Evidence map›Paper›PMID 38702782›Full record

ArticleAnnals of clinical microbiology and antimicrobials2024

Prevalence and genetic basis of Mycobacterium tuberculosis resistance to pretomanid in China.

Bing Zhao, Huiwen Zheng, Juliano Timm, Zexuan Song, Shaojun Pei, Ruida Xing, Yajie Guo, Ling Ma, Feina Li, Qing Li and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of clinical microbiology and antimicrobials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. EliminateJournal of medical microbiology · 2026
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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

19 authors.

Bing Zhao *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Huiwen Zheng *Laboratory of Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Children's Hospital, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, Beijing Pediatric Research Institute, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.
Juliano Timm *TB Alliance, New York, United States of America.
Zexuan SongNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Shaojun PeiSchool of Public Health, Peking University, Beijing, 100191, China.
Ruida XingNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Yajie GuoLaboratory of Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Children's Hospital, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, Beijing Pediatric Research Institute, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.
Ling MaInstitute of Tuberculosis Prevention and Control, Gansu Provincial Center for Disease Control and Prevention, Lanzhou, 730020, China.
Feina LiLaboratory of Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Children's Hospital, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, Beijing Pediatric Research Institute, Capital Medical University, National Center for Children's Health, Beijing, 100045, China.
Qing LiInstitute of Tuberculosis Prevention and Control, Gansu Provincial Center for Disease Control and Prevention, Lanzhou, 730020, China.
Yan LiDepartment of Tuberculosis Control, Chengde Center of Disease Prevention and Control, Chengde, 067000, China.
Lin HuangDepartment of Tuberculosis Control, Chengde Center of Disease Prevention and Control, Chengde, 067000, China.
Chong TengNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Ni WangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Aastha GuptaTB Alliance, New York, United States of America.
Sandeep JunejaTB Alliance, New York, United States of America.
Fei HuangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. huangfei@chinacdc.cn.
Yanlin ZhaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. zhaoyl@chinacdc.cn.
Xichao OuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. ouxc@chinacdc.cn.

Funding

Beijing Natural Science Foundation 7224328National Key R&D Program of China 2022YFC2305204Natural Science Foundation of Gansu Province 22JR5RA712Science and Technology Plan Project of Gansu Province 21JR11RA184
6 · The paper itself

Abstract

backgroundPretomanid is a key component of new regimens for the treatment of drug-resistant tuberculosis (TB) which are being rolled out globally. However, there is limited information on the prevalence of pre-existing resistance to the drug.

methodsTo investigate pretomanid resistance rates in China and its underlying genetic basis, as well as to generate additional minimum inhibitory concentration (MIC) data for epidemiological cutoff (ECOFF)/breakpoint setting, we performed MIC determinations in the Mycobacterial Growth Indicator Tube™ (MGIT) system, followed by WGS analysis, on 475 Mycobacterium tuberculosis (MTB) isolated from Chinese TB patients between 2013 and 2020.

resultsWe observed a pretomanid MIC distribution with a 99% ECOFF equal to 0.5 mg/L. Of the 15 isolates with MIC values > 0.5 mg/L, one (MIC = 1 mg/L) was identified as MTB lineage 1 (L1), a genotype previously reported to be intrinsically less susceptible to pretomanid, two were borderline resistant (MIC = 2-4 mg/L) and the remaining 12 isolates were highly resistant (MIC ≥ 16 mg/L) to the drug. Five resistant isolates did not harbor mutations in the known pretomanid resistant genes.

conclusionsOur results further support a breakpoint of 0.5 mg/L for a non-L1 MTB population, which is characteristic of China. Further, our data point to an unexpected high (14/475, 3%) pre-existing pretomanid resistance rate in the country, as well as to the existence of yet-to-be-discovered pretomanid resistance genes.

Indexed as

Antitubercular AgentsMicrobial Sensitivity TestsMycobacterium tuberculosisTuberculosis, Multidrug-ResistantChinaGenotypeHumansMutationNitroimidazolesPrevalenceWhole Genome SequencingAntitubercular AgentsNitroimidazolespretomanidBreakpointMutationPretomanidResistance

Identifiers

PMID38702782
PMCPMC11069242

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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.