Evidence map›Paper›PMID 40122135›Full record

SynthesisThe Cochrane database of systematic reviews2025

Truenat MTB assays for pulmonary tuberculosis and rifampicin resistance in adults and adolescents.

Leeberk Raja Inbaraj, Jefferson Daniel, Mukesh Kumar Sathya Narayanan, Vignes Anand Srinivasalu, Adhin Bhaskar, Katie Scandrett, Priya Rajendran, Richard Kirubakaran, Hemant D Shewade, Muniyandi Malaisamy and 2 more

Abstract readMeta-AnalysisReview
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

12 authors.

Leeberk Raja InbarajDepartment of Clinical Research, ICMR - National Institute for Research in Tuberculosis, Chennai, India.
Jefferson DanielDepartment of Pulmonary Medicine, Christian Medical College, Vellore, India.
Mukesh Kumar Sathya NarayananDepartment of Epidemiology, ICMR - National Institute for Research in Tuberculosis, Chennai, India.
Vignes Anand SrinivasaluDepartment of Clinical Research, ICMR - National Institute for Research in Tuberculosis, Chennai, India.
Adhin BhaskarDepartment of Statistics, ICMR - National Institute for Research in Tuberculosis, Chennai, India.
Katie ScandrettDepartment of Applied Health Sciences, College of Medicine and Health, University of Birmingham, Birmingham, UK.
Priya RajendranDepartment of Bacteriology, ICMR - National Institute for Research in Tuberculosis, Chennai, India.
Richard KirubakaranProf. BV Moses Center for Evidence-Informed Health Care and Health Policy, Christian Medical College, Vellore, India.
Hemant D ShewadeDivision of Health System Research, ICMR - National Institute of Epidemiology, Chennai, India.
Muniyandi MalaisamyDepartment of Health Economics, ICMR - National Institute for Research in Tuberculosis, Chennai, India.
Chandrasekaran PadmapriyadarsiniDirector, ICMR - National Institute for Research in Tuberculosis, Chennai, India.
Yemisi TakwoingiDepartment of Applied Health Sciences, College of Medicine and Health, University of Birmingham, Birmingham, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate and rapid diagnosis is crucial for ending the tuberculosis epidemic. Truenat assays are World Health Organization (WHO)-recommended rapid molecular diagnostic tests that detect Mycobacterium tuberculosis complex and rifampicin resistance.

objectivesPrimary objective To assess the diagnostic accuracy of Truenat assays (MTB, MTB Plus, and MTB-RIF Dx) for detecting pulmonary tuberculosis and rifampicin resistance in adults and adolescents with presumptive pulmonary tuberculosis. Secondary objectives To compare the diagnostic accuracy of Truenat assays and Xpert MTB/RIF Ultra for detecting pulmonary tuberculosis and rifampicin resistance and to investigate potential sources of heterogeneity (e.g. HIV status and smear status). SEARCH

methodsWe searched MEDLINE, Embase, Science Citation Index and Biosis previews, Global Index Medicus, SCOPUS, WHO ICTRP, and ClinicalTrials.gov for published articles and trials in progress on 16and 17 October 2023. We searched ProQuest Dissertations & Theses A&I for dissertations. We contacted tuberculosis experts for ongoing and unpublished studies. A WHO public call for data was made between 30 November 2023 and 15 February 2024. SELECTION CRITERIA: We included cross-sectional and cohort studies that evaluated Truenat assays in sputum samples from adolescents and adults (aged 10 years and older). The microbiological reference standard for identifying pulmonary tuberculosis is culture. The reference standard for rifampicin resistance is a culture-based drug susceptibility test. Two review authors independently screened titles and abstracts, and assessed the full texts of potentially eligible articles. A third review author resolved any disagreements. DATA COLLECTION AND ANALYSIS: We tailored and applied the QUADAS-2 and QUADAS-C tools to assess the risk of bias and applicability. Two review authors independently extracted data for each included study, and a third review author resolved any disagreements. We performed meta-analyses to estimate summary sensitivities and specificities using a bivariate model. We assessed the certainty of evidence using the GRADEpro GDT tool. MAIN

resultsOf nine eligible articles, one contributed two distinct participant cohorts, which we considered as separate studies. Thus, we included 10 studies; three assessed Xpert Ultra. Most studies were set in low- and middle-income countries with a high tuberculosis burden. Six studies (4081 participants, 1379 with tuberculosis) assessed Truenat MTB, and four studies (3073 participants, 750 with tuberculosis) assessed Truenat MTB Plus. Two studies (966 participants, 111 with rifampicin resistance) assessed Truenat MTB-RIF Dx. Overall, the risk of bias in the included studies was low. Three of the 10 studies were judged to have high applicability concern in the patient selection domain. Detection of pulmonary tuberculosis The summary sensitivity of Truenat MTB was 87.6% (95% confidence interval (CI) 81.6 to 91.8; high-certainty evidence), and the summary specificity was 86.1% (95% CI 70.1 to 94.3; moderate-certainty evidence). For Truenat MTB Plus, the summary sensitivity was 90.6% (95% CI 83.7 to 94.8; high-certainty evidence), and the summary specificity was 95.7% (95% CI 94.7 to 96.5; high-certainty evidence). Based on the three comparative studies, the summary sensitivity of Truenat MTB was lower (81.0%, 95% CI 72.8 to 87.2) than that of Xpert Ultra (93.7%, 95% CI 90.4 to 95.9), while the summary specificity of Truenat MTB (97.0%, 95% CI 91.9 to 98.9) was marginally higher than Xpert Ultra (95.3%, 95% CI 90.9 to 97.7). Detection of rifampicin resistance The sensitivities from the two studies were 53% and 85% (moderate-certainty evidence) and specificities were both 97% (high-certainty evidence). AUTHORS'

conclusionsTruenat MTB Plus had higher sensitivity and specificity than Truenat MTB. The high false-positive rate for Truenat MTB is a concern. The sensitivity of Xpert Ultra was significantly higher than that of Truenat MTB, while specificity was slightly lower. Evidence on the accuracy of Truenat MTB-RIF Dx was limited.

Indexed as

Antibiotics, AntitubercularDrug Resistance, BacterialMolecular Diagnostic TechniquesMycobacterium tuberculosisRifampinTuberculosis, Multidrug-ResistantTuberculosis, PulmonaryAdolescentAdultBiasHumansSensitivity and SpecificityAntibiotics, AntitubercularRifampin

Identifiers

PMID40122135
PMCPMC11930391

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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.