Suboptimal Viral Suppression Rates Among HIV-Infected Children in Low- and Middle-Income Countries: A Meta-analysis

Boerma, Ragna S.; Boender, T. Sonia; Bussink, Anton P.; Calis, Job C. J.; Bertagnolio, Silvia; Wit, Tobias F. Rinke de; Hensbroek, Michaël Boele van; Sigaloff, Kim C.E.

doi:10.1093/cid/ciw645

Cited by 102 publications

(109 citation statements)

References 21 publications

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“…However, the suppression rates are about 10%−20% lower among pediatric and adolescent populations. This is similar to findings from other countries [31, 32]. Many factors account for low viral suppression rates among these groups, including poor adherence to ART, limited number of appropriate pediatric-friendly ARV formulations, nondisclosure of HIV status, lack of a support network, stigma, poor compliance with VL testing guidelines, and keeping patients on failing regimens [33–35].…”

Section: Discussionsupporting

confidence: 81%

Low Case Finding Among Men and Poor Viral Load Suppression Among Adolescents Are Impeding Namibia’s Ability to Achieve UNAIDS 90-90-90 Targets

Agolory¹,

Klerk²,

Baughman³

et al. 2018

Open Forum Infectious Diseases

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BackgroundIn 2015, Namibia implemented an Acceleration Plan to address the high burden of HIV (13.0% adult prevalence and 216 311 people living with HIV [PLHIV]) and achieve the UNAIDS 90-90-90 targets by 2020. We provide an update on Namibia’s overall progress toward achieving these targets and estimate the percent reduction in HIV incidence since 2010.MethodsData sources include the 2013 Namibia Demographic and Health Survey (2013 NDHS), the national electronic patient monitoring system, and laboratory data from the Namibian Institute of Pathology. These sources were used to estimate (1) the percentage of PLHIV who know their HIV status, (2) the percentage of PLHIV on antiretroviral therapy (ART), (3) the percentage of patients on ART with suppressed viral loads, and (4) the percent reduction in HIV incidence.ResultsIn the 2013 NDHS, knowledge of HIV status was higher among HIV-positive women 91.8% (95% confidence interval [CI], 89.4%–93.7%) than HIV-positive men 82.5% (95% CI, 78.1%–86.1%). At the end of 2016, an estimated 88.3% (95% CI, 86.3%–90.1%) of PLHIV knew their status, and 165 939 (76.7%) PLHIV were active on ART. The viral load suppression rate among those on ART was 87%, and it was highest among ≥20-year-olds (90%) and lowest among 15–19-year-olds (68%). HIV incidence has declined by 21% since 2010.ConclusionsWith 76.7% of PLHIV on ART and 87% of those on ART virally suppressed, Namibia is on track to achieve UNAIDS 90-90-90 targets by 2020. Innovative strategies are needed to improve HIV case identification among men and adherence to ART among youth.

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Section: Discussionsupporting

confidence: 81%

Low Case Finding Among Men and Poor Viral Load Suppression Among Adolescents Are Impeding Namibia’s Ability to Achieve UNAIDS 90-90-90 Targets

Agolory¹,

Klerk²,

Baughman³

et al. 2018

Open Forum Infectious Diseases

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“…A large meta-analysis conducted in 2016 of both observational studies and randomized controlled trials evaluating viral suppression identified 72 studies reporting on 51,374 children <18 years. After 12 months on first-line ART, viral suppression was achieved by 64.7% (95% CI: 57.5-71.8) in studies conducted from 2000 to 2005, 74.2% (95% CI: 70.2-78.2) in studies conducted from 2006 to 2009 and 72.7% (95% CI: 62.6-82.8) in studies conducted after 2010 [11]. These rates are considerably lower than those typically observed in adults, including in a meta-analysis of virologic outcomes in adults, which found viral suppression rates >80% in the first five years on ART [12].…”

Section: Reasons For Prioritizing Hiv-infected Infants and Childrenmentioning

confidence: 99%

Routine viral load monitoring in HIV‐infected infants and children in low‐ and middle‐income countries: challenges and opportunities

et al. 2017

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IntroductionThe objective of this commentary is to review considerations for implementing routine viral load (VL) monitoring programmes for HIV‐infected infants and children living in low‐ and middle‐income countries (LMIC). Since 2013, the World Health Organization (WHO) guidelines recommend VL testing as the preferred monitoring approach for all individuals treated with ART in order to assess treatment response, detect treatment failure and determine the need to switch to a second‐line regimen in a timely manner. More recently, WHO guidelines from 2016 identify HIV‐infected infants and children as a priority group for routine VL monitoring.DiscussionThere are a number of reasons why HIV‐infected infants and children should be prioritized for routine VL monitoring. Data from national VL monitoring programmes as well as systematic reviews and meta‐analyses from LMIC indicate rates of viral suppression are lower for infants and children compared to adults. The number of antiretroviral drugs and palatable formulations suitable for young children are limited. In addition, emotional and developmental issues particular to children can make daily medication administration difficult and pose a challenge to adherence and achievement of sustained viral suppression. VL monitoring can be instrumental for identifying those in need of additional adherence support, reducing regimen switches and preserving treatment options. The needs of infants and children warrant consideration in all aspects of VL monitoring services. If capacity for paediatric venipuncture is not assured, platforms that accept dried blood spot specimens are necessary in order for infants and children to have equitable access. Healthcare systems also need to prepare to manage the substantial number of infants and children identified with elevated VL, including adherence interventions that are appropriate for children. Establishing robust systems to evaluate processes and outcomes of routine VL monitoring services and to support drug forecasting and supply management is essential to determine best practices for infants and children in LMIC.ConclusionsThe particular concerns of HIV‐infected infants and children warrant attention during all phases of planning and implementation of VL monitoring services. There are a number of key areas, including frequency of monitoring, blood specimen type and adherence challenges, where specific approaches tailored for infants and children may be required.

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“…This method would facilitate cross-comparison of research studies by providing a standard for viral load pattern classification. Such standardization would be immensely useful in meta-analyses of diverse research reports [32][33][34][35][36]. It is possible that, in the future additional viral load patterns may emerge with, for example, the emergence of new HIV variants that are resistant to, or escape suppression of, current therapies.…”

Section: Discussionmentioning

confidence: 99%

“…The code used to analyze the data can be found on github at https://github.com/SamirRCHI/Viral Load Data Categorization. [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] week range for a different part of their statistical analysis; however, in our categorical implementation, we modify the range to 24-32 weeks to build coherent categories according to the procedure they outline (as we are about to describe). Phillips et.…”

Section: Supporting Informationmentioning

confidence: 99%

Revealing HIV viral load patterns using unsupervised machine learning and cluster summarization

et al. 2018

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HIV RNA viral load (VL) is an important outcome variable in studies of HIV infected persons. There exists only a handful of methods which classify patients by VL patterns. Most methods place limits on the use of viral load measurements, are often specific to a particular study design, and do not account for complex, temporal variation. To address this issue, we propose a set of four unambiguous computable characteristics (features) of time-varying HIV viral load patterns, along with a novel centroid-based classification algorithm, which we use to classify a population of 1,576 HIV positive clinic patients into one of five different viral load patterns (clusters) often found in the literature: durably suppressed viral load (DSVL), sustained low viral load (SLVL), sustained high viral load (SHVL), high viral load suppression (HVLS), and rebounding viral load (RVL). The centroid algorithm summarizes these clusters in terms of their centroids and radii. We show that this allows new VL patterns to be assigned pattern membership based on the distance from the centroid relative to its radius, which we term radial normalization classification. This method has the benefit of providing an objective and quantitative method to assign VL pattern membership with a concise and interpretable model that aids clinical decision making. This method also facilitates meta-analyses by providing computably distinct HIV categories. Finally we propose that this novel centroid algorithm could also be useful in the areas of cluster comparison for outcomes research and data reduction in machine learning.

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Suboptimal Viral Suppression Rates Among HIV-Infected Children in Low- and Middle-Income Countries: A Meta-analysis

Cited by 102 publications

References 21 publications

Low Case Finding Among Men and Poor Viral Load Suppression Among Adolescents Are Impeding Namibia’s Ability to Achieve UNAIDS 90-90-90 Targets

Low Case Finding Among Men and Poor Viral Load Suppression Among Adolescents Are Impeding Namibia’s Ability to Achieve UNAIDS 90-90-90 Targets

Routine viral load monitoring in HIV‐infected infants and children in low‐ and middle‐income countries: challenges and opportunities

Revealing HIV viral load patterns using unsupervised machine learning and cluster summarization

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