Evidence map›Paper›PMID 30005018›Full record

ArticleAIDS (London, England)2018

Beyond binary retention in HIV care: predictors of the dynamic processes of patient engagement, disengagement, and re-entry into care in a US clinical cohort.

Hana Lee, Xiaotian K Wu, Becky L Genberg, Michael J Mugavero, Stephen R Cole, Bryan Lau, Joseph W Hogan, Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) Investigators

Open access · greenAbstract read
In one paragraph

Article in AIDS (London, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% 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

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 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

8 authors at 4 institutions in 1 country.

Hana LeeDepartment of Biostatistics, Brown University, Providence, Rhode Island.
Xiaotian K WuDepartment of Biostatistics, Brown University, Providence, Rhode Island.
Becky L GenbergDepartment of Epidemiology, Johns Hopkins University, Baltimore, Maryland.
Michael J MugaveroSchool of Medicine, University of Alabama at Birmingham, Birmingham, Alabama.
Stephen R ColeDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Bryan LauDepartment of Epidemiology, Johns Hopkins University, Baltimore, Maryland.
Joseph W HoganDepartment of Biostatistics, Brown University, Providence, Rhode Island.
Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) Investigators
Brown University · USJohns Hopkins University · USUniversity of Alabama at Birmingham · USUniversity of North Carolina at Chapel Hill · US

Funding

Unsolicited R24 for the CFAR-Network of Integrated Clinical Sciences, CNICSR24AI067039 · NIAID · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Michael S. Saag · 2006 to 2026
$99.4M
Virology, Immunology, and Microbiology CoreP30AI050410 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVID M. MARGOLIS · 2001 to 2026
$76.9M
Vaccine Response and Immunotherapeutics SWGP30AI094189 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Richard E. Chaisson · 2012 to 2026
$67.0M
Translational ScienceP30AI042853 · NIAID · MIRIAM HOSPITAL · PI CURT G BECKWITH · 1998 to 2026
$51.7M
Science/Technical CoreP2CHD041020 · NICHD · BROWN UNIVERSITY · PI Margot Jackson · 2016 to 2026
$7.6M
Optimizing HIV Treatment Monitoring under Resource ConstraintsR01AI108441 · NIAID · BROWN UNIVERSITY · PI HOGAN, JOSEPH W, KANTOR, RAMI · 2015 to 2019
$3.5M
NIAID NIH HHS P30 AI042853NIAID NIH HHS P30 AI050410NIAID NIH HHS P30 AI094189NIAID NIH HHS R01 AI108441NIAID NIH HHS R24 AI067039NICHD NIH HHS P2C HD041020
6 · The paper itself

Abstract

objectivesStudies examining engagement in HIV care often capture cross-sectional patient status to estimate retention and identify predictors of attrition, which ignore longitudinal patient care-seeking behaviors. We describe the cyclical nature of (dis)engagement and re-entry into HIV care using the state transition framework.

designWe represent the dynamic patterns of patient care-retention using five states: engaged in care, missed one, two, three, or more expected visits, and deceased. Then we describe various care-seeking behaviors in terms of transitioning from one state to another (e.g. from disengaged to engaged). This analysis includes 31 009 patients enrolled in the Center for AIDS Research Network of Integrated Systems (CNICS) in the United States from 1996 to 2014.

methodMultistate models for longitudinal data were used to identify barriers to retention and subgroups at higher risk of falling out of care.

resultsThe initial 2 years following primary engagement in care were a crucial time for improving retention. Patients who had not initiated antiretroviral therapy, with lower CD4 cell counts, higher viral load, or not having an AIDS-defining illness were less likely to be retained in care.

conclusionBeyond the individual patient characteristics typically used to characterize retention in HIV care, we identified specific periods of time and points in the care continuum associated with elevated risk of transitioning out of care. Our findings can contribute to evidence-based recommendations to enhance long-term retention in CNICS. This approach can also be applied to other cohort data to identify retention strategies tailored to each population.

Indexed as

Medication AdherencePatient Acceptance of Health CarePatient ParticipationCD4 Lymphocyte CountHIV InfectionsHumansLongitudinal StudiesRetention in CareUnited StatesViral Load

Identifiers

PMID30005018
PMCPMC6136972
OpenAlexW2884907490

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.