Evidence map›Paper›PMID 32481368›Full record

SynthesisMedicine2020

The diagnostic value of miRNA-141 in prostate cancer: A systematic review and PRISMA-compliant meta-analysis.

Yun Ye, Xiao-Hua Yuan, Jian-Jun Wang, Yu-Chen Wang, Su-Liang Li

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 32% 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

8 citing papers in PubMed, 19 citations in OpenAlex.

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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 at 1 institution in 1 country.

Yun YeDepartment of Laboratory Medicine.
Xiao-Hua YuanDepartment of Laboratory Medicine.
Jian-Jun WangEmergency Department, The First Affiliated Hospital of Xi'an Medical University, Xi'an, Shaanxi, China.
Yu-Chen WangDepartment of Laboratory Medicine.
Su-Liang LiDepartment of Laboratory Medicine.
Xi'an Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundmiR-141 has gradually demonstrated its value in the diagnosis of prostate cancer. However, the diagnostic parameters in previous studies differ. A systematic review was conducted to explore the diagnostic value of miR-141 in prostate cancer.

methodsA comprehensive search of the literature in the PubMed, Medline, Cochrane Library, and Embase databases was performed. The included 7 studies assessed the diagnostic value of miR-141 in patients with prostate cancer up to October 31, 2019. We used meta-disc version 1.4 and STATA software version 12.0 to analyze the data.

resultsThe pooled sensitivity and specificity were 0.70 (95% confidence interval [CI] 0.64-0.75) and 0.73 (95% CI 0.64-0.80), respectively. The positive likelihood ratio was 2.88 (95% CI 1.40-5.93), and the negative likelihood ratio was 0.38 (95% CI 0.20-0.71). Further, we note that the pooled diagnostic odds ratio of miR-141 for prostate cancer was 9.94 (95% CI: 2.55-38.80). The summary area under the receiver operating characteristic curve was 0.83 (95% CI: 0.79-0.86). The results of meta-regression suggested that heterogeneity was mainly derived from patient age. The results of the Fagan nomogram showed that it was increased significantly by testing miR-141 for diagnosing prostate cancer.

conclusionThis meta-analysis suggests that miR-141 has a high diagnostic value for prostate cancer. In the future, large-scale prospective studies are needed to verify and evaluate this result.

Indexed as

HumansMaleMicroRNAsProstatic NeoplasmsMicroRNAsMIRN141 microRNA, human

Identifiers

PMID32481368
PMCPMC12245275
OpenAlexW3031176944

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.