Incidence of switch to second-line antiretroviral therapy and associated factors in children with HIV: A global analysis

BACKGROUND: Estimates of incidence of switching to second-line antiretroviral therapy (ART) among children with HIV are necessary to inform the need for paediatric second-line formulations. We aimed to quantify the cumulative incidence of switching to second-line ART among children in an international cohort collaboration. // METHODS: In this international cohort collaboration study, we pooled individual patient-level data for children younger than 18 years who initiated ART (two or more nucleoside reverse-transcriptase inhibitors [NRTI] plus a non-NRTI [NNRTI] or boosted protease inhibitor) between 1993 and 2015 from 12 observational cohort networks in the Collaborative Initiative for Paediatric HIV Education and Research (CIPHER) Global Cohort Collaboration. Patients who were reported to be horizontally infected with HIV and those who were enrolled in trials of treatment monitoring, switching, or interruption strategies were excluded. Switch to second-line ART was defined as change of one or more NRTI plus either change in drug class (NNRTI to protease inhibitor or vice versa) or protease inhibitor change, change from single to dual protease inhibitor, or addition of a new drug class. We used cumulative incidence curves to assess time to switching, and multivariable proportional hazards models to explore patient-level and cohort-level factors associated with switching, with death and loss to follow-up as competing risks. // FINDINGS: At the data cutoff of Sept 16, 2015, 182 747 children with HIV were included in the CIPHER dataset, of whom 93 351 were eligible, with 83 984 (90·0%) from sub-Saharan Africa. At ART initiation, the median patient age was 3·9 years (IQR 1·6–6·9) and 82 885 (88·8%) patients initiated NNRTI-based and 10 466 (11·2%) initiated protease inhibitor-based regimens. Median duration of follow-up after ART initiation was 26 months (IQR 9–52). 3883 (4·2%) patients switched to second-line ART after a median of 35 months (IQR 20–57) of ART. The cumulative incidence of switching at 3 years was 3·1% (95% CI 3·0–3·2), but this estimate varied widely depending on the cohort monitoring strategy, from 6·8% (6·5–7·2) in settings with routine monitoring of CD4 (CD4% or CD4 count) and viral load to 0·8% (0·6–1·0) in settings with clinical only monitoring. In multivariable analyses, patient-level factors associated with an increased likelihood of switching were male sex, older age at ART initiation, and initial NNRTI-based regimen (p<0·0001). Cohort-level factors that increased the likelihood of switching were higher-income country (p=0·0017) and routine or targeted monitoring of CD4 and viral load (p<0·0001), which was associated with a 166% increase in likelihood of switching compared with CD4 only monitoring (subdistributional hazard ratio 2·66, 95% CI 2·22–3·19). // INTERPRETATION: Our global paediatric analysis found wide variations in the incidence of switching to second-line ART across monitoring strategies. These findings suggest the scale-up of viral load monitoring would probably increase demand for paediatric second-line ART formulations. // FUNDING: International AIDS Society-CIPHER

Pregnancy is associated with elevation of liver enzymes in HIV-positive women on antiretroviral therapy.

The objective of this study is to assess whether pregnancy is associated with an increased risk of liver enzyme elevation (LEE) and severe LEE in HIV-positive women on antiretroviral therapy (ART)

Who Gets Severe Gynecomastia Among HIV-Infected Children In The UK And Ireland?

There are few data on gynecomastia in HIV-infected children. Within the UK/Ireland's national cohort, 56/1,873 (3%) HIV-infected children had gynecomastia, of which 10 (0.5%) were severe. All 10 had received antiretroviral therapy for a median of 27.5 [21,42] months; 4/10 had received efavirenz, 7/10 and 6/10 stavudine and/or didanosine respectively. Five were non-reversible, despite changing ART, and required breast reduction surgery

The use of funnel plots with regression as a tool to visually compare HIV treatment outcomes between centres adjusting for patient characteristics and size: a UK Collaborative HIV Cohort study

OBJECTIVES: A measure used for assessing the effectiveness of HIV care and comparing clinical centres is the proportion of people starting antiretroviral therapy (ART) with viral suppression (VS) after 1 year. We propose a method that adjusts for patients' demographic characteristics, and visually compares this measure between different sites accounting for centre size. METHODS: We analysed viral load measurements for UK Collaborative HIV Cohort (UK CHIC) patients starting ART between 2006 and 2013. We used logistic regression to estimate the proportion with VS after 1 year of ART adjusted for patient mix (in terms of age and a combined gender/ethnicity/acquisition mode variable) and calendar year. We compared outcomes between centres using funnel plots which account for centre size. RESULTS: The overall proportion of the cohort with VS 1 year after starting ART was 90% and increased from 83% to 93% between 2006 and 2013. VS was lower in younger individuals. White men who have sex with men (MSM) had the highest (94%), and black African (81%) and white (82%) heterosexual women the lowest proportions achieving VS. Comparing the unadjusted funnel plot with the adjusted, there were movements of some centres from outside to inside the 95% contour limits, which was largely explained by the patient mix of these centres. CONCLUSIONS: VS 1 year after ART start was associated with demographic characteristics and centre size; therefore, to compare the performances of centres, adjustment for these factors is required. Adjusted funnel plot is an effective tool which accounts for both the demographic characteristics and the centre size. Social factors, rather than treatment decisions within the control of the centres, may drive differences in outcomes

Differences in HIV clinical outcomes amongst heterosexuals in the United Kingdom by ethnicity

OBJECTIVE: We investigated differences in clinical outcomes in heterosexual participants, by ethnicity in the UK Collaborative HIV Cohort Study from 2000-2017. DESIGN: Cohort analysis. METHODS: Logistic/Proportional hazard regression assessed ethnic group differences in CD4+ cell count at presentation, engagement-in-care, combination antiretroviral therapy (cART) initiation, viral suppression and rebound. RESULTS: Of 12,302 participants (median age: 37 [interquartile range: 31, 44] years, 52.5% women, total follow-up: 85,846 person-years), 64.4% were Black African, 19.1% White, 6.3% Black Caribbean, 3.6% Black Other, 3.3% South Asian/Other Asian and 3.4% Other/Mixed. CD4+ cell count at presentation amongst participants from non-White groups were lower than the White group. Participants were engaged-in-care for 79.6% of follow-up time, however Black and Other/Mixed groups were less likely to be engaged-in-care than the White group (adjusted odds ratios vs. White: Black African: 0.70 [95% confidence interval 0.63, 0.79], Black Caribbean: 0.74 [0.63, 0.88], Other/Mixed: 0.78 [0.62, 0.98], Black Other: 0.81 [0.64, 1.02]). Of 8,867 who started cART, 79.1% achieved viral suppression, with no differences by ethnicity in cART initiation or viral suppression. Viral rebound (22.2%) was more common in the Black Other (1.95 [1.37, 2.77]), Black African (1.85 [1.52, 2.24]), Black Caribbean (1.73 [1.28, 2.33]), South Asian/Other Asian (1.35 [0.90, 2.03]) and Other/Mixed (1.09 [0.69, 1.71]) groups than in White participants. CONCLUSIONS: Heterosexual people from Black, Asian and minority ethnic groups presented with lower CD4+ cell counts, spent less time engaged-in-care and were more likely to experience viral rebound than White people. Work to understand and address these differences is needed

Evolution of CD4 T-Cell count with age in a cohort of young people growing up with perinatally acquired HIV

Background: Recent studies have shown a decrease in CD4 count during adolescence in young people with perinatally acquired HIV (PHIV). We examine changes and predictors of CD4 over time in PHIV in the UK and compare to published CD4 data in the general population.// Methods: PHIV followed in the Collaborative HIV Paediatric Study who started antiretroviral therapy (ART) from 2000 onwards were included. Follow-up data from the UK Collaborative HIV Cohort Study were also used. Changes in CD4 count over time from age 10 to 20 years were analysed using mixed effects models. Potential predictors included demographics, age at ART start, nadir CD4 z-score (age-adjusted) in childhood and time-updated viral load.// Results: Of 1,258 PHIV included, 669 (53%) were female, median [IQR] age at ART initiation was 8.3 years [3.5, 12.1] and nadir CD4 z-score was -4.0 [-5.9, -2.5]. In multivariable analysis, mean CD4 count was higher in PHIV who started ART before age 10 and had a nadir CD4 z-score ≥-4 in childhood; these PHIV had a decline in CD4 count after age 10 which was comparable to the general population. Mean CD4 count was lower in PHIV who had started ART before age 10 and had a nadir CD4 z-score <-4 in childhood; for this group the decline in CD4 count after age 10 was steeper over time.// Conclusions: In children, as well as starting ART at an early age, optimising ART to maintain a higher CD4 z-score during childhood may be important to maximize immune reconstitution later in life

Associations between baseline characteristics, CD4 cell count response and virological failure on first-line efavirenz + tenofovir + emtricitabine for HIV

Objectives: The aim of this study was to investigate associations between baseline characteristics and CD4 cell count response on first-line antiretroviral therapy and risk of virological failure (VF) with or without drug resistance. Methods: We conducted an analysis of UK Collaborative HIV Cohort data linked to the UK HIV Drug Resistance Database. Inclusion criteria were viral sequence showing no resistance prior to initiation of first-line efavirenz + tenofovir disoproxil fumarate + emtricitabine and virological suppression within 6 months. Outcomes of VF (≥200 copies/mL) with or without drug resistance were assessed using a competing risks approach fitted jointly with a model for CD4 cell count recovery. Hazard ratios for each VF outcome were estimated for baseline CD4 cell count and viral load and characteristics of CD4 cell count response using latent variables on a standard normal scale. Results: A total of 3640 people were included with 338 VF events; corresponding viral sequences were available in 134 with ≥1 resistance mutation in 36. VF with resistance was associated with lower baseline CD4 (0.30, 0.09-0.62), lower CD4 recovery (0.04, 0.00-0.17) and higher CD4 variability (4.40, 1.22-12.68). A different pattern of associations was observed for VF without resistance, but the strength of these results was less consistent across sensitivity analyses. Cumulative incidence of VF with resistance was estimated to be <2% at 3 years for baseline CD4 ≥350 cells/μL. Conclusion: Lower baseline CD4 cell count and suboptimal CD4 recovery are associated with VF with drug resistance. People with low CD4 cell count before ART or with suboptimal CD4 recovery on treatment should be a priority for regimens with high genetic barrier to resistance

Mortality and AIDS-defining events among young people following transition from paediatric to adult HIV care in the UK

OBJECTIVES: To investigate risk of AIDS and mortality after transition from paediatric to adult care in a UK cohort of young people with perinatally acquired HIV. METHODS: Records of people aged ≥ 13 years on 31 December 2015 in the UK paediatric HIV cohort (Collaborative HIV Paediatric Study) were linked to those of adults in the UK Collaborative HIV Cohort (CHIC) cohort. We calculated time from transition to a new AIDS event/death, with follow-up censored at the last visit or 31 December 2015, whichever was the earliest. Cumulative incidence of and risk factors for AIDS/mortality were assessed using Kaplan-Meier and Cox regression. RESULTS: At the final paediatric visit, the 474 participants [51% female, 80% black, 60% born outside the UK, median (interquartile range) age at antiretroviral therapy (ART) initiation = 9 (5-13) years] had a median age of 18 (17-19) years and CD4 count of 471 (280-663) cell/μL; 89% were prescribed ART and 60% overall had a viral load ≤ 400 copies/mL. Over median follow-up in adult care of 3 (2-6) years, 35 (8%) experienced a new AIDS event (n = 25) or death (n = 14) (incidence = 1.8/100 person-years). In multivariable analyses, lower CD4 count at the last paediatric visit [adjusted hazard ratio = 0.8 (95% confidence interval: 0.7-1.0)/100 cells/μL increment] and AIDS diagnosis in paediatric care [2.7 (1.4-5.5)] were associated with a new AIDS event/mortality in adult care. CONCLUSIONS: Young people with perinatally acquired HIV transitioning to adult care with markers of disease progression in paediatric care experienced poorer outcomes in adult care. Increased investment in multidisciplinary specialized services is required to support this population at high risk of morbidity and mortality

The effects of age on associations between markers of HIV progression and markers of metabolic function including albumin, haemoglobin and lipid concentrations.

OBJECTIVES: We investigated whether age modified associations between markers of HIV progression, CD4 T lymphocyte count and HIV RNA viral load (VL), and the following markers of metabolic function: albumin, haemoglobin, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC). METHODS: A retrospective analysis of data from the United Kingdom Collaborative HIV Cohort was carried out. Analyses were limited to antiretroviral-naïve subjects to focus on the impact of HIV disease itself. A total of 16670 subjects were included in the analysis. Multilevel linear regression models assessed associations between CD4 count/VL and each of the outcomes. Statistical tests for interactions assessed whether associations differed among age groups. RESULTS: After adjustment for gender and ethnicity, there was evidence that lower CD4 count and higher VL were associated with lower TC, LDL-C, haemoglobin and albumin concentrations but higher triglyceride concentrations. Age modified associations between CD4 count and albumin (P 50 years, a 50 cells/μL lower CD4 count correlated with a 2.4 [95% confidence interval (CI) 1.7-3.0], 3.6 (95% CI 3.2-4.0) and 5.1 (95% CI 4.0-6.1) g/L lower haemoglobin concentration and a 0.09 (95% CI 0.07-0.11), 0.12 (95% CI 0.11-0.13) and 0.16 (95% CI 0.13-0.19) g/L lower albumin concentration, respectively. CONCLUSIONS: We present evidence that age modifies associations between CD4 count and plasma albumin and haemoglobin levels. A given reduction in CD4 count was associated with a greater reduction in haemoglobin and albumin concentrations among older people living with HIV. These findings increase our understanding of how the metabolic impact of HIV is influenced by age