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.
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.
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: 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: 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.
Methods: Sixteen LMIC sites included in the International Epidemiology Databases to Evaluate AIDS - Asia-Pacific network were surveyed.
Results: Sites were mostly (81%) based in urban public referral hospitals. Half had protocols to assess tobacco and alcohol use. Protocols for assessing physical inactivity and obesity were in place at 31% and 38% of sites, respectively. Most sites provided educational material on ASCVD risk factors (between 56% and 75% depending on risk factors). A total of 94% reported performing routine screening for hypertension, 100% for hyperlipidaemia and 88% for diabetes. Routine ASCVD risk assessment was reported by 94% of sites. Protocols for the management of hypertension, hyperlipidaemia, diabetes, high ASCVD risk and chronic ischaemic stroke were in place at 50%, 69%, 56%, 19% and 38% of sites, respectively. Blood pressure monitoring was free for patients at 69% of sites; however, most required patients to pay some or all the costs for other ASCVD-related procedures. Medications available in the clinic or within the same facility included angiotensin-converting enzyme inhibitors (81%), statins (94%) and sulphonylureas (94%).
Conclusion: The consistent availability of clinical screening, diagnostic testing and procedures and the availability of ASCVD medications in the Asian LMIC clinics surveyed are strengths that should be leveraged to improve the implementation of cardiovascular care protocols.
SETTINGS: A validation study among people living with HIV(PLHIV) aged ≥18 years among the cohorts in the Asia-Pacific region.
METHODS: PLHIV with baseline eGFR>60 mL/min/1.73m were included for validation of the D:A:D CKD full version and the short version without cardiovascular risk factors. Those with <3 eGFR measurements from baseline or previous exposure to potentially nephrotoxic antiretrovirals were excluded. Kaplan-Meier methods were used to estimate the probability of CKD development. Area Under the Receiver Operating Characteristics (AUROC) was also used to validate the risk score.
RESULTS: We included 5,701 participants in full model(median 8.1 [IQR 4.8-10.9] years follow-up) and 9,791 in short model validation(median 4.9 [IQR 2.5-7.3] years follow-up). The crude incidence rate of CKD was 8.1 (95%CI 7.3-8.9) per 1,000 person-years(PYS) in the full model cohort and 10.5 (95%CI 9.6-11.4) per 1,000 PYS in the short model cohort. The progression rates for CKD at 10 years in the full model cohort were 2.7%, 8.9% and 26.1% for low-, medium- and high-risk groups, and 3.5%, 11.7% and 32.4% in the short model cohort. The AUROC for the full and short risk score was 0.81 (95%CI 0.79-0.83) and 0.83 (95%CI 0.81-0.85), respectively.
CONCLUSION: The D:A:D CKD full- and short-risk score performed well in predicting CKD events among Asian PLHIV. These risk prediction models may be useful to assist clinicians in identifying individuals at high risk of developing CKD.
METHODS: Participants enrolled in a regional Asian HIV-infected cohort with weight and height measurements at ART initiation were eligible for inclusion in the analysis. Factors associated with weight changes and incident MetS (according to the International Diabetic Federation (IDF) definition) were analysed using linear mixed models and Cox regression, respectively. Competing-risk regression models were used to investigate the association of MetS with all-cause mortality.
RESULTS: Among 4931 people living with HIV (PLWH), 66% were male. At ART initiation, the median age was 34 [interquartile range (IQR) 29-41] years, and the median (IQR) weight and body mass index (BMI) were 55 (48-63) kg and 20.5 (18.4-22.9) kg/m2 , respectively. At 1, 2 and 3 years of ART, overall mean (± standard deviation) weight gain was 2.2 (±5.3), 3.0 (±6.2) and 3.7 (±6.5) kg, respectively. Participants with baseline CD4 count ≤ 200 cells/µL [weight difference (diff) = 2.2 kg; 95% confidence interval (CI) 1.9-2.5 kg] and baseline HIV RNA ≥ 100 000 HIV-1 RNA copies/mL (diff = 0.6 kg; 95% CI 0.2-1.0 kg), and those starting with integrase strand transfer inhibitor (INSTI)-based ART (diff = 2.1 kg; 95% CI 0.7-3.5 kg vs. nonnucleoside reverse transcriptase inhibitors) had greater weight gain. After exclusion of those with abnormal baseline levels of MetS components, 295/3503 had incident MetS [1.18 (95% CI 1.05-1.32)/100 person-years (PY)]. The mortality rate was 0.7 (95% CI 0.6-0.8)/100 PY. MetS was not significantly associated with all-cause mortality in the adjusted model (P = 0.236).
CONCLUSIONS: Weight gain after ART initiation was significantly higher among those initiating ART with lower CD4 count, higher HIV RNA and an INSTI-based regimen after controlling for baseline BMI. Greater efforts to identify and manage MetS among PLWH are needed.
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: Long-term LTFU was defined as LTFU occurring after 5 years on ART. LTFU was defined as (1) patients not seen in the previous 12 months; and (2) patients not seen in the previous 6 months. Factors associated with LTFU were analysed using competing risk regression.
RESULTS: Under the 12-month definition, the LTFU rate was 2.0 per 100 person-years (PY) [95% confidence interval (CI) 1.8-2.2 among 4889 patients included in the study. LTFU was associated with age > 50 years [sub-hazard ratio (SHR) 1.64; 95% CI 1.17-2.31] compared with 31-40 years, viral load ≥ 1000 copies/mL (SHR 1.86; 95% CI 1.16-2.97) compared with viral load < 1000 copies/mL, and hepatitis C coinfection (SHR 1.48; 95% CI 1.06-2.05). LTFU was less likely to occur in females, in individuals with higher CD4 counts, in those with self-reported adherence ≥ 95%, and in those living in high-income countries. The 6-month LTFU definition produced an incidence rate of 3.2 per 100 PY (95% CI 2.9-3.4 and had similar associations but with greater risks of LTFU for ART initiation in later years (2006-2009: SHR 2.38; 95% CI 1.93-2.94; and 2010-2011: SHR 4.26; 95% CI 3.17-5.73) compared with 2003-2005.
CONCLUSIONS: The long-term LTFU rate in our cohort was low, with older age being associated with LTFU. The increased risk of LTFU with later years of ART initiation in the 6-month analysis, but not the 12-month analysis, implies that there was a possible move towards longer HIV clinic scheduling in Asia.
METHODS: Treatment modification was defined as a change of two antiretrovirals, a drug class change or treatment interruption (TI), all for >14 days. We assessed factors associated with CD4 changes and undetectable viral load (UVL <1,000 copies/ml) at 1 year after second-line failure using linear and logistic regression, respectively. Survival time was analysed using competing risk regression.
RESULTS: Of the 328 patients who failed second-line ART in our cohorts, 208 (63%) had a subsequent treatment modification. Compared with those who continued the failing regimen, the average CD4 cell increase was higher in patients who had a modification without TI (difference =77.5, 95% CI 35.3, 119.7) while no difference was observed among those with TI (difference =-5.3, 95% CI -67.3, 56.8). Compared with those who continued the failing regimen, the odds of achieving UVL was lower in patients with TI (OR=0.18, 95% CI 0.06, 0.60) and similar among those who had a modification without TI (OR=1.97, 95% CI 0.95, 4.10), with proportions of UVL 60%, 22% and 75%, respectively. Survival time was not affected by treatment modifications.
CONCLUSIONS: CD4 cell improvements were observed in those who had treatment modification without TI compared with those on the failing regimen. When no other options are available, maintaining the same failing ART combination provided better VL control than interrupting treatment.
METHODS: Treatment modification was defined as a change of two antiretrovirals, a drug class change or treatment interruption (TI), all for >14 days. We assessed factors associated with CD4 changes and undetectable viral load (UVL <1,000 copies/ml) at 1 year after second-line failure using linear and logistic regression, respectively. Survival time was analysed using competing risk regression.
RESULTS: Of the 328 patients who failed second-line ART in our cohorts, 208 (63%) had a subsequent treatment modification. Compared with those who continued the failing regimen, the average CD4 cell increase was higher in patients who had a modification without TI (difference =77.5, 95% CI 35.3, 119.7) while no difference was observed among those with TI (difference =-5.3, 95% CI -67.3, 56.8). Compared with those who continued the failing regimen, the odds of achieving UVL was lower in patients with TI (OR=0.18, 95% CI 0.06, 0.60) and similar among those who had a modification without TI (OR=1.97, 95% CI 0.95, 4.10), with proportions of UVL 60%, 22% and 75%, respectively. Survival time was not affected by treatment modifications.
CONCLUSIONS: CD4 cell improvements were observed in those who had treatment modification without TI compared with those on the failing regimen. When no other options are available, maintaining the same failing ART combination provided better VL control than interrupting treatment.
METHODS: We used data from the TREAT Asia HIV Observational Database. Patients were included if they started antiretroviral therapy during or after 2003, had a serum creatinine measurement at antiretroviral therapy initiation (baseline), and had at least 2 follow-up creatinine measurements taken ≥3 months apart. Patients with a baseline estimated glomerular filtration rate (eGFR) ≤60 mL/min/1.73 m2 were excluded. Chronic kidney disease was defined as 2 consecutive eGFR values ≤60 mL/min/1.73 m2 taken ≥3 months apart. Generalized estimating equations were used to identify factors associated with eGFR change. Competing risk regression adjusted for study site, age and sex, and cumulative incidence plots were used to evaluate factors associated with chronic kidney disease (CKD).
RESULTS: Of 2547 patients eligible for this analysis, tenofovir was being used by 703 (27.6%) at baseline. Tenofovir use, high baseline eGFR, advanced HIV disease stage, and low nadir CD4 were associated with a decrease in eGFR during follow-up. Chronic kidney disease occurred at a rate of 3.4 per 1000 patient/years. Factors associated with CKD were tenofovir use, old age, low baseline eGFR, low nadir CD4, and protease inhibitor use.
CONCLUSIONS: There is an urgent need to enhance renal monitoring and management capacity among at-risk groups in Asia and improve access to less nephrotoxic antiretrovirals.
METHODS: This study included people living with HIV enrolled in a longitudinal cohort study from 2003 to 2019, receiving antiretroviral therapy (ART), and without prior tuberculosis. BMI at ART initiation was categorized using Asian BMI classifications: underweight (<18.5 kg/m2 ), normal (18.5-22.9 kg/m2 ), overweight (23-24.9 kg/m2 ), and obese (≥25 kg/m2 ). High FBG was defined as a single post-ART FBG measurement ≥126 mg/dL. Factors associated with high FBG were analyzed using Cox regression models stratified by site.
RESULTS: A total of 3939 people living with HIV (63% male) were included. In total, 50% had a BMI in the normal weight range, 23% were underweight, 13% were overweight, and 14% were obese. Median age at ART initiation was 34 years (interquartile range 29-41). Overall, 8% had a high FBG, with an incidence rate of 1.14 per 100 person-years. Factors associated with an increased hazard of high FBG included being obese (≥25 kg/m2 ) compared with normal weight (hazard ratio [HR] = 1.79; 95% confidence interval [CI] 1.31-2.44; p 25 kg/m2 were at increased risk of high FBG. This indicates that regular assessments should be performed in those with high BMI, irrespective of the classification used.
METHODS: HIV-infected adults enrolled in the TREAT Asia HIV Observational Database were eligible if they had an HIV RNA measurement documented at the time of ART initiation. The dataset was randomly split into a derivation data set (75% of patients) and a validation data set (25%). Factors associated with pre-treatment HIV RNA <100,000 copies/mL were evaluated by logistic regression adjusted for study site. A prediction model and prediction scores were created.
RESULTS: A total of 2592 patients were enrolled for the analysis. Median [interquartile range (IQR)] age was 35.8 (29.9-42.5) years; CD4 count was 147 (50-248) cells/mm3; and pre-treatment HIV RNA was 100,000 (34,045-301,075) copies/mL. Factors associated with pre-treatment HIV RNA <100,000 copies/mL were age <30 years [OR 1.40 vs. 41-50 years; 95% confidence interval (CI) 1.10-1.80, p = 0.01], body mass index >30 kg/m2(OR 2.4 vs. <18.5 kg/m2; 95% CI 1.1-5.1, p = 0.02), anemia (OR 1.70; 95% CI 1.40-2.10, p 350 cells/mm3(OR 3.9 vs. <100 cells/mm3; 95% CI 2.0-4.1, p 2000 cells/mm3(OR 1.7 vs. <1000 cells/mm3; 95% CI 1.3-2.3, p 25 yielded the sensitivity of 46.7%, specificity of 79.1%, positive predictive value of 67.7%, and negative predictive value of 61.2% for prediction of pre-treatment HIV RNA <100,000 copies/mL among derivation patients.
CONCLUSION: A model prediction for pre-treatment HIV RNA <100,000 copies/mL produced an area under the ROC curve of 0.70. A larger sample size for prediction model development as well as for model validation is warranted.
METHODS: Adults living with HIV enrolled in a regional observational cohort in Asia who had initiated combination antiretroviral therapy (cART) were included in the analysis. Factors associated with new TB diagnoses after cohort entry and survival after cART initiation were analysed using Cox regression, stratified by site.
RESULTS: A total of 7355 patients from 12 countries enrolled into the cohort between 2003 and 2016 were included in the study. There were 368 reported cases of TB after cohort entry with an incidence rate of 0.99 per 100 person-years (/100 pys). Multivariate analyses adjusted for viral load (VL), CD4 count, body mass index (BMI) and cART duration showed that CTX reduced the hazard for new TB infection by 28% (HR 0.72, 95% CI l 0.56, 0.93). Mortality after cART initiation was 0.85/100 pys, with a median follow-up time of 4.63 years. Predictors of survival included age, female sex, hepatitis C co-infection, TB diagnosis, HIV VL, CD4 count and BMI.
CONCLUSIONS: CTX was associated with a reduction in the hazard for new TB infection but did not impact survival in our Asian cohort. The potential preventive effect of CTX against TB during periods of severe immunosuppression should be further explored.