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: 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.
DESIGN: A collaboration of 12 prospective cohort studies from Europe and the United States (the HIV-CAUSAL Collaboration) that includes 62 760 HIV-infected, therapy-naive individuals followed for an average of 3.3 years. Inverse probability weighting of marginal structural models was used to adjust for measured confounding by indication.
RESULTS: Two thousand and thirty-nine individuals died during the follow-up. The mortality hazard ratio was 0.48 (95% confidence interval 0.41-0.57) for cART initiation versus no initiation. In analyses stratified by CD4 cell count at baseline, the corresponding hazard ratios were 0.29 (0.22-0.37) for less than 100 cells/microl, 0.33 (0.25-0.44) for 100 to less than 200 cells/microl, 0.38 (0.28-0.52) for 200 to less than 350 cells/microl, 0.55 (0.41-0.74) for 350 to less than 500 cells/microl, and 0.77 (0.58-1.01) for 500 cells/microl or more. The estimated hazard ratio varied with years since initiation of cART from 0.57 (0.49-0.67) for less than 1 year since initiation to 0.21 (0.14-0.31) for 5 years or more (P value for trend <0.001).
CONCLUSION: We estimated that cART halved the average mortality rate in HIV-infected individuals. The mortality reduction was greater in those with worse prognosis at the start of follow-up.
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.