Evidence map›Paper›PMID 29942152›Full record

ArticleCancer management and research2018

A two-microRNA signature as a diagnostic and prognostic marker of pancreatic adenocarcinoma.

Yang Yu, Xiao Feng, Shundong Cang

Open access · goldAbstract read
In one paragraph

Article in Cancer management and research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 28% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 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

3 authors at 2 institutions in 1 country.

Yang Yu *Department of Oncology, Henan Province People's Hospital, Henan University, Zhengzhou, Henan, China.
Xiao Feng *Department of Oncology, Henan Province People's Hospital, Henan University, Zhengzhou, Henan, China.
Shundong CangDepartment of Oncology, Henan Province People's Hospital, Henan University, Zhengzhou, Henan, China.
Henan University · CNHenan Provincial People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimSome cancer-specific miRNAs are dysregulated in pancreatic adenocarcinoma (PAAD) and involved in cell autophagy, differentiation, proliferation, migration, invasion, and malignant transformation. The aim of our study was to determine a panel of new diagnostic and prognostic biomarkers for PAAD.

methodsWe conducted a comprehensive analysis of global miRNA-expression profiles and corresponding prognosis information of 168 PAAD patients from the Cancer Genome Atlas data set. A total of 16 differentially expressed miRNAs were identified as aberrantly expressed in PAAD, and six of these were evaluated for use as diagnostic markers for PAAD. Next, we confirmed a two-miRNA signature significantly associated with PAAD patient diagnosis and outcome prediction.

resultsThe panel of two miRNAs showed outstanding diagnostic performance, with sensitivity of 100% and specificity of 87.5%. Finally, we divided the PAAD patients into high-risk and low-risk groups based on the expression profile of the two miRNAs. Kaplan-Meier analysis demonstrated that patients in the high-risk group had significantly worse prognosis than patients in the low-risk group. Univariate and multivariate Cox regression analysis showed that the two-miRNA signature was an independent prognostic factor for the overall survival of PAAD patients.

conclusionTaken together, the two-miRNA signature may serve as an accurate and sensitive biomarker for diagnosis and PAAD-outcome prediction, facilitating the diagnosis and potentially improving treatment outcome of PAAD.

Indexed as

diagnosismicroRNA signaturepancreatic adenocarcinomaprognosisTCGA

Identifiers

PMID29942152
PMCPMC6005310
OpenAlexW2808296703

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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.