Evidence map›Paper›PMID 29887920›Full record

SynthesisDisease markers2018

Systematic Review and Meta-Analysis of Diagnostic Accuracy of miRNAs in Patients with Pancreatic Cancer.

Xiao Sun, Xiaobin Zhou, Yuan Zhang, Xiaoyan Zhu, Haihua Liu

Abstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Disease markers, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Xiao SunDepartment of Epidemiology and Health Statistics, College of Public Health, Qingdao University, Qingdao, Shandong 266021, China.
Xiaobin ZhouDepartment of Epidemiology and Health Statistics, College of Public Health, Qingdao University, Qingdao, Shandong 266021, China.ORCID 0000-0003-0504-3061
Yuan ZhangDepartment of Cardiac Surgery, Qingdao Municipal Hospital, Qingdao, Shandong 266021, China.
Xiaoyan ZhuDepartment of Epidemiology and Health Statistics, College of Public Health, Qingdao University, Qingdao, Shandong 266021, China.
Haihua LiuDepartment of Epidemiology and Health Statistics, College of Public Health, Qingdao University, Qingdao, Shandong 266021, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is reported that miRNAs are aberrantly expressed in patients with pancreatic cancer. However, the diagnostic value of miRNAs in pancreatic cancer remains controversial. The meta-analysis was to access diagnostic accuracy of miRNAs in pancreatic cancer.

methodsPubMed, Scopus, Web of Science, Chinese National Knowledge Infrastructure (CNKI), WANFANG Data, China Biomedical Literature Database (CBM), and VIP databases were retrieved up to June 30, 2016, to collect articles concerning the diagnosis of miRNAs in pancreatic cancer. The methodological quality of each study was assessed by the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). This meta-analysis was conducted using RevMan5.0, MetaDiSc 1.4, and Stata 12.0 software.

resultsThere are 40 articles including 109 studies. The pooled SEN was 0.81 (95% CI, 0.80-0.82), the pooled SPE was 0.78 (95% CI, 0.77-0.79), the pooled +LR was 3.32 (95% CI, 2.92-3.80), the pooled -LR was 0.27 (95% CI, 0.24-0.31), the pooled DOR was 14.56 (95% CI, 11.55-18.34), and pooled AUC was 0.86 (95% CI, 0.84-0.88). DISCUSSION: This meta-analysis demonstrated that miRNA makes a significant impact in the pancreatic cancer diagnosis with a high SEN and SPE, particularly using multiple miRNAs.

Indexed as

Biomarkers, TumorChinaEarly Detection of CancerGene Expression Regulation, NeoplasticHumansMicroRNAsPancreatic NeoplasmsBiomarkers, TumorMicroRNAs

Identifiers

PMID29887920
PMCPMC5977035

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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.