METHODS: Participants who were enrolled between January 2003 and March 2019 in a regional Asia HIV cohort with weight and height measurements prior to antiretroviral therapy (ART) initiation were included. Factors associated with mean CD4 increase were analysed using repeated-measures linear regression. Time to first VF after 6 months on ART and time to first development of CVD risk markers were analysed using Cox regression models. Sensitivity analyses were done adjusting for Asian BMI thresholds.
RESULTS: Of 4993 PLHIV (66% male), 62% had pre-treatment BMI in the normal range (18.5-25.0 kg/m2 ), while 26%, 10% and 2% were underweight ( 30 kg/m2 ), respectively. Both higher baseline and time-updated BMI were associated with larger CD4 gains compared with normal BMI. After adjusting for Asian BMI thresholds, higher baseline BMIs of 23-27.5 and > 27.5 kg/m2 were associated with larger CD4 increases of 15.6 cells/µL [95% confidence interval (CI): 2.9-28.3] and 28.8 cells/µL (95% CI: 6.6-50.9), respectively, compared with normal BMI (18.5-23 kg/m2 ). PLHIV with BMIs of 25-30 and > 30 kg/m2 were 1.27 times (95% CI: 1.10-1.47) and 1.61 times (95% CI: 1.13-2.24) more likely to develop CVD risk factors. No relationship between pre-treatment BMI and VF was observed.
CONCLUSIONS: High pre-treatment BMI was associated with better immune reconstitution and CVD risk factor development in an Asian PLHIV cohort.
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: Incidence of malignancy after cohort enrollment was evaluated. Factors associated with development of hematological and nonhematological malignancy were analyzed using competing risk regression and survival time using Kaplan-Meier.
RESULTS: Of 7455 patients, 107 patients (1%) developed a malignancy: 34 (0.5%) hematological [0.08 per 100 person-years (/100PY)] and 73 (1%) nonhematological (0.17/100PY). Of the hematological malignancies, non-Hodgkin lymphoma was predominant (n = 26, 76%): immunoblastic (n = 6, 18%), Burkitt (n = 5, 15%), diffuse large B-cell (n = 5, 15%), and unspecified (n = 10, 30%). Others include central nervous system lymphoma (n = 7, 21%) and myelodysplastic syndrome (n = 1, 3%). Nonhematological malignancies were mostly Kaposi sarcoma (n = 12, 16%) and cervical cancer (n = 10, 14%). Risk factors for hematological malignancy included age >50 vs. ≤30 years [subhazard ratio (SHR) = 6.48, 95% confidence interval (CI): 1.79 to 23.43] and being from a high-income vs. a lower-middle-income country (SHR = 3.97, 95% CI: 1.45 to 10.84). Risk was reduced with CD4 351-500 cells/µL (SHR = 0.20, 95% CI: 0.05 to 0.74) and CD4 >500 cells/µL (SHR = 0.14, 95% CI: 0.04 to 0.78), compared to CD4 ≤200 cells/µL. Similar risk factors were seen for nonhematological malignancy, with prior AIDS diagnosis showing a weak association. Patients diagnosed with a hematological malignancy had shorter survival time compared to patients diagnosed with a nonhematological malignancy.
CONCLUSIONS: Nonhematological malignancies were common but non-Hodgkin lymphoma was more predominant in our cohort. PLHIV from high-income countries were more likely to be diagnosed, indicating a potential underdiagnosis of cancer in low-income settings.
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.
METHODS: Data from two regional cohort observational databases were analyzed for trends in median CD4 cell counts at ART initiation and the proportion of late ART initiation (CD4 cell counts <200 cells/mm(3) or prior AIDS diagnosis). Predictors for late ART initiation and mortality were determined.
RESULTS: A total of 2737 HIV-positive ART-naïve patients from 22 sites in 13 Asian countries and territories were eligible. The overall median (IQR) CD4 cell count at ART initiation was 150 (46-241) cells/mm(3). Median CD4 cell counts at ART initiation increased over time, from a low point of 115 cells/mm(3) in 2008 to a peak of 302 cells/mm(3) after 2011 (p for trend 0.002). The proportion of patients with late ART initiation significantly decreased over time from 79.1% before 2007 to 36.3% after 2011 (p for trend <0.001). Factors associated with late ART initiation were year of ART initiation (e.g. 2010 vs. before 2007; OR 0.40, 95% CI 0.27-0.59; p<0.001), sex (male vs. female; OR 1.51, 95% CI 1.18-1.93; p=0.001) and HIV exposure risk (heterosexual vs. homosexual; OR 1.66, 95% CI 1.24-2.23; p=0.001 and intravenous drug use vs. homosexual; OR 3.03, 95% CI 1.77-5.21; p<0.001). Factors associated with mortality after ART initiation were late ART initiation (HR 2.13, 95% CI 1.19-3.79; p=0.010), sex (male vs. female; HR 2.12, 95% CI 1.31-3.43; p=0.002), age (≥51 vs. ≤30 years; HR 3.91, 95% CI 2.18-7.04; p<0.001) and hepatitis C serostatus (positive vs. negative; HR 2.48, 95% CI 1.-4.36; p=0.035).
CONCLUSIONS: Median CD4 cell count at ART initiation among Asian patients significantly increases over time but the proportion of patients with late ART initiation is still significant. ART initiation at higher CD4 cell counts remains a challenge. Strategic interventions to increase earlier diagnosis of HIV infection and prompt more rapid linkage to ART must be implemented.
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: 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: CLHIV 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
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: A multisite cross-sectional study was conducted in HIV-infected patients currently <25 years old receiving antiretroviral treatment (ART) who had HBV surface antigen (HBsAg), or HBV surface antibody (anti-HBs) or HBV core antibody (anti-HBc) tested during 2012-2013. HBV coinfection was defined as having either a positive HBsAg test or being anti-HBc positive and anti-HBs negative, reflective of past HBV infection. HBV seroprotection was defined as having a positive anti-HBs test.
RESULTS: A total of 3380 patients from 6 countries (Vietnam, Thailand, Cambodia, Malaysia, Indonesia and India) were included. The current median (interquartile range) age was 11.2 (7.8-15.1) years. Of the 2755 patients (81.5%) with HBsAg testing, 130 (4.7%) were positive. Of 1558 (46%) with anti-HBc testing, 77 (4.9%) were positive. Thirteen of 1037 patients with all 3 tests were anti-HBc positive and HBsAg and anti-HBs negative. One child was positive for anti-HBc and negative for anti-HBs but did not have HBsAg tested. The prevalence of HBV coinfection was 144/2759 (5.2%) (95% confidence interval: 4.4-6.1). Of 1093 patients (32%) with anti-HBs testing, 257 (23.5%; confidence interval: 21.0-26.0) had positive tests representing HBV seroprotection.
CONCLUSIONS: The estimated prevalence of HBV coinfection in this cohort of Asian HIV-infected children and adolescents on ART was 5.2%. The majority of children and adolescents tested in this cohort (76.5%) did not have protective HBV antibody. The finding supports HBV screening of HIV-infected children and adolescents to guide revaccination, the use of ART with anti-HBV activity and future monitoring.
METHODS: Children enrolled in the TREAT Asia Pediatric HIV Observational Database who had SM (weight-for-height or body mass index-for-age Z score less than -3) at ART initiation were analyzed. Generalized estimating equations were used to investigate poor weight recovery (weight-for-age Z score less than -3) and poor CD4% recovery (CD4% <25), and competing risk regression was used to analyze mortality and toxicity-associated treatment modification.
RESULTS: Three hundred fifty-five (11.9%) of 2993 children starting ART had SM. Their median weight-for-age Z score increased from -5.6 at ART initiation to -2.3 after 36 months. Not using trimethoprim-sulfamethoxazole prophylaxis at baseline was associated with poor weight recovery [odds ratio: 2.49 vs. using; 95% confidence interval (CI): 1.66-3.74; P < 0.001]. Median CD4% increased from 3.0 at ART initiation to 27.2 after 36 months, and 56 (15.3%) children died during follow-up. More profound SM was associated with poor CD4% recovery (odds ratio: 1.78 for Z score less than -4.5 vs. -3.5 to less than -3.0; 95% CI: 1.08-2.92; P = 0.023) and mortality (hazard ratio: 2.57 for Z score less than -4.5 vs. -3.5 to less than -3.0; 95% CI: 1.24-5.33; P = 0.011). Twenty-two toxicity-associated ART modifications occurred at a rate of 2.4 per 100 patient-years, and rates did not differ by malnutrition severity.
CONCLUSION: Trimethoprim-sulfamethoxazole prophylaxis is important for the recovery of weight-for-age in severely malnourished children starting ART. The extent of SM does not impede weight-for-age recovery or antiretroviral tolerability, but CD4% response is compromised in children with a very low weight-for-height/body mass index-for-age Z score, which may contribute to their high rate of mortality.
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: In a regional HIV observational cohort in the Asia-Pacific region, patients with viral suppression (2 consecutive viral loads <400 copies/mL) and a CD4 count ≥200 cells per microliter who had CD4 testing 6 monthly were analyzed. Main study end points were occurrence of 1 CD4 count <200 cells per microliter (single CD4 <200) and 2 CD4 counts <200 cells per microliter within a 6-month period (confirmed CD4 <200). A comparison of time with single and confirmed CD4 <200 with biannual or annual CD4 assessment was performed by generating a hypothetical group comprising the same patients with annual CD4 testing by removing every second CD4 count.
RESULTS: Among 1538 patients, the rate of single CD4 <200 was 3.45/100 patient-years and of confirmed CD4 <200 was 0.77/100 patient-years. During 5 years of viral suppression, patients with baseline CD4 200-249 cells per microliter were significantly more likely to experience confirmed CD4 <200 compared with patients with higher baseline CD4 [hazard ratio, 55.47 (95% confidence interval: 7.36 to 418.20), P < 0.001 versus baseline CD4 ≥500 cells/μL]. Cumulative probabilities of confirmed CD4 <200 was also higher in patients with baseline CD4 200-249 cells per microliter compared with patients with higher baseline CD4. There was no significant difference in time to confirmed CD4 <200 between biannual and annual CD4 measurement (P = 0.336).
CONCLUSIONS: Annual CD4 monitoring in virally suppressed HIV patients with a baseline CD4 ≥250 cells per microliter may be sufficient for clinical management.
METHODS: We investigated serum creatinine (S-Cr) monitoring rates before and during ART and the incidence and prevalence of renal dysfunction after starting TDF by using data from a regional cohort of HIV-infected individuals in the Asia-Pacific. Time to renal dysfunction was defined as time from TDF initiation to the decline in estimated glomerular filtration rate (eGFR) to <60 ml/min/1.73m2 with >30% reduction from baseline using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation or the decision to stop TDF for reported TDF-nephrotoxicity. Predictors of S-Cr monitoring rates were assessed by Poisson regression and risk factors for developing renal dysfunction were assessed by Cox regression.
RESULTS: Among 2,425 patients who received TDF, S-Cr monitoring rates increased from 1.01 to 1.84 per person per year after starting TDF (incidence rate ratio 1.68, 95%CI 1.62-1.74, p <0.001). Renal dysfunction on TDF occurred in 103 patients over 5,368 person-years of TDF use (4.2%; incidence 1.75 per 100 person-years). Risk factors for developing renal dysfunction included older age (>50 vs. ≤30, hazard ratio [HR] 5.39, 95%CI 2.52-11.50, p <0.001; and using PI-based regimen (HR 1.93, 95%CI 1.22-3.07, p = 0.005). Having an eGFR prior to TDF (pre-TDF eGFR) of ≥60 ml/min/1.73m2 showed a protective effect (HR 0.38, 95%CI, 0.17-0.85, p = 0.018).
CONCLUSIONS: Renal dysfunction on commencing TDF use was not common, however, older age, lower baseline eGFR and PI-based ART were associated with higher risk of renal dysfunction during TDF use in adult HIV-infected individuals in the Asia-Pacific region.