METHODS: We used Cox regression to analyze data of a cohort of Asian children.
RESULTS: A total of 2608 children were included; median age at cART was 5.7 years. Time-updated weight for age z score < -3 was associated with mortality (P < 0.001) independent of CD4% and < -2 was associated with immunological failure (P ≤ 0.03) independent of age at cART.
CONCLUSIONS: Weight monitoring provides useful data to inform clinical management of children on cART in resource-limited settings.
METHODS: Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.
RESULTS: 5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.
CONCLUSION: Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips.
METHODS: A retrospective analysis was performed on 145 HIV-positive Malaysians of Chinese descent from two centers at the University Hospital Kuala Lumpur (UHKL) and the General Hospital Kuala Lumpur (GHKL) from March 1997 to February 1998. Demographic data and clinical data were analyzed.
RESULTS: The analysis showed that 104 out of 145 patients had mucocutaneous disorders (71.7%). In the study, there were 100 men (96.2%) and four women (3.8%). The majority of patients were in the age group 20-50 years. The patients who presented with mucocutaneous disease also had low CD4+ T-lymphocyte counts and most had acquired immunodeficiency syndrome (AIDS) defining illness. The number of cases with generalized hyperpigmentation was very high in the group (35.9%), followed by nodular prurigo (29.7%) and xerosis (27.6%). Seborrheic dermatitis was seen in 20.7% of cases, with psoriasis in 8.3%. The most common infections were oral candidiasis (35.9%), tinea corporis and onychomycosis (9.7%), and herpes infection (5.5%); however, mucocutaneous manifestations of Kaposi's sarcoma were rare.
CONCLUSIONS: The results suggest that mucocutaneous findings are useful clinical predictors of HIV infection or signs of the presence of advanced HIV infection.
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: 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: Treatment modification was defined as a change of two antiretrovirals, a drug class change or treatment interruption (TI), all for >14 days. We assessed factors associated with CD4 changes and undetectable viral load (UVL <1,000 copies/ml) at 1 year after second-line failure using linear and logistic regression, respectively. Survival time was analysed using competing risk regression.
RESULTS: Of the 328 patients who failed second-line ART in our cohorts, 208 (63%) had a subsequent treatment modification. Compared with those who continued the failing regimen, the average CD4 cell increase was higher in patients who had a modification without TI (difference =77.5, 95% CI 35.3, 119.7) while no difference was observed among those with TI (difference =-5.3, 95% CI -67.3, 56.8). Compared with those who continued the failing regimen, the odds of achieving UVL was lower in patients with TI (OR=0.18, 95% CI 0.06, 0.60) and similar among those who had a modification without TI (OR=1.97, 95% CI 0.95, 4.10), with proportions of UVL 60%, 22% and 75%, respectively. Survival time was not affected by treatment modifications.
CONCLUSIONS: CD4 cell improvements were observed in those who had treatment modification without TI compared with those on the failing regimen. When no other options are available, maintaining the same failing ART combination provided better VL control than interrupting treatment.
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 assess the socio-economic determinants of TB in HIV-infected patients in Asia.
DESIGN: This was a matched case-control study. HIV-positive, TB-positive cases were matched to HIV-positive, TB-negative controls according to age, sex and CD4 cell count. A socio-economic questionnaire comprising 23 questions, including education level, employment, housing and substance use, was distributed. Socio-economic risk factors for TB were analysed using conditional logistic regression analysis.
RESULTS: A total of 340 patients (170 matched pairs) were recruited, with 262 (77.1%) matched for all three criteria. Pulmonary TB was the predominant type (n = 115, 67.6%). The main risk factor for TB was not having a university level education (OR 4.45, 95%CI 1.50-13.17, P = 0.007). Burning wood or coal regularly inside the house and living in the same place of origin were weakly associated with TB diagnosis.
CONCLUSIONS: These data suggest that lower socio-economic status is associated with an increased risk of TB in Asia. Integrating clinical and socio-economic factors into HIV treatment may help in the prevention of opportunistic infections and disease progression.
METHODS: Data linkages with the national death registry or national HIV database were conducted in 2020 on all PLHIV who met LTFU criteria while enrolled in care at participating HIV clinical sites. LTFU was defined as having no documented clinical contact in the previous year, excluding transfers and deaths. Survival time was analyzed using the Cox regression, stratified by site.
RESULTS: Data linkages were performed for 489 PLHIV who had been LTFU at sites in Malaysia (n = 2) and Thailand (n = 4). There were 151 (31%) deaths after being LTFU; the mortality rate was 4.89 per 100 person-years. Risk factors for mortality after being LTFU were older age [41-50 years: hazard ratio (HR) = 1.99, 95% confidence interval (CI): 1.08 to 3.68; and older than 50 years: HR = 4.93, 95% CI: 2.63 to 9.22; vs. age 30 years or younger]; receiving NRTI + PI (HR = 1.87, 95% CI: 1.22 to 2.85 vs. NRTI + NNRTI); positive hepatitis C antibody (HR = 2.25, 95% CI: 1.40 to 3.62); and having previous AIDS illness (HR = 1.45, 95% CI: 1.03 to 2.05). An improved survival was seen with a higher CD4 count (CD4 351-500 cells/µL: HR = 0.40, 95%CI: 0.21-0.76; and CD4 >500 cells/µL: HR = 0.43, 95%CI: 0.25-0.75; vs. CD4 ≤200 cells/µL).
CONCLUSIONS: Almost one-third of PLHIV who were LTFU in this cohort had died while out of care, emphasizing the importance of efforts to reengage PLHIV after they have been LTFU and ensure they have access to ongoing ART.
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: 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: Participants enrolled in a regional Asian HIV-infected cohort with weight and height measurements at ART initiation were eligible for inclusion in the analysis. Factors associated with weight changes and incident MetS (according to the International Diabetic Federation (IDF) definition) were analysed using linear mixed models and Cox regression, respectively. Competing-risk regression models were used to investigate the association of MetS with all-cause mortality.
RESULTS: Among 4931 people living with HIV (PLWH), 66% were male. At ART initiation, the median age was 34 [interquartile range (IQR) 29-41] years, and the median (IQR) weight and body mass index (BMI) were 55 (48-63) kg and 20.5 (18.4-22.9) kg/m2 , respectively. At 1, 2 and 3 years of ART, overall mean (± standard deviation) weight gain was 2.2 (±5.3), 3.0 (±6.2) and 3.7 (±6.5) kg, respectively. Participants with baseline CD4 count ≤ 200 cells/µL [weight difference (diff) = 2.2 kg; 95% confidence interval (CI) 1.9-2.5 kg] and baseline HIV RNA ≥ 100 000 HIV-1 RNA copies/mL (diff = 0.6 kg; 95% CI 0.2-1.0 kg), and those starting with integrase strand transfer inhibitor (INSTI)-based ART (diff = 2.1 kg; 95% CI 0.7-3.5 kg vs. nonnucleoside reverse transcriptase inhibitors) had greater weight gain. After exclusion of those with abnormal baseline levels of MetS components, 295/3503 had incident MetS [1.18 (95% CI 1.05-1.32)/100 person-years (PY)]. The mortality rate was 0.7 (95% CI 0.6-0.8)/100 PY. MetS was not significantly associated with all-cause mortality in the adjusted model (P = 0.236).
CONCLUSIONS: Weight gain after ART initiation was significantly higher among those initiating ART with lower CD4 count, higher HIV RNA and an INSTI-based regimen after controlling for baseline BMI. Greater efforts to identify and manage MetS among PLWH are needed.
METHODS: We compared these regimens with respect to clinical, immunologic, and virologic outcomes using data from prospective studies of human immunodeficiency virus (HIV)-infected individuals in Europe and the United States in the HIV-CAUSAL Collaboration, 2004-2013. Antiretroviral therapy-naive and AIDS-free individuals were followed from the time they started a lopinavir or an atazanavir regimen. We estimated the 'intention-to-treat' effect for atazanavir vs lopinavir regimens on each of the outcomes.
RESULTS: A total of 6668 individuals started a lopinavir regimen (213 deaths, 457 AIDS-defining illnesses or deaths), and 4301 individuals started an atazanavir regimen (83 deaths, 157 AIDS-defining illnesses or deaths). The adjusted intention-to-treat hazard ratios for atazanavir vs lopinavir regimens were 0.70 (95% confidence interval [CI], .53-.91) for death, 0.67 (95% CI, .55-.82) for AIDS-defining illness or death, and 0.91 (95% CI, .84-.99) for virologic failure at 12 months. The mean 12-month increase in CD4 count was 8.15 (95% CI, -.13 to 16.43) cells/µL higher in the atazanavir group. Estimates differed by NRTI backbone.
CONCLUSIONS: Our estimates are consistent with a lower mortality, a lower incidence of AIDS-defining illness, a greater 12-month increase in CD4 cell count, and a smaller risk of virologic failure at 12 months for atazanavir compared with lopinavir regimens.
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.