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: Adults > 18 years of age on second-line ART for ≥ 6 months were eligible. Cross-sectional data on HIV viral load (VL) and genotypic resistance testing were collected or testing was conducted between July 2015 and May 2017 at 12 Asia-Pacific sites. Virological failure (VF) was defined as VL > 1000 copies/mL with a second VL > 1000 copies/mL within 3-6 months. FASTA files were submitted to Stanford University HIV Drug Resistance Database and RAMs were compared against the IAS-USA 2019 mutations list. VF risk factors were analysed using logistic regression.
RESULTS: Of 1378 patients, 74% were male and 70% acquired HIV through heterosexual exposure. At second-line switch, median [interquartile range (IQR)] age was 37 (32-42) years and median (IQR) CD4 count was 103 (43.5-229.5) cells/µL; 93% received regimens with boosted protease inhibitors (PIs). Median duration on second line was 3 years. Among 101 patients (7%) with VF, CD4 count > 200 cells/µL at switch [odds ratio (OR) = 0.36, 95% confidence interval (CI): 0.17-0.77 vs. CD4 ≤ 50) and HIV exposure through male-male sex (OR = 0.32, 95% CI: 0.17-0.64 vs. heterosexual) or injecting drug use (OR = 0.24, 95% CI: 0.12-0.49) were associated with reduced VF. Of 41 (41%) patients with resistance data, 80% had at least one RAM to nonnucleoside reverse transcriptase inhibitors (NNRTIs), 63% to NRTIs, and 35% to PIs. Of those with PI RAMs, 71% had two or more.
CONCLUSIONS: There were low proportions with VF and significant RAMs in our cohort, reflecting the durability of current second-line regimens.
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: 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: 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: 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: Perinatally HIV-infected Asian adolescents (10-19 years) with documented virologic suppression (two consecutive viral loads [VLs] <400 copies/mL ≥6 months apart) were included. Baseline was the date of the first VL <400 copies/mL at age ≥10 years or the 10th birthday for those with prior suppression. Cox proportional hazards models were used to identify predictors of postsuppression VR (VL >1,000 copies/mL).
RESULTS: Of 1,379 eligible adolescents, 47% were males. At baseline, 22% were receiving protease inhibitor-containing regimens; median CD4 cell count (interquartile range [IQR]) was 685 (448-937) cells/mm3; 2% had preadolescent virologic failure (VF) before subsequent suppression. During adolescence, 180 individuals (13%) experienced postsuppression VR at a rate of 3.4 (95% confidence interval: 2.9-3.9) per 100 person-years, which was consistent over time. Median time to VR during adolescence (IQR) was 3.3 (2.1-4.8) years. Wasting (weight-for-age z-score
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.
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
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: 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: PLHIV enrolled in the Therapeutics, Research, Education and AIDS Training in Asia (TREAT Asia) HIV Observational Database (TAHOD) who initiated ART with a CD4 count 1 year were censored at 12 months. Competing risk regression was used to analyse risk factors with loss to follow-up as a competing risk.
RESULTS: A total of 1813 PLHIV were included in the study, of whom 74% were male. With 73 (4%) deaths, the overall first-year mortality rate was 4.27 per 100 person-years (PY). Thirty-eight deaths (52%) were AIDS-related, 10 (14%) were immune reconstituted inflammatory syndrome (IRIS)-related, 13 (18%) were non-AIDS-related and 12 (16%) had an unknown cause. Risk factors included having a body mass index (BMI) 100 cells/μL: SHR 0.12; 95% CI 0.05-0.26) was associated with reduced hazard for mortality compared to CD4 count ≤ 25 cells/μL.
CONCLUSIONS: Fifty-two per cent of early deaths were AIDS-related. Efforts to initiate ART at CD4 counts > 50 cell/μL are associated with improved short-term survival rates, even in those with late stages of HIV disease.
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: 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.