Evidence map›Paper›PMID 29660899›Full record

ArticleCancer biomarkers : section A of Disease markers2018

Plasma exosome levels in non-small-cell lung cancer: Correlation with clinicopathological features and prognostic implications.

Qingyun Liu, Ying Xiang, Shuai Yuan, Weijia Xie, Chengying Li, Zeyao Hu, Na Wu, Long Wu, Zubin Yu, Li Bai and 1 more

Abstract read
In one paragraph

Article in Cancer biomarkers : section A of Disease markers, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  14. [Advances in Exosomes in the Pathogenesis and Diagnosis of Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2020
    Review
  15. Article
  16. Understanding the Mechanisms of Resistance inInternational journal of molecular sciences · 2019
    Review
  17. Article
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

11 authors.

Qingyun LiuDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China.
Ying XiangDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China.
Shuai YuanDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China.
Weijia XieDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China.
Chengying LiDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China.
Zeyao HuDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China.
Na WuDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China.
Long WuDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China.
Zubin YuDepartment of Thoracic Surgery, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing 400038, China.
Li BaiDepartment of Respiratory Disease, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing 400038, China.
Yafei LiDepartment of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing 400038, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBiomarker studies revealed important clinical significance of exosome for cancer patients. However, there is currently no consensus on exosome quantification methods.

methodsBicinchoninic acid (BCA) method, acetylcholinesterase (AChE) method and nanoparticle tracking analysis (NTA) were utilized to quantify 20 plasma exosome samples, and interrelations between these three methods were explored. Associations of plasma exosome levels with characteristics and prognosis of 208 non-small-cell lung cancer (NSCLC) patients were investigated.

resultsResults of the three methods for exosome quantification were significantly correlated with each other. Correlation coefficient between AChE and NTA (r= 0.79, P< 0.001) was greater than that between BCA and NTA (r= 0.64, P= 0.003). Plasma exosome levels of 208 NSCLC patients were then quantified with AChE method. Exosome level was significantly associated with tumour stage (P< 0.001) and the history of chronic obstructive pulmonary disease (P= 0.023). Cox proportional hazard analysis demonstrated that higher exosome level was independently associated with poorer overall survival (P= 0.033; hazard ratio = 1.72, 95% confidence interval: 1.05-2.83).

conclusionsPlasma exosome level correlates with tumor stage and the history of chronic obstructive pulmonary disease, and may serve as a prognostic factor for NSCLC.

Indexed as

ExosomesAgedBiomarkersCarcinoma, Non-Small-Cell LungCombined Modality TherapyFemaleHumansKaplan-Meier EstimateLung NeoplasmsMaleMiddle AgedNeoplasm GradingNeoplasm StagingPrognosisProportional Hazards ModelsBiomarkersbiomarkerexosomeNon-small-cell lung cancerprognosisquantification

Identifiers

PMID29660899
PMCPMC13078434

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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.