DESIGN: Death-related data were retrospectively and prospectively assessed in a longitudinal regional cohort study.
METHODS: Children under routine HIV care at sites in Cambodia, India, Indonesia, Malaysia, Thailand, and Vietnam between 2008 and 2017 were followed. Causes of death were reported and then independently and centrally reviewed. Predictors were compared using competing risks survival regression analyses.
RESULTS: Among 5918 children, 5523 (93%; 52% male) had ever been on combination antiretroviral therapy. Of 371 (6.3%) deaths, 312 (84%) occurred in those with a history of combination antiretroviral therapy (crude all-cause mortality 9.6 per 1000 person-years; total follow-up time 32 361 person-years). In this group, median age at death was 7.0 (2.9-13) years; median CD4 cell count was 73 (16-325) cells/μl. The most common underlying causes of death were pneumonia due to unspecified pathogens (17%), tuberculosis (16%), sepsis (8.0%), and AIDS (6.7%); 12% of causes were unknown. These clinical diagnoses were further grouped into AIDS-related infections (22%) and noninfections (5.8%), and non-AIDS-related infections (47%) and noninfections (11%); with 12% unknown, 2.2% not reviewed. Higher CD4 cell count and better weight-for-age z-score were protective against death.
CONCLUSION: Our standardized cause of death assessment provides robust data to inform regional resource allocation for pediatric diagnostic evaluations and prioritization of clinical interventions, and highlight the continued importance of opportunistic and nonopportunistic infections as causes of death in our cohort.
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.
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.
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.
METHODS: Children enrolled in the TREAT Asia Pediatric HIV Observational Database were included if they started antiretroviral therapy (ART) on or after January 1st, 2008. Factors associated with severe recurrent bacterial pneumonia were assessed using competing-risk regression.
RESULTS: A total of 3,944 children were included in the analysis; 136 cases of severe recurrent bacterial pneumonia were reported at a rate of 6.5 [95% confidence interval (CI): 5.5-7.7] events per 1,000 patient-years. Clinical factors associated with severe recurrent bacterial pneumonia were younger age [adjusted subdistribution hazard ratio (aHR): 4.4 for <5 years versus ≥10 years, 95% CI: 2.2-8.4, P < 0.001], lower weight-for-age z-score (aHR: 1.5 for -2.0, 95% CI: 1.1-2.3, P = 0.024), pre-ART diagnosis of severe recurrent bacterial pneumonia (aHR: 4.0 versus no pre-ART diagnosis, 95% CI: 2.7-5.8, P < 0.001), past diagnosis of symptomatic lymphoid interstitial pneumonitis or chronic HIV-associated lung disease, including bronchiectasis (aHR: 4.8 versus no past diagnosis, 95% CI: 2.8-8.4, P < 0.001), low CD4% (aHR: 3.5 for <10% versus ≥25%, 95% CI: 1.9-6.4, P < 0.001) and detectable HIV viral load (aHR: 2.6 versus undetectable, 95% CI: 1.2-5.9, P = 0.018).
CONCLUSIONS: Children <10-years-old and those with low weight-for-age, a history of respiratory illness, low CD4% or poorly controlled HIV are likely to gain the greatest benefit from targeted prevention and treatment programs to reduce the burden of bacterial pneumonia in children living with HIV.
METHODS: CLHIV were considered to have lipid or glucose abnormalities if they had total cholesterol ≥200 mg/dL, high-density lipoprotein (HDL) ≤35 mg/dL, low-density lipoprotein (LDL) ≥100 mg/dL, triglycerides (TG) ≥110 mg/dL, or fasting glucose >110 mg/dL. Factors associated with lipid and glucose abnormalities were assessed by logistic regression.
RESULTS: Of 951 CLHIV, 52% were male with a median age of 8.0 (interquartile range [IQR] 5.0-12.0) years at ART start and 15.0 (IQR 12.0-18.0) years at their last clinic visit. 89% acquired HIV perinatally, and 30% had ever used protease inhibitors (PIs). Overall, 225 (24%) had hypercholesterolemia, 105 (27%) low HDL, 213 (58%) high LDL, 369 (54%) hypertriglyceridemia, and 130 (17%) hyperglycemia. Hypercholesterolemia was more likely among females (versus males, aOR 1.93, 95% CI 1.40-2.67). Current PIs use was associated with hypercholesterolemia (current use: aOR 1.54, 95% CI 1.09-2.20); low HDL (current use: aOR 3.16, 95% CI 1.94-5.15; prior use: aOR 10.55, 95% CI 2.53-43.95); hypertriglyceridemia (current use: aOR 3.90, 95% CI 2.65-5.74; prior use: aOR 2.89, 95% CI 1.31-6.39); high LDL (current use: aOR 1.74, 95% CI 1.09-2.76); and hyperglycemia (prior use: aOR 2.43, 95% CI 1.42-4.18).
CONCLUSION: More than half and one-fifth of CLHIV have dyslipidemia and hyperglycemia, respectively. Routine paediatric HIV care should include metabolic monitoring. The association between PIs use and dyslipidemia emphasizes the importance of rapidly transitioning to integrase inhibitor-containing regimens.