The number of HIV-infected children accessing HIV care and treatment has been increasing worldwide. Triple-drug combinations consisting of 2 nucleoside reverse transcriptase inhibitors (NRTIs) and 1 non-nucleoside reverse transcriptase inhibitor (NNRTI) are the most commonly used first-line antiretroviral therapy (ART) regimens in Asia.1 Data from cohorts in resource-limited settings have shown that up to 80% of children receiving first-line ART achieved viral suppression after the first year of treatment.2–4 However, increasing numbers of children are developing first-line treatment failure.
Studies in Thai and Ugandan cohorts found that one-third of children receiving NNRTI-based first-line ART experienced virologic failure (VF), with the majority detected within the first year of treatment.5,6 A history of adherence problems during first-line treatment is associated with subsequent second-line treatment failure.7 Therefore, long-term adherence and regimen durability are particular challenges for perinatally infected children, given the potential for pre-ART drug resistance associated with prevention of mother-to-child HIV interventions and the need for lifelong therapy.6,8–10
Although second-line boosted protease inhibitors (PIs) are largely accessible for children and adolescents in the region, the availability of alternative antiretrovirals beyond these drugs is limited. Because clinicians and policy makers consider how to prepare for procuring third-line drug options, data on second-line treatment effectiveness, risk of failure, and resistance patterns are critically needed to guide prevention interventions, management decisions, and treatment guidelines.
Study Design and Enrollment
The Prospective Monitoring of Second-line Antiretroviral Therapy Failure and Resistance in Children (TASER-P) study is a longitudinal observational cohort study to monitor for treatment failure on second-line ART in Asian children. We included HIV-infected children <18 years who failed first-line ART and were switched to second-line ART before the enrollment and currently taking their second-line ART or about to switch to second-line ART at the enrollment from 8 sites in Indonesia (1 site), Thailand (4 sites), and Vietnam (3 sites). Second-line ART was defined as the second regimen with an antiretroviral class switch from an NNRTI to a PI. Children who were exposed to mono/dual NRTI therapy before a triple-drug regimen were switched to second-line ART without failure of first-line therapy (eg, for toxicity), and those on nonstandard treatment regimens including once-daily boosted lopinavir (LPV/r) or mono-boosted PI without any NRTI or double-boosted PI were not eligible for the study. Criteria to switch to second-line ART and ART regimens were determined by the treating physicians and the patients based on previous treatment history, viral resistance results, current clinical staging, other medical considerations, local ARV drug availability, and local pediatric guidelines at each site.
Data Collection and Monitoring
Patients were evaluated at study entry and every 6 months thereafter. Clinical assessments and laboratory testing including HIV-RNA were conducted every 6 months and up to week 168 of the study. Adherence was evaluated using pill counts and the WHO's adherence visual analogue scale.11,12 All patients were co-enrolled in a parallel cohort study (TREAT Asia Pediatric HIV Observational Database; TApHOD13). Clinical data before TASER-P enrolment were collected through that study.
Patients with HIV-RNA >1000 copies per milliliter (virologic failure; VF) had resistance testing on the same blood sample. Genotyping was done at each study site. Local laboratories participated in an external HIV drug resistance quality assurance program for the duration of the study.14 Resistance testing was interpreted using the Stanford University HIV Drug Resistance Database.15,16
Patients with study follow-up for at least 6 months were included in the analysis. The primary endpoint was VF. Secondary endpoints were resistance by drug mutation development, adherence, and predictors of VF. Demographic and clinical characteristics were summarized in terms of medians (interquartile range, IQR) and proportions, as appropriate. Baseline was at the time of switching to second-line ART, and the last clinic visit was the most recent visit with an available viral load test. Virologic suppression was defined as having HIV-RNA levels <400 copies per milliliter throughout the study period. Persistent VF was when repeated, consecutive viral load tests were >1000 copies per milliliter. VF rates were calculated and Cox proportional hazards regression analysis was used to determine predictors of VF as a first event. For children not experiencing VF, data were censored at the last clinic visit. The linearity of continuous covariates was assessed against the hazard function, and where these assumptions were not met, covariates were modeled as quartiles. Adjacent categories were collapsed together if the hazard ratio (HR) and size of the 95% confidence interval (CI) were similar.
Univariate risk factor analysis for VF included age, weight for age z score, height for age z score, sex, WHO clinical disease stage, CD4, and HIV-RNA at baseline, and duration of first-line ART. All covariates with P-value <0.10 were adjusted for in multivariate analyses. Resistance patterns were reported as proportions of children with VF. Statistical significance was based on a 2-sided P-value of 0.05. Analyses were performed using SAS version 9.3 (SAS Institute Inc., Cary, NC) and Stata version 12 (Statacorp, College Station, TX).
All participating study sites and coordinating centers obtained local Institutional Review Board approvals for study participation. Informed consent was provided by primary caregivers; children over the age of 7 years who were aware of their own HIV status through previous disclosure were asked to provide assent when this was required by the local review board.
Characteristics at Switching to Second-Line ART
A total of 277 children were enrolled in the TASER-P study between February 2011 and December 2012. At enrollment, 41% were female and 134 (48%) were Vietnamese, 115 (42%) were Thai and 28 (10%) were Indonesian (Table 1). Of these, they were experienced the WHO clinical stage 1 (41; 15%), stage 2 (91; 33%), stage 3 (87; 31%), and stage 4 (31; 11%). The median (IQR) age at the enrollment was 9.9 (7.3–12.9) years. The median age at first-line ART initiation was 4.1 (2.6–6.7) years, and the median weight for age z score was -0.64 (−1.44 to 0.21). Most patients (243; 88%) were switched to second-line ART before study enrollment. At second-line switch, the median age was 7.5 (5.3–10.3) years, the median prior duration on first-line ART was 2.7 (1.7–4.2) years, the median weight for age z score was −1.27 (−2.06 to −0.35), the median CD4 count was 300 (146–562) cells per cubic millimeter, the median CD4 percentage was 13 (7–20%), and the median HIV-RNA was 5.0 (4.4–5.5) log10 copies per milliliter. All children had been on NNRTI-based first-line regimens.
Second-line regimens contained lamivudine (3TC; 90%), tenofovir (TDF; 43%), and zidovudine (ZDV) or abacavir (ABC) (30%). Most of the children were on LPV/r-based regimens (91%), 7% were on boosted atazanavir (ATV/r), and 2% were on boosted indinavir (IDV/r). Of the 156 (56%) children who had available resistance testing at the time of first-line failure, mutations included M184V (82%), ≥1 thymidine analog mutation (TAM; 64%), ≥4 TAMs (18%), T215Y/F (43%), K65R (10%), ≥1 NNRTI mutation (92%), Y181I/C (44%), G190A (33%), K103N/S (27%), and V108I (15%); 30 (19%) children had DUET weighted scores ≥4 (Table 2).
A total of 274 of 277 children were followed for at least 6 months after study enrollment and included in the study analyses; 112 (41%) were female. At the last follow-up visit or upon censoring at VF, the median duration on second-line ART was 3.3 (1.8–5.3) years, median CD4 count was 763 (556–1060) cells per cubic millimeter and median CD4 percentage was 26 (20–31%), and 192 (70%) had HIV-RNA <400 copies per milliliter; 18 (6%) had WHO clinical stage 3 or 4 events during the follow-up period. There were 5 (2%) deaths from HIV-related illnesses; 3 occurred during the first 6 months after enrollment.
At 1 year of second-line ART, 5% of children had VF, and this increased to 20% within 3 years after switch (Fig. 1). The median duration after second-line switch to the first documented VF was 2.4 (1.3–4.0) years, 2.6 (1.5–3.9) years to the second documented VF, and 3.1 (1.8–4.1) years to the third documented VF.
During the study monitoring period, 73 (27%) children developed VF, representing an incidence of 7.25 per 100 person-years (95% CI: 5.77 to 9.12). Forty of 73 (55%) children had persistent VF for 24 weeks and 23 (32%) children had persistent VF for 48 weeks of follow-up while remaining on second-line regimens. At the time of the first documented VF during the study monitoring period, >95% adherence was reported among 52 (71%) by pill count and 53 (73%) by visual analogue scale. In those with persistent VF, adherence decreased to 65% by pill count and 68% by visual analogue scale at the second documented VF, and to 57% by pill count and 52% by visual analogue scale at the third documented VF. Patients who developed VF during the study period were counseled and managed according to the local/nation treatment guidelines that were determined by their physicians and patients based on their decision. None of the patients switched from second-line to third-line regimens during the study monitoring period.
Multivariate analysis showed that VF was associated with starting second-line ART at age >11 years (HR 4.06; 95% CI: 2.15 to 7.66) and having an HIV-RNA >5.0 log10 copies per milliliter (HR 2.42; 95% CI: 1.27 to 4.59) at the time of second-line ART switch, and was seen more commonly in children enrolled in sites at Vietnam (HR 2.79; 95%CI: 1.55 to 5.02) (Table 3). However, sex, prior duration on first-line ART, WHO stage, CD4, and weight or height for age z score at initiation of second-line ART were not significantly associated with VF.
Resistance Mutations After Virologic Failure
At the first documented VF while on second-line ART, HIV drug-resistant genotypes were available for 48 (66%) children. NRTI mutations included ≥1 TAM (40%), ≥4 TAMs (10%), T215Y/F (23%), Q151M (4%), M184V (56%), K65R (2%). Data on PI resistance mutations were available among 50 (68%) children and included any major LPV mutation (L76V V82A V82S; 8%), ≥6 LPV mutations (2%), any major darunavir (DRV) mutation (I84V, L76V; 2%), and any major ATV mutation (I84V, N88S; 4%) (Table 2).
At the first documented VF during the study monitoring period, there was high-level resistance to 3TC (56%), AZT (25%), and TDF (10%). Most patients remained susceptible to LPV (86%) and ATV (84%). Among children who had persistent VF, 30/40 (75%) had genotypes available at the second VF and 20/23 (87%) at the third VF. Percentages of NRTI and PI resistance mutations were the same or decreased with successive viral load testing. However, overall susceptibility to LPV decreased from 86% to 83%–80% with each subsequent viral load >1000 copies per milliliter.
This is the first prospective, regional observational cohort study of Asian HIV-infected children receiving second-line ART. We identified generally high rates of virologic suppression during the study period. Our data are consistent with suppression rates in Thai17 (79%) and Ugandan18 (84.5%) cohorts of children on PI-based second-line regimens. Higher virologic suppression rates have been reported while on second-line PI regimens compared with second-line NNRTI regimens (80% vs. 25%; P = 0.009),19 reflecting the potency of boosted PI regimens and the reduced risk of archived mutations compared with NNRTIs.20,21 Although the majority of our patients remained virologically suppressed throughout the study period, 27% developed at least one episode of VF during the study monitoring period. We observed that 55% of those with an initial elevated viral load had persistent VF for 24 weeks (2 consecutive measurements) and 32% had persistent VF for 48 weeks (3 consecutive measurements). Of note is that 45% were able to achieve virologic suppression after the first documented VF without switching to third-line or intensification of their regimen.
Even among those with persistently elevated viral load, only a small percentage acquired major PI resistance mutations, with most patients remaining susceptible to second-line PIs throughout the follow-up period, representing a median time on second line of 3.3 years. At second-line switch, about half or more of the patients already had high-level resistance to 3TC (87%), d4T (52%), and AZT (50%). At the first documented VF during the study, the percentage of children with high-level NRTI resistance decreased (eg, 3TC 87% to 56%, AZT 50% to 24%). Although we observed a decrease over time in adherence in children with persistent VF, overall adherence levels by self-report and pill count were still higher than expected in comparison with HIV-RNA results. It is likely that the low levels of resistance were related in part to reversion to wild-type virus because of low drug exposure.22,23
Significant risk factors for VF identified in this study were older age (age >11 years; HR 4.06), higher HIV-RNA level (>5.0 log10 copies/mL; HR 2.4) at second-line ART switch, and being enrolled at sites in Vietnam. The challenges associated with transitioning into adolescence are exacerbated by HIV infection and can result in poor adherence, mental health conditions (eg, depression), and high rates of loss to follow-up.24–26 Unfortunately, we were not able to include adherence in the statistical models because we were missing adherence data from the time period immediately after second-line switch and before study enrolment. Interventions to ensure adherence and prevent treatment failure during adolescence are critical to prevent treatment failure, particularly when third-line options are limited. It is unclear why children from Vietnam were at higher risk of VF and may be related to variations in adherence support, clinic volumes, and healthcare provider staffing levels.
Poor adherence is a major risk factor for treatment failure. Although adherence monitoring is a critical tool to promote ART success,1,27 different adherence assessment methods may not be sensitive enough to identify patients at risk of VF.28 Providing effective adherence support is more challenging with children and adolescents because of issues such as limited drug formulations, reliance on caretakers to supervise taking medicines, and pill fatigue associated with lifelong therapy. High pill burden and increased medicine frequency are known barriers to adherence,29 and second-line regimens often require more pills more often than first-line ART.
Our study also identified low levels of PI resistance after VF. Susceptibility to LPV only decreased from 86% to 80% at 48 weeks of persistently elevated viral load. These data are consistent with reports in adults which observed limited PI resistance after PI regimen failure, where adherence strengthening helped improve virologic responses.30,31 In our study, 45% were able to resuppress their virus after the initial VF and an additional 23% were able to resuppress within 48 weeks after counseling, but without major changes to their regimens. The viral resuppression after VF in this study may be related to better adherence and improved understanding of treatment outcomes after counseling after VF. It is notable that none of the children and adolescents were switched to third line during the study monitoring period, reflecting concerns for making switches because of poor adherence and the lack of accessible third-line options in our region. Although serious triple-class failure is rare (eg, DRV resistance was ≤10%), additional research is needed to determine optimal second-line failure management strategies to maximize future therapeutic options.
A key limitation of this study is that the majority of the participants were switched to second-line ART before study enrollment, and unlike clinical and treatment data, adherence data were not recorded before the study enrollment. In addition, 10% had VF before the study enrollment, resulting in incomplete adherence and resistance data. Moreover, although we were able to combine retrospective and prospective HIV-RNA data to improve our assessment of VF (eg, reflected in Fig. 1), adherence was not evaluable in our risk factor analysis. Study sites are all tertiary-care referral centers in largely urban areas, which limit the generalizability of our results to centers with fewer subspecialty resources and in rural settings.
In summary, we observed high rates of extended virologic suppression among a cohort of Asian children and adolescents on second-line ART. One-fourth developed VF within a few years after second-line ART initiation. However, only few acquired major PI resistance mutations and most remained susceptible to their regimens, which likely reflects poor adherence. Older age and high HIV-RNA level at the start of second-line ART were significant risk factors and emphasize the importance of providing additional adherence support for adolescents on second line to maximize treatment effectiveness over time and prevent treatment failure.
The authors gratefully acknowledge the participation of the children, adolescents, and their families, and the contributions of all study staff. The study is an initiative of TREAT Asia, a program of amfAR, The Foundation for AIDS Research.
The TASER-Pediatrics Network: K. H. Truong and T. P. K. Le, Children's Hospital 1, Ho Chi Minh City, Vietnam; V. C. Do, V. T. An, and T. M. Ha, Children's Hospital 2, Ho Chi Minh City, Vietnam; W. Prasitsuebsai, S. Kerr, T. Bunupuradah, A. Avihingsanon, T. Jupimai, N Thammajaruk, and C. Ruengpanyathip, HIV-NAT, the Thai Red Cross AIDS Research Centre, Bangkok, Thailand; L. V. Nguyen and K. D. T. Khu, National Hospital of Pediatrics, Hanoi, Vietnam; N. Kurniati and D. Muktiarti, Cipto Mangunkusumo General Hospital, Jakarta, Indonesia; P. Kosalaraksa, P. Lumbiganon, and C. Sopharak, Division of Infectious Diseases, Department of Pediatrics, Khon Kaen University, Khon Kaen, Thailand; T. Sudjaritruk, V. Sirisanthana, and L. Aurpibul, and, Research Institute for Health Sciences and Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand; K. Chokephaibulkit, S. Sricharoenchai, and N. Kongstan, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand; A. H. Sohn, N. Durier, and T. Singtoroj, TREAT Asia/amfAR, The Foundation for AIDS Research, Bangkok, Thailand.
2. Janssens B, Raleigh B, Soeung S, et al. Effectiveness of highly active antiretroviral therapy in HIV-positive children
: evaluation at 12 months in a routine program in Cambodia. Pediatrics. 2007;120:e1134–e1140.
3. Kamya MR, Mayanja-Kizza H, Kambugu A, et al. Predictors of long-term viral failure among Ugandan children
and adults treated with antiretroviral therapy. J Acquir Immune Defic Syndr. 2007;46:187–193.
4. Puthanakit T, Oberdorfer A, Akarathum N, et al. Efficacy of highly active antiretroviral therapy in HIV-infected children
participating in Thailand's National Access to Antiretroviral Program. Clin Infect Dis. 2005;41:100–107.
5. Bunupuradah T, Puthanakit T, Kosalaraksa P, et al. Immunologic and virologic failure after first-line NNRTI-based antiretroviral therapy in Thai HIV-infected children
. AIDS Res Ther. 2011;8:40.
6. Sebunya R, Musiime V, Kitaka SB, et al. Incidence and risk factors for first line anti retroviral treatment failure among Ugandan children
attending an urban HIV clinic. AIDS Res Ther. 2013;10:25.
7. Ramadhani HO, Bartlett JA, Thielman NM, et al. Association of first-line and second-line antiretroviral therapy
adherence. Open Forum Infect Dis. 2014;1:ofu079.
8. Kuhn L, Hunt G, Technau KG, et al. Drug resistance
among newly diagnosed HIV-infected children
in the era of more efficacious antiretroviral prophylaxis. AIDS. 2014;28:1673–1678.
9. Penazzato M, Prendergast AJ, Muhe LM, et al. Optimisation of antiretroviral therapy in HIV-infected children
under 3 years of age. Cochrane Database Syst Rev. 2014;5:CD004772.
10. Sohn AH, Hazra R. The changing epidemiology of the global paediatric HIV epidemic: keeping track of perinatally HIV-infected adolescents
. J Int AIDS Soc. 2013;16:18555.
11. Amico KR, Fisher WA, Cornman DH, et al. Visual analog scale of ART adherence: association with 3-day self-report and adherence barriers. J Acquir Immune Defic Syndr. 2006;42:455–459.
12. Giordano TP, Guzman D, Clark R, et al. Measuring adherence to antiretroviral therapy in a diverse population using a visual analogue scale. HIV Clin Trials. 2004;5:74–79.
13. Kariminia A, Chokephaibulkit K, Pang J, et al. Cohort profile: the TREAT Asia
pediatric HIV observational database. Int J Epidemiol. 2011;40:15–24.
14. Land S, Zhou J, Cunningham P, et al. Capacity building and predictors of success for HIV-1 drug resistance
testing in the Asia
-Pacific region and Africa. J Int AIDS Soc. 2013;16:18580.
15. Rhee SY, Gonzales MJ, Kantor R, et al. Human immunodeficiency virus reverse transcriptase and protease sequence database. Nucleic Acids Res. 2003;31:298–303.
16. Shafer RW. Rationale and uses of a public HIV drug-resistance
database. J Infect Dis. 2006;194(suppl 1):S51–S58.
17. Puthanakit T, Jourdain G, Suntarattiwong P, et al. High virologic response rate after second-line boosted protease inhibitor-based antiretroviral therapy regimens in children
from a resource limited setting. AIDS Res Ther. 2012;9:20.
18. Musiime V, Kaudha E, Kayiwa J, et al. Antiretroviral drug resistance
profiles and response to second-line therapy among HIV type 1-infected Ugandan children
. AIDS Res Hum Retroviruses. 2013;29:449–455.
19. Zanoni BC, Sunpath H, Feeney ME. Pediatric response to second-line antiretroviral therapy
in South Africa. PLoS One. 2012;7:e49591.
20. Antunes F, Zindoga P, Gomes P, et al. Development of nevirapine resistance
exposed to the prevention of mother-to-child HIV-1 transmission programme in Maputo, Mozambique. PLoS One. 2015;10:e0131994.
21. Persaud D, Bedri A, Ziemniak C, et al. Slower clearance of nevirapine resistant virus in infants failing extended nevirapine prophylaxis for prevention of mother-to-child HIV transmission. AIDS Res Hum Retroviruses. 2011;27:823–829.
22. Perno CF, Ceccherini-Silberstein F, De Luca A, et al. Virologic correlates of adherence to antiretroviral medications and therapeutic failure. J Acquir Immune Defic Syndr. 2002;31(suppl 3):S118–S122.
23. Miller V, Sabin C, Hertogs K, et al. Virological and immunological effects of treatment interruptions in HIV-1 infected patients with treatment failure. AIDS. 2000;14:2857–2867.
24. Garvie PA, Wilkins ML, Young JC. Medication adherence in adolescents
with behaviorally-acquired HIV: evidence for using a multimethod assessment protocol. J Adolesc Health. 2010;47:504–511.
25. Merzel C, VanDevanter N, Irvine M. Adherence to antiretroviral therapy among older children
with HIV: a qualitative study of psychosocial contexts. AIDS Patient Care STDS. 2008;22:977–987.
26. Shroufi A, Gunguwo H, Dixon M, et al. HIV-infected adolescents
in southern Africa can achieve good treatment outcomes
: results from a retrospective cohort study. AIDS. 2013;27:1971–1978.
27. World Health Organization (WHO). Antiretroviral therapy of HIV infection in infants and children
: towards universal access: recommendations for a public health approach—2010 revision. Available at: http://whqlibdoc.who.int/publications/2010/9789241599801_eng.pdf
. Accessed June 9, 2015.
28. Kerr SJ, Avihingsanon A, Putcharoen O, et al. Assessing adherence in Thai patients taking combination antiretroviral therapy. Int J STD AIDS. 2012;23:160–165.
29. Parienti JJ, Bangsberg DR, Verdon R, et al. Better adherence with once-daily antiretroviral regimens: a meta-analysis. Clin Infect Dis. 2009;48:484–488.
30. Zheng Y, Hughes MD, Lockman S, et al. Antiretroviral therapy and efficacy after virologic failure on first-line boosted protease inhibitor regimens. Clin Infect Dis. 2014;59:888–896.
31. van Zyl GU, van der Merwe L, Claassen M, et al. Protease inhibitor resistance
in South African children
with virologic failure. Pediatr Infect Dis J. 2009;28:1125–1127.