METHODS: Data (2014-2018) from a regional cohort of Asian PHIVA who received at least 6 months of continuous cART were analyzed. Treatment failure was defined according to World Health Organization criteria. Descriptive analyses were used to report treatment failure and subsequent management and evaluate postfailure CD4 count and viral load trends. Kaplan-Meier survival analyses were used to compare the cumulative incidence of death and loss to follow-up (LTFU) by treatment failure status.
RESULTS: A total 3196 PHIVA were included in the analysis with a median follow-up period of 3.0 years, of whom 230 (7.2%) had experienced 292 treatment failure events (161 virologic, 128 immunologic, 11 clinical) at a rate of 3.78 per 100 person-years. Of the 292 treatment failure events, 31 (10.6%) had a subsequent cART switch within 6 months, which resulted in better immunologic and virologic outcomes compared to those who did not switch cART. The 5-year cumulative incidence of death and LTFU following treatment failure was 18.5% compared to 10.1% without treatment failure.
CONCLUSIONS: Improved implementation of virologic monitoring is required to realize the benefits of virologic determination of cART failure. There is a need to address issues related to accessibility to subsequent cART regimens, poor adherence limiting scope to switch regimens, and the role of antiretroviral resistance testing.
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: 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: 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.
DESIGN: Death-related data were retrospectively and prospectively assessed in a longitudinal regional cohort study.
METHODS: Children under routine HIV care at sites in Cambodia, India, Indonesia, Malaysia, Thailand, and Vietnam between 2008 and 2017 were followed. Causes of death were reported and then independently and centrally reviewed. Predictors were compared using competing risks survival regression analyses.
RESULTS: Among 5918 children, 5523 (93%; 52% male) had ever been on combination antiretroviral therapy. Of 371 (6.3%) deaths, 312 (84%) occurred in those with a history of combination antiretroviral therapy (crude all-cause mortality 9.6 per 1000 person-years; total follow-up time 32 361 person-years). In this group, median age at death was 7.0 (2.9-13) years; median CD4 cell count was 73 (16-325) cells/μl. The most common underlying causes of death were pneumonia due to unspecified pathogens (17%), tuberculosis (16%), sepsis (8.0%), and AIDS (6.7%); 12% of causes were unknown. These clinical diagnoses were further grouped into AIDS-related infections (22%) and noninfections (5.8%), and non-AIDS-related infections (47%) and noninfections (11%); with 12% unknown, 2.2% not reviewed. Higher CD4 cell count and better weight-for-age z-score were protective against death.
CONCLUSION: Our standardized cause of death assessment provides robust data to inform regional resource allocation for pediatric diagnostic evaluations and prioritization of clinical interventions, and highlight the continued importance of opportunistic and nonopportunistic infections as causes of death in our cohort.
DESIGN: Ongoing observational database collating clinical data on HIV-infected children and adolescents in Asia.
METHODS: Data from 2001 to 2016 relating to adolescents (10-19 years) with perinatal HIV infection were analysed to describe characteristics at adolescent entry and transition and combination antiretroviral therapy (cART) regimens across adolescence. A competing risk regression analysis was used to determine characteristics at adolescent entry associated with mortality. Outcomes at transition were compared on the basis of age at cART initiation.
RESULTS: Of 3448 PHIVA, 644 had reached transition. Median age at HIV diagnosis was 5.5 years, cART initiation 7.2 years and transition 17.9 years. At adolescent entry, 35.0% had CD4+ cell count less than 500 cells/μl and 51.1% had experienced a WHO stage III/IV clinical event. At transition, 38.9% had CD4+ cell count less than 500 copies/ml, and 53.4% had experienced a WHO stage III/IV clinical event. Mortality rate was 0.71 per 100 person-years, with HIV RNA ≥1000 copies/ml, CD4+ cell count less than 500 cells/μl, height-for-age or weight-for-age z-score less than -2, history of a WHO stage III/IV clinical event or hospitalization and at least second cART associated with mortality. For transitioning PHIVA, those who commenced cART age less than 5 years had better virologic and immunologic outcomes, though were more likely to be on at least second cART.
CONCLUSION: Delayed HIV diagnosis and cART initiation resulted in considerable morbidity and poor immune status by adolescent entry. Durable first-line cART regimens to optimize disease control are key to minimizing mortality. Early cART initiation provides the best virologic and immunologic outcomes at transition.