METHODS: Patients testing HBs antigen (Ag) or HCV antibody (Ab) positive within enrollment into TAHOD were considered HBV or HCV co-infected. Factors associated with HBV and/or HCV co-infection were assessed by logistic regression models. Factors associated with post-ART HIV immunological response (CD4 change after six months) and virological response (HIV RNA <400 copies/ml after 12 months) were also determined. Survival was assessed by the Kaplan-Meier method and log rank test.
RESULTS: A total of 7,455 subjects were recruited by December 2012. Of patients tested, 591/5656 (10.4%) were HBsAg positive, 794/5215 (15.2%) were HCVAb positive, and 88/4966 (1.8%) were positive for both markers. In multivariate analysis, HCV co-infection, age, route of HIV infection, baseline CD4 count, baseline HIV RNA, and HIV-1 subtype were associated with immunological recovery. Age, route of HIV infection, baseline CD4 count, baseline HIV RNA, ART regimen, prior ART and HIV-1 subtype, but not HBV or HCV co-infection, affected HIV RNA suppression. Risk factors affecting mortality included HCV co-infection, age, CDC stage, baseline CD4 count, baseline HIV RNA and prior mono/dual ART. Shortest survival was seen in subjects who were both HBV- and HCV-positive.
CONCLUSION: In this Asian cohort of HIV-infected patients, HCV co-infection, but not HBV co-infection, was associated with lower CD4 cell recovery after ART and increased mortality.
METHODS: Data from perinatally HIV-infected, antiretroviral-naïve patients initiated on NNRTI-based ART aged 10-19 years who had ≥6 months of follow-up were analyzed. Competing risk regression was used to assess predictors of NNRTI substitution and clinical failure (World Health Organization Stage 3/4 event or death). Viral suppression was defined as a viral load <400 copies/mL.
RESULTS: Data from 534 adolescents met our inclusion criteria (56.2% female; median age at treatment initiation 11.8 years). After 5 years of treatment, median height-for-age z score increased from -2.3 to -1.6, and median CD4+ cell count increased from 131 to 580 cells/mm(3). The proportion of patients with viral suppression after 6 months was 87.6% and remained >80% up to 5 years of follow-up. NNRTI substitution and clinical failure occurred at rates of 4.9 and 1.4 events per 100 patient-years, respectively. Not using cotrimoxazole prophylaxis at ART initiation was associated with NNRTI substitution (hazard ratio [HR], 1.5 vs. using; 95% confidence interval [CI] = 1.0-2.2; p = .05). Baseline CD4+ count ≤200 cells/mm(3) (HR, 3.3 vs. >200; 95% CI = 1.2-8.9; p = .02) and not using cotrimoxazole prophylaxis at ART initiation (HR, 2.1 vs. using; 95% CI = 1.0-4.6; p = .05) were both associated with clinical failure.
CONCLUSIONS: Despite late ART initiation, adolescents achieved good rates of catch-up growth, CD4+ count recovery, and virological suppression. Earlier ART initiation and routine cotrimoxazole prophylaxis in this population may help to reduce current rates of NNRTI substitution and clinical failure.
OBJECTIVE: To identify the optimal CD4 cell count at which cART should be initiated.
DESIGN: Prospective observational data from the HIV-CAUSAL Collaboration and dynamic marginal structural models were used to compare cART initiation strategies for CD4 thresholds between 0.200 and 0.500 × 10(9) cells/L.
SETTING: HIV clinics in Europe and the Veterans Health Administration system in the United States.
PATIENTS: 20, 971 HIV-infected, therapy-naive persons with baseline CD4 cell counts at or above 0.500 × 10(9) cells/L and no previous AIDS-defining illnesses, of whom 8392 had a CD4 cell count that decreased into the range of 0.200 to 0.499 × 10(9) cells/L and were included in the analysis.
MEASUREMENTS: Hazard ratios and survival proportions for all-cause mortality and a combined end point of AIDS-defining illness or death.
RESULTS: Compared with initiating cART at the CD4 cell count threshold of 0.500 × 10(9) cells/L, the mortality hazard ratio was 1.01 (95% CI, 0.84 to 1.22) for the 0.350 threshold and 1.20 (CI, 0.97 to 1.48) for the 0.200 threshold. The corresponding hazard ratios were 1.38 (CI, 1.23 to 1.56) and 1.90 (CI, 1.67 to 2.15), respectively, for the combined end point of AIDS-defining illness or death.
LIMITATIONS: CD4 cell count at cART initiation was not randomized. Residual confounding may exist.
CONCLUSION: Initiation of cART at a threshold CD4 count of 0.500 × 10(9) cells/L increases AIDS-free survival. However, mortality did not vary substantially with the use of CD4 thresholds between 0.300 and 0.500 × 10(9) cells/L.
METHODS: Adults with HIV, who have been taking ART for more than 3 months were randomly assigned to receive either a pharmacist-led intervention or their usual care. Measures of adherence were collected at 1) baseline 2) just prior to delivery of intervention and 3) 8 weeks later. The primary outcomes were CD4 cell count and self-reported adherence measured with the AIDS Clinical Trial Group (ACTG) questionnaire.
RESULTS: Post-intervention, the intervention group showed a statistically significant increase in CD4 cell counts as compared to the usual care group (p = 0.0054). In addition, adherence improved in the intervention group, with participants being 5.96 times more likely to report having not missed their medication for longer periods of time (p = 0.0086) while participants in the intervention group were 7.74 times more likely to report missing their ART less frequently (p
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: 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.
OBJECTIVE: To evaluate immune-hematological profiles among HIV infected patients compared to HIV/malaria co-infected for ART management improvement.
METHODS: This was a cross sectional study conducted at Infectious Disease Hospital, Kano. A total of 761 consenting adults attending ART clinic were randomly selected and recruited between June and December 2015. Participants' characteristics and clinical details including two previous CD4 counts were collected. Venous blood sample (4ml) was collected in EDTA tube for malaria parasite diagnosis by rapid test and confirmed with microscopy. Hematological profiles were analyzed by Sysmex XP-300 and CD4 count by Cyflow cytometry. Data was analyzed with SPSS 22.0 using Chi-Square test for association between HIV/malaria parasites co-infection with age groups, gender, ART, cotrimoxazole and usage of treated bed nets. Mean hematological profiles by HIV/malaria co-infection and HIV only were compared using independent t-test and mean CD4 count tested by mixed design repeated measures ANOVA. Statistical significant difference at probability of <0.05 was considered for all variables.
RESULTS: Of the 761 HIV infected, 64% were females, with a mean age of ± (SD) 37.30 (10.4) years. Prevalence of HIV/malaria co-infection was 27.7% with Plasmodium falciparum specie accounting for 99.1%. No statistical significant difference was observed between HIV/malaria co-infection in association to age (p = 0.498) and gender (p = 0.789). A significantly (p = 0.026) higher prevalence (35.2%) of co-infection was observed among non-ART patients compared to (26%) ART patients. Prevalence of co-infection was significantly lower (20.0%) among cotrimoxazole users compared to those not on cotrimoxazole (37%). The same significantly lower co-infection prevalence (22.5%) was observed among treated bed net users compared to those not using treated bed nets (42.9%) (p = 0.001). Out of 16 hematology profiles evaluated, six showed significant difference between the two groups (i) packed cell volume (p = <0.001), (ii) mean cell volume (p = 0.005), (iii) mean cell hemoglobin concentration (p = 0.011), (iv) absolute lymphocyte count (p = 0.022), (v) neutrophil percentage count (p = 0.020) and (vi) platelets distribution width (p = <0.001). Current mean CD4 count cell/μl (349±12) was significantly higher in HIV infected only compared to co-infected (306±17), (p = 0.035). A significantly lower mean CD4 count (234.6 ± 6.9) was observed among respondents on ART compared to non-ART (372.5 ± 13.2), p<0.001, mean difference = -137.9).
CONCLUSION: The study revealed a high burden of HIV and malaria co-infection among the studied population. Co-infection was significantly lower among patients who use treated bed nets as well as cotrimoxazole chemotherapy and ART. Six hematological indices differed significantly between the two groups. Malaria and HIV co-infection significantly reduces CD4 count. In general, to achieve better management of all HIV patients in this setting, diagnosing malaria, prompt antiretroviral therapy, monitoring CD4 and some hematology indices on regular basis is critical.
METHODS: HIV-positive patients enrolled in the TREAT Asia HIV Observational Database who had used second-line ART for ≥6 months were included. ART use and rates and predictors of second-line treatment failure were evaluated.
RESULTS: There were 302 eligible patients. Most were male (76.5%) and exposed to HIV via heterosexual contact (71.5%). Median age at second-line initiation was 39.2 years, median CD4 cell count was 146 cells per cubic millimeter, and median HIV viral load was 16,224 copies per milliliter. Patients started second-line ART before 2007 (n = 105), 2007-2010 (n = 147) and after 2010 (n = 50). Ritonavir-boosted lopinavir and atazanavir accounted for the majority of protease inhibitor use after 2006. Median follow-up time on second-line therapy was 2.3 years. The rates of treatment failure and mortality per 100 patient/years were 8.8 (95% confidence interval: 7.1 to 10.9) and 1.1 (95% confidence interval: 0.6 to 1.9), respectively. Older age, high baseline viral load, and use of a protease inhibitor other than lopinavir or atazanavir were associated with a significantly shorter time to second-line failure.
CONCLUSIONS: Increased access to viral load monitoring to facilitate early detection of first-line ART failure and subsequent treatment switch is important for maximizing the durability of second-line therapy in Asia. Although second-line ART is highly effective in the region, the reported rate of failure emphasizes the need for third-line ART in a small portion of patients.
METHODS: The HIV-CAUSAL Collaboration consisted of 12 cohorts from the United States and Europe of HIV-positive, ART-naive, AIDS-free individuals aged ≥18 years with baseline CD4 cell count and HIV RNA levels followed up from 1996 through 2007. We estimated hazard ratios (HRs) for cART versus no cART, adjusted for time-varying CD4 cell count and HIV RNA level via inverse probability weighting.
RESULTS: Of 65 121 individuals, 712 developed tuberculosis over 28 months of median follow-up (incidence, 3.0 cases per 1000 person-years). The HR for tuberculosis for cART versus no cART was 0.56 (95% confidence interval [CI], 0.44-0.72) overall, 1.04 (95% CI, 0.64-1.68) for individuals aged >50 years, and 1.46 (95% CI, 0.70-3.04) for people with a CD4 cell count of <50 cells/μL. Compared with people who had not started cART, HRs differed by time since cART initiation: 1.36 (95% CI, 0.98-1.89) for initiation <3 months ago and 0.44 (95% CI, 0.34-0.58) for initiation ≥3 months ago. Compared with people who had not initiated cART, HRs <3 months after cART initiation were 0.67 (95% CI, 0.38-1.18), 1.51 (95% CI, 0.98-2.31), and 3.20 (95% CI, 1.34-7.60) for people <35, 35-50, and >50 years old, respectively, and 2.30 (95% CI, 1.03-5.14) for people with a CD4 cell count of <50 cells/μL.
CONCLUSIONS: Tuberculosis incidence decreased after cART initiation but not among people >50 years old or with CD4 cell counts of <50 cells/μL. Despite an overall decrease in tuberculosis incidence, the increased rate during 3 months of ART suggests unmasking IRIS.
METHODS: Patients from TREAT Asia HIV Observational Database (September 2015 data transfer) aged 18 years and older with a CD4 count <50 cells/mm at ART initiation were included. The effect of macrolide prophylaxis on HIV-associated mortality or AIDS-defining conditions (as a combined outcome) and HIV-associated mortality alone were evaluated using competing risk regression. Sensitivity analysis was conducted in patients with a CD4 <100 cells/mm at ART initiation.
RESULTS: Of 1345 eligible patients, 10.6% received macrolide prophylaxis. The rate of the combined outcome was 7.35 [95% confidence interval (CI): 6.04 to 8.95] per 100 patient-years, whereas the rate of HIV-associated mortality was 3.14 (95% CI: 2.35 to 4.19) per 100 patient-years. Macrolide use was associated with a significantly decreased risk of HIV-associated mortality (hazard ratio 0.10, 95% CI: 0.01 to 0.80, P = 0.031) but not with the combined outcome (hazard ratio 0.86, 95% CI: 0.32 to 2.229, P = 0.764). Sensitivity analyses showed consistent results among patients with a CD4 <100 cells/mm at ART initiation.
CONCLUSIONS: Macrolide prophylaxis is associated with improved survival among Asian HIV-infected patients with low CD4 cell counts and on ART. This study suggests the increased usage and coverage of macrolide prophylaxis among people living with HIV in Asia.