METHODS: Factors associated with survival and failure were analyzed using Cox proportional hazards and discrete time conditional logistic models.
RESULTS: TDR, found in 60 (4.1%) of 1471 Asian treatment-naive patients, was one of the significant predictors of failure. Patients with TDR to >1 drug in their regimen were >3 times as likely to fail compared to no TDR.
CONCLUSIONS: TDR was associated with failure in the context of non-fully sensitive regimens. Efforts are needed to incorporate resistance testing into national treatment programs.
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: The study population consisted of HIV-infected patients enrolled in the TREAT Asia HIV Observational Database (TAHOD). Individuals were included in this analysis if they started combination antiretroviral treatment (cART) after 2002, were being treated at a centre that documented a median rate of viral load monitoring ≥0.8 tests/patient/year among TAHOD enrolees, and experienced a minor or major treatment substitution while on virally suppressive cART. The primary endpoint to evaluate outcomes was clinical or virological failure (VF), followed by an ART class change. Clinical failure was defined as death or an AIDS diagnosis. VF was defined as confirmed viral load measurements ≥400 copies/mL followed by an ART class change within six months. Minor regimen substitutions were defined as within-class changes and major regimen substitutions were defined as changes to a drug class. The patterns of substitutions and rate of clinical or VF after substitutions were analyzed.
RESULTS: Of 3994 adults who started ART after 2002, 3119 (78.1%) had at least one period of virological suppression. Among these, 1170 (37.5%) underwent a minor regimen substitution, and 296 (9.5%) underwent a major regimen substitution during suppression. The rates of clinical or VF were 1.48/100 person years (95% CI 1.14 to 1.91) in the minor substitution group, 2.85/100 person years (95% CI 1.88 to 4.33) in the major substitution group and 2.53/100 person years (95% CI 2.20 to 2.92) among patients that did not undergo a treatment substitution.
CONCLUSIONS: The rate of clinical or VF was low in both major and minor substitution groups, showing that regimen substitution is generally effective in non-clinical trial settings in Asian countries.
METHODS: Patient data from 2003-2017 were obtained from the Therapeutics, Research, Education and AIDS Training in Asia (TREAT Asia) HIV Observational Database (TAHOD). We included patients on antiretroviral therapy (ART) with > 1 day of follow-up. Cumulative incidences were plotted for CVD-related, AIDS-related, non-AIDS-related, and unknown CODs, and any CVD (i.e. fatal and nonfatal). Competing risk regression was used to assess risk factors of any CVD.
RESULTS: Of 8069 patients with a median follow-up of 7.3 years [interquartile range (IQR) 4.4-10.7 years], 378 patients died [incidence rate (IR) 6.2 per 1000 person-years (PY)], and this total included 22 CVD-related deaths (IR 0.36 per 1000 PY). Factors significantly associated with any CVD event (IR 2.2 per 1000 PY) were older age [sub-hazard ratio (sHR) 2.21; 95% confidence interval (CI) 1.36-3.58 for age 41-50 years; sHR 5.52; 95% CI 3.43-8.91 for ≥ 51 years, compared with < 40 years], high blood pressure (sHR 1.62; 95% CI 1.04-2.52), high total cholesterol (sHR 1.89; 95% CI 1.27-2.82), high triglycerides (sHR 1.55; 95% CI 1.02-2.37) and high body mass index (BMI) (sHR 1.66; 95% CI 1.12-2.46). CVD crude IRs were lower in the later ART initiation period and in lower middle- and upper middle-income countries.
CONCLUSIONS: The development of fatal and nonfatal CVD events in our cohort was associated with older age, and treatable risk factors such as high blood pressure, triglycerides, total cholesterol and BMI. Lower CVD event rates in middle-income countries may indicate under-diagnosis of CVD in Asian-Pacific resource-limited settings.
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: Logistic regression analysis was used to distinguish associated current smoking characteristics. Five-year predictive risks of CVD, CHD and MI and the impact of simulated interventions were calculated utilizing the Data Collection on Adverse Effects of Anti-HIV Drugs Study (D:A:D) algorithm.
RESULTS: Smoking status data were collected from 4274 participants and 1496 of these had sufficient data for simulated intervention calculations. Current smoking prevalence in these two groups was similar (23.2% vs. 19.9%, respectively). Characteristics associated with current smoking included age > 50 years compared with 30-39 years [odds ratio (OR) 0.65; 95% confidence interval (CI) 0.51-0.83], HIV exposure through injecting drug use compared with heterosexual exposure (OR 3.03; 95% CI 2.25-4.07), and receiving antiretroviral therapy (ART) at study sites in Singapore, South Korea, Malaysia, Japan and Vietnam in comparison to Thailand (all OR > 2). Women were less likely to smoke than men (OR 0.11; 95% CI 0.08-0.14). In simulated interventions, smoking cessation demonstrated the greatest impact in reducing CVD and CHD risk and closely approximated the impact of switching from abacavir to an alternate antiretroviral in the reduction of 5-year MI risk.
CONCLUSIONS: Multiple interventions could reduce CVD, CHD and MI risk in Asian HIV-positive patients, with smoking cessation potentially being the most influential.
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: 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: 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.
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.
METHODS: Analyses were based on patients recruited to the TREAT Asia HIV Observational Database (TAHOD), consisting of 21 sites in 12 countries. Patients on triple antiretroviral therapy (ART) were included if they were alive, without previous CVD, and had data on CVD risk factors. Annual new CVD events for 2019-2028 were estimated with the D:A:D equation, accounting for age- and sex-adjusted mortality. Modelled intervention scenarios were treatment of high total cholesterol, low high-density lipoprotein cholesterol (HDL) or high blood pressure, abacavir or lopinavir substitution, and smoking cessation.
RESULTS: Of 3,703 included patients, 69% were male, median age was 46 (IQR 40-53) years and median time since ART initiation was 9.8 years (IQR 7.5-14.1). Cohort incidence rates of CVD were projected to increase from 730 per 100,000 person-years (pys) in 2019 to 1,432 per 100,000 pys in 2028. In the modelled intervention scenarios, most events can be avoided by smoking cessation, abacavir substitution, lopinavir substitution, decreasing total cholesterol, treating high blood pressure and increasing HDL.
CONCLUSIONS: Our projections suggest a doubling of CVD incidence rates in Asian HIV-positive adults in our cohort. An increase in CVD can be expected in any ageing population, however, according to our models, this can be close to averted by interventions. Thus, there is an urgent need for risk screening and integration of HIV and CVD programmes to reduce the future CVD burden.
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: 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 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.