In one paragraphArticle in American journal of respiratory and critical care medicine, 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
5 · Who and what moneyAuthors and funding
17 authors.
Simon C MendelsohnSouth African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa.ORCID 0000-0002-4054-2766 Bruno B AndradeLaboratório de Pesquisa Clínica e Translacional, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.ORCID 0000-0001-6833-3811 Mariana Araújo-PereiraLaboratório de Pesquisa Clínica e Translacional, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.ORCID 0000-0002-1141-1580 Mzwandile ErasmusSouth African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa.
Alice M S AndradeLaboratório de Pesquisa Clínica e Translacional, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.
Michelle FisherSouth African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa.
Vanessa M MuwangaSouth African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa.ORCID 0000-0002-9415-5438 Afranio L KritskiFaculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil.ORCID 0000-0002-5900-6007 Marcelo Cordeiro-SantosFundação de Medicina Tropical Doutor Heitor Vieira Dourado, Manaus, Amazonas, Brazil.ORCID 0000-0002-7140-7145 Valeria C RollaLaboratorio de Pesquisa Clinica em Micobacterioses, Instituto Nacional de Infectologia Evandro Chagas, Fiocruz, Rio de Janeiro, Brazil.ORCID 0000-0002-0841-1408 Mark HatherillSouth African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa.
Thomas J ScribaSouth African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa.ORCID 0000-0002-0641-1359 and members of the RePORT South Africa
and RePORT-Brazil Consortia
Funding
CCASAnet: Caribbean, Central and South America NetworkU01AI069923 · NIAID · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Pedro Enrique Cahn, Jessica L Castilho · 2006 to 2026
$41.6MImmunogenetic predictors of active and incipient TB in HIV-negative and -positive close TB contactsR01AI147765 · NIAID · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ANDRADE, BRUNO DE BEZERRIL, HAWN, THOMAS R · 2019 to 2023
$4.3MRegional Prospective Observational Research in Tuberculosis (RePORT) – Brazil NetworkU01AI172064 · NIAID · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BRUNO DE BEZERRIL ANDRADE, TIMOTHY R STERLING · 2023 to 2026
$4.0MPredictors of treatment toxicity, failure, and relapse in HIV-related tuberculosisR01AI120790 · NIAID · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ROLLA, VALERIA CAVALCANTI, STERLING, TIMOTHY R · 2016 to 2019
$2.6MCivilian Research and Development Foundation Global G-202212-69603Civilian Research and Development Foundation Global R-202208-69014Conselho Nacional de Desenvolvimento Científico e TecnológicoDepartamento de Ciência e TecnologiaMinistério da Saúde 25029.000507/2013-07NIAID NIH HHS R01 AI120790NIAID NIH HHS R01 AI147765NIAID NIH HHS U01 AI069923NIAID NIH HHS U01 AI172064NIH HHS R01 AI120790NIH HHS R01 AI147765NIH HHS U01AI069923NIH HHS U01AI172064RePORT South AfricaSecretaria de Ciência e TecnologiaSouth African Medical Research Council and CRDF Global 71788
6 · The paper itselfAbstract
rationaleNon-sputum biomarkers to monitor tuberculosis treatment and predict poor outcomes are lacking.
objectivesTo evaluate host-blood transcriptomic signatures for treatment monitoring and prognosis of death, treatment failure, and recurrence in adults with pulmonary tuberculosis.
methodsAdults with culture-confirmed, drug-susceptible pulmonary tuberculosis were enrolled at 5 Brazilian sites. Whole-blood PAXgene samples were collected at baseline, month 2 (M2), and end of treatment (EoT). Treatment failure was defined as sputum culture positivity at month 5 or later. Participants were followed for 24 months from treatment initiation for clinical or microbiological tuberculosis recurrence. Unfavorable outcomes were matched ∼1:3 to recurrence-free cure. Twenty-two published blood transcriptomic signatures were measured by microfluidic RT-qPCR and benchmarked against the WHO Target Product Profile (TPP) criteria. MEASUREMENTS AND MAIN
resultsWe matched 263 participants with recurrence-free cure to 33 with treatment failure, 24 who died (tuberculosis/unknown cause), and 9 with recurrence. Signature scores generally declined from baseline to EoT. Multiple signatures measured at baseline and M2 predicted recurrence (AUC range 0.71-0.91), with waning performance when measured at EoT (AUC range 0.42-0.89). Against the WHO TPP, 2/22 signatures met minimum criteria at baseline, 13/22 at M2, and none at EoT. Prediction of treatment failure was poor across timepoints (AUC < 0.70). In contrast, several signatures measured at baseline predicted death during treatment or follow-up (AUC ≥ 0.80).
conclusionsBlood transcriptomic signatures tracked treatment response and predicted recurrence and death, meeting WHO TPP benchmarks at baseline and M2. These findings support prospective, biomarker-guided trials to individualize tuberculosis therapy-shortening regimens for early responders and intensifying care for high-risk patients.
Indexed as
Antitubercular AgentsTranscriptomeTuberculosis, PulmonaryAdultBiomarkersBrazilFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisRecurrenceTreatment FailureTreatment OutcomeAntitubercular AgentsBiomarkersbiomarkersgene expression signatureprognosistreatment outcometuberculosis
Identifiers
PMID42085241
PMCPMC13519344
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