METHODS: Data collected 2001 to 2016 from PHIVA 10-19 years of age within a regional Asian cohort were analyzed using competing risk time-to-event and Poisson regression analyses to describe the nature and incidence of morbidity events and hospitalizations and identify factors associated with disease-related, treatment-related and overall morbidity. Morbidity was defined according to World Health Organization clinical staging criteria and U.S. National Institutes of Health Division of AIDS criteria.
RESULTS: A total 3,448 PHIVA contributed 17,778 person-years. Median age at HIV diagnosis was 5.5 years, and ART initiation was 6.9 years. There were 2,562 morbidity events and 307 hospitalizations. Cumulative incidence for any morbidity was 51.7%, and hospitalization was 10.0%. Early adolescence was dominated by disease-related infectious morbidity, with a trend toward noninfectious and treatment-related morbidity in later adolescence. Higher overall morbidity rates were associated with a CD4 count <350 cells/µL, HIV viral load ≥10,000 copies/mL and experiencing prior morbidity at age <10 years. Lower overall morbidity rates were found for those 15-19 years of age compared with 10-14 years and those who initiated ART at age 5-9 years compared with <5 or ≥10 years.
CONCLUSIONS: Half of our PHIVA cohort experienced a morbidity event, with a trend from disease-related infectious events to treatment-related and noninfectious events as PHIVA age. ART initiation to prevent immune system damage, optimize virologic control and minimize childhood morbidity are key to limiting adolescent morbidity.
DESIGN: Ongoing observational database collating clinical data on HIV-infected children and adolescents in Asia.
METHODS: Data from 2001 to 2016 relating to adolescents (10-19 years) with perinatal HIV infection were analysed to describe characteristics at adolescent entry and transition and combination antiretroviral therapy (cART) regimens across adolescence. A competing risk regression analysis was used to determine characteristics at adolescent entry associated with mortality. Outcomes at transition were compared on the basis of age at cART initiation.
RESULTS: Of 3448 PHIVA, 644 had reached transition. Median age at HIV diagnosis was 5.5 years, cART initiation 7.2 years and transition 17.9 years. At adolescent entry, 35.0% had CD4+ cell count less than 500 cells/μl and 51.1% had experienced a WHO stage III/IV clinical event. At transition, 38.9% had CD4+ cell count less than 500 copies/ml, and 53.4% had experienced a WHO stage III/IV clinical event. Mortality rate was 0.71 per 100 person-years, with HIV RNA ≥1000 copies/ml, CD4+ cell count less than 500 cells/μl, height-for-age or weight-for-age z-score less than -2, history of a WHO stage III/IV clinical event or hospitalization and at least second cART associated with mortality. For transitioning PHIVA, those who commenced cART age less than 5 years had better virologic and immunologic outcomes, though were more likely to be on at least second cART.
CONCLUSION: Delayed HIV diagnosis and cART initiation resulted in considerable morbidity and poor immune status by adolescent entry. Durable first-line cART regimens to optimize disease control are key to minimizing mortality. Early cART initiation provides the best virologic and immunologic outcomes at transition.
METHODS: Data (2014-2018) from a regional cohort of Asian PHIVA who received at least 6 months of continuous cART were analyzed. Treatment failure was defined according to World Health Organization criteria. Descriptive analyses were used to report treatment failure and subsequent management and evaluate postfailure CD4 count and viral load trends. Kaplan-Meier survival analyses were used to compare the cumulative incidence of death and loss to follow-up (LTFU) by treatment failure status.
RESULTS: A total 3196 PHIVA were included in the analysis with a median follow-up period of 3.0 years, of whom 230 (7.2%) had experienced 292 treatment failure events (161 virologic, 128 immunologic, 11 clinical) at a rate of 3.78 per 100 person-years. Of the 292 treatment failure events, 31 (10.6%) had a subsequent cART switch within 6 months, which resulted in better immunologic and virologic outcomes compared to those who did not switch cART. The 5-year cumulative incidence of death and LTFU following treatment failure was 18.5% compared to 10.1% without treatment failure.
CONCLUSIONS: Improved implementation of virologic monitoring is required to realize the benefits of virologic determination of cART failure. There is a need to address issues related to accessibility to subsequent cART regimens, poor adherence limiting scope to switch regimens, and the role of antiretroviral resistance testing.
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.
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.