METHODS: We used data from the AIDS Care Cohort to Evaluate Exposure to Survival Services (ACCESS) study, a long-running study of a community-recruited cohort of HIV-positive PWUD, linked to comprehensive HIV clinical records in Vancouver, Canada, a setting of no-cost, universal access to HIV care. The longitudinal relationship between MMT-ART dispensation at the same facility and the odds of ≥ 95% ART adherence was analysed using multivariable generalized linear mixed-effects modelling. We conducted a further analysis using a marginal structural mode with inverse probability of treatment weights as a sensitivity analysis.
RESULTS: This study included data on 1690 interviews of 345 ART- and MMT-exposed participants carried out between June 2012 and December 2017. In the final multivariable model, MMT-ART dispensation, compared with nondispensation at the same facility, was associated with greater odds of achieving ≥ 95% adherence [adjusted odds ratio (AOR) 1.56; 95% confidence interval (CI) 1.26-1.96]. A marginal structural model estimated a 1.48 (95% CI 1.15-1.80) greater odds of ≥ 95% adherence among participants who reported MMT-ART dispensation at the same facility compared with those who did not.
CONCLUSIONS: The odds of achieving optimal adherence to ART were 56% higher during periods in which MMT and ART medications were dispensed at the same facility, in a low-barrier setting. Our findings highlight the need to consider a simpler integrated approach with medication dispensation at the same facility in low-threshold settings.
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: HIV+ patients from the Australian HIV Observational Database (AHOD) and the TREAT Asia HIV Observational Database (TAHOD) meeting specific criteria were included. In these analyses Asian and Caucasian status were defined by cohort. Factors associated with a low CD4:CD8 ratio (cutoff <0.2) prior to ART commencement, and with achieving a normal CD4:CD8 ratio (>1) at 12 and 24 months post ART commencement were assessed using logistic regression.
RESULTS: There were 591 patients from AHOD and 2,620 patients from TAHOD who met the inclusion criteria. TAHOD patients had a significantly (P<0.001) lower odds of having a baseline (prior to ART initiation) CD4:CD8 ratio greater than 0.2. After 12 months of ART, AHOD patients were more than twice as likely to achieve a normal CD4:CD8 ratio compared to TAHOD patients (15% versus 6%). However, after adjustment for confounding factors there was no significant difference between cohorts in the odds of achieving a CD4:CD8 ratio >1 (P=0.475).
CONCLUSIONS: We found a significantly lower CD4:CD8 ratio prior to commencing ART in TAHOD compared to AHOD even after adjusting for confounders. However, after adjustment, there was no significant difference between the cohorts in odds of achieving normal ratio. Baseline CD4+ and CD8+ counts seem to be the main driver for this difference between these two populations.
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: 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: 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.
DESIGN: We analyzed data from a community-recruited prospective cohort in Vancouver, Canada (n = 623), from 2014 to 2017.
METHODS: We used multivariable generalized mixed-effects analyses to estimate longitudinal factors associated with mean material security score. We then estimated the association between achieving at least 95% adherence to ART and overall mean material score, as well as mean score for three factors derived from a factor analysis. The three-factor structure, employed in the current analyses, were factor 1 (basic needs); factor 2 (housing-related variables) and factor 3 (economic resources).
RESULTS: Recent incarceration [β-coefficient (β) = -0.176, 95% confidence interval (95% CI): -0.288 to -0.063], unmet health needs [β = -0.110, 95% CI: -0.178 to -0.042), unmet social service needs (β = -0.264, 95% CI: -0.336 to -0.193) and having access to social services (β= -0.102, 95% CI: -0.1586 to -0.0465) were among the factors associated with lower material security scores. Contrary to expectations that low levels of material security in this population would lead to poor ART adherence, we did not observe a significant relationship between adherence and overall material security score, or for each factor individually.
CONCLUSION: Our findings highlight the potentially important role of no-cost, universal access to HIV prevention and treatment, in mitigating the impact of socioeconomic disadvantage on ART adherence.
METHODS: Ninety-four HIV-infected patients were recruited to the study; a longitudinal cohort of patients recruited just prior to commencing cART and followed up for 48 weeks (n = 27), and a cross-sectional cohort (n = 67) consisting of patients with sIR (CD4 T-cell count < 350 cells/μL) and oIR (CD4 T-cell count > 500 cells/μL) after a minimum of 2 years on cART. Controls (n = 29) consisted of HIV-negative individuals. IFN-γ ELISPOT responses against HPV16 and HPV52 E6 were correlated to clinical characteristics, anal and oral HPV carriage, T-cell maturational subsets, markers of activation, senescence and T-regulatory cells.
RESULTS: HPV16 and HPV52 E6-specific T-cell responses were detected in only one of 27 patients (3.7%) during the initial phase of immune recovery. After at least 2 years of cART, those who achieved oIR had significantly higher E6-specific responses (9 of 34; 26.5%) compared with those with sIR (2 of 32; 6.3%) (P = 0.029). Apart from higher CD4 T-cell counts and lower CD4 T-cell activation, no other immunological correlates were associated with the detection of HPV16 and HPV52 E6-specific responses.
CONCLUSIONS: HPV16 and HPV52 E6-specific IFN-γ T-cell responses, a correlate of protective immunity, were detected more frequently among HIV-infected patients who achieved optimal immune recovery on cART (26.5%) compared with those with suboptimal recovery (6.3%).
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.