In one paragraphArticle in The Journal of infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
20 authors.
Silver AlkhafajiDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA.ORCID 0000-0002-2248-1381 Eunsol YangDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA.ORCID 0000-0003-2581-349X Kaylee LeeDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA.ORCID 0009-0007-3867-654X Vincent K ChangDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA.
Patrick P J PhillipsUCSF Center for Tuberculosis, University of California, San Francisco, San Francisco, California, USA.ORCID 0000-0002-6336-7024 Payam NahidUCSF Center for Tuberculosis, University of California, San Francisco, San Francisco, California, USA.ORCID 0000-0003-2811-1311 Susan E DormanDepartment of Medicine, Division of Infectious Diseases, Medical University of South Carolina, Charleston, South Carolina, USA.ORCID 0000-0001-6882-9470 Marc WeinerSan Antonio and the South Texas Veterans Health Care System, University of Texas Health Science Center, San Antonio, Texas, USA.
Ekaterina V KurbatovaDivision of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Kia BryantDivision of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.ORCID 0000-0003-0785-7800 Wendy CarrDivision of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Melissa L EngleSan Antonio and the South Texas Veterans Health Care System, University of Texas Health Science Center, San Antonio, Texas, USA.ORCID 0000-0001-7740-8192 Nguyen Viet NhungSan Francisco Research Collaboration Unit, Vietnam National Tuberculosis Program-University of California, Hanoi, Vietnam.
Pheona NsubugaUganda-Case Western Reserve University Research Collaboration, Kampala, Uganda.
Kelly E DooleyDivision of Infectious Diseases, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0000-0001-9013-5256 Richard E ChaissonSchool of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID 0000-0003-4710-925X Susan SwindellsDivision of Infectious Diseases, University of Nebraska Medical Center, Omaha, Nebraska, USA.ORCID 0000-0001-5826-6037 Radojka M SavicDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA.ORCID 0000-0003-3143-5579 AIDS Clinical Trial Group and the Tuberculosis Trials Consortium
Funding
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
$1073.1MStatistical 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
$246.6MValidation, 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
$116.8MStatistical and Data Management Center for the AIDS Clinical Trials GroupU01AI068634 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI HUGHES, MICHAEL DAVID · 2006 to 2010
$71.9MDivision of Tuberculosis EliminationDivision of Tuberculosis Elimination 200-2009-32582Division of Tuberculosis Elimination 200-2009-32589Division of Tuberculosis Elimination 200-2009-32593Division of Tuberculosis Elimination 200-2009-32594Division of Tuberculosis Elimination 200-2009-32597Division of Tuberculosis Elimination 200-2009-32598Division of Tuberculosis Elimination 75D30119C06010Division of Tuberculosis Elimination 75D30119C06222Division of Tuberculosis Elimination 75D30119C06225Division of Tuberculosis Elimination 75D30119C06701Division of Tuberculosis Elimination 75D30119C06702Division of Tuberculosis Elimination 75D30119C06703National Center for HIV/AIDS, Viral Hepatitis, STD, and TB PreventionNational Institute of Allergy and Infectious DiseasesNIAID NIH HHS U01 AI068634NIAID NIH HHS UM1 AI068634NIAID NIH HHS UM1 AI068636NIAID NIH HHS UM1 AI106701NIH HHS UM1 AI068634NIH HHS UM1 AI068636NIH HHS UM1 AI106701U.S. Centers for Disease Control and Prevention
6 · The paper itselfAbstract
backgroundEthambutol, a longstanding treatment for tuberculosis (TB), lacks comprehensive pharmacokinetic (PK) data, particularly regarding covariates affecting exposure and their link to treatment outcomes. Using the largest data to date from Study 31/AIDS Clinical Trials Group A5349, we aimed to characterize ethambutol PKs, identify risk factors for lower exposure, quantify relationships between exposure and efficacy and safety outcomes, and explore dosing considerations that optimize risks and benefits.
methodsWe analyzed ethambutol PK data using nonlinear mixed-effect modeling. We evaluated the contribution of ethambutol exposure to efficacy outcomes using parametric time-to-event modeling and safety outcomes using logistic regression.
resultsIn 1493 participants with 3077 plasma samples, a one-compartment model with first-order elimination best described ethambutol PKs, with diabetes, higher creatinine clearance, and higher weight linked to increased clearance. Higher ethambutol exposure was modestly associated with grade 3 or higher adverse events and a reduced risk of TB-related unfavorable outcomes. Target exposures for 95% cure were 8.9 µg·h/mL in the 6-month control regimen and 25.6 µg·h/mL in the 4-month rifapentine regimen. Simulations showed that reducing doses in middle (1200 to 1000 mg) and highest (1600 to 1200 mg) weight bands could equalize median exposures, lowering toxicity risk while maintaining efficacy in the control regimen, but might not achieve target exposure in the rifapentine regimen.
conclusionsThe contribution of ethambutol exposure is regimen-dependent, with a higher efficacy target required for the 4-month rifapentine regimen. Dose reductions for patients above 55 kg may mitigate toxicity in standard therapy but risk compromising efficacy in the shorter regimen.
Indexed as
dose-responseethambutolexposure-responsepopulation pharmacokineticstuberculosis
Identifiers
PMID42813385
PMCPMC13629508
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