Cleveland, OH, USA. 4. Joint Clinical Research Center, Kampala, Uganda. 5. Social & Scientific Systems, Inc, Silver Spring, MD, USA. 6. Frontier Science & Technology Research Foundation, Amherst, NY, USA. 7. Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA. 8. Division of AIDS, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA. 9. Instituto Nacional de Infectologia Evandro Chagas, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil. 10. Kenya Medical Research Institute, Kisumu, Kenya; Center of Disease Control, Kisumu, Kenya. 11. Wits HIV Clinical Research Site, Johannesburg, South Africa. 12. BJ Medical College Clinical Research Site, Pune, India. 13. AMPATH, Moi University Teaching Hospital Eldoret Clinical Research Site, Eldoret, Kenya. 14. Les Centres GHESKIO Clinical Research Site, Port-au-Prince, Haiti. 15. University of Zimbabwe College of Health Sciences Clinical Trials Research Centre, University of Zimbabwe, Harare, Zimbabwe. 16. Family Clinical Research Unit Clinical Research Site, Stellenbosch University, Cape Town, South Africa. 17. Durban Adult HIV Clinical Research Site, Enhancing Care Foundation, Durban, South Africa. 18. Soweto AIDS Clinical Trials Group Clinical Research Site, University of the Witwatersrand, Johannesburg, South Africa. 19. Barranco Clinical Research Site, Lima, Peru. 20. Center for AIDS and STDs, Chiang Mai University, Chiang Mai, Thailand. 21. San Miguel Clinical Research Site, Lima, Peru. 22. Thai Red Cross AIDS Research Center Treatment Clinical Research Site, Bangkok, Thailand. 23. Serviço de Infectologia, Hospital Nossa Senhora da Conceicao, Grupo Hospitalar Conceição, Porto Alegre, Brazil. 24. Chennai Antiviral Research and Treatment Clinical Research Site, Chennai, India. 25. University of North Carolina Project, Kamuzu Central Hospital, Lilongwe, Malawi. 26. Division of Infectious Disease, University of California, San Diego, CA, USA. 27. Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. 28. Bio Analytical Research Corporation South Africa, Lancet Laboratories, Johannesburg, South Africa. 29. University of Washington School of Medicine, University of Washington, Seattle, WA, USA.
Abstract
BACKGROUND: Antiretroviral therapy (ART) management is challenging for individuals in resource-limited settings presenting for third-line treatment because of complex resistance patterns, partly due to reduced access to viral load monitoring. We aimed to evaluate use of newer antiretroviral drugs and contemporary management approaches, including population-based sequencing, to select appropriate antiretrovirals, plasma viral load monitoring, and interventions to improve adherence in individuals presenting with second-line viral failure. METHODS: A5288 was a phase 4, third-line ART strategy study done at 19 urban sites in ten countries that enrolled adult participants with confirmed plasma HIV-1 RNA (viral load) of 1000 copies per mL or more after more than 24 weeks of protease inhibitor-based second-line ART. The primary objective was to use antiretrovirals (raltegravir, etravirine, and ritonavir-boosted darunavir) and diagnostic monitoring technologies, including viral load, genotyping, and adherence support to achieve viral load suppression (defined as ≤200 copies per mL) in 65% or more of participants. ART history and real-time drug resistance genotypes were used to assign participants to one of four cohorts: cohort A (no lopinavir resistance) stayed on second-line ART and cohorts B (B1, best available nucleoside reverse transcriptase inhibitors [NRTIs] plus ritonavir-boosted darunavir plus raltegravir; B2, ritonavir-boosted darunavir plus raltegravir plus etravirine; B3, ritonavir-boosted darunavir, raltegravir, and either tenofovir plus emtricitabine or tenofovir plus lamivudine), C (ritonavir-boosted darunavir plus raltegravir plus tenofovir-emtricitabine or tenofovir plus lamivudine), and D (best available NRTIs plus ritonavir-boosted darunavir plus raltegravir) were defined by increasing levels of resistance and received appropriate regimens, including new antiretrovirals. Participants in Cohort B without detectable hepatitis B surface antigen were assigned by blocked randomisation to cohorts B1 and B2, and those with detectable hepatitis B surface antigen were assigned to cohort B3. The trial is registered with ClinicalTrials.gov, number NCT01641367. FINDINGS: From Jan 10, 2013, to Sept 10, 2015, 545 participants were enrolled. 287 (53%) were assigned to cohort A, 74 (14%) to B1, 72 (13%) to B2, eight (1%) to B3, 70 (13%) to C, and 34 (6%) to D. Overall, 349 (64%, 95% CI 60-68) participants achieved viral suppression at week 48, with proportions varying from 125 (44%) of 287 in cohort A to 65 (88%) of 74 in cohort B1, 63 (88%) of 72 in B2, eight (100%) of eight in B3, 63 (90%) of 70 in C, and 25 (74%) of 34 in D. Participants in cohort A remained on their second-line protease inhibitor, and had the most participants with grade 3 or higher adverse events (147 [51%]). INTERPRETATION: Targeted real-time genotyping to select third-line ART can appropriately allocate more costly antiretrovirals to those with greater levels of HIV drug resistance. FUNDING: National Institutes of Health.
BACKGROUND: Antiretroviral therapy (ART) management is challenging for individuals in resource-limited settings presenting for third-line treatment because of complex resistance patterns, partly due to reduced access to viral load monitoring. We aimed to evaluate use of newer antiretroviral drugs and contemporary management approaches, including population-based sequencing, to select appropriate antiretrovirals, plasma viral load monitoring, and interventions to improve adherence in individuals presenting with second-line viral failure. METHODS:A5288 was a phase 4, third-line ART strategy study done at 19 urban sites in ten countries that enrolled adult participants with confirmed plasma HIV-1 RNA (viral load) of 1000 copies per mL or more after more than 24 weeks of protease inhibitor-based second-line ART. The primary objective was to use antiretrovirals (raltegravir, etravirine, and ritonavir-boosted darunavir) and diagnostic monitoring technologies, including viral load, genotyping, and adherence support to achieve viral load suppression (defined as ≤200 copies per mL) in 65% or more of participants. ART history and real-time drug resistance genotypes were used to assign participants to one of four cohorts: cohort A (no lopinavir resistance) stayed on second-line ART and cohorts B (B1, best available nucleoside reverse transcriptase inhibitors [NRTIs] plus ritonavir-boosted darunavir plus raltegravir; B2, ritonavir-boosted darunavir plus raltegravir plus etravirine; B3, ritonavir-boosted darunavir, raltegravir, and either tenofovir plus emtricitabine or tenofovir plus lamivudine), C (ritonavir-boosted darunavir plus raltegravir plus tenofovir-emtricitabine or tenofovir plus lamivudine), and D (best available NRTIs plus ritonavir-boosted darunavir plus raltegravir) were defined by increasing levels of resistance and received appropriate regimens, including new antiretrovirals. Participants in Cohort B without detectable hepatitis B surface antigen were assigned by blocked randomisation to cohorts B1 and B2, and those with detectable hepatitis B surface antigen were assigned to cohort B3. The trial is registered with ClinicalTrials.gov, number NCT01641367. FINDINGS: From Jan 10, 2013, to Sept 10, 2015, 545 participants were enrolled. 287 (53%) were assigned to cohort A, 74 (14%) to B1, 72 (13%) to B2, eight (1%) to B3, 70 (13%) to C, and 34 (6%) to D. Overall, 349 (64%, 95% CI 60-68) participants achieved viral suppression at week 48, with proportions varying from 125 (44%) of 287 in cohort A to 65 (88%) of 74 in cohort B1, 63 (88%) of 72 in B2, eight (100%) of eight in B3, 63 (90%) of 70 in C, and 25 (74%) of 34 in D. Participants in cohort A remained on their second-line protease inhibitor, and had the most participants with grade 3 or higher adverse events (147 [51%]). INTERPRETATION: Targeted real-time genotyping to select third-line ART can appropriately allocate more costly antiretrovirals to those with greater levels of HIV drug resistance. FUNDING: National Institutes of Health.
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