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September 12, 2025Microbiology Spectrum0 citationsOpen Access

Hierarchical integration of mNGS, PCR, and other conventional methods for precision TB diagnostics

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YZYating ZhaoLDLifang DuJSJunli Song

Key Points

  • mNGS achieved the highest sensitivity at 100%, demonstrating its efficacy in tuberculosis detection amid various methods.
  • The study evaluated seven TB diagnostic methods, revealing significant differences in sensitivity and specificity across techniques.
  • A retrospective analysis of 141 samples highlighted the advantages of specific combinations of TB detection methods for healthcare resources.
  • This comprehensive evaluation provides viable strategies for optimizing tuberculosis diagnostics aligned with WHO guidelines.

Abstract

ABSTRACT This study systematically compared the diagnostic accuracy of seven assays for detecting the Mycobacterium tuberculosis complex, including metagenomic next-generation sequencing (mNGS), droplet digital polymerase chain reaction, real-time quantitative polymerase chain reaction, EasyNAT MTC, GeneXpert MTB/RIF, interferon-gamma release assay (IGRA), and acid‒fast staining (AFS). We try to select appropriate combinations of tuberculosis (TB) detection methods for regions with varying levels of medical resources, based on sensitivity, cost-effectiveness, and operational feasibility. A retrospective analysis was conducted on 141 samples collected from patients with suspected active TB at The First Affiliated Hospital of Sun Yat-sen University between April 2022 and April 2024. Among these samples, there were 100 cases assigned to the case group and 41 cases to the control group, based on the tuberculosis diagnostic criteria. Historical data for Xpert, IGRA, and AFS were collected, and parallel experiments using mNGS, droplet digital PCR (ddPCR), real-time quantitative polymerase chain reaction (RT-qPCR), and EasyNAT were conducted on all samples. Diagnostic performance was evaluated by comparing it with the final clinical diagnoses. Sensitivity, specificity, positive predictive value, negative predictive value, and receiver operating characteristic (ROC) curve analysis were conducted, along with DeLong tests for statistical comparison. Compared with the final clinical diagnosis, mNGS demonstrated the highest sensitivity (100%), followed by IGRA (79.2%), EasyNAT (79.1%), RT-qPCR (78.0%), ddPCR (75.8%), Xpert (75.3%), and AFS (16.7%). The specificity was 100% for both Xpert and AFS, followed by ddPCR (97.6%), RT-qPCR (95.1%), EasyNAT (92.7%), IGRA (72.7%), and mNGS (75.6%). ROC analysis revealed a significantly greater area under the ROC curve for mNGS (0.878) than for ddPCR (0.817, P = 0.031). DeLong tests revealed statistically significant differences in diagnostic performance between mNGS and ddPCR ( P < 0.05) and between IGRA and AFS ( P < 0.01). mNGS uniquely identified the pathogens involved in co-infection and quantified pathogen-specific sequencing reads. Through a comprehensive evaluation of the diagnostic efficacy, cost-effectiveness, and timeliness of tuberculosis detection methods, we propose corresponding combinations of TB testing approaches for regions with different healthcare resources. For undeveloped regions with limited resources, a combination of AFS +EasyNAT + chest X-ray is recommended. Primary care facilities may additionally employ IGRA + RT-qPCR. Intermediate-level hospitals can incorporate Xpert MTB/RIF for drug resistance testing, while tertiary hospitals or specialized centers should, on the basis of these fundamental tests, utilize mNGS for diagnosis and ddPCR for therapeutic monitoring in patients with complex mixed infections. IMPORTANCE This study is the first to comprehensively evaluate the diagnostic efficacy, cost-effectiveness, and timeliness of seven TB detection methods in a single-center cohort. Our findings provide actionable solutions for optimizing TB diagnostics in diverse healthcare ecosystems, aligning with the WHO’s End TB Strategy to ensure equitable access to rapid diagnostics.

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Cite This Study

Zhao et al. (2025) studied this question.

synapsesocial.com/papers/68d46cc631b076d99fa68c56https://doi.org/10.1128/spectrum.01931-25
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