ArticleScientific reports2025
Diagnostic efficacy of targeted next-generation sequencing in suspected lower respiratory tract infections of patients with cancer: a retrospective study.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Harnessing next-generation microbial diagnostics to optimize infection management in immunocompromised hosts.Current opinion in infectious diseases · 2026Review
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9 authors.
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Abstract
Lower respiratory tract infections (LRTIs) significantly threaten the prognosis of cancer. Conventional microbial culture (CMC) often fails to identify pathogens, leading to inappropriate antibiotic use and delayed treatment. This study assesses the effectiveness of targeted next-generation sequencing (tNGS) for diagnosing LRTIs in malignant patients, including those with lung cancer and extrapulmonary malignancies. A retrospective study was conducted on 190 patients diagnosed with malignant tumours and suspected LRTI. Sputum and bronchoalveolar lavage fluid (BALF) samples were analysed using both tNGS and CMC concurrently. tNGS involves DNA/RNA extraction, PCR amplification, and sequencing, followed by clinical interpretation of the results. tNGS identified 58 pathogens compared with the 16 identified by CMC, with detection rates of 91.6% versus 24.2%, respectively. The sensitivity of tNGS was significantly greater (96.1%) than that of CMC (33.3%). Notably, 67.4% of patients tested positive exclusively via tNGS, highlighting its superior ability to detect pathogens, especially in mixed infections. Moreover, antibiotic therapy was modified for 41 patients on the basis of the findings from tNGS, resulting in escalations, de-escalations, or maintenance strategies. tNGS is an efficient diagnostic tool for LRTIs in cancer patients. Its rapid results can improve clinical decision-making and antibiotic optimization, potentially enhancing patient outcomes, especially in the diagnosis and treatment of special infection cases.
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