Evidence map›Paper›PMID 41331079›Full record

ArticleScientific reports2025

Diagnostic efficacy of targeted next-generation sequencing in suspected lower respiratory tract infections of patients with cancer: a retrospective study.

Xiaoqing Fan, Yue Liang, Xinmiao Liu, Liping Meng, Xinfei Zhao, Yajun Huang, Yan Sun, Yulin Sun, Hongjun Gao

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

9 authors.

Xiaoqing Fan *Department of Clinical Laboratory, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China.
Yue Liang *Department of Clinical Laboratory, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China.
Xinmiao Liu *Department of Clinical Laboratory, State Key Laboratory of Molecular Oncology, National Clinical Research Center for Cancer/Cancer Hospital, National Cancer Center, Chinese Academy of Medical Sciences, Peking Union Medical College, Chaoyang District, Beijing, China.
Liping Meng *Department of Clinical Laboratory, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China.
Xinfei ZhaoTaiyuan Kingmed Center for Clinical Laboratory Co., Ltd, Taiyuan, China.
Yajun HuangTaiyuan Kingmed Center for Clinical Laboratory Co., Ltd, Taiyuan, China.
Yan SunDepartment of Clinical Laboratory, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China.
Yulin SunDepartment of Clinical Laboratory, State Key Laboratory of Molecular Oncology, National Clinical Research Center for Cancer/Cancer Hospital, National Cancer Center, Chinese Academy of Medical Sciences, Peking Union Medical College, Chaoyang District, Beijing, China.
Hongjun GaoDepartment of Clinical Laboratory, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China. gaohongjun@cicams.ac.cn.

Funding

Internal Fund of Shanxi Province Cancer Hospital IIT-2024-069Science and Technology Department Basic Research Project of Shanxi 202303021211225
6 · The paper itself

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.

Indexed as

High-Throughput Nucleotide SequencingNeoplasmsRespiratory Tract InfectionsAdultAgedAged, 80 and overAnti-Bacterial AgentsBronchoalveolar Lavage FluidFemaleHumansMaleMiddle AgedRetrospective StudiesSputumAnti-Bacterial AgentsConventional microbial cultureExtrapulmonary malignanciesLower respiratory tract infectionsLung cancerTargeted next-generation sequencing

Identifiers

PMID41331079
PMCPMC12783647

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.