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Avihingsanon A, Hughes MD, Salata R, Godfrey C, McCarthy C, Mugyenyi P, Hogg E, Gross R, Cardoso SW, Bukuru A, Makanga M, Badal‐aesen S, Mave V, Ndege BW, Fontain SN, Samaneka W, Secours R, Van Schalkwyk M, Mngqibisa R, Mohapi L, Valencia J, Sugandhavesa P, Montalban E, Munyanga C, Chagomerana M, Santos BR, Kumarasamy N, Kanyama C, Schooley RT, Mellors JW, Wallis CL, Collier AC, Grinsztejn B. Third‐line antiretroviral therapy, including raltegravir (RAL), darunavir (DRV/r) and/or etravirine (ETR), is well tolerated and achieves durable virologic suppression over 144 weeks in resource‐limited settings: ACTG A5288 strategy trial. J Int AIDS Soc 2022; 25:e25905. [PMID: 36039892 PMCID: PMC9332128 DOI: 10.1002/jia2.25905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Accepted: 03/23/2022] [Indexed: 11/22/2022] Open
Abstract
Introduction ACTG A5288 was a strategy trial conducted in diverse populations from multiple continents of people living with HIV (PLWH) failing second‐line protease inhibitor (PI)‐based antiretroviral therapy (ART) from 10 low‐ and middle‐income countries (LMICs). Participants resistant to lopinavir (LPV) and/or multiple nucleotide reverse transcriptase inhibitors started on third‐line regimens that included raltegravir (RAL), darunavir/ritonavir (DRV/r) and/or etravirine (ETR) according to their resistance profiles. At 48 weeks, 87% of these participants achieved HIV‐1 RNA ≤200 copies/ml. We report here long‐term outcomes over 144 weeks. Methods Study participants were enrolled from 2013 to 2015, prior to the availability of dolutegravir in LMICs. “Extended Follow‐up” of the study started after the last participant enrolled had reached 48 weeks and included participants still on antiretroviral (ARV) regimens containing RAL, DRV/r and/or ETR at that time. RAL, DRV/r and ETR were provided for an additional 96 weeks (giving total follow‐up of ≥144 weeks), with HIV‐1 RNA measured at 48 and 96 weeks and CD4 count at 96 weeks after entry into Extended Follow‐up. Proportion of participants with HIV‐1 RNA ≤200 copies/ml was estimated every 24 weeks, using imputation if necessary to handle the different measurement schedule in Extended Follow‐up; mean CD4 count changes were estimated using loess regression. Results and Discussion Of 257 participants (38% females), at study entry, median CD4 count was 179 cells/mm3, and HIV‐1 RNA was 4.6 log10 copies/ml. Median follow‐up was 168 weeks (IQR: 156–204); 15 (6%) participants were lost to follow‐up and 9 (4%) died. 27/246 (11%), 26/246 (11%) and 13/92 (14%) of participants who started RAL, DRV/r and ETR, respectively, discontinued these drugs; only three due to adverse events. 87%, 86%, 83% and 80% of the participants had HIV‐1 RNA ≤200 copies/ml at weeks 48, 96, 144 and 168 (95% CI at week 168: 74–85%), respectively. Mean increase from study entry in CD4 count at week 168 was 265 cells/mm3 (95% CI 247–283). Conclusions Third‐line regimens comprising of RAL, DRV/r and/or ETR were very well tolerated and had high rates of durable virologic suppression among PLWH in LMICs who were failing on second‐line PI‐based ART prior to the availability of dolutegravir.
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Affiliation(s)
- Anchalee Avihingsanon
- HIV‐NAT, Thai Red Cross AIDS Research Centre and Centre of Excellence in Tuberculosis Faculty of Medicine Chulalongkorn University Bangkok Thailand
| | - Michael D. Hughes
- Center for Biostatistics in AIDS Research in the Department of Biostatistics Harvard T H Chan School of Public Health Boston Massachusetts USA
| | | | - Catherine Godfrey
- Division of AIDS National Institutes of Allergy and Infectious Disease National Institutes of Health Bethesda Maryland USA
| | - Caitlyn McCarthy
- Center for Biostatistics in AIDS Research in the Department of Biostatistics Harvard T H Chan School of Public Health Boston Massachusetts USA
| | | | - Evelyn Hogg
- Social & Scientific Systems Inc. a DLH Holdings Company Silver Spring Maryland USA
| | - Robert Gross
- Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia Pennsylvania USA
| | - Sandra W. Cardoso
- Instituto Nacional de Infectologia Evandro Chagas Fundacao Oswaldo Cruz Rio de Janeiro Brazil
| | | | - Mumbi Makanga
- Kenya Medical Research Institute/Center of Disease Control Kisumu Kenya
| | - Sharlaa Badal‐aesen
- Clinical HIV Research Unit Helen Joseph Hospital University of Witwatersrand Johannesburg South Africa
| | - Vidya Mave
- BJ Medical College Clinical Research Site Pune India
| | | | | | - Wadzanai Samaneka
- University of Zimbabwe Clinical Trials Research Centre Harare Zimbabwe
| | - Rode Secours
- Les Centres GHESKIO Clinical Research Site Port‐au‐Prince Haiti
| | - Marije Van Schalkwyk
- Family Centre for Research with Ubuntu (FAMCRU) Stellenbosch University Cape Town South Africa
| | - Rosie Mngqibisa
- Durban International Clinical Research Site, King Edward Hospital, Enhancing Care Foundation Durban South Africa
| | - Lerato Mohapi
- Soweto AIDS Clinical Trials Group Clinical Research Site, Perinatal HIV Research Unit University of the Witwatersrand Johannesburg South Africa
| | | | | | | | - Cornelius Munyanga
- University of North Carolina Project, Kamazu Central Hospital Lilongwe Malawi
| | | | | | | | - Cecilia Kanyama
- University of North Carolina Project, Kamazu Central Hospital Lilongwe Malawi
| | - Robert T. Schooley
- Division of Infectious Diseases University of California San Diego California USA
| | - John W. Mellors
- Division of Infectious Diseases Department of Medicine University of Pittsburgh School of Medicine Pittsburgh Pennsylvania USA
| | - Carole L. Wallis
- BARC‐South Africa and Lancet Laboratories Johannesburg South Africa
| | - Ann C. Collier
- University of Washington School of Medicine University of Washington Seattle Washington USA
| | - Beatriz Grinsztejn
- Instituto Nacional de Infectologia Evandro Chagas Fundacao Oswaldo Cruz Rio de Janeiro Brazil
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Grinsztejn B, Hughes MD, Ritz J, Salata R, Mugyenyi P, Hogg E, Wieclaw L, Gross R, Godfrey C, Cardoso SW, Bukuru A, Makanga M, Faesen S, Mave V, Wangari Ndege B, Nerette Fontain S, Samaneka W, Secours R, van Schalkwyk M, Mngqibisa R, Mohapi L, Valencia J, Sugandhavesa P, Montalban E, Avihingsanon A, Santos BR, Kumarasamy N, Kanyama C, Schooley RT, Mellors JW, Wallis CL, Collier AC. Third-line antiretroviral therapy in low-income and middle-income countries (ACTG A5288): a prospective strategy study. Lancet HIV 2019; 6:e588-e600. [PMID: 31371262 PMCID: PMC6857629 DOI: 10.1016/s2352-3018(19)30146-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 03/22/2019] [Accepted: 04/26/2019] [Indexed: 11/17/2022]
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.
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Affiliation(s)
- Beatriz Grinsztejn
- Instituto Nacional de Infectologia Evandro Chagas, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
| | | | - Justin Ritz
- Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Robert Salata
- Department of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | | | - Evelyn Hogg
- Social & Scientific Systems, Inc, Silver Spring, MD, USA
| | - Linda Wieclaw
- Frontier Science & Technology Research Foundation, Amherst, NY, USA
| | - Robert Gross
- Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
| | - Catherine Godfrey
- Division of AIDS, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Sandra W Cardoso
- Instituto Nacional de Infectologia Evandro Chagas, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | | | - Mumbi Makanga
- Kenya Medical Research Institute, Kisumu, Kenya; Center of Disease Control, Kisumu, Kenya
| | - Sharlaa Faesen
- Wits HIV Clinical Research Site, Johannesburg, South Africa
| | - Vidya Mave
- BJ Medical College Clinical Research Site, Pune, India
| | | | | | - Wadzanai Samaneka
- University of Zimbabwe College of Health Sciences Clinical Trials Research Centre, University of Zimbabwe, Harare, Zimbabwe
| | - Rode Secours
- Les Centres GHESKIO Clinical Research Site, Port-au-Prince, Haiti
| | - Marije van Schalkwyk
- Family Clinical Research Unit Clinical Research Site, Stellenbosch University, Cape Town, South Africa
| | - Rosie Mngqibisa
- Durban Adult HIV Clinical Research Site, Enhancing Care Foundation, Durban, South Africa
| | - Lerato Mohapi
- Soweto AIDS Clinical Trials Group Clinical Research Site, University of the Witwatersrand, Johannesburg, South Africa
| | | | | | | | - Anchalee Avihingsanon
- Thai Red Cross AIDS Research Center Treatment Clinical Research Site, Bangkok, Thailand
| | - Breno R Santos
- Serviço de Infectologia, Hospital Nossa Senhora da Conceicao, Grupo Hospitalar Conceição, Porto Alegre, Brazil
| | | | - Cecilia Kanyama
- University of North Carolina Project, Kamuzu Central Hospital, Lilongwe, Malawi
| | - Robert T Schooley
- Division of Infectious Disease, University of California, San Diego, CA, USA
| | - John W Mellors
- Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Carole L Wallis
- Bio Analytical Research Corporation South Africa, Lancet Laboratories, Johannesburg, South Africa
| | - Ann C Collier
- University of Washington School of Medicine, University of Washington, Seattle, WA, USA
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Ndege BW, Diero LO, Owiti MOG, Anjichi G, Siika AM. PREVALENCE, TREATMENT AND CONTROL OF HYPERTENSION AMONG TYPE 2 DIABETIC PATIENTS AT MOI TEACHING AND REFERRAL HOSPITAL, ELDORET, KENYA. East Afr Med J 2014; 91:253-260. [PMID: 26862649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
OBJECTIVES To describe the prevalence, treatment and control of hypertension among type 2 diabetic patients at Moi Teaching and Referral Hospital (MTRH) and to determine predictors of blood pressure (BP) control. DESIGN A cross-sectional study. SETTING Diabetic Outpatient Clinic at MTRH, Eldoret, Kenya. SUBJECTS Type 2 diabetic patients. INTERVENTIONS The study collected socio-demographic (age, gender, employment status, monthly income, education level, marital status, cigarette smoking and alcohol use), clinical (BP, weight, height and waist circumference) and laboratory (serum fasting lipids and creatinine, urine proteins) data from type 2 diabetic patients. Good BP control was defined as < 130mmHg systolic and < 80mmHg diastolic. Association between BP control and social demographic, clinical and laboratory variables of study subjects was determined using the chi-square, T-test, fisher's exact test and logistic regression. RESULTS We studied 218 type 2 diabetics: mean age 57 ± 9 years; 122 (56%) were females. Average duration of diabetes was 11 ± 7 years. Prevalence of hypertension was 185/218 (85%) out of who 40 (21%) had good BP control. Average duration of hypertension was 7 ± 5 years. Of the 185 hypertensive diabetics: 92 (50%) had total cholesterol at goal; 102 (55%) had low density lipoproteins (LDL) at goal; 74 (40%) had triglycerides at goal; 65 (35%) had high density lipoprotein (HDL) at goal and 85(45%) had Proteinuria. All hypertensive patients had > 1 anti-hypertensive agent prescribed. Good BP control was associated with compliance to anti-hypertensives (OR = 0.342, 95% CI: 0.105- 1.432) and having HDL at goal (OR = 0.247, 95% CI: 0.126-0.845). Poor BP control was associated with a higher number of prescribed anti-hypertensive agents (OR = 1.377, 95% CI: 1.112- 2.302). CONCLUSION Prevalence of hypertension among type 2 diabetic patients in MTRH is high and BP control is poor despite anti-hypertensive treatment. Significant predictors of BP control include compliance to anti-hypertensives and control of HDL.
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