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: Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.
RESULTS: 5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.
CONCLUSION: Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips.
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.
Objectives: The aim of this study was to analyze the TTI and outcomes of ART among MMT clients in primary health-care centers in Kuantan, Pahang.
Materials and Methods: This was a retrospective evaluation of MMT clients from 2006 to 2019. The TTI was calculated from the day of MMT enrolment to ART initiation. The trends of CD4 counts and viral loads were descriptively evaluated. Cox proportional hazard model was used to analyze the survival and treatment retention rate.
Results: A total of 67 MMT clients from six primary health-care centers were HIV-positive, of which 37 clients were started on ART. The mean TTI of ART was 27 months. The clients who were given ART had a mean CD4 count of 119 cells/mm3 at baseline and increased to 219 cells/mm3 after 6 months of ART. Only two patients (5.4%) in the ART subgroup had an unsuppressed viral load. The initiation of ART had reduced the risk of death by 72.8% (hazard ratio = 0.27, P = 0.024), and they are 13.1 times more likely to remain in treatment (P < 0.01).
Conclusion: The TTI of ART was delayed in this population. MMT clients who were given ART have better CD4 and viral load outcomes, helped reduced death risk and showed higher retention rates in MMT program.
METHODS: Prospectively collected longitudinal data from patients in Thailand, Hong Kong, Malaysia, Japan, Taiwan, and South Korea were provided for analysis. Covariates included demographics, hepatitis B and C coinfections, baseline CD4 T lymphocyte count, and plasma HIV-1 RNA levels. Clinical deterioration (a new diagnosis of Centers for Disease Control and Prevention category B/AIDS-defining illness or death) was assessed by proportional hazards models. Surrogate endpoints were 12-month change in CD4 cell count and virologic suppression post therapy, evaluated by linear and logistic regression, respectively.
RESULTS: Of 1105 patients, 1036 (93.8%) infected with CRF01_AE or subtype B were eligible for inclusion in clinical deterioration analyses and contributed 1546.7 person-years of follow-up (median: 413 days, interquartile range: 169-672 days). Patients >40 years demonstrated smaller immunological increases (P = 0.002) and higher risk of clinical deterioration (hazard ratio = 2.17; P = 0.008). Patients with baseline CD4 cell counts >200 cells per microliter had lower risk of clinical deterioration (hazard ratio = 0.373; P = 0.003). A total of 532 patients (48.1% of eligible) had CD4 counts available at baseline and 12 months post therapy for inclusion in immunolgic analyses. Patients infected with subtype B had larger increases in CD4 counts at 12 months (P = 0.024). A total of 530 patients (48.0% of eligible) were included in virological analyses with no differences in response found between genotypes.
CONCLUSIONS: Results suggest that patients infected with CRF01_AE have reduced immunologic response to therapy at 12 months, compared with subtype B-infected counterparts. Clinical deterioration was associated with low baseline CD4 counts and older age. The lack of differences in virologic outcomes suggests that all patients have opportunities for virological suppression.
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.
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 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: We used Cox regression to analyze data of a cohort of Asian children.
RESULTS: A total of 2608 children were included; median age at cART was 5.7 years. Time-updated weight for age z score < -3 was associated with mortality (P < 0.001) independent of CD4% and < -2 was associated with immunological failure (P ≤ 0.03) independent of age at cART.
CONCLUSIONS: Weight monitoring provides useful data to inform clinical management of children on cART in resource-limited settings.
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: 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: 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: Patients initiating cART between 2006 and 2013 were included. TI was defined as stopping cART for >1 day. Treatment failure was defined as confirmed virological, immunological or clinical failure. Time to treatment failure during cART was analysed using Cox regression, not including periods off treatment. Covariables with P < 0.10 in univariable analyses were included in multivariable analyses, where P < 0.05 was considered statistically significant.
RESULTS: Of 4549 patients from 13 countries in Asia, 3176 (69.8%) were male and the median age was 34 years. A total of 111 (2.4%) had TIs due to AEs and 135 (3.0%) had TIs for other reasons. Median interruption times were 22 days for AE and 148 days for non-AE TIs. In multivariable analyses, interruptions >30 days were associated with failure (31-180 days HR = 2.66, 95%CI (1.70-4.16); 181-365 days HR = 6.22, 95%CI (3.26-11.86); and >365 days HR = 9.10, 95% CI (4.27-19.38), all P < 0.001, compared to 0-14 days). Reasons for previous TI were not statistically significant (P = 0.158).
CONCLUSIONS: Duration of interruptions of more than 30 days was the key factor associated with large increases in subsequent risk of treatment failure. If TI is unavoidable, its duration should be minimised to reduce the risk of failure after treatment resumption.