Evidence map›Paper›PMID 25027397›Full record

SynthesisTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2014

MicroRNAs as novel biomarkers in the diagnosis of non-small cell lung cancer: a meta-analysis based on 20 studies.

Ling Chen, Hai Jin

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
1.0field-weighted citation impact, top 26% of its field
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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. [Research Advances of Immunotherapy of Exosome PD-L1 
in Non-small Cell Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2022
    Review
  5. Ultrafast Detection of Exosomal RNAsACS applied nano materials · 2021
    Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. miRNA profiling in serum and tissue samples to assess noninvasive biomarkers for NSCLC clinical outcome.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016
    Article
  15. 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

2 authors at 2 institutions in 1 country.

Ling ChenDepartment of Thoracic Surgery, Changhai Hospital, Second Military Medical University, No. 168 Changhai Road, Shanghai, 200433, China.
Hai Jin
Changhai Hospital · CNSecond Military Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The detection of microRNAs (miRNAs), particularly those obtained from the bloodstream, is an emerging method for diagnosing human cancers, including non-small cell lung cancer (NSCLC). However, studies on the accuracy of miRNAs detection in diagnosing NSCLC have yield inconsistent conclusions, making it necessary to conduct a meta-analysis to systematically evaluate the diagnostic value of miRNAs in the diagnosis of NSCLC. The Medline, Embase, Chinese National Knowledge Infrastructure (CNKI), and Sinomed electronic databases were searched to identify all related articles evaluating the diagnostic value of miRNAs for NSCLC. A bivariate regression model was used to calculate the pooled diagnostic accuracy estimates. A total of 20 articles were included in this meta-analysis, involving 1,563 NSCLC patients and 1,060 healthy controls. Overall, our bivariate random effects meta-analysis yielded area under curve (AUC) of 0.85 (95 % CI: 0.82-0.88) with sensitivity of 76 % (95 CI: 72-80) and specificity of 80 % (95 % CI: 77-84) for the use of miRNAs in differentiating NSCLC patients from healthy controls. In addition, subgroup and meta-regression analyses revealed that a combination of multiple miRNAs (AUC, sensitivity, and specificity of 0.89, 81, and 84, respectively) had a higher diagnostic accuracy than single miRNA-based assays (AUC, sensitivity, and specificity of 0.81, 73, and 77 %, respectively). Furthermore, a comparison of miRNAs expression patterns between blood and sputum samples provides additional evidence that miRNAs obtained from blood (AUC, sensitivity, and specificity of 0.86, 78, and 80 %, respectively) are more credible diagnostic biomarkers than those from sputum (AUC, sensitivity, and specificity of 0.79, 66, and 79 %, respectively). In summary, the current meta-analysis suggests that the detection of miRNAs may be used in the future as an initial screening test for NSCLC, particularly, the detection of a combination of multiple miRNAs, which is a more comprehensive indicator than individual miRNAs.

Indexed as

Biomarkers, TumorCarcinoma, Non-Small-Cell LungGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLung NeoplasmsMicroRNAsMultivariate AnalysisRegression AnalysisSensitivity and SpecificityBiomarkers, TumorMicroRNAs

Identifiers

PMID25027397
OpenAlexW2069382023

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.