Application Research of Targeted Next-Generation Sequencing Technology Based on Bronchoalveolar Lavage Fluid in the Diagnosis of Pulmonary Tuberculosis and Drug-Resistance Detection
Year: 2026
Type: article
Study design: Observational Study
Abstract: Purpose: To evaluate the clinical value of targeted next-generation sequencing (tNGS) using bronchoalveolar lavage fluid (BALF) in diagnosing pulmonary tuberculosis (PTB) and detecting resistance to first-line anti-tuberculosis drugs, and to compare its performance with traditional methods. Patients and Methods: In this study, BALF samples were collected from 258 patients with suspected PTB and subjected to AFB staining, mycobacterial solid culture, TB-DNA PCR, Xpert MTB/RIF, and tNGS. Using comprehensive clinical diagnosis or phenotypic DST as the reference, we evaluated the sensitivity, specificity, and other metrics of each method and assessed tNGS performance in detecting resistance to rifampicin, isoniazid, streptomycin, and ethambutol. Results: Overall, tNGS achieved a sensitivity of 91.10%, specificity of 89.70%, and an AUC of 0.904, all significantly higher than traditional methods. It uniquely identified 24 positive cases missed by other methods. In smear-negative patients, sensitivity remained high at 88.10%, with an AUC of 0.891. For drug-resistance detection, tNGS showed the best performance in judging isoniazid resistance (sensitivity 83.10%, specificity 90.30%), and also showed high negative predictive values for rifampicin, streptomycin, and ethambutol (all > 94%). Conclusion: tNGS provides excellent diagnostic accuracy for PTB and reliable detection of drug-resistant mutations from BALF samples. It is particularly suitable for smear-negative cases and for resistance screening, making it a powerful complement to the existing TB diagnosis system with high clinical application potential.
Source: Infection and Drug Resistance
DOI: 10.2147/idr.s567798
Institution: Guangxi Medical University
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,836
OpenAlex ID: W7119511418
