Evidence map›Paper›PMID 39558958›Full record

SynthesisFrontiers in oncology2024

Meta-analysis of the diagnostic value of exosomal microRNAs in renal cell carcinoma.

Qingru Li, Jing Tian, Cuiqing Chen, Hong Liu, Binyi Li

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Targeting miRNAs in renal cell carcinoma: emerging therapeutic strategies.International journal of clinical oncology · 2025
    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

5 authors.

Qingru LiDepartment of Nephrology, the Eighth Clinical Medical School of Guangzhou University of Chinese Medicine, Foshan, China.
Jing TianDepartment of Cardiovascular, the First Clinical Medical College of Henan University of Chinese Medicine, Zhengzhou, China.
Cuiqing ChenDepartment of Nephrology, Foshan Hospital of Traditional Chinese Medicine, Foshan, China.
Hong LiuDepartment of Nephrology, Foshan Hospital of Traditional Chinese Medicine, Foshan, China.
Binyi LiDepartment of Oncology, Shenzhen Bao'an Authentic TCM Therapy Hospital, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: This meta-analysis aims to evaluate the potential of exosomal microRNAs(Exo-miRs) as diagnostic biomarkers for renal cell carcinoma(RCC). Methods: Clinical studies reporting the use of Exo-miRs in the diagnosis of RCC were retrieved from PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Wanfang, VIP, and Chinese Biomedical Literature Database (SinoMed). After relevant data were screened and extracted, the quality of the included studies was assessed using the QUADAS-2 tool. The Meta-disc (version 1.4) software was used to analyze the heterogeneity of threshold/non-threshold effects in the included studies. The Stata MP (version 16.0) software was used to calculate sensitivity(Sen), specificity(Spe), positive likelihood ratio(+LR), negative likelihood ratio(-LR), area under the curve(AUC), diagnostic odds ratio(DOR), and publication bias. Results: A total of 11 studies were included in this meta-analysis. Spearman correlation coefficient was 0.319 ( Conclusion: The expression of Exo-miRs plays an important role in the diagnosis of RCC. However, owing to the limited number of included studies and heterogeneity among them, further clinical research is necessary to verify the findings of this meta-analysis. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023445956.

Indexed as

diagnosisexosomal microRNAsmeta-analysismiRNArenal cell carcinoma

Identifiers

PMID39558958
PMCPMC11571148

What OpenQuestion 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 OpenQuestion graph.