Evidence map›Paper›PMID 39486428›Full record

ArticleThe Lancet. Infectious diseases2025

Evaluating culture-free targeted next-generation sequencing for diagnosing drug-resistant tuberculosis: a multicentre clinical study of two end-to-end commercial workflows.

Rebecca E Colman, Marva Seifert, Andres De la Rossa, Sophia B Georghiou, Christine Hoogland, Swapna Uplekar, Sacha Laurent, Camilla Rodrigues, Priti Kambli, Nestani Tukvadze and 5 more

Abstract readMulticenter Study
In one paragraph

Article in The Lancet. Infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Article
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  3. Use of reverse dot blot hybridization DNA-array and targeted next-generation sequencing for the detection of drug resistance in patients with tuberculosis: a prospective diagnostic accuracy study.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
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  19. Characterizing the epidemiology ofEmerging microbes & infections · 2025
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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

15 authors.

Rebecca E ColmanFIND, Geneva, Switzerland; Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, University of San Diego, San Diego, CA, USA. Electronic address: rcolman@health.ucsd.edu.
Marva SeifertFIND, Geneva, Switzerland; Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, University of San Diego, San Diego, CA, USA.
Andres De la RossaFIND, Geneva, Switzerland.
Sophia B GeorghiouFIND, Geneva, Switzerland.
Christine HooglandFIND, Geneva, Switzerland.
Swapna UplekarFIND, Geneva, Switzerland.
Sacha LaurentFIND, Geneva, Switzerland.
Camilla RodriguesHinduja Hospital and Medical Research Centre, Mumbai, India.
Priti KambliHinduja Hospital and Medical Research Centre, Mumbai, India.
Nestani TukvadzeNational Center for Tuberculosis and Lung Diseases, Tbilisi, Georgia.
Nino MaghradzeNational Center for Tuberculosis and Lung Diseases, Tbilisi, Georgia.
Shaheed V OmarCentre for Tuberculosis, National & WHO Supranational TB Reference Laboratory, National Institute for Communicable Diseases, a division of the National Health Laboratory Service, Johannesburg, South Africa.
Lavania JosephCentre for Tuberculosis, National & WHO Supranational TB Reference Laboratory, National Institute for Communicable Diseases, a division of the National Health Laboratory Service, Johannesburg, South Africa.
Anita SureshFIND, Geneva, Switzerland.
Timothy C RodwellFIND, Geneva, Switzerland; Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, University of San Diego, San Diego, CA, USA.

Funding

VirologyP30AI036214 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SONIA JAIN · 1994 to 2026
$78.4M
Emory-Georgia TB Research Training ProgramD43TW007124 · FIC · EMORY UNIVERSITY · PI HENRY M BLUMBERG, Nestani Tukvadze · 2004 to 2026
$4.6M
Automated Sequencing for Culture-free Diagnosis of Drug Resistant TBR01AI176401 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Rebecca Elizabeth Colman, Timothy Charles Rodwell · 2023 to 2026
$2.9M
FIC NIH HHS D43 TW007124NIAID NIH HHS P30 AI036214NIAID NIH HHS R01 AI176401
6 · The paper itself

Abstract

backgroundDrug-resistant tuberculosis remains a major obstacle in ending the global tuberculosis epidemic. Deployment of molecular tools for comprehensive drug resistance profiling is imperative for successful detection and characterisation of tuberculosis drug resistance. We aimed to assess the diagnostic accuracy of a new class of molecular diagnostics for drug-resistant tuberculosis.

methodsWe conducted a prospective, cross-sectional, multicentre clinical evaluation of the performance of two targeted next-generation sequencing (tNGS) assays for drug-resistant tuberculosis at reference laboratories in three countries (Georgia, India, and South Africa) to assess diagnostic accuracy and index test failure rates. Eligible participants were aged 18 years or older, with molecularly confirmed pulmonary tuberculosis, and at risk for rifampicin-resistant tuberculosis. Sensitivity and specificity for both tNGS index tests (GenoScreen Deeplex Myc-TB and Oxford Nanopore Technologies [ONT] Tuberculosis Drug Resistance Test) were calculated for rifampicin, isoniazid, fluoroquinolones (moxifloxacin, levofloxacin), second line-injectables (amikacin, kanamycin, capreomycin), pyrazinamide, bedaquiline, linezolid, clofazimine, ethambutol, and streptomycin against a composite reference standard of phenotypic drug susceptibility testing and whole-genome sequencing.

findingsBetween April 1, 2021, and June 30, 2022, 832 individuals were invited to participate in the study, of whom 720 were included in the final analysis (212, 376, and 132 participants in Georgia, India, and South Africa, respectively). Of 720 clinical sediment samples evaluated, 658 (91%) and 684 (95%) produced complete or partial results on the GenoScreen and ONT tNGS workflows, respectively, with 593 (96%) and 603 (98%) of 616 smear-positive samples producing tNGS sequence data. Both workflows had sensitivities and specificities of more than 95% for rifampicin and isoniazid, and high accuracy for fluoroquinolones (sensitivity approximately ≥94%) and second line-injectables (sensitivity 80%) compared with the composite reference standard. Importantly, these assays also detected mutations associated with resistance to critical new and repurposed drugs (bedaquiline, linezolid) not currently detectable by any other WHO-recommended rapid diagnostics on the market. We note that the current format of assays have low sensitivity (≤50%) for linezolid and more work on mutations associated with drug resistance is needed.

interpretationThis multicentre evaluation demonstrates that culture-free tNGS can provide accurate sequencing results for detection and characterisation of drug resistance from Mycobacterium tuberculosis clinical sediment samples for timely, comprehensive profiling of drug-resistant tuberculosis.

fundingUnitaid.

Indexed as

High-Throughput Nucleotide SequencingMycobacterium tuberculosisTuberculosis, Multidrug-ResistantAdultAntitubercular AgentsCross-Sectional StudiesFemaleHumansIndiaMaleMicrobial Sensitivity TestsMiddle AgedProspective StudiesSensitivity and SpecificitySouth AfricaWorkflowAntitubercular Agents

Identifiers

PMID39486428
PMCPMC11871994

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Registered trials

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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.