Evidence map›Paper›PMID 41970393›Full record

ArticleFrontiers in medicine2026

Multidimensional biomarker profiling of bronchoalveolar lavage fluid for diagnostic and prognostic evaluation of lung cancer: a retrospective observational study.

Yu Wang, Jie Huang, Xiaomeng Xie, Shaolin Li, Qiang Fu

Abstract read
In one paragraph

Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Yu WangDepartment of Respiratory, The Fifth Affiliated Hospital of Jinan University (Heyuan Shenhe People's Hospital), Heyuan City, Guangdong Province, China.
Jie HuangDepartment of Oncology, The Fifth Affiliated Hospital of Jinan University (Heyuan Shenhe People's Hospital), Heyuan City, Guangdong Province, China.
Xiaomeng XieDepartment of Digestive, The Fifth Affiliated Hospital of Jinan University (Heyuan Shenhe People's Hospital), Heyuan City, Guangdong Province, China.
Shaolin LiDepartment of Cardiovascular, The Fifth Affiliated Hospital of Jinan University (Heyuan Shenhe People's Hospital), Heyuan City, Guangdong Province, China.
Qiang FuDepartment of Urology, The First People's Hospital of Xiangcheng, Zhoukou City, Henan Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lung cancer remains a leading cause of cancer-related mortality worldwide. This study evaluated multidimensional biomarkers in bronchoalveolar lavage fluid (BALF) for the diagnosis and prognostic evaluation of lung cancer. Methods: This retrospective observational study included 100 patients who underwent clinically indicated bronchoscopy between April 2022 and April 2024, comprising 65 patients with histopathologically confirmed lung cancer and 35 patients with benign pulmonary diseases. BALF data obtained during routine clinical care were retrospectively collected for tumor markers (CEA, CYFRA21-1, NSE, ProGRP), cytokines (IL-6, IL-8, TNF- Results: BALF concentrations of CEA, CYFRA21-1, NSE, ProGRP, IL-6, IL-8, and TNF- Conclusion: BALF provides tumor-proximal diagnostic and prognostic information in lung cancer. Enriched tumor markers, inflammatory imbalance, particularly the IL-6/IL-10 ratio, enhanced ctDNA detection, and local immunosuppressive immune features support the utility of BALF as a minimally invasive liquid biopsy for lung cancer evaluation and risk stratification.

Indexed as

biomarkersbronchoalveolar lavage fluidcirculating tumor DNAcytokinesliquid biopsylung neoplasmstumor microenvironment

Identifiers

PMID41970393
PMCPMC13066139

What Socratic holds

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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 Socratic graph.