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: 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: 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: 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: We investigated serum creatinine (S-Cr) monitoring rates before and during ART and the incidence and prevalence of renal dysfunction after starting TDF by using data from a regional cohort of HIV-infected individuals in the Asia-Pacific. Time to renal dysfunction was defined as time from TDF initiation to the decline in estimated glomerular filtration rate (eGFR) to <60 ml/min/1.73m2 with >30% reduction from baseline using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation or the decision to stop TDF for reported TDF-nephrotoxicity. Predictors of S-Cr monitoring rates were assessed by Poisson regression and risk factors for developing renal dysfunction were assessed by Cox regression.
RESULTS: Among 2,425 patients who received TDF, S-Cr monitoring rates increased from 1.01 to 1.84 per person per year after starting TDF (incidence rate ratio 1.68, 95%CI 1.62-1.74, p <0.001). Renal dysfunction on TDF occurred in 103 patients over 5,368 person-years of TDF use (4.2%; incidence 1.75 per 100 person-years). Risk factors for developing renal dysfunction included older age (>50 vs. ≤30, hazard ratio [HR] 5.39, 95%CI 2.52-11.50, p <0.001; and using PI-based regimen (HR 1.93, 95%CI 1.22-3.07, p = 0.005). Having an eGFR prior to TDF (pre-TDF eGFR) of ≥60 ml/min/1.73m2 showed a protective effect (HR 0.38, 95%CI, 0.17-0.85, p = 0.018).
CONCLUSIONS: Renal dysfunction on commencing TDF use was not common, however, older age, lower baseline eGFR and PI-based ART were associated with higher risk of renal dysfunction during TDF use in adult HIV-infected individuals in the Asia-Pacific region.
METHODS: We used data from the TREAT Asia HIV Observational Database. Patients were included if they started antiretroviral therapy during or after 2003, had a serum creatinine measurement at antiretroviral therapy initiation (baseline), and had at least 2 follow-up creatinine measurements taken ≥3 months apart. Patients with a baseline estimated glomerular filtration rate (eGFR) ≤60 mL/min/1.73 m2 were excluded. Chronic kidney disease was defined as 2 consecutive eGFR values ≤60 mL/min/1.73 m2 taken ≥3 months apart. Generalized estimating equations were used to identify factors associated with eGFR change. Competing risk regression adjusted for study site, age and sex, and cumulative incidence plots were used to evaluate factors associated with chronic kidney disease (CKD).
RESULTS: Of 2547 patients eligible for this analysis, tenofovir was being used by 703 (27.6%) at baseline. Tenofovir use, high baseline eGFR, advanced HIV disease stage, and low nadir CD4 were associated with a decrease in eGFR during follow-up. Chronic kidney disease occurred at a rate of 3.4 per 1000 patient/years. Factors associated with CKD were tenofovir use, old age, low baseline eGFR, low nadir CD4, and protease inhibitor use.
CONCLUSIONS: There is an urgent need to enhance renal monitoring and management capacity among at-risk groups in Asia and improve access to less nephrotoxic antiretrovirals.
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.
METHODS: PLHIV from a regional observational cohort without DM prior to antiretroviral therapy (ART) initiation were included in the analysis. DM was defined as having a fasting blood glucose ≥126 mg/dL, glycated haemoglobin ≥6.5%, a two-hour plasma glucose ≥200 mg/dL, or a random plasma glucose ≥200 mg/dL. A Cox regression model, stratified by site, was used to identify risk factors associated with DM.
RESULTS AND DISCUSSION: Of the 1927 participants included, 127 were diagnosed with DM after ART initiation. Median follow-up time from ART initiation to DM diagnosis was 5.9 years (interquartile range (IQR): 2.8 to 8.9 years). The crude incidence rate of DM was 1.08 per 100 person-years (100 PYS), 95% confidence interval (CI) (0.9 to 1.3). In the multivariate analysis, later years of follow-up (2011 to 2013: HR = 2.34, 95% CI 1.14 to 4.79, p = 0.02; and 2014 to 2017: HR = 7.20, 95% CI 3.27 to 15.87, p 50 years: HR = 4.19, 95% CI 2.12 to 8.28, p 30 kg/m2 (HR = 4.3, 95% CI 1.53 to 12.09, p = 0.006) compared to BMI <18.5 kg/m2 , and high blood pressure (HR = 2.05, 95% CI 1.16 to 3.63, p = 0.013) compared to those without high blood pressure, were associated with developing DM. The hazard was reduced for females (HR = 0.47, 95% CI 0.28 to 0.80, p = 0.006).
CONCLUSIONS: Type 2 DM in HIV-infected Asians was associated with later years of follow-up, high blood pressure, obesity and older age. This highlights the importance of monitoring and routine screening for non-communicable diseases including DM as PLHIV age.
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.