Article in The Journal of infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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
5 citing papers in PubMed.
CD56bioRxiv : the preprint server for biology · 2026
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
14 authors.
Gesham MagombedzeBiology Department, Gilead Sciences, Foster City, California, USA.
Elena VendrameBiology Department, Gilead Sciences, Foster City, California, USA.ORCID 0000-0002-5595-1773
Devi SenGuptaBiology Department, Gilead Sciences, Foster City, California, USA.
Romas GeleziunasBiology Department, Gilead Sciences, Foster City, California, USA.
Susan LittleDepartment of Medicine, University of California, San Diego, La Jolla, California, USA.ORCID 0000-0002-7645-9737
Davey SmithDepartment of Medicine, University of California, San Diego, La Jolla, California, USA.
Bruce WalkerThe Ragon Institute of Mass General, MIT, and Harvard, Cambridge, Massachusetts, USA.
Jean-Pierre RoutyDivision of Hematology and Chronic Viral Illness Service, McGill University Health Centre: Glen Site Research Institute, Montreal, Quebec, Canada.ORCID 0000-0001-9897-7589
Frederick M HechtOsher Center for Integrative Health, University of California, San Francisco, California, USA.
Tae-Wook ChunLaboratory of Immunoregulation, National Institutes of Health, Bethesda, Maryland, USA.
Michael SnellerLaboratory of Immunoregulation, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0003-2816-7905
Jonathan Z LiDivision of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0001-9914-9662
Steven G DeeksDivision of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco, California, USA.
Michael J PelusoDivision of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco, California, USA.ORCID 0000-0003-0585-6230
Funding
WORK ORDER 126643 B539 EXPAND IC SUITE75N91019D00024 · NIAID · LEIDOS BIOMEDICAL RESEARCH, INC. · PI BRISCOE, LYNN · 2019 to 2025
$3932.6M
Leadership and Operations Center (LOC), AIDS Clinical Trials Group (ACTG); LOC 1/UM1AI068636 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Joseph J Eron, RAJESH T GANDHI · 2011 to 2026
$1073.1M
Statistical and Data Management Center (SDMC), AIDS Clinical Trials Group (ACTG)UM1AI068634 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Marlene Ann Cooper, Michael David Hughes · 2011 to 2026
$246.6M
AIDS Clinical Trials Group NetworkU01AI068636 · NIAID · SOCIAL AND SCIENTIFIC SYSTEMS, INC. · PI KURITZKES, DANIEL R. · 2006 to 2010
$147.1M
Validation, CLIA and Qualification (VQC): Enhancing the RS ratio as a tool for AIDS Clinical Trial Group (ACTG) tuberculosis trialsUM1AI106701 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Grace M Aldrovandi · 2014 to 2026
$116.8M
The impact of HIV viral diversity and cellular immunity on HIV pathogenesisP30AI060354 · NIAID · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI RAJESH T GANDHI · 2004 to 2026
$94.4M
Statistical and Data Management Center for the AIDS Clinical Trials GroupU01AI068634 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI HUGHES, MICHAEL DAVID · 2006 to 2010
$71.9M
Harvard Medical School Vaccine Clinical Trials UnitUM1AI069412 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI Lindsey Robert Baden, Daniel R. Kuritzkes · 2012 to 2026
$57.2M
Delaney AIDS Research Enterprise to Cure HIVUM1AI164560 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI STEVEN Grant DEEKS, Sharon Ruth Lewin · 2021 to 2026
$32.0M
San Francisco Vaccine and Prevention UnitUM1AI069496 · NIAID · PUBLIC HEALTH FOUNDATION ENTERPRISES · PI Susan Buchbinder, Diane V Havlir · 2012 to 2026
$30.5M
HIV Reservoir Ecology of Viral Remission (PTC)R01AI150396 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI LI, JONATHAN · 2020 to 2025
$5.4M
Characterizing the virologic and immunologic signatures of HIV exceptional controlK23AI157875 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PELUSO, MICHAEL JOSEPH · 2021 to 2025
$927k
National Institute of Allergy and Infectious DiseasesNational Institute of Allergy and Infectious Diseases, NIHNCI NIH HHS 75N91019D00024NHLBI NIH HHSNIAID NIH HHS K23 AI157875NIAID NIH HHS P30 AI060354NIAID NIH HHS R01 AI150396NIAID NIH HHS R37 AI150396NIAID NIH HHS U01 AI068634NIAID NIH HHS U01 AI068636NIAID NIH HHS UM1 AI068634NIAID NIH HHS UM1 AI068636NIAID NIH HHS UM1 AI069412NIAID NIH HHS UM1 AI069496NIAID NIH HHS UM1 AI106701NIAID NIH HHS UM1 AI164560(NIH) AI068634NIH HHS
6 · The paper itself
Abstract
backgroundA key research priority for developing a human immunodeficiency virus (HIV) cure strategy is to define the viral dynamics and biomarkers associated with sustained posttreatment control. The ability to predict the likelihood of sustained posttreatment control or noncontrol could minimize the time off antiretroviral therapy (ART) for those destined to be controllers and anticipate longer periods off ART for those destined to be controllers.
methodsMathematical modeling and machine learning were used to characterize virologic predictors of long-term virologic control, using viral kinetics data from several studies in which participants interrupted ART. Predictors of post-ART outcomes were characterized using data accumulated from the time of treatment interruption, replicating real-time data collection in a clinical study, and classifying outcomes as either posttreatment control (plasma viremia, ≤400 copies/mL at 2 of 3 time points for ≥24 weeks) or noncontrol.
resultsPotential predictors of virologic control were the time to rebound, the rate of initial rebound, and the peak plasma viremia. We found that people destined to be noncontrollers could be identified within 3 weeks of rebound (prediction scores: accuracy, 80%; sensitivity, 82%; specificity, 71%).
conclusionsGiven the widespread use of analytic treatment interruption in cure-related trials, these predictors may be useful to increase the safety of analytic treatment interruption through early identification of people who are unlikely to become posttreatment controllers.
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.
Early Viral Dynamics Predict Human Immunodeficiency Virus Posttreatment Control After Analytic Treatment Interruption. · full record | OpenQuestion