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: 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: 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 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: We did a cohort analysis of TB cases in SECOND-LINE. TB cases included any clinical or laboratory-confirmed diagnoses and/or commencement of treatment for TB after randomization. Baseline factors associated with TB were analyzed using Cox regression stratified by site.
RESULTS: TB cases occurred at sites in Argentina, India, Malaysia, Nigeria, South Africa, and Thailand, in a cohort of 355 of the 541 SECOND-LINE participants. Overall, 20 cases of TB occurred, an incidence rate of 3.4 per 100 person-years (95% CI: 2.1 to 5.1). Increased TB risk was associated with a low CD4+-cell count (≤200 cells/μL), high viral load (>200 copies/mL), low platelet count (<150 ×109/L), and low total serum cholesterol (≤4.5 mmol/L) at baseline. An increased risk of death was associated with TB, adjusted for CD4, platelets, and cholesterol. A low CD4+-cell count was significantly associated with incident TB, mortality, other AIDS diagnoses, and virologic failure.
DISCUSSION: The risk of TB remains elevated in PLHIV in the setting of second-line HIV therapy in TB endemic regions. TB was associated with a greater risk of death. Finding that low CD4+ T-cell count was significantly associated with poor outcomes in this population supports the value of CD4+ monitoring in HIV clinical management.
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: 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: 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.
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.
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.