Disease progression and mortality with untreated HIV infection: evidence synthesis of HIV seroconverter cohorts, antiretroviral treatment clinical cohorts, and population-based survey data
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Background: Model-based estimates of key HIV indicators depend on past epidemic trends that are
derived based on assumptions about HIV disease progression and mortality in the absence of
antiretroviral treatment (ART). Population-based HIV Impact Assessment (PHIA) household surveys
conducted between 2015 and 2018 found substantial numbers of respondents living with untreated HIV
infection. CD4 cell counts measured in these individuals provide novel information to estimate HIV
disease progression and mortality rates off ART.
Methods: We used Bayesian multi-parameter evidence synthesis to combine data on i) cross-sectional
CD4 cell counts among untreated adults living with HIV from ten PHIA surveys, ii) survival after HIV
seroconversion in East African seroconverter cohorts, and iii) post-seroconversion CD4 counts and iv)
mortality rates by CD4 count predominantly from European, North American, and Australian
seroconverter cohorts. We used Incremental Mixture Importance Sampling to estimate HIV natural
history and ART uptake parameters used in the Spectrum software. We validated modeled trends in CD4
count at ART initiation against ART initiator cohorts in sub-Saharan Africa.
Results: Median untreated HIV survival decreased with increasing age at seroconversion, from 12.5
years (95% credible interval [CrI]: 12.1-12.7) at ages 15-24 to 7.2 years (95% CrI: 7.1-7.7) at ages 45-54.
Older age was associated with lower initial CD4 counts, faster CD4 count decline and higher HIV-related
mortality rates. Our estimates suggested a weaker association between ART uptake and HIV-related
mortality rates than previously assumed in Spectrum. Modeled CD4 counts in untreated people living
with HIV matched recent household survey data well, though some intercountry variation in frequencies
of CD4 counts above 500 cells/mm3 was not explained. Trends in CD4 counts at ART initiation were
comparable to data from ART initiator cohorts. An alternate model that stratified progression and
mortality rates by sex did not improve model fit appreciably.
Conclusions: Synthesis of multiple data sources results in similar overall survival as previous Spectrum
parameter assumptions but implies more rapid progression and longer survival in lower CD4 categories.
New natural history parameter values improve consistency of model estimates with recent cross-sectional
CD4 data and trends in CD4 counts at ART initiation.
derived based on assumptions about HIV disease progression and mortality in the absence of
antiretroviral treatment (ART). Population-based HIV Impact Assessment (PHIA) household surveys
conducted between 2015 and 2018 found substantial numbers of respondents living with untreated HIV
infection. CD4 cell counts measured in these individuals provide novel information to estimate HIV
disease progression and mortality rates off ART.
Methods: We used Bayesian multi-parameter evidence synthesis to combine data on i) cross-sectional
CD4 cell counts among untreated adults living with HIV from ten PHIA surveys, ii) survival after HIV
seroconversion in East African seroconverter cohorts, and iii) post-seroconversion CD4 counts and iv)
mortality rates by CD4 count predominantly from European, North American, and Australian
seroconverter cohorts. We used Incremental Mixture Importance Sampling to estimate HIV natural
history and ART uptake parameters used in the Spectrum software. We validated modeled trends in CD4
count at ART initiation against ART initiator cohorts in sub-Saharan Africa.
Results: Median untreated HIV survival decreased with increasing age at seroconversion, from 12.5
years (95% credible interval [CrI]: 12.1-12.7) at ages 15-24 to 7.2 years (95% CrI: 7.1-7.7) at ages 45-54.
Older age was associated with lower initial CD4 counts, faster CD4 count decline and higher HIV-related
mortality rates. Our estimates suggested a weaker association between ART uptake and HIV-related
mortality rates than previously assumed in Spectrum. Modeled CD4 counts in untreated people living
with HIV matched recent household survey data well, though some intercountry variation in frequencies
of CD4 counts above 500 cells/mm3 was not explained. Trends in CD4 counts at ART initiation were
comparable to data from ART initiator cohorts. An alternate model that stratified progression and
mortality rates by sex did not improve model fit appreciably.
Conclusions: Synthesis of multiple data sources results in similar overall survival as previous Spectrum
parameter assumptions but implies more rapid progression and longer survival in lower CD4 categories.
New natural history parameter values improve consistency of model estimates with recent cross-sectional
CD4 data and trends in CD4 counts at ART initiation.
Date Issued
2021-09
Date Acceptance
2021-07-19
Citation
Journal of the International AIDS Society, 2021, 24 (S5), pp.1-11
ISSN
1758-2652
Publisher
International AIDS Society
Start Page
1
End Page
11
Journal / Book Title
Journal of the International AIDS Society
Volume
24
Issue
S5
Copyright Statement
© 2021 The Authors. Journal of the International AIDS Society published by John Wiley & Sons Ltd on behalf of the International AIDS Society.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
License URL
Sponsor
National Institutes of Health
UNAIDS
Bill & Melinda Gates Foundation
Medical Research Council (MRC)
Identifier
https://onlinelibrary.wiley.com/doi/10.1002/jia2.25784
Grant Number
5776-ICS-DHHS-6664
2017/778519
INV-006733
MR/R015600/1
Subjects
Science & Technology
Life Sciences & Biomedicine
Immunology
Infectious Diseases
adults
cell counts
CD4
disease progression
HIV
statistical model
survival
COUNT
TIME
THERAPY
ADULTS
DEATH
MODEL
AIDS
EPIDEMIOLOGY
INDIVIDUALS
SURVIVAL
CD4
HIV
adults
cell counts
disease progression
statistical model
survival
1103 Clinical Sciences
1117 Public Health and Health Services
1199 Other Medical and Health Sciences
Publication Status
Published
Date Publish Online
2021-07-19