RESEARCH ARTICLE
The epidemiology of adolescents living with
perinatally acquired HIV: A cross-region global
cohort analysis
The Collaborative Initiative for Paediatric HIV Education and Research (CIPHER) Global
Cohort Collaboration¶, Amy L. Slogrove1, Michael Schomaker1, Mary-Ann Davies1,
Paige Williams2, Suna Balkan3, Jihane Ben-Farhat3, Nancy Calles4, Kulkanya Chokephaibulkit5,
Charlotte Duff6, Tanoh François Eboua7, Adeodata Kekitiinwa-Rukyalekere8, Nicola Maxwell1,
Jorge Pinto9, George Seage, III2, Chloe A. Teasdale10, Sebastian Wanless4,
a1111111111
Josiane Warszawski11, Kara Wools-Kaloustian12, Marcel Yotebieng13, Venessa Timmerman1,
a1111111111 Intira J. Collins6, Ruth Goodall6, Colette Smith6, Kunjal Patel2, Mary Paul4, Diana Gibb6,
a1111111111 Rachel Vreeman12, Elaine J. Abrams10, Rohan Hazra14, Russell Van Dyke15, Linda-
a1111111111 Gail Bekker16, Lynne Mofenson17, Marissa Vicari18, Shaffiq Essajee19, Martina Penazzato20,
a1111111111 Gabriel Anabwani21, Edith Q. Mohapi22, Peter N. Kazembe23, Makhosazana Hlatshwayo24,
Mwita Lumumba25, Tessa Goetghebuer26, Claire Thorne27, Luisa Galli28, Annemarie van
Rossum29, Carlo Giaquinto30, Magdalena Marczynska31, Laura Marques32, Filipa Prata33,
Luminita Ene34, Liubov Okhonskaia35, Pablo Rojo36, Claudia Fortuny37, Lars Naver38,
Christoph Rudin39, Sophie Le Coeur40,41, Alla Volokha42, Vanessa Rouzier43, Regina Succi44,
OPENACCESS Annette Sohn45, Azar Kariminia46, Andrew Edmonds47, Patricia Lelo48, Samuel Ayaya49,
Patricia Ongwen50, Laura F. Jefferys51, Sam Phiri52, Mwangelwa Mubiana-Mbewe53,
Citation: The Collaborative Initiative for Paediatric
Shobna Sawry54,55, Lorna Renner56, Mariam Sylla57, Mark J. Abzug58, Myron Levin58,
HIV Education and Research (CIPHER) Global
James Oleske59, Miriam Chernoff2, Shirley Traite2, Murli Purswani60, Ellen G. Chadwick61,
Cohort Collaboration, Slogrove AL, Schomaker M,
Ali Judd6‡*, Valériane Leroy62‡*
Davies M-A, Williams P, Balkan S, et al. (2018) The
epidemiology of adolescents living with perinatally 1 Center for Infectious Diseases Epidemiology and Research, University of Cape Town, Cape Town, South
acquired HIV: A cross-region global cohort Africa, 2 Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America,
analysis. PLoS Med 15(3): e1002514. https://doi. 3 Epicentre, Médecins Sans Frontières, Paris, France, 4 Baylor International Pediatric AIDS Initiative, Texas
org/10.1371/journal.pmed.1002514 Children’s Hospital-USA, Houston, Texas, United States of America, 5 Faculty of Medicine, Siriraj Hospital,
Mahidol University, Bangkok, Thailand, 6 MRC Clinical Trials Unit at University College London, London, United
Academic Editor: Steven G. Deeks, San Francisco Kingdom, 7 Yopougon University Hospital, University Félix Houphouët-Boigny, Abidjan, Côte d’Ivoire, 8 Baylor
General Hospital, UNITED STATES International Pediatric AIDS Initiative, Kampala, Uganda, 9 School of Medicine, Federal University of Minas
Gerais, Belo Horizonte, Brazil, 10 ICAP at Columbia University Mailman School of Public Health, New York, New
Received: May 30, 2017 York, United States of America, 11 Inserm (French Institute of Health and Medical Research), CESP UMR
Villejuif, France, 12 Indiana University School of Medicine, Indianapolis, Indiana, United States of America,
Accepted: January 24, 2018
13 College of Public Health, Ohio State University, Columbus, Ohio, United States of America, 14 National
Published: March 1, 2018 Institute of Child Health and Human Development (NICHD), US National Institutes of Health, Rockville,
Maryland, United States of America, 15 Tulane University, New Orleans, Louisiana, United States of America,
Copyright: © 2018 The Collaborative Initiative for 16 Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa, 17 Elizabeth Glaser
Paediatric HIV Education and Research (CIPHER) Pediatric AIDS Foundation, Washington, DC, United States of America, 18 International AIDS Society, Geneva,
Global Cohort Collaboration et al. This is an open Switzerland, 19 UNICEF, New York, New York, United States of America, 20 World Health Organization,
access article distributed under the terms of the Geneva, Switzerland, 21 Baylor International Pediatric AIDS Initiative, Gaborone, Botswana, 22 Baylor
Creative Commons Attribution License, which International Pediatric AIDS Initiative, Maseru, Lesotho, 23 Baylor International Pediatric AIDS Initiative,
permits unrestricted use, distribution, and Lilongwe, Malawi, 24 Baylor International Pediatric AIDS Initiative, Mbabane, Swaziland, 25 Baylor International
Pediatric AIDS Initiative, Mbeya, Tanzania, 26 Hospital St Pierre Cohort, Bruxelles, Belgium, 27 Institute of Child
reproduction in any medium, provided the original
Health, University College London, London, United Kingdom, 28 Department of Health Sciences, University of
author and source are credited.
Florence, Florence, Italy, 29 Erasmus MC University Medical Center Rotterdam-Sophia Children’s Hospital,
Data Availability Statement: Data are accessible in Rotterdam, the Netherlands, 30 PENTA Foundation, Padova, Italy, 31 Medical University of Warsaw, Hospital
principle by applying to the CIPHER Cohort of Infectious Diseases in Warsaw, Warsaw, Poland, 32 Centro Hospitalar do Porto, Porto, Portugal, 33 Hospital
de Santa Maria/CHLN, Lisbon, Portugal, 34 Victor Babes Hospital, Bucharest, Romania, 35 Republican
Collaboration Data Centres. The CIPHER Cohort
Hospital of Infectious Diseases, St Petersburg, Russian Federation, 36 Hospital Doce de Octubre, Madrid,
Collaboration is a multi-network, multi-site
Spain, 37 Hospital Sant Joan de Déu, Universitat de Barcelona, Barcelona, Spain, 38 Karolinska University
collaboration and this analysis combined data from
Hospital, Stockholm, Sweden, 39 University Children’s Hospital, Basel, Switzerland, 40 Institut de Recherche
different sites. The data do not belong to the pour le Développement (IRD) 174/PHPT, Faculty of Associated Medical Sciences, Chiang Mai University,
CIPHER Cohort Collaboration itself, but data Chiang Mai, Thailand, 41 Institut National d’Etudes Démograhiques (Ined), F-75020 Paris, France, 42 Shupyk
ownership remains with the participating sites.
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 1 / 21
The epidemiology of adolescents living with perinatally acquired HIV
Each site has approval from its own local National Medical Academy of Postgraduate Education, Kiev, Ukraine, 43 GHESKIO Center, Port-au-Prince,
Institutional Review Board to collect routine data Haiti, 44 Universidade Federal de São Paulo, São Paulo, Brazil, 45 TREAT Asia/amfAR, Bangkok, Thailand,
on patients and to transfer those data 46 Kirby Institute, UNSW, Sydney, Australia, 47 Gillings School of Global Public Health, The University of
anonymously to the CIPHER Cohort Collaboration North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America, 48 Pediatric Hospital
Kalembe Lembe, Lingwala, Kinshasa, Democratic Republic of Congo, 49 Academic Model Providing Access
Project data center. For some sites and networks,
to Healthcare (AMPATH), Eldoret, Kenya, 50 Family AIDS Care and Education Services, Kenya Medical
IRB approval for use of this data is restricted to the
Research Institute, Kisumu, Kenya, 51 SolidarMed Lesotho, Mozambique and Zimbabwe, Lucerne, Switzerland,
specific protocols approved in order to protect
52 Lighthouse Trust Clinic, Lilongwe, Malawi, 53 Center for Infectious Disease Research in Zambia, Lusaka,
patient identities. Requests for access to data can Zambia, 54 Wits Reproductive Health and HIV Institute, Faculty of Health Sciences, University of the
be directed to the International AIDS Society Witwatersrand, Johannesburg, South Africa, 55 Harriet Shezi Children’s Clinic, Chris Hani Baragwanath
CIPHER, Samantha Hodgetts, email: samantha. Hospital, Johannesburg, South Africa, 56 University of Ghana School of Medicine and Dentistry, Accra, Ghana,
hodgetts@iasociety.org. 57 CHU Gabriel Touré, Bamako, Mali, 58 University of Colorado School of Medicine and Children’s Hospital
Colorado, Aurora, Colorado, United States of America, 59 Rutgers New Jersey Medical School, Newark, New
Funding: IAS-CIPHER (http://www.iasociety.org/ Jersey, United States of America, 60 Bronx-Lebanon Hospital Center (Icahn School of Medicine at Mount Sinai),
CIPHER) is made possible through funding from Bronx, New York, United States of America, 61 Feinberg School of Medicine, Northwestern University,
CIPHER Founding Sponsor ViiV Healthcare (https:// Evanston, Illinois, United States of America, 62 Inserm (French Institute of Health and Medical Research), UMR
www.viivhealthcare.com) and Janssen (http:// 1027 Université Toulouse 3, Toulouse, France
www.janssen.com). Individual networks
contributing to the CIPHER Cohort Collaboration ‡ These authors contributed equally to this work as project cochairs and are corresponding authors.
have received the following financial support: ¶ Membership of the Collaborative Initiative for Paediatric HIV Education and Research (CIPHER) Global Cohort
Collaboration is listed in S1 Text.
CCASAnet receives funding from the United States
* a.judd@ucl.ac.uk (AJ); valeriane.leroy@inserm.fr (VL)
(US) National Institutes of Health (NIH) (https://
www.nih.gov) (U01AI069923); IeDEA Asia Pacific
receives funding from the US NIH (U01AI069907);
IeDEA Central Africa receives funding from the US Abstract
NIH (U01AI096299-07); IeDEA East Africa receives
funding from the US NIH (U01-A1069911); IeDEA
Southern Africa receives funding from the US NIH Background
(U01-AI069924); IeDEA West Africa receives
funding from the US NIH (U01AI069919); Globally, the population of adolescents living with perinatally acquired HIV (APHs) continues
IMPAACT P1074 receives funding from the US NIH to expand. In this study, we pooled data from observational pediatric HIV cohorts and cohort
(UM1AI068616 and US NIH UM1AI068632);
networks, allowing comparisons of adolescents with perinatally acquired HIV in “real-life”
PHACS receives funding from the US NIH (U01
HD052102 and US NIH U01 HD052104); the settings across multiple regions. We describe the geographic and temporal characteristics
Optimal Models project was supported by the and mortality outcomes of APHs across multiple regions, including South America and the
President’s Emergency Plan for AIDS Relief Caribbean, North America, Europe, sub-Saharan Africa, and South and Southeast Asia.
(PEPFAR) through the Centers for Disease Control
and Prevention (https://www.pepfar.gov) under the
terms of Cooperative Agreement Number Methods and findings
5U62PS223540 and 5U2GPS001537. EPPICC Through the Collaborative Initiative for Paediatric HIV Education and Research (CIPHER),
receives funding from EuroCoord no260694
individual retrospective longitudinal data from 12 cohort networks were pooled. All children
(http://www.eurocoord.net, PENTA Foundation
(http://penta-id.org). EPPICC was partly funded by infected with HIV who entered care before age 10 years, were not known to have horizon-
the Medical Research Council (https://www.mrc.ac. tally acquired HIV, and were followed up beyond age 10 years were included in this analysis
uk), programme number MC_UU_12023/26. conducted from May 2016 to January 2017. Our primary analysis describes patient and
Individual cohorts contributing to EPPICC receive
treatment characteristics of APHs at key time points, including first HIV-associated clinic
the following support: the ATHENA database is
maintained by Stichting HIV Monitoring and visit, antiretroviral therapy (ART) start, age 10 years, and last visit, and compares these
supported by a grant from the Dutch Ministry of characteristics by geographic region, country income group (CIG), and birth period. Our sec-
Health, Welfare and Sport through the Centre for
ondary analysis describes mortality, transfer out, and lost to follow-up (LTFU) as outcomes
Infectious Disease Control of the National Institute
for Public Health and the Environment. CoRISPE- at age 15 years, using competing risk analysis. Among the 38,187 APHs included, 51%
cat receives financial support from the Instituto de were female, 79% were from sub-Saharan Africa and 65% lived in low-income countries.
Salud Carlos III through the Red Temática de APHs from 51 countries were included (Europe: 14 countries and 3,054 APHs; North Amer-
Investigación Cooperativa en Sida. CoRISPE-s and
ica: 1 country and 1,032 APHs; South America and the Caribbean: 4 countries and 903
Madrid Cohort is partially funded by the Fundación
para la Investigación y Prevención de SIDA en APHs; South and Southeast Asia: 7 countries and 2,902 APHs; sub-Saharan Africa, 25
España (FIPSE) (FIPSE 3608229/09, FIPSE countries and 30,296 APHs). Observation started as early as 1982 in Europe and 1996 in
240800/09, FIPSE 361910/10), Red Temática de sub-Saharan Africa, and continued until at least 2014 in all regions. The median
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 2 / 21
The epidemiology of adolescents living with perinatally acquired HIV
Investigación en SIDA (RED RIS) is supported by (interquartile range [IQR]) duration of adolescent follow-up was 3.1 (1.5–5.2) years for the
Instituto de Salud Carlos III (ISCIII) (RD12/0017/ total cohort and 6.4 (3.6–8.0) years in Europe, 3.7 (2.0–5.4) years in North America, 2.5
0035 and RD12/0017/0037) project as part of the
(1.2–4.4) years in South and Southeast Asia, 5.0 (2.7–7.5) years in South America and the
Plan R+D+I and cofinanced by ISCIII-Subdirección
General de Evaluación and Fondo Europeo de Caribbean, and 2.1 (0.9–3.8) years in sub-Saharan Africa. Median (IQR) age at first visit dif-
Desarrollo Regional (FEDER), Mutua Madrileña fered substantially by region, ranging from 0.7 (0.3–2.1) years in North America to 7.1 (5.3–
2012/0077, Gilead Fellowship (www.gilead.com)
8.6) years in sub-Saharan Africa. The median age at ART start varied from 0.9 (0.4–2.6)
2013/0071, FIS PI15/00694, CoRISpe (RED RIS
RD06/0006/0035 y RD06/0006/0021). The Swiss years in North America to 7.9 (6.0–9.3) years in sub-Saharan Africa. The cumulative inci-
HIV Cohort Study is supported by the Swiss dence estimates (95% confidence interval [CI]) at age 15 years for mortality, transfers out,
National Science Foundation (grant #148522) and and LTFU for all APHs were 2.6% (2.4%–2.8%), 15.6% (15.1%–16.0%), and 11.3%
by the SHCS research foundation. Ukraine
(10.9%–11.8%), respectively. Mortality was lowest in Europe (0.8% [0.5%–1.1%]) and high-
Paediatric HIV Cohort is supported by the PENTA
Foundation (http://penta-id.org). CHIPS is funded est in South America and the Caribbean (4.4% [3.1%–6.1%]). However, LTFU was lowest in
by the NHS (London Specialised Commissioning South America and the Caribbean (4.8% [3.4%–6.7%]) and highest in sub-Saharan Africa
Group, https://www.england.nhs.uk/commissi (13.2% [12.6%–13.7%]). Study limitations include the high LTFU rate in sub-Saharan Africa,
oning/spec-services/) and has received additional
which could have affected the comparison of mortality across regions; inclusion of data only
support from Bristol-Myers Squibb (https://www.
bms.com), Boehringer Ingelheim (https://www. for APHs receiving ART from some countries; and unavailability of data from high-burden
boehringer-ingelheim.com), GlaxoSmithKline countries such as Nigeria.
(https://www.gsk.com), Roche (www.roche.com),
Abbott (www.abbott.com), and Gilead Sciences
Conclusion
(www.gilead.com). The MRC Clinical Trials Unit at
UCL is supported by the Medical Research Council To our knowledge, our study represents the largest multiregional epidemiological analysis
(https://www.mrc.ac.uk) programme number
of APHs. Despite probable under-ascertained mortality, mortality in APHs remains substan-
MC_UU_12023/26. No funding bodies had any role
in study design, data collection and analysis, tially higher in sub-Saharan Africa, South and Southeast Asia, and South America and the
decision to publish, or preparation of the Caribbean than in Europe. Collaborations such as CIPHER enable us to monitor current
manuscript. global temporal trends in outcomes over time to inform appropriate policy responses.
Competing interests: I have read the journal’s
policy and the authors of this manuscript have the
following competing interests: AS’s institution
receives research and travel funding from ViiV
Healthcare. CT has participated in an advisory Author summary
board for ViiV Healthcare and received research
grants from the European Commission, UK
Why was this study done?
Medical Research Council, Public Health England,
PENTA Foundation, Abbvie, and ViiV. CT is on the
• With increasing access to antiretroviral therapy across the globe, children with HIV
Advisory Board of the Antiretroviral Pregnancy
Registry, the Board of the PENTA Foundation, and acquired around the time of birth or through breastfeeding (perinatally acquired HIV)
the UK Infectious Diseases in Pregnancy Screening are surviving into adolescence. However, globally, adolescents living with perinatally
Advisory Group. MV’s work at CIPHER is funded acquired HIV experience poorer HIV-related outcomes compared to younger children
through Unrestricted Educational grants received and adults with HIV, dying more often and experiencing greater challenges in terms of
from ViiV Healthcare and Janssen to the
treatment adherence and staying in care.
International AIDS Society. CS has received
personal payment for preparation of educational • A direct comparison of outcomes for adolescents living with perinatally acquired HIV
materials for Gilead Sciences and ViiV Healthcare.
across multiple regions of the world has not previously been conducted, yet such an
JW’s institution has received academic grants from
understanding is required to inform the appropriate policy responses to meet the needs
the INSERM-ANRS for cohorts of JW’s
responsibility involved in the study. SW receives a of this dynamic and complex population of adolescents.
fee from Baylor International Pediatric AIDS
• The Collaborative Initiative for Paediatric HIV Education and Research (CIPHER)
Initiative for consultancy services related to
research. MJA receives funding from NIH to global project describes for the first time, as far as we are aware, the global epidemiology
perform research in the IMPAACT network. LGB is of adolescents living with perinatally acquired HIV in terms of geographic and temporal
guest editor for the PLOS Medicine HIV Collection. trends and compares mortality, transfer, and loss to follow-up between 10 and 15 years
of age across geographic regions, country income groups, and birth cohorts.
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 3 / 21
The epidemiology of adolescents living with perinatally acquired HIV
Abbreviations: aHR, adjusted hazard ratio; APH,
adolescent living with perinatally acquired HIV; What did the researchers do and find?
ART, antiretroviral therapy; BIPAI, Baylor
International Pediatric AIDS Initiative at Texas • Among 38,000 adolescents living with perinatally acquired HIV, 79% of whom were liv-
Children’s Hospital; CCASAnet, Caribbean, Central ing in sub-Saharan Africa.
and South America Network for HIV Research; CI,
confidence interval; CIG, country income group; • Analysis by country income group suggested that patients in high-income countries
CIPHER, Collaborative Initiative for Paediatric HIV (North America and Europe) had younger age, higher CD4 percent, and less impaired
Education and Research; EPPICC, European
height when starting antiretroviral therapy compared to middle- or low-income
Pregnancy and Paediatric HIV Cohort
countries.
Collaboration; HAZ, height-for-age Z-score; HR,
hazard ratio; IeDEA, International Epidemiology • Lost to follow-up rate was lowest in South America and the Caribbean and highest in
Databases to Evaluate AIDS; IPW, inverse
sub-Saharan Africa.
probability weighting; IQR, interquartile range;
LTFU, lost to follow-up; MI, multiple imputation; • HIV-associated mortality during adolescence was substantially higher in sub-Saharan
MSF, Médecins Sans Frontières; PHACS AMP,
Africa, South and Southeast Asia, and South America and the Caribbean than in
Pediatric HIV/AIDS Cohort Study Adolescent
Europe.
Master Protocol; UCT HREC, University of Cape
Town Health Research Ethics Committee; uHR,
unadjusted hazard ratio; WHO, World Health
What do these findings mean?
Organization.
• Although the population of adolescents living with perinatally acquired HIV is likely to
decline in the future due to declining new perinatally acquired HIV infections, there is
still much work to be done to achieve equality in health and survival for all adolescents
living with perinatally acquired HIV, irrespective of geographic location.
• Collaborations such as CIPHER are useful to monitor current global temporal trends in
outcomes of adolescents living with perinatally acquired HIV over time to inform and
guide policy responses.
Introduction
It is estimated that almost 2.1 million (uncertainty bounds 1.4–2.7 million) adolescents aged
10–19 years are living with either perinatally or horizontally acquired HIV [1,2]. Prior to 2005,
children perinatally infected with HIV in most of the world had poor access to antiretroviral
therapy (ART), with high mortality during infancy and poor survival beyond childhood [3].
With the expansion of effective ART initially in Europe and North America, subsequently in
South America and Asia, and now in Africa, the population of children living with perinatally
acquired HIV surviving into adolescence and early adulthood is growing [1,4,5].
By the time children perinatally infected with HIV reach the developmental transition
period of adolescence, they have been living for a decade with a chronic disease that even with
ART treatment can still result in substantial morbidity [6]. Globally, it is recognized that ado-
lescents living with perinatally acquired HIV (APHs) experience poorer HIV-related outcomes
compared to younger children and adults, including higher mortality and virologic treatment
failure rates and poorer retention in care [1,7–15]. Studies assessing the outcomes of APHs
over time and across geographic and economic settings are limited [16]. Based on studies in
adults, after 2 years on ART, HIV-associated mortality in South Africa approached that in the
United States, and the differential between South Africa and Europe was substantially reduced
[17]. As the global community pursues attainment of the Sustainable Development Goals by
2030, particularly to ensure healthy lives and promote wellbeing for all at all ages (Goal 3), to
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 4 / 21
The epidemiology of adolescents living with perinatally acquired HIV
achieve gender equality (Goal 5), and to reduce inequality within and among countries (Goal
10), multiregional direct comparisons of APH outcomes can inform the appropriate policy
responses to meet the needs of this dynamic and complex population of adolescents living
with HIV [18].
The primary objective of this Collaborative Initiative for Paediatric HIV Education and
Research (CIPHER) global project was to describe the global epidemiology of APH in terms of
geographic and temporal trends of patient and treatment characteristics at entry into care,
ART start, entry into adolescence (age 10 years), and last visit. Our secondary objective was to
compare the outcomes of mortality, transfer out, and lost to follow-up (LTFU) between 10 and
15 years of age across regions, country income groups (CIGs), and birth cohorts.
Methods
Primary data collection by all participating networks was approved by their respective research
ethics boards of authority, and consent or assent for study participation was provided by par-
ticipants as required. The pooling of data and analysis at the UCT data center was approved by
the University of Cape Town Health Research Ethics Committee (UCT HREC reference 264/
2014). The study concept and a priori analysis plan are available in supplementary material (S1
Analysis Plan). All analyses were prespecified.
Study methods
The CIPHER Cohort Collaboration is a global network of observational pediatric HIV cohorts
or cohort networks convened by CIPHER of the International AIDS Society. The following 12
cohort networks contributed data to this collaborative project: Baylor International Pediatric
AIDS Initiative at Texas Children’s Hospital (BIPAI); European Pregnancy and Paediatric
HIV Cohort Collaboration (EPPICC); International Epidemiology Databases to Evaluate
AIDS (IeDEA)—Asia Pacific; IeDEA—Central Africa; IeDEA—East Africa; IeDEA—Southern
Africa; IeDEA—West Africa; Caribbean, Central and South America Network for HIV
Research (CCASAnet); Pediatric Late Outcomes Protocol (PACTG/IMPAACT 219/219c);
Prospective Surveillance Study of Long-term Outcomes in HIV-infected Infants, Children and
Adolescents (IMPAACT P1074); Médecins Sans Frontières (MSF) Pediatric Cohorts; Pediatric
HIV/AIDS Cohort Study Adolescent Master Protocol (PHACS AMP); and Identifying Opti-
mal Models for Care in Africa (Optimal Models-ICAP). The data contributed by the networks
were drawn from a range of care settings, including dedicated research cohorts, routine care
cohorts, and programmatic services. Using a standardized data transfer protocol based on the
HIV Cohorts Data Exchange Protocol [19] and following quality checks and queries at the cen-
tral University of Cape Town data center, individual-level data on 183,119 children infected
with HIV were merged in May 2016. Participants contributed data to only a single network
and there was no duplication of participants amongst networks.
Analytic methods
We conducted a retrospective cohort analysis. APHs were defined as children infected with
HIV with at least one documented HIV care visit prior to age 10 years, as a proxy for perina-
tally acquired HIV, and as having at least one additional HIV care visit after 10 years of age.
Children with known nonvertical routes of HIV infection, e.g., horizontal transmission from
blood products, unsafe injections, or sexual abuse, were excluded. Our primary analysis
described patient and treatment characteristics of APH at key time points, including first
HIV-associated clinic visit, ART start, age 10 years, and last visit, and compared these
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 5 / 21
The epidemiology of adolescents living with perinatally acquired HIV
characteristics by geographic region, CIG, and birth cohort. Observation time was censored at
19 years of age in adolescents with follow-up beyond this age.
The first visit was defined as the first recorded date in the database of any contact with a
healthcare facility for HIV-related care, and first visit measurements (height, CD4 T lympho-
cyte counts and percentages, and HIV viral load) were taken as the closest measurement to the
first visit date but could be no later than 182 days after the first visit. If ART was started within
182 days of the first visit, only measurements up to 14 days after ART start were considered.
The date of ART start was defined as the earliest date in the network database of initiation of
any two antiretroviral drugs prior to the year 2000 or three or more antiretroviral drugs from
the year 2000 or later. Measurements at ART start were taken as those closest to the ART start
date but limited to a window of 182 days prior to or 14 days after ART start. Measurements at
age 10 years were taken as those closest to the child’s 10th birthday, limited to a window of 182
days either side of the 10th birthday. The last visit was defined as the last date of any recorded
visit, laboratory test, or ART record. Measurements at the last visit were taken as those closest
to the last visit date, within a window of 18 months prior to the last visit date, to allow for only
annual monitoring in stable patients on ART. It is possible for there to be overlap, with indi-
vidual measurements classified as occurring at more than 1 time point, e.g., a measurement
classified as a first visit measurement can also be classified as an ART start measurement and
similarly for measurements at age 10 years and last visit. World Health Organization (WHO)
height-for-age Z-scores (HAZs) were calculated for APHs in all regions from the measured
heights using the WHO “igrowup_restricted” Stata macro for HAZ up to 5 years of age [20]
and the “who2007” Stata macro for HAZ from 5–19 years of age [21]. Stunting was defined as
HAZ < −2 standard deviations from the mean. Viral suppression was considered as an HIV
viral load measurement of less than 400 copies/ml or less than the level of detection of the test
at the time, if greater than 400 copies/ml. Geographic regions were categorized as Europe,
North America, South America and the Caribbean, South and Southeast Asia, and sub-Saha-
ran Africa. CIGs were assigned according to World Bank CIG classification for the median
year of first visit for each country [22]. Birth cohorts were categorized as born prior to 1995,
born between 1995 and 1999, and born between 2000 and 2005.
Our secondary analysis focused on patient outcomes between 10 and 15 years of age and
classified as mortality, transfer out, LTFU, or alive and retained in care. Mortality included all-
cause mortality, as reported in the database. Transfer out included documented transfer to a
different HIV care site for any reason. LTFU was defined as no observed visit for more than
365 days before the last observed visit for the cohort. APHs classified as LTFU were censored
365 days after their last observed visit. APHs considered to be alive and in care at database clo-
sure were those not known to have died or transferred and with an observed visit within 365
days prior to the last visit for the cohort. Cumulative incidence functions for the outcomes
mortality, transfer out, and LTFU at 15 years of age were calculated using competing risks
analysis for the whole cohort as well as by region, CIG, and birth period, with person-time
accruing from age 10 years [23]. Cumulative incidence functions for birth cohorts stratified
separately by region or by CIG were calculated for the outcomes at 13 years of age due to few
APHs in the most recent birth cohort having reached the age of 15 years. Transfer out and
LTFU were both considered to be competing risks for mortality rather than censoring events.
This approach was chosen because the survival distribution of adolescents transferred out or
LTFU is likely to be different to those retained in care, with better survival in stable transferred
patients and poorer survival in patients LTFU and possibly no longer on ART [23]. For com-
parison, cumulative mortality estimates at 15 years of age were also calculated using the
Kaplan-Meier product limit estimator.
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 6 / 21
The epidemiology of adolescents living with perinatally acquired HIV
Mortality hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for geo-
graphic regions using Cox proportional hazard models, with Europe as the reference group.
Continuous variables, including age, CD4 count, and CD4 percent were included in the Cox
models as continuous variables after confirming a linear relationship with mortality. Propor-
tionality assumptions were evaluated using the Schoenfeld test. Adjusted HRs (aHRs) were cal-
culated, adjusting for baseline differences between regions. Missing CD4 and height
measurements were imputed for the multivariable models using multiple imputation (MI) by
chained equations [24]. The imputation model contained all measured variables and used pre-
dictive mean matching for CD4 counts. Imputation of missing CD4 measurements was per-
formed for all countries and subsequently also restricted to only countries with at least 50 CD4
measurements at first visit or, for countries with fewer than 50 APHs, at least 50% of APHs
with CD4 measurements at first visit. Sensitivity analyses were conducted to better understand
how LTFU may have biased mortality estimates. Firstly, inverse probability weighting (IPW)
was applied to the multivariable model, giving greater weight to APHs not LTFU but with
characteristics similar to APHs who were LTFU. Secondly, under varying assumptions about
the proportion of LTFU that could be due to mortality, mortality was randomly assigned to a
proportion of APHs that were originally classified as LTFU [25]. Unadjusted HRs (uHRs) as
well as cumulative incidence functions were recalculated under these assumptions. All analyses
were conducted using Stata version 13.0 (StataCorp, College Station, TX, USA), and the
“stcompet” package was used to calculate the cumulative incidence functions from the compet-
ing risks analysis. Figures were plotted using the ggplot2 package in R version 3.2.2 (R Founda-
tion for Statistical Computing, Vienna, Austria).
Results
Of the 183,119 children included in the CIPHER multiregional dataset, a total of 38,187 APHs
were included (Fig 1), from 51 countries across 5 regions of the world, with 79% from sub-
Saharan Africa (Table 1). Observation started as early as 1982 in Europe and 1996 in sub-Saha-
ran Africa and continued until at least 2014 in all regions. The median (interquartile range
[IQR]) year of birth was earliest in North America (1994 [1992–1996]) and latest in South and
Southeast Asia, (2001 [1999–2002]). A total of 112,976 person-years were observed between 10
Fig 1. Flow diagram of inclusion of adolescents living with perinatally acquired HIV (N = 38,187). CIPHER,
Collaborative Initiative for Paediatric HIV Education and Research.
https://doi.org/10.1371/journal.pmed.1002514.g001
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The epidemiology of adolescents living with perinatally acquired HIV
Table 1. Profile of geographic regions included in the CIPHER global cohort adolescent analysis (N = 38,187 adolescents).
Region Countries included Number of Number of Observation Year of birth Duration of adolescent
study centers adolescents (%) period median follow-up (from age 10
(IQR) years) median (IQR) years
Europe Belgium, France, Ireland, Italy, Netherlands, 153 3,054 (8.0) 1982–2015 1995 (1991– 6.4 (3.6–8.0)
Poland, Portugal, Romania, Russian Federation, 1999)
Spain, Sweden, Switzerland, Ukraine, United
Kingdom
North America United States of America 117 1,032 (2.7) 1991–2014 1994 (1992– 3.7 (2.0–5.4)
1996)
South and Cambodia, India, Indonesia, Malaysia, Myanmar, 73 2,902 (7.6) 1994–2014 2001 (1999– 2.5 (1.2–4.4)
Southeast Asia Thailand, Vietnam 2002)
South America Argentina, Brazil, Haiti, Honduras 6 903 (2.4) 1990–2015 1998 (1995– 5.0 (2.7–7.5)
and the 2000)
Caribbean
Sub-Saharan Benin, Botswana, Burkina Faso, Burundi, 565 30,296 (79.3) 1996–2015 2000 (1999– 2.1 (0.9–3.8)
Africa Cameroon, Central African Republic, Democratic 2002)
Republic of Congo, Côte d’Ivoire, Ethiopia, Ghana,
Guinea, Kenya, Lesotho, Malawi, Mali,
Mozambique, Rwanda, Senegal, South Africa,
Swaziland, Tanzania, Togo, Uganda, Zambia,
Zimbabwe
Total 914 38,187 1982–2015 2000 (1998– 3.1 (1.5–5.2)
2002)
Abbreviations: CIPHER, Collaborative Initiative for Paediatric HIV Education and Research; IQR, interquartile range.
https://doi.org/10.1371/journal.pmed.1002514.t001
and 19 years of age, and the median (IQR) duration of adolescent follow-up was longest in
Europe (6.4 [3.6–8.0] years) and shortest in sub-Saharan Africa (2.1 [0.9–3.8] years) (Table 1).
Overall, 44% (46/104) of included cohorts provided data only on APHs that had ever received
ART.
Comparison by geographic region
More than two-thirds of APHs living in sub-Saharan Africa and South and Southeast Asia
were born between 2000 and 2005, compared to only 7% of APHs in North America (Table 2).
In all regions, approximately half of the APHs were female. Median (IQR) age at first visit dif-
fered substantially by region, ranging from 0.7 (0.3–2.1) years in North America to 7.1 (5.3–
8.6) years in sub-Saharan Africa. Similarly, APHs in North America started ART at a median
(IQR) age of 0.9 (0.4–2.6) years, compared to 7.9 (6.0–9.3) years in sub-Saharan Africa
(Table 2, Fig 2 Panel A). In the 61% of APHs with a CD4 count or percent measurement
recorded at ART start, the median (IQR) CD4 count was 321 (165–575), with substantial varia-
tion by region (Table 2). Similarly, median (IQR) CD4 percent at ART start varied by region
and was highest in North America (28% [20%–36%]) and lowest in South and Southeast Asia
(10% [4%–16%]). By age 10 years and last visit there was less variation in CD4 percent by
region (Fig 2 Panel B). Median (IQR) HAZ at first visit and ART start was well below WHO
normative data in all regions and lowest in South and Southeast Asia, at −2.36 (−3.26–−1.42)
at first visit and −2.41 (−3.31–−1.51) at ART start (Fig 2 Panel C). In APHs in Europe and
North America, HAZ improved by age 10 years and last visit, but at least 25% of APHs in
South and Southeast Asia, South America and the Caribbean, and sub-Saharan Africa
remained stunted at their last visit (Table 2). Eighty-eight percent of APHs received ART at
some stage, of whom 12% started ART after age 10 years and 80% remained on ART at their
last visit. Of the 7,401 (19%) APHs not known to be on ART at their last visit, 62% were ART
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 8 / 21
The epidemiology of adolescents living with perinatally acquired HIV
Table 2. Adolescent characteristics at first visit, ART start, age 10 years, and last visit and cumulative incidence of outcomes (mortality, transferred out, LTFU),
compared by region.
Characteristic Total Europe North America South and Southeast South America and the Sub-Saharan
Asia Caribbean Africa
Total N (row %) 38,187 (100) 3,054 (8.0) 1,032 (2.7) 2,902 (7.6) 903 (2.4) 30,296 (79.3)
Birth Cohort, N (%)
Pre-1995 2,660 (7.0) 1,399 (45.8) 640 (62.0) 91 (3.1) 182 (20.2) 348 (1.1)
1995–1999 13,267 (34.7) 989 (32.4) 318 (30.8) 918 (31.6) 446 (51.6) 10,596 (35.0)
2000–2005 22,260 (58.3) 666 (21.8) 74 (7.2) 1,893 (65.2) 275 (30.5) 19,352 (63.9)
Male, N (%) 18,863 (49.4) 1,475 (48.3) 515 (49.9) 1,449 (49.9) 417 (46.2) 15,007 (49.5)
Age in years, median (IQR)
First visit 6.7 (4.4–8.4) 1.9 (0.2–5.5) 0.7 (0.3–2.1) 5.6 (3.5–7.5) 3.5 (1.4–6.2) 7.1 (5.3–8.6)
ART start 7.5 (5.2–9.2) 4.4 (1.2–8.2) 0.9 (0.4–2.6) 6.5 (4.4–8.4) 5.0 (2.2–8.0) 7.9 (6.0–9.3)
Last visit 12.4 (11.1–14.4) 16.4 (13.6– 13.7 (12.0–15.4) 12.5 (11.2–14.4) 15.0 (12.7–17.5) 12.1 (10.9–13.8)
18.0)
CD4 count in cells/mm3,
median (IQR)
First visit all ages (N = 19,979) 427 (200–757) 768 (375– 1,263 (775– 252 (68–575) 583 (268–990) 405 (201–699)
1,580) 2,207)
First visit if age5 years (N = 358 (165–632) 415 (202–629) 504 (298–598) 189 (53–447) 349 (120–562) 370 (180–646)
14,585)
ART start all ages (N = 20,608) 321 (165–575) 464 (241– 1,129 (702– 219 (73–406) 462 (222–785) 310 (165–520)
1,029) 1,921)
ART start if age5 years (N = 292 (161–469) 298 (161–469) 590 (384–767) 189 (60–322) 328 (139–540) 301 (158–500)
16,612)
Age 10 years (N = 26,953) 685 (445–972) 697 (468–970) 796 (575–1,049) 746 (491–999) 639 (412–914) 671 (430–964)
Last visit (N = 31,951) 687 (464–946) 628 (434–868) 700 (494–930) 749 (541–1,004) 601 (381–861) 689 (460–953)
CD4%, median (IQR)
First visit (N = 13,674) 16 (9–25) 23 (15–35) 30 (20–39) 10 (3–19) 19 (12–27) 15 (9–23)
ART start (N = 14,740) 14 (8–20) 18 (12–28) 28 (20–36) 10 (4–16) 16 (11–23) 13 (8–18)
Age 10 years (N = 17,974) 28 (20–34) 29 (21–35) 33 (26–39) 26 (21–31) 27 (19–35) 27 (20–34)
Last visit (N = 23,292) 29 (21–35) 30 (22–37) 32 (25–38) 28 (22–32) 28 (19–35) 28 (20–35)
HAZ, median (IQR)
First visit (N = 20,269) −1.92 (−2.91– −0.75 (−1.60– −1.15 (−2.22– −2.36 (−3.26–−1.42) −1.67 (−2.60–−0.78) −1.97 (−2.94–
−0.97) 0.15) −0.15) −1.04)
ART start (N = 20,372) −1.95 (−2.91– −0.77 (−1.61– −1.19 (−2.21– −2.41 (−3.31–−1.51) −1.64 (−2.65–−0.73) −2.02 (−2.95–
−1.02) 0.09) −0.16) −1.11)
Age 10 years (N = 26,883) −1.53 (−2.35– −0.32 (−1.08– −0.35 (−1.11– −1.91 (−2.68–−1.20) −1.05 (−1.85–−0.34) −1.66 (−2.45–
−0.72) 0.43) 0.47) −0.91)
Last visit (N = 32,752) −1.59 (−2.45– −0.40 (−1.14– −0.33 (−1.09– −1.76 (−2.52–−1.03) −1.21 (−2.00–−0.36) −1.75 (−2.57–
−0.72) 0.29) 0.42) −0.94)
ART, N (%)
Ever received 33,514 (87.8) 2,889 (94.6) 1,016 (98.5) 2,708 (93.3) 883 (97.8) 26,018 (85.9)
Started > age 10 years 4,037 (12.0) 371 (12.8) 1 (0.1) 217 (8.0) 96 (10.9) 3,352 (12.9)
On ART at age 10 years 25,713 (67.3) 2,021 (66.2) 866 (83.9) 2,400 (82.7) 697 (77.2) 19,729 (65.1)
On ART at last visit 30,072(80.3) 2,540 (84.1) 878 (86.1) 2,565 (89.8) 768 (89.8) 23,321 (78.5)
Virologic suppression, n/N (%)
Age 10 years 6,919/10,209 1,442/2,500 576/1,012 (56.9) 1,099/1,332 (82.5) 267/515 (51.8) 3,535/4,850
(67.8) (57.7) (72.9)
Last visit 9,741/14,200 2,149/2,994 617/1,020 (60.5) 1,544/1,882 (82.0) 403/601 (67.1) 5,028/7,703
(68.6) (71.8) (65.3)
Cumulative incidence (95% CI) at age 15 years
Mortality (%) 2.6 (2.4–2.8) 0.8 (0.5–1.2) 1.1 (0.5–2.1) 2.7 (1.9–3.8) 4.4 (3.1–6.1) 2.9 (2.7–3.2)
(Continued)
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The epidemiology of adolescents living with perinatally acquired HIV
Table 2. (Continued)
Characteristic Total Europe North America South and Southeast South America and the Sub-Saharan
Asia Caribbean Africa
Transferred out (%) 15.6 (15.1–16.0) 3.5 (2.9–4.3) 1.9 (1.1–3.1) 6.7 (5.5–8.0) 6.5 (4.9–8.5) 19.3 (18.7–20.0)
Lost to follow-up (%) 11.3 (10.9–11.8) 6.1 (5.2–7.0) 8.9 (6.7–11.3) 7.1 (5.6–8.7) 4.8 (3.4–6.7) 13.2 (12.6–13.7)
Note: 48.5%, 47.7%, and 26.9% of first visit CD4 count, CD4 percent, and HAZ measurements, respectively, overlapped with ART start measurements, and 14.9%,
15.5%, and 7.3% of age 10 year CD4 count, CD4 percent, and HAZ measurements, respectively, overlapped with last visit measurements.
Abbreviations: ART, antiretroviral therapy; CI, confidence interval; HAZ, WHO height-for-age Z-score; IQR, interquartile range; LTFU, loss to follow-up.
https://doi.org/10.1371/journal.pmed.1002514.t002
naïve. Only 38% of all APHs had an HIV viral load recorded at some stage, and this proportion
was lowest in sub-Saharan Africa, at 25% (Table 2). Of those with an HIV viral load measure-
ment and on ART at their last visit, 72% (9,388/13,114) were virologically suppressed.
By competing risks analysis, the cumulative incidence estimates (95% CI) at 15 years of age
for mortality, transfers out, and LTFU for all APHs were 2.6% (2.4%–2.8%), 15.6% (15.1%–
16.0%), and 11.3% (10.9%–11.8%), respectively (Table 2). Cumulative incidence of mortality
before any other competing event occurred was estimated to be lowest in Europe (0.8% [0.5%–
1.1%]) and highest in South America and the Caribbean (4.4% [3.1%–6.1%]) (Table 2). How-
ever, LTFU before mortality or transfer out was lowest in South America and the Caribbean
(4.8% [3.4%–6.7%]) and highest in sub-Saharan Africa (13.2% [12.6%–13.7%]). Transfers out
before mortality or LTFU were also highest in sub-Saharan Africa (19.3% [18.7%–20.0%]).
Cumulative mortality (95% CI) when estimated by the Kaplan-Meier product limit estimator
was similar, at 3.0% (2.8%–3.3%) for the total cohort, ranging from 0.8% (0.5%–1.2%) in
Europe to 4.7% (3.3%–6.6%) in South America and the Caribbean (S1 Table).
Comparison by CIG
Sixty-five percent of all APHs in this cohort lived in low-income countries, 7.9% in lower-mid-
dle-income-, 17.5% upper-middle-income-, and 9.7% in high-income countries. Variation in
characteristics by CIG followed the geographic region trends, with younger age, higher CD4
percent, and less impaired HAZ at first visit and ART start in APHs in high-income countries
compared to upper-middle-, lower-middle-, or low-income countries (Table 3, Fig 3). Mortal-
ity before transfer out or LTFU was lowest in high-income countries (0.9% [0.6%–1.3%]) and
highest in low-income countries (3.5% [3.1%–3.8%]) (Table 3). However, LTFU before mor-
tality or transfer out was highest in upper-middle-income countries (12.8% [11.8%–13.9%]).
Comparison by birth cohort
Fifty-eight percent of all APHs were born in the year 2000 or later, ranging from 0.3% living in
North America and 2.8% in high-income countries to 86.9% living in sub-Saharan Africa and
73.6% in low-income countries (S2 Table). Three-quarters (76.7%) of APHs born prior to
1995 lived in Europe and North America, and age at first visit and ART start appeared to be
younger and CD4 count, CD4 percent, and HAZ at first visit and ART start appeared to be bet-
ter in this group compared to those born in later calendar periods (S2 Table, S1 Fig). However,
for the two more recent birth cohorts, the majority of APHs were from sub-Saharan Africa,
and age at first visit and ART start was younger and CD4 count higher in APHs born during
2000–2005 than 1995–1999. HAZ, however, did not show any improvement over time at ART
start or at last visit for APHs born between 2000 and 2005 compared to APHs born between
1995 and 1999. Mortality before transfer or LTFU was lowest in APHs born between 2000 and
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 10 / 21
The epidemiology of adolescents living with perinatally acquired HIV
Fig 2. Comparison by geographic region of characteristics at first visit, ART start, age 10 years, and last visit of
adolescents living with perinatally acquired HIV. ART, antiretroviral therapy; IQR, interquartile range; S&SE Asia,
South and Southeast Asia; WHO, World Health Organization.
https://doi.org/10.1371/journal.pmed.1002514.g002
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The epidemiology of adolescents living with perinatally acquired HIV
Table 3. Adolescent characteristics at first visit, ART start, age 10 years, and last visit and cumulative incidence of outcomes (mortality, transferred out, LTFU),
compared by CIG.
Characteristic Total Low Income Lower-Middle Income Upper-Middle Income High Income
Total N (row %) 38,187 (100) 24,794 (64.9) 3,015 (7.9) 6,669 (17.5) 3,709 (9.7)
Male, N (%) 18,863 (49.4) 12,191 (49.2) 1,503 (49.9) 3,372 (50.6) 1,797 (48.5)
Age in years, median (IQR)
First visit 6.7 (4.4–8.4) 7.1 (5.4–8.6) 6.3 (3.8–8.1) 6.3 (3.7–8.3) 1.1 (0.2–4.1)
ART start 7.5 (5.2–9.2) 8.0 (6.2–9.4) 7.2 (4.7–9.0) 7.0 (4.7–8.8) 2.5 (0.6–6.1)
Last visit 12.4 (11.1–14.4) 12.1 (10.9–13.7) 13.2 (11.4–15.3) 12.6 (11.1–14.6) 15.4 (13.1–17.6)
CD4 count in cells/mm3, median (IQR)
First visit (N = 19,979) 427 (200–757) 405 (194–707) 348 (142–610) 393 (183–709) 924 (470–1,800)
First visit if age5 years (N = 14,585) 358 (165–632) 377 (176–664) 302 (116–540) 298 (132–527) 442 (234–660)
ART start (N = 20,608) 321 (165–575) 302 (155–504) 277 (108–455) 336 (171–602) 624 (294–1,318)
ART start if age5 years (N = 16,612) 292 (161–469) 300 (154–504) 245 (91–360) 283 (139–478) 320 (190–502)
Age 10 years (N = 26,953) 685 (445–972) 661 (421–955) 702 (463–953) 719 (472–1,004) 730 (500–998)
Last visit (N = 31,951) 687 (464–946) 679 (443–956) 692 (492–917) 727 (511–968) 650 (451–882)
CD4%, median (IQR)
First visit (N = 13,674) 16 (9–25) 16 (9–24) 13 (7–20) 14 (8–21) 25 (16–37)
ART start (N = 14,740) 14 (8–20) 13 (8–18) 11 (6–17) 13 (8–19) 21 (13–31)
Age 10 years (N = 17,974) 28 (20–34) 27 (19–34) 27 (21–33) 28 (20–35) 30 (23–37)
Last visit (N = 23,292) 29 (21–35) 28 (20–35) 29 (22–35) 29 (22–35) 31 (24–37)
HAZ, median (IQR)
First visit (N = 20,269) −1.92 (−2.91–−0.97) −2.02 (−3.00–−1.07) −1.98 (−2.87–−1.09) −1.89 (−2.80–−1.00) −0.84 (−1.78–0.07)
ART start (N = 20,372) −1.95 (−2.91–−1.02) −2.05 (−3.01–−1.13) −2.13 (−3.05–−1.29) −1.93 (−2.79–−1.10) −0.83 (−1.70–0.07)
Age 10 years (N = 26,883) −1.53 (−2.35–−0.72) −1.69 (−2.48–−0.92) −1.83 (−2.55–−1.08) −1.46 (−2.20–−0.77) −0.29 (−1.04–0.48)
Last visit (N = 32,752) −1.59 (−2.45–−0.72) −1.79 (−2.62–−0.97) −1.65 (−2.44–−0.87) −1.46 (−2.24–−0.67) −0.34 (−1.09–0.37)
ART, N (%)
Ever received 33,514 (87.8) 20,851 (84.1) 2,776 (92.1) 6,351 (95.2) 3,536 (95.3)
Started > age 10 years 4,037 (12.0) 3,028 (14.5) 305 (11.0) 423 (6.7) 281 (7.9)
On ART at age 10 years 25,713 (67.3) 15,444 (62.3) 2,279 (75.6) 5,323 (79.8) 2,667 (71.9)
On ART at last visit 30,072 (80.3) 18,408 (75.9) 2,589 (87.8) 6,002 (91.1) 3,073 (83.8)
Virologic suppression, n/N (%)
Age 10 years 6,919/10,209 (67.8) 467/932 (50.2) 885/1,039 (85.2) 3,637/4,843 (75.1) 1,930/3,396 (56.8)
Last visit 9,741/14,200 (68.6) 1,342/2,777 (48.3) 1,210/1,486 (81.4) 4,684/6,274 (74.7) 2,505/3,663 (68.4)
Cumulative incidence (95% CI) at age 15 years
Mortality (%) 2.6 (2.4–2.8) 3.5 (3.1–3.8) 2.7 (2.1–3.5) 1.4 (1.1–1.9) 0.9 (0.6–1.3)
Transferred out (%) 15.6 (15.1–16.0) 16.7 (16.1–17.4) 14.3 (12.8–15.8) 2.1 (2.0–2.3) 3.5 (2.9–4.2)
Lost to follow-up (%) 11.3 (10.9–11.8) 12.6 (12.0–13.2) 7.5 (6.3–8.8) 12.8 (11.8–13.9) 6.7 (5.8–7.7)
Abbreviations: ART, antiretroviral therapy; CI, confidence interval; CIG, country income group; HAZ, height-for-age-Z-score; IQR, interquartile range; LTFU, lost to
follow-up.
https://doi.org/10.1371/journal.pmed.1002514.t003
2005 (1.84% [95% CI 1.50%–2.23%]), although LTFU in this group was also more than double
that of the previous 2 birth periods (23.34% [95% CI 19.96%–26.88%]). When looking at birth
cohort trends by region, mortality declined in every region for APHs born between 2000 and
2005 compared to those born in the earlier birth cohorts, and no mortality was observed in the
most recent APH birth cohort in Europe, North America, and South America and the Carib-
bean (S3 Table). However, LTFU increased for APHs born between 2000 and 2005 in all
regions except South America and the Caribbean.
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The epidemiology of adolescents living with perinatally acquired HIV
Fig 3. Comparison by CIG of characteristics at first visit, ART start, age 10 years, and last visit of adolescents
living with perinatally acquired HIV. ART, antiretroviral therapy; CIG, country income group; IQR, interquartile
range; WHO, World Health Organization.
https://doi.org/10.1371/journal.pmed.1002514.g003
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The epidemiology of adolescents living with perinatally acquired HIV
Mortality hazards compared by region
Relative to Europe, the unadjusted mortality HR (95% CI) was significantly higher in South
and Southeast Asia (3.21 [2.03–5.07]), South America and the Caribbean (6.07 [3.87–9.50]),
and sub-Saharan Africa (4.35 [3.02–6.28]) but not in North America (1.70 [0.87–3.31])
(Table 4, model 1). After controlling for baseline characteristics, including sex, birth cohort,
age at first visit, and any ART received, the aHR increased slightly for North America and
decreased for sub-Saharan Africa (Table 4, model 2). Inclusion of IPW in the model marginally
reduced the HR further for all regions except North America (Table 4, model 3). Adjustment
for CD4 measures, either as CD4 count or CD4 percent, at first visit only or time-updated and
with or without MI for missing CD4 measures, also altered the individual region aHRs relative
to Europe, but the general pattern remained of elevated mortality in all regions relative to
Europe and substantially elevated mortality in sub-Saharan Africa and South America and the
Caribbean (Table 4 and S4 Table).
Sensitivity analyses
In sensitivity analyses, under varying assumptions of the proportion of APHs classified as
LTFU who may be cases of unascertained mortality, the cumulative incidence for mortality
Table 4. Mortality HRs (95% CIs) by region with reference to Europe.
North America South and Southeast Asia South America and the Caribbean Sub-Saharan Africa
1. Crude mortality HR compared to Europe (N = 38,187)
1.70 (0.87–3.31) 3.21 (2.03–5.07) 6.07 (3.87–9.50) 4.35 (3.02–6.28)
2. Adjusted for complete baseline characteristicsa (N = 38,187)
2.03 (1.02–4.02) 2.96 (1.79–4.88) 5.94 (3.77–9.38) 3.37 (2.17–5.23)
3. Adjusted for complete baseline characteristicsa with IPW (N = 38,187)
2.52 (1.24–5.11) 2.78 (1.75–4.42) 5.61 (3.58–8.77) 3.23 (2.21–4.73)
4. Adjusted for baseline characteristicsa, including CD4 percent, using complete cases only (N = 13,699)
1.84 (0.58–5.81) 1.90 (0.73–4.91) 4.20 (1.72–10.29) 4.09 (1.84–9.13)
5. Adjusted for baseline characteristicsa, including CD4 percent, with imputation for missing CD4 (N = 38,187)
2.34 (1.19–4.71) 1.87 (1.12–3.13) 5.00 (3.17–7.90) 2.70 (1.75–4.19)
6. Adjusted for baseline characteristicsa, including CD4 percent, with restricted imputationb (N = 33,126)
1.97 (0.97–4.02) 1.56 (0.91–2.67) 4.16 (2.54–6.80) 2.42 (1.51–3.87)
7. Adjusted for baseline characteristicsa, including CD4 count, using complete cases only (N = 19,979)
2.18 (0.71–6.66) 3.16 (1.44–6.96) 5.52 (2.62–11.67) 4.57 (2.23–9.35)
8. Adjusted for baseline characteristicsa, including CD4 count, with imputation (N = 38,187)
2.37 (1.19–4.71) 2.40 (1.45–3.96) 5.49 (3.48–8.65) 3.01 (1.95–4.67)
9. Adjusted for baseline characteristicsa, including CD4 count, with restricted imputationb (N = 33,126)
2.02 (0.99–4.11) 2.05 (1.20–3.49) 4.67 (2.86–7.63) 2.70 (1.68–4.33)
10. Adjusted for baseline characteristicsa and time-updated CD4 count, with imputation (N = 38,187)
2.07 (1.05–4.10) 4.06 (2.45–6.73) 5.49 (3.46–8.71) 3.58 (2.28–5.64)
11. Adjusted for baseline characteristicsa, including CD4 count and HAZ, with imputation (N = 38,187)
2.31 (1.16–4.60) 2.21 (1.33–3.67) 5.21 (3.29–8.23) 2.85 (1.83–4.43)
aSex, birth period (pre-1995, 1995–1999, 2000–2005), age at first visit, antiretroviral therapy (never started, started on
dual therapy before 2000, started on triple therapy).
bMultiple imputation for missing CD4 restricted to countries with at least 50 CD4 observations at first visit, or <50%
missing CD4 if total country N< 50.
Abbreviations: HAZ, height-for-age-Z-score; HR, hazard ratio; IPW, inverse probability weights.
https://doi.org/10.1371/journal.pmed.1002514.t004
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 14 / 21
The epidemiology of adolescents living with perinatally acquired HIV
before transfer out or LTFU in sub-Saharan Africa could be as high as 14.9% (95% CI 14.3%–
15.5%) if 100% of APHs LTFU was truly mortality (S5 Table). Under the assumption that
100% of LTFU is due to mortality in all regions, the relative difference in mortality is attenu-
ated in all regions in comparison to Europe, with the highest uHR in sub-Saharan Africa, at
1.46 (95% CI 1.33–1.61) (S6 Table). If it is differentially assumed that, in sub-Saharan Africa,
50% of LTFU is unascertained mortality but only 5% in all other regions, the uHR for mortality
in sub-Saharan Africa may be as high as 7.09 (95% CI 5.45–9.23), relative to Europe.
Discussion
To our knowledge, this is the largest analysis of APHs to date, describing the characteristics
and outcomes of more than 38,000 APHs across more than 100,000 person-years of follow-up
during adolescence, from 5 regions of the world, including 14 of the 15 highest adolescent
HIV burden countries [1] and across low-, middle-, and high-income countries. This analysis
essentially describes characteristics of and care for younger adolescents (10–14 years of age),
79% of whom were living in sub-Saharan Africa. Our findings show that APHs in North
America and Europe, as well as high-income group countries, generally presented to care and
started ART at a younger age and with higher CD4 counts, and less impaired height, compared
to other regions or CIGs. Conversely, age at presentation to care and ART start was highest in
sub-Saharan Africa. Despite probable under-ascertained mortality in some regions, the hazard
of HIV-associated mortality during adolescence was substantially higher in sub-Saharan
Africa, South and Southeast Asia, and South America and the Caribbean than in Europe.
Results suggested that mortality may also have been higher in North America than in Europe.
Analysis by CIG followed these geographic trends, with results suggesting younger age, higher
CD4 percent, and less impaired height at first visit and ART start in high-income countries
compared to middle- or low-income countries.
Results also suggested a marked difference in regional and income group distributions
across birth cohort groups. APHs from North America and Europe and, likewise, high-income
countries predominated in the earliest birth cohort, with minimal representation from Asia
and Africa, while the most recent birth cohort was dominated by APHs living in sub-Saharan
Africa. Younger age, higher CD4, and less impaired growth in the earliest birth cohort
reflected this regional and CIG distribution. These vastly different characteristics of APHs
across regions and over time require careful adjustment and interpretation due to different
effects of variables across time. Nevertheless, some improvements for all APHs born after 2000
compared to those born during 1995–1999 are evident, including younger age and higher CD4
count at first presentation and ART start. This trend is expected, as criteria for initiating ART
have progressively become less restrictive, with higher or no CD4 thresholds, and access to
ART has expanded across the globe [3,26–29]. Despite this, height was still severely impacted
in APHs in the most recent birth cohort. This may reflect that, although APHs born during
2000–2005 started ART earlier than APHs born during 1995–1999, they still only started at a
median of 7 years of age, having missed the benefits of early ART on growth and probably also
cognition and other morbidities, although the latter two outcomes were not evaluated in this
analysis [30–32].
Comparing mortality across the regions is limited by high LTFU in sub-Saharan Africa rela-
tive to other regions. Furthermore, LTFU rates in Europe may be overestimated due to a
reporting delay for some cohorts. Higher LTFU has been described in cohorts with shorter
durations of follow-up, in which people may not yet have had the opportunity to return to
care, while in cohorts of longer durations, people previously considered LTFU subsequently
return to care [33]. This could affect patients born in the most recent birth cohorts in our
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 15 / 21
The epidemiology of adolescents living with perinatally acquired HIV
analysis, particularly in sub-Saharan Africa. Methods have advanced in adult HIV cohort
research to informatively adjust mortality estimates for under-ascertainment in those LTFU,
informed by studies that actively traced patients LTFU to determine their vital status [34–37].
However, a recent systematic review identified few such tracing studies in children or adoles-
cents living with HIV [25]. One study from Malawi traced 201 children who were LTFU and,
of the 79% who were successfully traced, 11% had died, 26% had transferred to another clinic,
and 25% were alive but no longer on ART [38]. A better understanding of how program LTFU
can bias mortality estimates specifically in adolescents is needed to truly understand the impact
on mortality in adolescents living with HIV [1].
This study has limitations. As mode of transmission is generally poorly captured in routine
care cohorts, we used a pragmatic definition of APH and included only children infected with
HIV who had entered care before age 10 years. This was done to ensure exclusion of adoles-
cents with horizontally acquired HIV, who have a very different disease profile during adoles-
cence to APHs [39]. As a result of this approach, we may have excluded a relatively small but
important group of APHs diagnosed and entering care after age 10 years [40,41]. Our analysis
does not include Nigeria, a country with the second largest burden of adolescents living with
HIV and the only country in which mortality in younger adolescents (10–14 years of age) is
estimated to be rising [1]. Furthermore, the North American region is represented only by the
US in this analysis, and findings may not necessarily be generalizable to other North American
countries. Our analysis may overrepresent APHs treated in healthcare settings with higher
standards of care compared to the general population of adolescents, thus underestimating
true mortality in APHs. Additionally, approximately 44% of included cohorts collect data only
on children started on ART; thus, the proportion on ART observed in this analysis is likely
overestimated for some regions. HIV viral load measurements were sparsely available and pos-
sibly selectively performed in the lower CIGs, with likely targeting of HIV viral load measure-
ments to children with clinical or immunological failure, in which HIV viral load testing is not
part of routine monitoring. This would result in overestimation of the proportion of patients
with an unsuppressed HIV viral load, and these HIV viral load data should be interpreted with
care in this analysis.
The current generation of APHs, and those represented in this CIPHER analysis, largely
reflect children infected with HIV who survived early childhood without ART but at the same
time experienced substantial growth morbidity and possibly other morbidities not measured
in this analysis. This current generation may be substantially different to future cohorts of
APHs, who will have been more likely to have started ART in infancy and may be affected by
different issues. It is expected that APH survival will continue to improve with greater access
to early infant diagnosis and universal ART for all people living with HIV [42]. Although the
population of APHs is likely to decline in the future due to declines in new perinatally acquired
HIV infections, there is still a lot of work to be done to achieve equality in health and survival
for all APHs, irrespective of geographic location. Collaborations such as CIPHER enable us to
monitor current global temporal trends in APH outcomes over time to ensure that this and
future generations of APHs across the globe have the potential to thrive and contribute to soci-
ety, outcomes that were denied to previous generations of children infected with HIV.
In summary, our analysis of a large cohort of APHs between 1982 and 2014 across several
regions of the globe suggests that APHs generally entered HIV care at an earlier age in high-
income countries compared to other CIGs. Despite probable under-ascertainment, mortality
continued to be substantially higher in sub-Saharan Africa, South and Southeast Asia, and
South America and the Caribbean than in Europe and warrants further monitoring and
understanding.
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 16 / 21
The epidemiology of adolescents living with perinatally acquired HIV
Supporting information
S1 STROBE Checklist. STROBE checklist.
(DOC)
S1 Text. Group authorship list.
(DOCX)
S2 Text. Acknowledgments.
(DOCX)
S1 Analysis Plan. Project concept analysis plan.
(PDF)
S1 Table. Standard survival mortality estimates.
(DOCX)
S2 Table. Characteristics by birth cohort.
(DOCX)
S3 Table. Cumulative incidence 10–13 sensitivity.
(DOCX)
S4 Table. Selected full models.
(DOCX)
S5 Table. Cumulative incidence 10–15 sensitivity.
(DOCX)
S6 Table. Crude mortality hazard ratios sensitivity.
(DOCX)
S1 Fig. Comparison by birth cohort.
(TIFF)
Acknowledgments
We thank all contributing networks, their study teams, and participants. Please see full list of
acknowledgments in the supplementary material (S2 Text).
Author Contributions
Conceptualization: Michael Schomaker, Mary-Ann Davies, Paige Williams, Suna Balkan,
Jihane Ben-Farhat, Nancy Calles, Kulkanya Chokephaibulkit, Charlotte Duff, Tanoh Fran-
çois Eboua, Adeodata Kekitiinwa-Rukyalekere, Nicola Maxwell, Jorge Pinto, George Seage,
III, Chloe A. Teasdale, Sebastian Wanless, Josiane Warszawski, Kara Wools-Kaloustian,
Marcel Yotebieng, Intira J. Collins, Ruth Goodall, Colette Smith, Kunjal Patel, Mary Paul,
Diana Gibb, Rachel Vreeman, Elaine J. Abrams, Rohan Hazra, Russell Van Dyke, Linda-
Gail Bekker, Lynne Mofenson, Marissa Vicari, Shaffiq Essajee, Martina Penazzato, Annette
Sohn, Ali Judd, Valériane Leroy.
Data curation: Amy L. Slogrove, Michael Schomaker, Mary-Ann Davies, Charlotte Duff,
Nicola Maxwell, Chloe A. Teasdale, Sebastian Wanless, Venessa Timmerman, Azar Karimi-
nia, Shirley Traite.
Formal analysis: Amy L. Slogrove, Michael Schomaker.
Funding acquisition: Linda-Gail Bekker, Marissa Vicari.
PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002514 March 1, 2018 17 / 21
The epidemiology of adolescents living with perinatally acquired HIV
Investigation: Kulkanya Chokephaibulkit, Tanoh François Eboua, Jorge Pinto, Josiane Wars-
zawski, Kara Wools-Kaloustian, Marcel Yotebieng, Rachel Vreeman, Gabriel Anabwani,
Edith Q. Mohapi, Peter N. Kazembe, Makhosazana Hlatshwayo, Mwita Lumumba, Tessa
Goetghebuer, Claire Thorne, Luisa Galli, Annemarie van Rossum, Carlo Giaquinto, Mag-
dalena Marczynska, Laura Marques, Filipa Prata, Luminita Ene, Liubov Okhonskaia, Pablo
Rojo, Claudia Fortuny, Lars Naver, Christoph Rudin, Sophie Le Coeur, Alla Volokha,
Vanessa Rouzier, Regina Succi, Andrew Edmonds, Patricia Lelo, Samuel Ayaya, Patricia
Ongwen, Laura F. Jefferys, Sam Phiri, Mwangelwa Mubiana-Mbewe, Shobna Sawry, Lorna
Renner, Mariam Sylla, Mark J. Abzug, Myron Levin, James Oleske, Miriam Chernoff,
Murli Purswani, Ellen G. Chadwick.
Methodology: Amy L. Slogrove, Michael Schomaker.
Project administration: Mary-Ann Davies, George Seage, III, Marissa Vicari, Ali Judd.
Resources: Michael Schomaker.
Software: Michael Schomaker.
Supervision: Michael Schomaker, Mary-Ann Davies, Paige Williams, Suna Balkan, Jihane
Ben-Farhat, George Seage, III, Kara Wools-Kaloustian, Intira J. Collins, Ruth Goodall,
Colette Smith, Kunjal Patel, Mary Paul, Diana Gibb, Rachel Vreeman, Elaine J. Abrams,
Rohan Hazra, Russell Van Dyke, Linda-Gail Bekker, Lynne Mofenson, Marissa Vicari,
Shaffiq Essajee, Martina Penazzato, Annette Sohn, Ali Judd, Valériane Leroy.
Validation: Michael Schomaker.
Visualization: Amy L. Slogrove, Michael Schomaker.
Writing – original draft: Amy L. Slogrove.
Writing – review & editing: Michael Schomaker, Mary-Ann Davies, Paige Williams, Suna
Balkan, Jihane Ben-Farhat, Nancy Calles, Kulkanya Chokephaibulkit, Charlotte Duff,
Tanoh François Eboua, Adeodata Kekitiinwa-Rukyalekere, Nicola Maxwell, Jorge Pinto,
George Seage, III, Chloe A. Teasdale, Sebastian Wanless, Josiane Warszawski, Kara Wools-
Kaloustian, Marcel Yotebieng, Venessa Timmerman, Intira J. Collins, Ruth Goodall,
Colette Smith, Kunjal Patel, Mary Paul, Diana Gibb, Rachel Vreeman, Elaine J. Abrams,
Rohan Hazra, Russell Van Dyke, Linda-Gail Bekker, Lynne Mofenson, Marissa Vicari,
Shaffiq Essajee, Martina Penazzato, Gabriel Anabwani, Edith Q. Mohapi, Peter N.
Kazembe, Makhosazana Hlatshwayo, Mwita Lumumba, Tessa Goetghebuer, Claire Thorne,
Luisa Galli, Annemarie van Rossum, Carlo Giaquinto, Magdalena Marczynska, Laura Mar-
ques, Filipa Prata, Luminita Ene, Liubov Okhonskaia, Pablo Rojo, Claudia Fortuny, Lars
Naver, Christoph Rudin, Sophie Le Coeur, Alla Volokha, Vanessa Rouzier, Regina Succi,
Annette Sohn, Azar Kariminia, Andrew Edmonds, Patricia Lelo, Samuel Ayaya, Patricia
Ongwen, Laura F. Jefferys, Sam Phiri, Mwangelwa Mubiana-Mbewe, Shobna Sawry, Lorna
Renner, Mariam Sylla, Mark J. Abzug, Myron Levin, James Oleske, Miriam Chernoff, Shir-
ley Traite, Murli Purswani, Ellen G. Chadwick, Ali Judd, Valériane Leroy.
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