METHODS: Data on children with perinatally acquired HIV aged <18 years on first-line, non-nucleoside reverse transcriptase inhibitor-based cART with viral suppression (two consecutive pVL <400 copies/mL over a six-month period) were included from a regional cohort study; those exposed to prior mono- or dual antiretroviral treatment were excluded. Frequency of pVL monitoring was determined at the site-level based on the median rate of pVL measurement: annual 0.75 to 1.5, and semi-annual >1.5 tests/patient/year. Treatment failure was defined as virologic failure (two consecutive pVL >1000 copies/mL), change of antiretroviral drug class, or death. Baseline was the date of the second consecutive pVL <400 copies/mL. Competing risk regression models were used to identify predictors of treatment failure.
RESULTS: During January 2008 to March 2015, there were 1220 eligible children from 10 sites that performed at least annual pVL monitoring, 1042 (85%) and 178 (15%) were from sites performing annual (n = 6) and semi-annual pVL monitoring (n = 4) respectively. Pre-cART, 675 children (55%) had World Health Organization clinical stage 3 or 4, the median nadir CD4 percentage was 9%, and the median pVL was 5.2 log10 copies/mL. At baseline, the median age was 9.2 years, 64% were on nevirapine-based regimens, the median cART duration was 1.6 years, and the median CD4 percentage was 26%. Over the follow-up period, 258 (25%) CLWH with annual and 40 (23%) with semi-annual pVL monitoring developed treatment failure, corresponding to incidence rates of 5.4 (95% CI: 4.8 to 6.1) and 4.3 (95% CI: 3.1 to 5.8) per 100 patient-years of follow-up respectively (p = 0.27). In multivariable analyses, the frequency of pVL monitoring was not associated with treatment failure (adjusted hazard ratio: 1.12; 95% CI: 0.80 to 1.59).
CONCLUSIONS: Annual compared to semi-annual pVL monitoring was not associated with an increased risk of treatment failure in our cohort of virally suppressed children with perinatally acquired HIV on first-line NNRTI-based cART.
SETTING: An Asian cohort in 16 pediatric HIV services across 6 countries.
METHODS: From 2005 to 2014, patients younger than 20 years who achieved virologic suppression and had subsequent viral load testing were included. Early virologic failure was defined as a HIV RNA ≥1000 copies per milliliter within 12 months of virologic suppression, and late virologic as a HIV RNA ≥1000 copies per milliliter after 12 months following virologic suppression. Characteristics at combination antiretroviral therapy initiation and virologic suppression were described, and a competing risk time-to-event analysis was used to determine cumulative incidence of virologic failure and factors at virologic suppression associated with early and late virologic failure.
RESULTS: Of 1105 included in the analysis, 182 (17.9%) experienced virologic failure. The median age at virologic suppression was 6.9 years, and the median time to virologic failure was 24.6 months after virologic suppression. The incidence rate for a first virologic failure event was 3.3 per 100 person-years. Factors at virologic suppression associated with late virologic failure included older age, mostly rural clinic setting, tuberculosis, protease inhibitor-based regimens, and early virologic failure. No risk factors were identified for early virologic failure.
CONCLUSIONS: Around 1 in 5 experienced virologic failure in our cohort after achieving virologic suppression. Targeted interventions to manage complex treatment scenarios, including adolescents, tuberculosis coinfection, and those with poor virologic control are required.
METHODS: Regional Asian data (2001-2016) were analyzed to describe PHIVA who experienced ≥2 weeks of lamivudine or emtricitabine monotherapy or treatment interruption and trends in CD4 count and HIV viral load during and after episodes. Survival analyses were used for World Health Organization (WHO) stage III/IV clinical and immunologic event-free survival during monotherapy or treatment interruption, and a Poisson regression to determine factors associated with monotherapy or treatment interruption.
RESULTS: Of 3,448 PHIVA, 84 (2.4%) experienced 94 monotherapy episodes, and 147 (4.3%) experienced 174 treatment interruptions. Monotherapy was associated with older age, HIV RNA >400 copies/mL, younger age at ART initiation, and exposure to ≥2 combination ART regimens. Treatment interruption was associated with CD4 count <350 cells/μL, HIV RNA ≥1,000 copies/mL, ART adverse event, and commencing ART age ≥10 years compared with age <3 years. WHO clinical stage III/IV 1-year event-free survival was 96% and 85% for monotherapy and treatment interruption cohorts, respectively. WHO immunologic stage III/IV 1-year event-free survival was 52% for both cohorts. Those who experienced monotherapy or treatment interruption for more than 6 months had worse immunologic and virologic outcomes.
CONCLUSIONS: Until challenges of treatment adherence, engagement in care, and combination ART durability/tolerability are met, monotherapy and treatment interruption will lead to poor long-term outcomes.
METHODS: Individuals enrolled in the Therapeutics Research, Education, and AIDS Training in Asia Pediatric HIV Observational Database were included if they started ART at ages 1 month-14 years and had both height and weight measurements available at ART initiation (baseline). Generalized estimating equations were used to identify factors associated with change in height-for-age z-score (HAZ), follow-up HAZ ≥ -2, change in weight-for-age z-score (WAZ), and follow-up WAZ ≥ -2.
RESULTS: A total of 3217 children were eligible for analysis. The adjusted mean change in HAZ among cotrimoxazole and non-cotrimoxazole users did not differ significantly over the first 24 months of ART. In children who were stunted (HAZ < -2) at baseline, cotrimoxazole use was not associated with a follow-up HAZ ≥ -2. The adjusted mean change in WAZ among children with a baseline CD4 percentage (CD4%) >25% became significantly different between cotrimoxazole and non-cotrimoxazole users after 6 months of ART and remained significant after 24 months (overall P < .01). Similar changes in WAZ were observed in those with a baseline CD4% between 10% and 24% (overall P < .01). Cotrimoxazole use was not associated with a significant difference in follow-up WAZ in children with a baseline CD4% <10%. In those underweight (WAZ < -2) at baseline, cotrimoxazole use was associated with a follow-up WAZ ≥ -2 (adjusted odds ratio, 1.70 vs not using cotrimoxazole [95% confidence interval, 1.28-2.25], P < .01). This association was driven by children with a baseline CD4% ≥10%.
CONCLUSIONS: Cotrimoxazole use is associated with benefits to WAZ but not HAZ during early ART in Asian children.
SETTING: Asian regional cohort incorporating 16 pediatric HIV services across 6 countries.
METHODS: Data from PHIVA (aged 10-19 years) who received combination antiretroviral therapy 2007-2016 were used to analyze LTFU through (1) an International epidemiology Databases to Evaluate AIDS (IeDEA) method that determined LTFU as >90 days late for an estimated next scheduled appointment without returning to care and (2) the absence of patient-level data for >365 days before the last data transfer from clinic sites. Descriptive analyses and competing-risk survival and regression analyses were used to evaluate LTFU epidemiology and associated factors when analyzed using each method.
RESULTS: Of 3509 included PHIVA, 275 (7.8%) met IeDEA and 149 (4.3%) met 365-day absence LTFU criteria. Cumulative incidence of LTFU was 19.9% and 11.8% using IeDEA and 365-day absence criteria, respectively. Risk factors for LTFU across both criteria included the following: age at combination antiretroviral therapy initiation <5 years compared with age ≥5 years, rural clinic settings compared with urban clinic settings, and high viral loads compared with undetectable viral loads. Age 10-14 years compared with age 15-19 years was another risk factor identified using 365-day absence criteria but not IeDEA LTFU criteria.
CONCLUSIONS: Between 12% and 20% of PHIVA were determined LTFU with treatment fatigue and rural treatment settings consistent risk factors. Better tracking of adolescents is required to provide a definitive understanding of LTFU and optimize evidence-based models of care.