Evidence map›Paper›PMID 34546644›Full record

ArticleJournal of the International AIDS Society2021

Disease progression and mortality with untreated HIV infection: evidence synthesis of HIV seroconverter cohorts, antiretroviral treatment clinical cohorts and population-based survey data.

Robert Glaubius, Nikhil Kothegal, Sehin Birhanu, Sasi Jonnalagadda, Severin Guy Mahiane, Leigh F Johnson, Tim Brown, John Stover, Tara D Mangal, Nikos Pantazis and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of the International AIDS Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
0.7field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 18 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 6 institutions in 6 countries.

Robert GlaubiusCenter for Modeling, Planning and Policy Analysis, Avenir Health, Glastonbury, Connecticut, USA.ORCID 0000-0002-4936-0264
Nikhil KothegalPublic Health Institute/CDC Global Health Fellow, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Sehin BirhanuDivision of Global HIV/AIDS, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Sasi JonnalagaddaDivision of Global HIV/AIDS, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Severin Guy MahianeCenter for Modeling, Planning and Policy Analysis, Avenir Health, Glastonbury, Connecticut, USA.ORCID 0000-0001-9460-4232
Leigh F JohnsonCentre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa.ORCID 0000-0002-2717-011X
Tim BrownResearch Program, East-West Center, Honolulu, Hawaii, USA.ORCID 0000-0002-0617-3848
John StoverCenter for Modeling, Planning and Policy Analysis, Avenir Health, Glastonbury, Connecticut, USA.ORCID 0000-0001-7236-1989
Tara D MangalMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
Nikos PantazisNational and Kapodistrian University of Athens Medical School, Athens, Greece.
Jeffrey W EatonMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.ORCID 0000-0001-7728-728X
Centers for Disease Control and Prevention · USPolicy Analysis (United States) · USImperial College London · GBEast–West Center · USNational and Kapodistrian University of Athens · GRUniversity of Cape Town · ZA

Funding

Statistical Models for Estimating and Projecting HIV/AIDS EpidemicsR01AI136664 · NIAID · PENNSYLVANIA STATE UNIVERSITY, THE · PI BAO, LE · 2017 to 2021
$3.6M
CGH CDC HHS U2G GH001226CGH CDC HHS U2G GH001271Medical Research Council MR/R015600/1NIAID NIH HHS R01 AI136664
6 · The paper itself

Abstract

introductionModel-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.

methodsWe used Bayesian multi-parameter evidence synthesis to combine data on (1) cross-sectional CD4 cell counts among untreated adults living with HIV from 10 PHIA surveys, (2) survival after HIV seroconversion in East African seroconverter cohorts, (3) post-seroconversion CD4 counts and (4) 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 modelled trends in CD4 count at ART initiation against ART initiator cohorts in sub-Saharan Africa.

resultsMedian 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. Modelled 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/mm

conclusionsSynthesis 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.

Indexed as

Anti-HIV AgentsHIV InfectionsAgedAustraliaBayes TheoremCD4 Lymphocyte CountCross-Sectional StudiesDisease ProgressionHumansMiddle AgedAnti-HIV AgentsadultsCD4cell countsdisease progressionHIVstatistical modelsurvival

Identifiers

PMID34546644
PMCPMC8454684
OpenAlexW3200302545

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.