Evidence map›Paper›PMID 42761426›Full record

ArticleThe Lancet regional health. Europe2026

Drug-resistance profiles, population structure, genomic clustering, and temporal trends in drug resistance among

Dmytro Butov, Tetiana Butova, Valerii Miasoiedov, Yurii Feshchenko, Oksana Nakonechna, Mykhailo Kuzhko, Alex Rosenthal, Alina Grinev, Drew Hoppes, Julia Kilmnick and 7 more

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Article in The Lancet regional health. Europe, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

17 authors.

Dmytro ButovDepartment of Infectious Diseases, Childhood Infectious Diseases and Phthisiology, Kharkiv National Medical University, Kharkiv, Ukraine.
Tetiana ButovaOutpatient Department, Merefa Central District Hospital, Merefa, Ukraine.
Valerii MiasoiedovDepartment of Biology, Kharkiv National Medical University, Kharkiv, Ukraine.
Yurii FeshchenkoNational Scientific Center of Phthisiatry, Pulmonology and Allergology named after F. G. Yanovskyi, National Academy of Medical Sciences of Ukraine, Kyiv, Ukraine.
Oksana NakonechnaDepartment of Biochemistry, Kharkiv National Medical University, Kharkiv, Ukraine.
Mykhailo KuzhkoNational Scientific Center of Phthisiatry, Pulmonology and Allergology named after F. G. Yanovskyi, National Academy of Medical Sciences of Ukraine, Kyiv, Ukraine.
Alex RosenthalOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA.
Alina GrinevOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA.
Drew HoppesOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA.
Julia KilmnickOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA.
Daria LevandovskaCherkasy Regional Tuberculosis Dispensary, Cherkasy, Ukraine.
Anastasiia HryhorievaCherkasy Regional Tuberculosis Dispensary, Cherkasy, Ukraine.
Vitalii VekshynCentral Scientific and Research Laboratory, Kharkiv National Medical University, Kharkiv, Ukraine.
Liliya AbramovaCentral Scientific and Research Laboratory, Kharkiv National Medical University, Kharkiv, Ukraine.
Stefan NiemannResearch Center Borstel-Leibniz Lung Center, Molecular and Experimental Mycobacteriology Group, Borstel, Germany.
Viola DreyerResearch Center Borstel-Leibniz Lung Center, Molecular and Experimental Mycobacteriology Group, Borstel, Germany.
Ukrainian TB Portal Collaborators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ukraine has a high burden of rifampicin-resistant (RR) tuberculosis (TB). We characterised whole-genome sequencing (WGS)-inferred drug-resistance (DR) profiles, population structure, genomic clustering, and temporal trends in DR among Methods: In this multicentre cohort study, we analysed WGS data from pretreatment Mtbc isolates collected across 18 of 24 Ukrainian regions. WGS enabled phylogenetic classification, resistance prediction, clustering. Clinical data were prospectively collected. Findings: WGS was completed for 4162 Mtbc-isolates, of which 3112/4162 (74.8%) were at least RR. Among 3040 multidrug-resistant (MDR) isolates, 1101/3040 (36.2%) had WGS-inferred fluoroquinolone (FQ) resistance and 78/3040 (2.6%) were classified as extensively DR-TB (XDR-TB); 57 had bedaquiline resistance, 32 had linezolid resistance, and 11 had resistance to both drugs. Lineage 2 (L2) accounted for 1608/1939 (82.9%) of MDR, 891/1023 (87.1%) of pre-XDR, and 70/78 (89.7%) of XDR isolates. Overall, 1712/3112 (55.0%) of DR-isolates formed genomic clusters; the three largest comprised 671/3112 (21.6%) of DR-TB cases and consisted exclusively of L2-isolates. WGS-inferred FQ resistance declined from 276/675 (40.9%) to 216/767 (28.2%) during 2019-2023 (absolute difference -12.7 percentage points [95% CI -17.5 to -7.8]; FDR-adjusted q = 4.1 × 10 Interpretation: DR-TB in this cohort was characterised by the predominance of genomically clustered L2 strains and frequent FQ resistance. Although WGS-inferred bedaquiline resistance and XDR-TB were uncommon, combined FQ, bedaquiline, and linezolid resistance warrants continued genomic surveillance. Temporal trends may reflect concurrent epidemiological, diagnostic, and health-system changes. Funding: NIAID/USCRDF; BMBF; Deutsche Forschungsgemeinschaft; EvoLUNG.

Indexed as

BPaL/MDrug-resistant tuberculosisLineage 2mSTRsMultidrug-resistant TBMycobacterium tuberculosisTuberculosisUkraine and warWhole-genome sequencing

Identifiers

PMID42761426
PMCPMC13586565

What OpenQuestion holds

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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.