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Background: Having 90% of patients on antiretroviral therapy (ART) and achieving an undetectable viral load (VL) is 1 of the 90: 90: 90 by 2020 targets. In this global analysis, we investigated the proportions of adult and paediatric patients with VL suppression in the first 3 years after ART initiation. Methods: Patients from the IeDEA cohorts who initiated ART between 2010 and 2014 were included. Proportions with VL suppression (<1000 copies/ mL) were estimated using (1) strict intention to treat (ITT)-loss to follow-up (LTFU) and dead patients counted as having detectable VL; and (2) modified ITT-LTFU and dead patients were excluded. Logistic regression was used to identify predictors of viral suppression at 1 year after ART initiation using modified ITT. Results: A total of 35,561 adults from 38 sites/16 countries and 2601 children from 18 sites/6 countries were included. When comparing strict with modified ITT methods, the proportion achieving VL suppression at 3 years from ART initiation changed from 45.1% to 90.2% in adults, and 60.6% to 80.4% in children. In adults, older age, higher CD4 count preART, and homosexual/bisexual HIV exposure were associated with VL suppression. In children, older age and higher CD4 percentage pre-ART showed significant associations with VL suppression. Conclusions: Large increases in the proportion of VL suppression in adults were observed when we excluded those who were LTFU or had died. The increases were less pronounced in children. Greater emphasis should be made to minimize LTFU and maximize patient retention in HIV-infected patients of all age groups. ; U.S. National Institutes of Health's National Institute of Allergy and Infectious Diseases ; Eunice Kennedy Shriver National Institute of Child Health and Human Development ; National Cancer Institute ; Centers for Disease Control and Prevention, USA ; Agency for Healthcare Research and Quality, USA ; Health Resources and Services Administration, USA ; Canadian Institutes of Health Research, Canada ; Ontario Ministry of Health and Long Term Care ; Government of Alberta, Canada ; Intramural Research Program of the National Cancer Institute ; Australian Government Department of Health and Ageing ; UNSW, Kirby Inst, Sydney, NSW 2052, Australia ; Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA ; Fdn Huesped, Buenos Aires, DF, Argentina ; Univ Chile, Sch Med, Santiago, Chile ; Fdn Arriaran, Santiago, Chile ; Univ Cape Town, Sch Publ Hlth & Family Med, Cape Town, South Africa ; Childrens Hosp 2, Ho Chi Minh City, Vietnam ; Univ Cape Town, Dept Paediat & Child Hlth, Cape Town, South Africa ; Univ Calgary, Calgary, AB, Canada ; YRGCARE Med Ctr, Madras, Tamil Nadu, India ; Univ Fed Sao Paulo, Pediat Infect Dis Div, Escola Paulista Med, Sao Paulo, Brazil ; Johns Hopkins Univ, Dept Med, Div Infect Dis, Baltimore, MD USA ; Univ Stellenbosch, Dept Med, Div Infect Dis, Cape Town, South Africa ; Tygerberg Hosp, Cape Town, South Africa ; Univ Bern, Inst Social & Prevent Med, Bern, Switzerland ; Univ Fed Sao Paulo, Pediat Infect Dis Div, Escola Paulista Med, Sao Paulo, Brazil ; NCI: U01AI035004 ; NCI: U01AI035039 ; NCI: U01AI035040 ; NCI: U01AI035041 ; NCI: U01AI035042 ; NCI: U01AI037613 ; NCI: U01AI037984 ; NCI: U01AI038855 ; NCI: U01AI038858 ; NCI: U01AI042590 ; NCI: U01AI068634 ; NCI: U01AI068636 ; NCI: U01AI069432 ; NCI: U01AI069434 ; Centers for Disease Control and Prevention, USA: CDC-200-2006-18797 ; Centers for Disease Control and Prevention, USA: CDC-200-2015-63931 ; Agency for Healthcare Research and Quality, USA: 90047713 ; Health Resources and Services Administration, USA: 90051652 ; Canadian Institutes of Health Research, Canada: CBR-86906 ; Canadian Institutes of Health Research, Canada: CBR-94036 ; Canadian Institutes of Health Research, Canada: HCP-97105 ; Canadian Institutes of Health Research, Canada: TGF-96118 ; NCI: P30AI027757 ; NCI: P30AI027763 ; NCI: P30AI027767 ; NCI: P30AI036219 ; NCI: P30AI050410 ; NCI: P30AI094189 ; NCI: P30AI110527 ; NCI: P30MH62246 ; NCI: R01AA016893 ; NCI: R01CA165937 ; NCI: R01DA004334 ; NCI: R01DA011602 ; NCI: R01DA012568 ; NCI: R24AI067039 ; NCI: U01AA013566 ; NCI: U01AA020790 ; NCI: U01AI1031834 ; NCI: U01AI034989 ; NCI: U01AI034993 ; NCI: U01AI034994 ; NCI: M01RR000052 ; NCI: U54MD007587 ; NCI: UL1RR024131 ; NCI: UL1TR000004 ; NCI: UL1TR000083 ; NCI: UL1TR000454 ; NCI: UM1AI035043 ; NCI: Z01CP010214 ; NCI: Z01CP010176 ; NCI: U01AI069907 ; NCI: U01AI069923 ; NCI: U01AI069924 ; NCI: U01AI069918 ; NCI: F31DA037788 ; NCI: G12MD007583 ; NCI: K01A1093197 ; NCI: K23EY013707 ; NCI: K24DA000432 ; NCI: K24AI065298 ; NCI: KL2TR000421 ; NCI: N02CP055504 ; NCI: U01AI103390 ; NCI: U01AI103397 ; NCI: U01AI103401 ; NCI: U01AI103408 ; NCI: U01DA036935 ; NCI: U01HD032632 ; NCI: U10EY008057 ; NCI: U10EY008052 ; NCI: U10EY008067 ; NCI: U24AA020794 ; Web of Science

AbstractIntroductionThe clinical relevance of low‐level viraemia (LLV) and virological outcomes among children living with HIV (CLHIV) remains controversial. This study aimed to determine the impact of LLV on virological failure (VF) among Asian CLHIV on first‐line combination antiretroviral therapy (cART).MethodsCLHIV aged <18 years, who were on first‐line cART for ≥12 months, and had virological suppression (two consecutive plasma viral load [pVL] <50 copies/mL) were included. Those who started treatment with mono/dual antiretroviral therapy, had a history of treatment interruption >14 days, or received treatment and care at sites with a pVL lower limit of detection >50 copies/mL were excluded. LLV was defined as a pVL 50 to 1000 copies/mL, and VF as a single pVL >1000 copies/mL. Baseline was the time of the second pVL < 50 copies/mL. Cox proportional hazards models were performed to assess the association between LLV and VF.ResultsFrom January 2008 to September 2016, 508 CLHIV (55% female) were eligible for the study. At baseline, the median age was 9.6 (IQR: 7.0 to 12.3) years, cART duration was 1.4 (IQR: 1.3 to 1.8) years, 97% of CLHIV were on non‐nucleoside reverse transcriptase inhibitor‐based regimens, and the median CD4 was 25% (IQR: 20% to 30%). Over a median follow‐up time of 6.0 (IQR: 3.1 to 8.9) years from baseline, 86 CLHIV (17%) had ever experienced LLV, of whom 32 (37%) had multiple LLV episodes. Female sex, living in Malaysia (compared to Cambodia), having family members other than biological parents/grandparents as a primary caregiver, and baseline CD4 < 25% increased risk of LLV. Overall, 115 children (23%) developed VF, corresponding to a rate of 4.0 (95%CI: 3.4 to 4.9) per 100 person‐years of follow‐up (PYFU). VF was greater among children who had ever experienced LLV compared with those who maintained virological suppression throughout the study period (8.9 vs. 3.3 per 100 PYFU;p < 0.001). In multivariable analyses, ever experiencing LLV was associated with increased risk of subsequent VF (adjusted hazard ratio: 3.01; 95%CI: 1.97 to 4.60).ConclusionsLLV increased the risk of subsequent VF among Asian CLHIV who had previously been suppressed on first‐line cART. Adherence interventions and additional targeted pVL monitoring may be warranted among children with LLV to facilitate early detection of VF.

AbstractIntroductionStunting is a key issue for adolescents with perinatally acquired HIV (APH) that needs to be better understood. As part of the IeDEA multiregional consortium, we described growth evolution during adolescence for APH on antiretroviral therapy (ART).MethodsWe included data from sub‐Saharan Africa, the Asia‐Pacific, and the Caribbean, Central and South America regions collected between 2003 and 2016. Adolescents on ART, reporting perinatally acquired infection or entering HIV care before 10 years of age, with at least one height measurement between 10 and 16 years of age, and followed in care until at least 14 years of age were included. Characteristics at ART initiation and at 10 years of age were compared by sex. Correlates of growth defined by height‐for‐age z‐scores (HAZ) between ages 10 and 19 years were studied separately for males and females, using linear mixed models.ResultsOverall, 8737 APH were included, with 46% from Southern Africa. Median age at ART initiation was 8.1 years (interquartile range (IQR) 6.1 to 9.6), 50% were females, and 41% were stunted (HAZ<−2 SD) at ART initiation. Males and females did not differ by age and stunting at ART initiation, CD4 count over time or retention in care. At 10 years of age, 34% of males were stunted versus 39% of females (p < 0.001). Females had better subsequent growth, resulting in a higher prevalence of stunting for males compared to females by age 15 (48% vs. 25%) and 18 years (31% vs. 15%). In linear mixed models, older age at ART initiation and low CD4 count were associated with poor growth over time (p < 0.001). Those stunted at 10 years of age or at ART initiation had the greatest growth improvement during adolescence.ConclusionsPrevalence of stunting is high among APH worldwide. Substantial sex‐based differences in growth evolution during adolescence were observed in this global cohort, which were not explained by differences in age of access to HIV care, degree of immunosuppression or region. Other factors influencing growth differences in APH, such as differences in pubertal development, should be better documented, to guide further research and inform interventions to optimize growth and health outcomes among APH.

AbstractIntroductionThe third of the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90‐90‐90 targets is to achieve a 90% rate of viral suppression (HIV viral load <1000 HIV‐1 RNA copies/ml) in patients on antiretroviral treatment (ART) by 2020. However, some countries use different thresholds when reporting viral suppression, and there is thus a need for an adjustment to standardize estimates to the <1000 threshold. We aim to propose such an adjustment, to support consistent monitoring of progress towards the "third 90" target.MethodsWe considered three possible distributions for viral loads in ART patients: Weibull, Pareto and reverse Weibull (imposing an upper limit but no lower limit on the log scale). The models were fitted to data on viral load distributions in ART patients in the International epidemiology Databases to Evaluate AIDS (IeDEA) collaboration (representing seven global regions) and the ART Cohort Collaboration (representing Europe), using separate random effects models for adults and children. The models were validated using data from the World Health Organization (WHO) HIV drug resistance report and the Brazilian national ART programme.ResultsModels were calibrated using 921,157 adult and 37,431 paediatric viral load measurements, over 2010–2019. The Pareto and reverse Weibull models provided the best fits to the data, but for all models, the "shape" parameters for the viral load distributions differed significantly between regions. The Weibull model performed best in the validation against the WHO drug resistance survey data, while the Pareto model produced uncertainty ranges that were too narrow, relative to the validation data. Based on these analyses, we recommend using the reverse Weibull model. For example, if a country reports an 80% rate of viral suppression at <200 copies/ml, this model estimates the proportion virally suppressed at <1000 copies/ml is 88.3% (0.800.56), with uncertainty range 85.5–90.6% (0.800.70–0.800.44).ConclusionsEstimates of viral suppression can change substantially depending on the threshold used in defining viral suppression. It is, therefore, important that viral suppression rates are standardized to the same threshold for the purpose of assessing progress towards UNAIDS targets. We have proposed a simple adjustment that allows this, and this has been incorporated into UNAIDS modelling software.

AbstractIntroduction: The number of HIV‐infected children and adolescents requiring second‐line antiretroviral treatment (ART) is increasing in low‐ and middle‐income countries (LMIC). However, the effectiveness of paediatric second‐line ART and potential risk factors for virologic failure are poorly characterized. We performed an aggregate analysis of second‐line ART outcomes for children and assessed the need for paediatric third‐line ART.Methods: We performed a multicentre analysis by systematically reviewing the literature to identify cohorts of children and adolescents receiving second‐line ART in LMIC, contacting the corresponding study groups and including patient‐level data on virologic and clinical outcomes. Kaplan–Meier survival estimates and Cox proportional hazard models were used to describe cumulative rates and predictors of virologic failure. Virologic failure was defined as two consecutive viral load measurements >1000 copies/ml after at least six months of second‐line treatment.Results: We included 12 cohorts representing 928 children on second‐line protease inhibitor (PI)‐based ART in 14 countries in Asia and sub‐Saharan Africa. After 24 months, 16.4% (95% confidence interval (CI): 13.9–19.4) of children experienced virologic failure. Adolescents (10–18 years) had failure rates of 14.5 (95% CI 11.9–17.6) per 100 person‐years compared to 4.5 (95% CI 3.4–5.8) for younger children (3–9 years). Risk factors for virologic failure were adolescence (adjusted hazard ratio [aHR] 3.93, p < 0.001) and short duration of first‐line ART before treatment switch (aHR 0.64 and 0.53, p = 0.008, for 24–48 months and >48 months, respectively, compared to <24 months).Conclusions: In LMIC, paediatric PI‐based second‐line ART was associated with relatively low virologic failure rates. However, adolescents showed exceptionally poor virologic outcomes in LMIC, and optimizing their HIV care requires urgent attention. In addition, 16% of children and adolescents failed PI‐based treatment and will require integrase inhibitors to construct salvage regimens. These drugs are currently not available in LMIC.

AbstractIntroductionWe assessed mortality and losses to follow‐up (LTFU) during adolescence in routine care settings in the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium.MethodsCohorts in the Asia‐Pacific, the Caribbean, Central, and South America, and sub‐Saharan Africa (Central, East, Southern, West) contributed data, and included adolescents living with HIV (ALHIV) enrolled from January 2003 and aged 10 to 19 years (period of adolescence) while under care up to database closure (June 2016). Follow‐up started at age 10 years or the first clinic visit, whichever was later. Entering care at <15 years was a proxy for perinatal infection, while entering care ≥15 years represented infection acquired during adolescence. Competing risk regression was used to assess associations with death and LTFU among those ever receiving triple‐drug antiretroviral therapy (triple‐ART).ResultsOf the 61,242 ALHIV from 270 clinics in 34 countries included in the analysis, 69% (n = 42,138) entered care <15 years of age (53% female), and 31% (n = 19,104) entered care ≥15 years (81% female). During adolescence, 3.9% died, 30% were LTFU and 8.1% were transferred. For those with infection acquired perinatally versus during adolescence, the four‐year cumulative incidences of mortality were 3.9% versus 5.4% and of LTFU were 26% versus 69% respectively (both p < 0.001). Overall, there were higher hazards of death for females (adjusted sub‐hazard ratio (asHR) 1.19, 95% confidence interval (CI) 1.07 to 1.33), and those starting treatment at ≥5 years of age (highest asHR for age ≥15: 8.72, 95% CI 5.85 to 13.02), and in care in mostly urban (asHR 1.40, 95% CI 1.13 to 1.75) and mostly rural settings (asHR 1.39, 95% CI 1.03 to 1.87) compared to urban settings. Overall, higher hazards of LTFU were observed among females (asHR 1.12, 95% CI 1.07 to 1.17), and those starting treatment at age ≥5 years (highest asHR for age ≥15: 11.11, 95% CI 9.86 to 12.53), in care at district hospitals (asHR 1.27, 95% CI 1.18 to 1.37) or in rural settings (asHR 1.21, 95% CI 1.13 to 1.29), and starting triple‐ART after 2006 (highest asHR for 2011 to 2016 1.84, 95% CI 1.71 to 1.99).ConclusionsBoth mortality and LTFU were worse among those entering care at ≥15 years. ALHIV should be evaluated apart from younger children and adults to identify population‐specific reasons for death and LTFU.

AbstractIntroductionThe Joint United Nations Programme on HIV/AIDS (UNAIDS) projections of paediatric HIV prevalence and deaths rely on the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium for mortality estimates among children living with HIV (CHIV) receiving antiretroviral therapy (ART). Previous estimates, based on data through 2014, may no longer be accurate due to expanded paediatric HIV care and treatment eligibility, and the possibility of unreported deaths in CHIV considered lost to follow‐up (LTFU). We therefore estimated all‐cause mortality and its trends in CHIV (<15 years old) on ART using extended and new IeDEA data.MethodsWe analysed (i) IeDEA observational data from CHIV in routine care globally, and (ii) novel data from an IeDEA tracing study that determined outcomes in a sample of CHIV after being LTFU in southern Africa. We included 45,711 CHIV on ART during 2004 to 2017 at 72 programmes in Africa, Asia‐Pacific and Latin America. We used mixed effects Poisson regression to estimate mortality by age, sex, CD4 at ART start, time on ART, region and calendar year. For Africa, in an adjusted analysis that accounts for unreported deaths among those LTFU, we first modified the routine data by simulating mortality outcomes within six months after LTFU, based on a Gompertz survival model fitted to the tracing data (n = 221).ResultsObserved mortality rates were 1.8 (95% CI: 1.7 to 1.9) and 9.4 (6.3 to 13.4) deaths per 100 person‐years in the routine and tracing data, respectively. We found strong evidence of higher mortality at shorter ART durations, lower CD4 values, and in infancy. Averaging over covariate patterns, the adjusted mortality rate was 54% higher than the unadjusted rate. In unadjusted analyses, mortality reduced by an average 60% and 73% from 2005 to 2017, within and outside of Africa, respectively. In the adjusted analysis for Africa, this temporal reduction was 42%.ConclusionsMortality rates among CHIV have decreased substantially over time. However, when accounting for worse outcomes among those LTFU, mortality estimates increased and temporal improvements were slightly reduced, suggesting caution in interpreting analyses based only on programme data. The improved and updated IeDEA estimates on mortality among CHIV on ART support UNAIDS efforts to accurately model global HIV statistics.