# Weight-for-age distributions among children with HIV on antiretroviral therapy in the International epidemiology Databases to Evaluate AIDS (IeDEA) multiregional consortium

Julie Jesson, S. Desmonde, C. T. Yiannoutsos, G. Patten, Karen Malateste, S. N. Duda, N. Kumarasamy, M. Yotebieng, M. A. Davies, B. Musick, et al.

<figure><img src="image_1.png" /></figure>

To cite this version:

Julie Jesson, S. Desmonde, C. T. Yiannoutsos, G. Patten, Karen Malateste, et al. Weight-for-age distributions among children with HIV on antiretroviral therapy in the International epidemiology Databases to Evaluate AIDS (IeDEA) multiregional consortium. BMC Research Notes, In press, 13 (1), pp.249. 10.1186/s13104-020-05081-7. doi:10.1186/s13104-020-05081-7

HAL Id: hal-03124341

https://hal.science/hal-03124341

Submitted on 28 Jan 2021

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

# Weight-for-age distributions among children with HIV on antiretroviral therapy in the International epidemiology Databases to Evaluate AIDS (IeDEA) multiregional consortium

Julie Jesson<fnref n="1" />,¹³*†, Sophie Desmonde<fnref n="1" />†, Constantin T. Yiannoutsos², Gabriela Patten³, Karen Malateste⁴,⁵, Stephany N. Duda⁶, Nagalingeswaran Kumarasamy⁷, Marcel Yotebieng⁸, Mary-Ann Davies³, Beverly Musick⁹, Valeriane Leroy<fnref n="1" /> and Andrea Ciaranello¹⁰,¹¹,¹² on behalf of IeDEA

**Abstract**

**Objective:** Pediatric antiretroviral therapy (ART) for children with HIV (CHIV) must be dosed appropriately for children's changing weights as they grow. To inform accurate estimates of ART formulations and doses needed, we described weight-for-age distributions among CHIV on ART in the IeDEA global pediatric collaboration between 2004 and 2016, using data from six regions (East, West, Central, and Southern Africa, Asia-Pacific, and Central/South America and the Caribbean).

**Results:** Overall, 59,862 children contributed to the analysis. Age and weight data were available from 530,080 clinical encounters for girls and 537,894 for boys. For each one-year age stratum from 0 to 15 years, we calculated the proportion of children in each of the weight bands designated by the World Health Organization as relevant to pediatric ART formulations: 0 to <3 kg, 3 to <6 kg, 6 to <10 kg, 10 to <14 kg, 14 to <20 kg, 20 to <25 kg, 25 to <30 kg, 30 to <35 kg, 35 to <40 kg, 40 to <45 kg, 45 to <50 kg, 50 to <55 kg, 55 to <60 kg, and ≥ 60 kg. Data are reported for the entire cohort, as well as stratified by sex and IeDEA region, calendar year of ART use, and duration on ART at time of assessment (< 12 or ≥ 12 months), provided in data tables. These data are critical to improve the accuracy of forecasting and procurement of pediatric ART formulations as the pediatric HIV epidemic and pediatric HIV treatment strategies evolve.

**Keywords:** Pediatric HIV, Pediatric antiretroviral therapy, Antiretroviral formulation, Weight-for-age

**Introduction**

Children with HIV (CHIV) require appropriate dosing of pediatric antiretroviral therapy (ART) to prevent HIV-related morbidity and mortality. HIV programs at national and international levels procure annual quantities of pediatric ART based on forecasts of the number of children likely to require each drug formulation and dose; dosing is weight-based in children < 15 years of age. Accurate forecasting of antiretroviral needs is

<footnote>*Correspondence: julie_jesson@sfu.ca</footnote>

<footnote>†Julie Jesson and Sophie Desmonde contributed equally to the work</footnote>

<footnote n="1">¹ Inserm U1027, Université Paul Sabatier Toulouse 3, Toulouse, France
Full list of author information is available at the end of the article</footnote>
particularly important, because the pediatric antiretroviral market is small. Procurement volume has a large impact on market prices and failure to procure sufficient quantities of antiretroviral medications (ARVs) leads to gaps in treatment access in low-income and middle-income countries [1]. While validated estimates exist of the numbers of children at each age likely to need ART [2], additional information about the weight distribution for CHIV by age are needed to permit accurate forecasts of the medication quantities that will be required. To date, ART forecasts rely on WHO and CDC growth curves for all children in the general population [3–5]. However, children and adolescents living with HIV are often malnourished at the time of initiating ART and their catch-up growth can be delayed even after initiating ART [6–9]. Because of these key differences for CHIV, growth curves derived from the general population likely overestimate weight-for-age among CHIV and therefore may lead to inaccurate estimates of the number of formulations and doses of pediatric ART that will be required globally [10]. Accurate data about volume trends in weight-for-age evolution among ART-treated CHIV are therefore needed to appropriately inform ART forecasting efforts [11].

This study reports a secondary analysis of data from a parent study conducted within the global International epidemiology Databases to Evaluate AIDS (IeDEA) pediatric research consortium (https://www.iedea.org/). The parent study sought to analyze age- and CD4-stratified risks of opportunistic infections and mortality for CHIV before and after ART initiation in six global IeDEA regions [12]. Using the database assembled for the parent study, we conducted a separate analysis, reported here, to evaluate the weight-for-age distributions in CHIV on ART in the IeDEA consortium in order to support accurate forecasting and procurement of pediatric ART formulations.

# Main text

## Methods

We analyzed individual patient data from the six regional pediatric cohorts within IeDEA: Asia-Pacific, West Africa, East Africa, Central Africa, Southern Africa, and the Caribbean, Central, and South America network (CCASAnet) [13]. Using eligibility criteria from the parent study [12], all patients were included if they enrolled into care at age < 24 years, were followed-up at any of the participating IeDEA sites between 2004 and 2016, had a confirmed HIV diagnosis, were ART-naïve at enrolment, and had at least one CD4 count or percent measurement during follow-up. In the current analysis, we limited the dataset to children aged < 15 years, because older youth primarily use adult ARV formulations and doses.

Although clinic protocols vary across the IeDEA consortium, CHIV are usually seen at least every 3 months while on ART. The data were generated during routine care encounters and included region, country, site, patient demographics (sex, date of birth, date of HIV diagnosis if available, and date of enrolment in care), laboratory values (CD4 count, CD4 percent), date of ART initiation, initial ART regimen, date of death, date of last clinical contact, and date of transfer out. Each participating IeDEA region obtained local institutional review board approval to participate. Written informed consent requirements were deferred to the local institutional review boards. The analysis only used de-identified data that had been collected as part of routine clinical care.

For the current study, we used data on weight at each visit as recorded in the medical record. For each one-year age stratum from 0 to 15 years, we calculated the number of children in each of the weight bands designated by the World Health Organization (WHO) to be relevant to pediatric ART formulations: 0 to <3 kg, 3 to <6 kg, 6 to <10 kg, 10 to <14 kg, 14 to <20 kg, 20 to <25 kg, 25 to <30 kg, 30 to <35 kg, 35 to <40 kg, 40 to <45 kg, 45 to <50 kg, 50 to <55 kg, 55 to <60 kg, and ≥ 60 kg. We derived these numbers, and resulting proportions, for the entire cohort of CHIV, total and stratified by sex; we additionally derived numbers and proportions stratified by sex and IeDEA region, calendar year of enrolment (before versus beyond January 1, 2013), and time on ART (< 12 months or ≥ 12 months). Children for whom sex was unknown were excluded from the analysis. Age at each visit was calculated based on the date of birth recorded in the database. A single child contributed multiple weight measurements over time and we deleted outlying measurements based on the following criteria: (1) weight-for-age z-scores (WAZ) > 3 for infants aged < 1 year, WAZ < -8 for children aged < 5 years, WAZ < -6 for children aged 5–10 years, and WAZ > 5 for all ages; (2) two values measured within the same month with a difference greater than 5 kg if age < 5 years, 8 kg if age 5 to < 10 years, and 10 kg if age 10–15 years.

## Results

Overall, 59,862 children and adolescents with HIV contributed to the analysis, of whom 50.7% were females. Demographic information is shown in Table 1. Age and weight data were available from 530,080 clinical encounters for girls and 537,894 clinical encounters for boys. Sex-stratified results for all CHIV in the study are shown in Table 2. Additional tables are included in Additional file 1:

1. Overall population (combined).

2. By sex (Table 2).
3. By IeDEA region, boys.

4. By IeDEA region, girls.

5. By ART duration and sex.

6. By year of visit and sex.

7. By IeDEA region, ART duration, boys.

8. By IeDEA region, ART duration, girls.

9. By IeDEA region, ART duration, < 2013, Boys.

10. By IeDEA region, ART duration, < 2013, Girls.

11. By IeDEA region, ART duration, ≥ 2013, Boys.

12. By IeDEA region, ART duration, ≥ 2013, Girls.

## Limitations

This study is subject to a number of limitations. Several characteristics of patients participating in the IeDEA cohort may lead to overestimation of the weight-for-age distribution of children receiving ART and thus may overestimate the amount of active pharmaceutical ingredient required per child. The first is survivorship bias, because CHIV who survived to initiate ART at IeDEA sites from 2004 to 2016 may have been healthier (and perhaps with higher weights for age) than those who did not. Children in this cohort do not represent a complete cohort of CHIV followed from birth, and there was

<table><caption>**Table 1 Characteristics of the 59,862 children in IeDEA at baseline**</caption><thead><tr><th>Characteristic</th><th></th></tr></thead><tbody><tr><td>Region, n (%)</td><td></td></tr><tr><td>Asia-Pacific</td><td>4004 (6.7)</td></tr><tr><td>CCASAnet</td><td>1502 (2.5)</td></tr><tr><td>Central Africa</td><td>2050 (3.4)</td></tr><tr><td>East Africa</td><td>11,068 (18.5)</td></tr><tr><td>Southern Africa</td><td>36,679 (61.3)</td></tr><tr><td>West Africa</td><td>4559 (7.6)</td></tr><tr><td>Age, median (IQR), years</td><td>6.1 (2.5–9.9)</td></tr><tr><td>Female, n (%)</td><td>30,343 (50.7)</td></tr><tr><td>Year at ART initiation</td><td></td></tr><tr><td>Year, n (%)</td><td></td></tr><tr><td>&lt; 2004</td><td>1729 (2.9)</td></tr><tr><td>2004–2007</td><td>17,821 (29.8)</td></tr><tr><td>2008–2012</td><td>31,272 (52.2)</td></tr><tr><td>2013–2014</td><td>7493 (12.5)</td></tr><tr><td>2015–2016</td><td>1547 (2.6)</td></tr><tr><td>Number of observations by year of visit</td><td></td></tr><tr><td>&lt; 2004</td><td>16,505 (1.5)</td></tr><tr><td>2004–2007</td><td>178,985 (16.8)</td></tr><tr><td>2008–2012</td><td>610,078 (57.1)</td></tr><tr><td>2013–2014</td><td>207,899 (19.5)</td></tr><tr><td>2015–2016</td><td>54,507 (5.1)</td></tr></tbody></table>

CCASAnet the Caribbean, Central and South American Network, ART antiretroviral therapy, IQR interquartile range

likely a high risk of death in children before the age of 2 years who therefore never entered the study. Similarly, a high proportion of CHIV were lost to follow-up during the study period, possibly leaving a healthier cohort to remain in care and with evaluable weights and ages. Nevertheless, these data likely accurately reflect weight-for-age among children who remained on treatment and for whom ARV procurement estimates currently apply, even if they may overestimate weight for the full population of CHIV in need of ART. On the other hand, approximately two-thirds of IeDEA sites are located at university hospitals in capital cities, where the standard of care may be different than in rural areas; if more intensive HIV care is provided, children at IeDEA sites may be healthier than at more rural sites in the same regions [13]. We also note a potential selection bias induced by the parent study, which only included children with available CD4 counts during follow-up, thus excluding the sicker children who may have initiated ART immediately, without their caregivers waiting for CD4 counts. This may also be possibly overestimating weights for ART-treated CHIV.

A second set of limitations may counteract these trends and may underestimate the quantities of active pharmaceutical ingredients needed. For example, before ART was recommended for all CHIV in 2013, it was offered only to the sickest children, potentially introducing an indication bias. This selection bias may particularly apply to older children in the IeDEA cohort, as access to early ART has improved over time for children, so adolescents aged 10–15 years in the future may be in better health than those observed in the IeDEA cohort over the study period reported in this study [14].

Despite these limitations, this dataset is, to our knowledge, the only available source of data about weight-for-age distributions among CHIV treated with ART built on the strength of a large cohort size and broad geographic coverage. Consequently, the resulting estimates and those, more generally, derived from observational cohorts conducted in real-world settings, offer a valuable opportunity to derive data-driven weight-for-age distributions among CHIV [15, 16].

These data were originally pooled to support adequate forecasting and procurement of pediatric ART formulations. Nevertheless, beyond this purpose, data about weight in children may also be helpful to create a secondary-hand framework for observing changes overtime regarding growth on ART, during childhood and adolescence as this has been done in the past [7, 11]. Especially, these data will be useful in refining projections of the number of CHIV who may need specific ARV formulations and doses allowing HIV care and treatment programs to procure sufficient quantities of medications for CHIV, avoiding both medication stock
outs and medication wastage, furthering the critical goal of improving access to ART for CHIV globally [1].

**Supplementary information**

**Supplementary information** accompanies this paper at https://doi.org/10.1186/s13104-020-05081-7.

**Additional file 1.** Weight-for-age distributions among CHIV on ART in the International Epidemiology to evaluate AIDS (leDEA) multiregional consortium - complete tables.

**Abbreviations**

CHIV: Children with HIV; ART: Antiretroviral Therapy; ARV: Antiretroviral medication; leDEA: International epidemiology Databases to Evaluate AIDS; WHO: World Health Organization.

**Acknowledgements**

We gratefully acknowledge all of the children and their families followed up in the participating pediatric centers. We also thank the staff from all participating pediatric centers. We warmly thank all the investigators and pediatric coordinators from the leDEA regions contributing to the project: Asia-Pacific (Annette Sohn), CCASAnet-Latin America (Jorge Pinto and Catherine McGowan), Central Africa (Marcel Yotebieng and Andrew Edmonds), East Africa (Kara Wools-Kaloustian), Southern Africa (Mary-Ann Davies), West Africa (François Dabis and Valériane Leroy), the leDEA Pediatric Working Group (Rachel Vreeman, Chair).

**Authors' contributions**

JJ, SDe, VL, CY, MAD and ALC designed the study and prepared concept sheets for submission to and approval by the leDEA network. KM, BM, GP, NK, SDu and MY provided the data. JJ analyzed the data. SDe, VL, and ALC provided critical feedback on the analysis and interpretation. JJ, SDe, VL and AC drafted the manuscript. JJ and SDe contributed equally to this work. All authors read and approved the final manuscript.

**Funding**

This work was supported by the leDEA Pediatric Methods and Modeling Group (IPM2) through a supplement to the leDEA regional grants by the National Institute Of Child Health & Human Development (NICHD). Research reported in this publication was supported by the US National Institutes of Health. Asia-Pacific: The TREAT Asia Pediatric HIV Observational Database is an initiative of TREAT Asia, a program of amfAR, The Foundation for AIDS Research, with support from the US National Institutes of Health's National Institute of Allergy and Infectious Diseases (NIAID), the *Eunice Kennedy Shriver NICHD*, National Cancer Institute (NCI), National Institute of Mental Health (NIMH), National Institute on Drug Abuse (NIDA), the National Heart, Lung, and Blood Institute (NHLBI), the National Institute on Alcohol Abuse and Alcoholism (NIAAA), the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), and the Fogarty International Center as part of the International Epidemiology Databases to Evaluate AIDS (leDEA; U01AI069907). Caribbean, Central and South America network for HIV epidemiology (CCASAnet) is a member cohort of leDEA (U01AI069923), with support from NIAID, NICHD, NCI, NIMH, NHLBI, NIAAA, and NIDDK). Central Africa research reported in this publication was supported by the NIAID of the National Institutes of Health under Award Number U01AI069299. East African Research reported in this publication was supported by the *Eunice Kennedy Shriver NICHD*, NIDA, NCI, and NIMH, in accordance with the regulatory requirements of the National Institutes of Health under Award Number U01AI069911, East Africa leDEA Consortium. Southern African research reported in this publication was supported by the NIAID of the National Institutes of Health under Award Number U01AI069924. West African Research reported in this publication was supported by the US National Institutes of Health (NIAID, NICHD, NCI and NIMH) under Award Number U01AI069919. Additional support for ALC and SDe was provided by the *Eunice Kennedy Shriver NICHD*; R01 HD079214. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The content of this publication is solely the

responsibility of the authors and does not necessarily represent the official views of any of the governments or institutions mentioned above.

**Availability of data and materials**

The datasets generated during and/or analyzed during the current study are not publicly available due to legal and ethics restrictions. The principles of collaboration of the leDEA cohort consortium and the regulatory requirements of the individual member site and country institutional review boards require the submission and approval of a project concept sheet by the leDEA Executive Committee, and the principal investigators and local site investigators from participating regions. leDEA promotes the signing of a Data Use Agreement before HIV clinical data can be released. Individuals interested in obtaining access to data may contact leDEA for additional information at https://www.iedea.org/home/who-we-are/. The project concept sheet template and other research-related resources are available at https://www.iedea.org/resources/.

**Ethics approval and consent to participate**

The leDEA data analyzed in this manuscript were collected from over 300 sites in 35 countries. Each of the local sites and regional cohort data and coordinating centers has their own IRBs under which they are authorized to collect and analyze research data. These IRBs are all registered with the US Officer of Human Research Protections of the US Department of Health and Human Services, and local approval by these IRBs is required prior to receiving leDEA funding. This work was also approved by the Partners Healthcare IRB (Boston, MA).

**Consent for publication**

Not applicable (no individual patient data are reported).

**Competing interests**

The authors declare that they have no competing interests.

**Author details**

¹ Inserm U1027, Université Paul Sabatier Toulouse 3, Toulouse, France. ² Indiana University, Fairbanks School of Public Health, Indianapolis, IN, USA. ³ School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa. ⁴ Inserm U1219, Bordeaux, France.

⁵ Bordeaux Population Health Center, Université de Bordeaux, Bordeaux, France. ⁶ Vanderbilt University Medical Center, Nashville, TN, USA. ⁷ Chennai Antiviral Research and Treatment Clinical Research Site (CART CRS), VHS-Infectious Diseases Medical Centre, VHS, Chennai, India. ⁸ Division of Epidemiology, The Ohio State University, College of Public Health, Columbus, OH, USA.

⁹ Indiana University School of Medicine, Indianapolis, IN, USA. ¹⁰ The Medical Practice Evaluation Center, Boston, MA, USA. ¹¹ The Division of General Internal Medicine, Department of Medicine, Harvard Medical School, Boston, MA, USA.

¹² Massachusetts General Hospital, Boston, MA, USA. ¹³ Inserm, UMR 1027 - Epidemiologie et analyses en santé publique: risques, maladies chroniques et handicaps - Université Paul Sabatier Toulouse 3, Equipe 2: Axe santé de l'enfant et de l'adolescent en Afrique, 37 Allées Jules Guesde, 31073 Toulouse Cedex 7, France, Toulouse Cedex 7, France.

Received: 3 December 2019 Accepted: 3 May 2020

Published online: 24 May 2020

**References**

1. Lee JSF, Sagaon Teyssier L, Dongmo Gnimfack B, Collins IJ, Lallemant M, Perriens J, et al. An analysis of volumes, prices and pricing trends of the pediatric antiretroviral market in developing countries from 2004 to 2012. BMC Pediatr. 2016;16:41.

2. World Health Organisation. UNAIDS DATA 2019 2019. https://www.unaid s.org/sites/default/files/media_asset/2019-UNAIDS-data_en.pdf.

3. Doherty K, Essajee S, Penazzato M, Holmes C, Resch S, Ciaramello A. Estimating age-based antiretroviral therapy costs for HIV-infected children in resource-limited settings based on World Health Organization weight-based dosing recommendations. BMC Health Serv Res. 2014;14:201.

4. World Health Organisation Multicentre Growth Reference Study Group. WHO Child Growth Standards: Length/Height-for-age, Weight-for-age, Weight-for-Length, Weight-for-Height and Body Mass Index-for-age:
Methods and Development. 2006. http://www.who.int/childgrowth/
standards/technical_report/en/index.html.

5. Center for Disease Control and Prevention (CDC). Data Table of Weight-for-age Charts 2001. http://www.cdc.gov/growthcharts/html_charts/wtage.htm.

6. McGrath CJ, Diener L, Richardson BA, Peacock-Chambers E, John-Stewart GC. Growth reconstitution following antiretroviral therapy and nutritional supplementation: systematic review and meta-analysis. AIDS. 2015;29(15):2009-23.

7. Jesson J, Koumakpai S, Diagne NR, Amorissani-Folquet M, Koueta F, Aka A, et al. Effect of age at antiretroviral therapy initiation on catch-up growth within the first 24 months among HIV-infected children in the leDEA West African Pediatric Cohort. Pediatr Infect Dis J. 2015;34(7):e159-68.

8. Gsponer T, Weigel R, Davies M-A, Bolton C, Moultrie H, Vaz P, et al. Variability of growth in children starting antiretroviral treatment in southern Africa. Pediatrics. 2012;130(4):e966-77.

9. Yotebieng M, Van Rie A, Moultrie H, Meyers T. Six-month gains in weight, height, and CD4 predict subsequent antiretroviral treatment responses in HIV-infected South African children. AIDS. 2011;24(1):139-46.

10. World Health Organization, United Nations Children's Fund. WHO child growth standards and the identification of severe acute malnutrition in infants and children. Geneva: World Health Organization; 2009.

11. Yotebieng M, Meyers T, Behets F, Davies MA, Keiser O, Ngonyani KZ, et al. Age-specific and sex-specific weight gain norms to monitor antiretroviral therapy in children in low-income and middle-income countries. AIDS. 2015;29(1):101-9.

12. Desmonde S, Nielan A, Malateste K, Musick B, Patten GE, Duda SN, et al. Age-stratified rates of mortality and key clinical events in youth ages 0-24 years in the multiregional leDEA network. In: 9th international workshop HIV pediatrics; 20-21 July 2017; Paris, France. 2017.

13. leDEA Pediatric Working Group. A survey of paediatric HIV programmatic and clinical management practices in Asia and sub-Saharan Africa—the International epidemiologic Databases to Evaluate AIDS (leDEA). J Int AIDS Soc. 2013;16(1):17998.

14. Desmonde S, Tanser F, Vreeman R, Takassi E, Edmonds A, Lumbiganon P, et al. Access to antiretroviral therapy in HIV-infected children aged 0–19 years in the International Epidemiology Databases to Evaluate AIDS (IeDEA) Global Cohort Consortium, 2004–2015: a prospective cohort study. PLoS Med. 2018;15(5):e1002565.

15. IeDEA Pediatric Working Group. Taking a critical look at the UNAIDS global estimates on paediatric and adolescent HIV survival and death. J Int AIDS Soc. 2017;20(1):21952.

16. Sohn AH, Judd A, Mofenson L, Vicari M, Jerene D, Leroy V, et al. Using observational data to inform HIV policy change for children and youth. J Acquir Immune Defic Syndr. 2018;78(Suppl 1):S22-6.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Ready to submit your research? Choose BMC and benefit from:

* fast, convenient online submission

* thorough peer review by experienced researchers in your field

* rapid publication on acceptance

* support for research data, including large and complex data types

* gold Open Access which fosters wider collaboration and increased citations

* maximum visibility for your research: over 100M website views per year

At BMC, research is always in progress.

Learn more biomedcentral.com/submissions

<figure><img src="image_4.png" /></figure>