Evidence map›Paper›PMID 40938850›Full record

ArticlePloS one2025

Evaluation of the Xpert MTB/XDR test for detection of isoniazid, fluoroquinolones, and second-line injectable drugs resistance to Mycobacterium tuberculosis-Anhui Province, China.

Ruiqing Zhang, Xundi Bao, Fangjin Bao, Chong Teng, Dongfang Xu, Zhou Liu, Yue Li, Bing Zhao, Hui Xia, Ruida Xing and 2 more

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. What is new in tuberculosis?Clinical medicine (London, England) · 2026
    Review
  2. Article
  3. Rapid Extensively Drug-Resistant (XDR) TB Diagnosis: An In-House DNA Biochip for Drug Resistance Detection and Mutation Profiling ofThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2026
    Article
  4. Article
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

12 authors.

Ruiqing ZhangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China.ORCID https://orcid.org/0009-0002-5704-8518
Xundi BaoMicrobiological Institute, Anhui Provincial Center for Disease Control and Prevention, Hefei, China.
Fangjin BaoTuberculosis Prevention and Control Institute, Anhui Provincial Center for Disease Control and Prevention, Hefei, China.
Chong TengDepartment of Tuberculosis, Beijing Dongcheng District Center for Disease Control and Prevention, Beijing, China.
Dongfang XuMicrobiological Institute, Anhui Provincial Center for Disease Control and Prevention, Hefei, China.
Zhou LiuDepartment of Clinical Laboratory, Anhui Chest Hospital, Hefei, China.
Yue LiDepartment of Clinical Laboratory, Anhui Chest Hospital, Hefei, China.
Bing ZhaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China.
Hui XiaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China.
Ruida XingNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China.
Xichao OuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China.
Yanlin ZhaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe emergence of drug-resistant tuberculosis (DR-TB) has posed significant challenges to TB control. This study assessed the diagnostic performance of the Xpert MTB/XDR test for detecting drug resistance in TB patients.

methodsThis study analyzed 276 samples collected from clinically suspected MDR-TB patients in Auhui Chest Hospital from 01/03/2022-01/03/2023. The Xpert MTB/XDR test was evaluated for its ability to detect resistance to isoniazid (INH), ethionamide (ETH), fluoroquinolones (FLQ), and second-line injectable drugs (SLIDs) compared with phenotypic drug susceptibility testing (pDST). Specimens were investigated by Sanger sequencing, where the MTB/XDR test and pDST results were inconsistent. Afterward, the clinical performance of the Xpert MTB/XDR test was also evaluated with the composite reference test (pDST + sequencing).

resultsThe sensitivity of the Xpert MTB/XDR test against pDST in detecting resistance to INH and FLQ using 276 samples was 95.77% (95% CI: 91.83-98.16) and 93.83% (95% CI: 86.18-97.97), respectively. In contrast, a lower sensitivity of the MTB XDR test in predicting SLIDs and ETH resistance (sensitivity < 75%) compared with pDST was demonstrated in this study. The specificity for detecting all drugs was greater than 90%. Thirty-three samples were retested by sequencing, which identified mutations predicting INH and FLQ resistance, determining whether resistant or not by combining pDST and sequencing results. When considering pDST + sequencing, the sensitivity and specificity of the MTB/XDR assay for INH and FLQ drug targets increased, especially the detection specificity of FLQ has reached 100% (95% CI: 97.95-100).

conclusionThe Xpert MTB/XDR has high sensitivity and specificity in drug-resistant tuberculosis patients, making it better suited to meet the needs of rapid, sensitive, and accurate detection for drug-resistant tuberculosis in resource-limited settings, and serving as a critical tool for achieving personalized treatment and TB control.

Indexed as

Antitubercular AgentsDrug Resistance, Multiple, BacterialFluoroquinolonesIsoniazidMycobacterium tuberculosisTuberculosis, Multidrug-ResistantAdultChinaFemaleHumansMaleMicrobial Sensitivity TestsMiddle AgedSensitivity and SpecificityAntitubercular AgentsFluoroquinolonesIsoniazid

Identifiers

PMID40938850
PMCPMC12431546

What OpenQuestion holds

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Registered trials

None linked

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.