Evidence map›Paper›PMID 26150727›Full record

ReviewOncoTargets and therapy2015

Prognostic role of urokinase plasminogen activator receptor in gastric and colorectal cancer: A systematic review and meta-analysis.

Hong Guo, Chun Ling, Yun-Yun Ma, Lan-Xia Zhou, Li Zhao

Abstract readReview
In one paragraph

Review in OncoTargets and therapy, 2015. 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. 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

5 authors.

Hong GuoThe First Clinical Medical College, Lanzhou University, Lanzhou, People's Republic of China ; The First Hospital, Lanzhou University, Lanzhou, People's Republic of China.
Chun LingThe First Clinical Medical College, Lanzhou University, Lanzhou, People's Republic of China.
Yun-Yun MaThe First Clinical Medical College, Lanzhou University, Lanzhou, People's Republic of China.
Lan-Xia ZhouThe First Clinical Medical College, Lanzhou University, Lanzhou, People's Republic of China.
Li ZhaoThe First Hospital, Lanzhou University, Lanzhou, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAlthough the urokinase plasminogen activator receptor (uPAR) is expressed in gastric cancer (GC) and colorectal cancer (CRC), its evaluation as a prognostic biomarker remains controversial. In this study, we performed a literature review and meta-analysis to evaluate the association of uPAR expression with the prognosis of patients with GC and CRC.

methodThe PubMed database was searched for material published in English, and data were then extracted and assessed by two reviewers independently. Correlations between uPAR expression and clinicopathological features and overall survival (OS) of patients with GC or CRC were analyzed.

resultsA total of 2,082 patients with GC and CRC from ten studies were included. The results of the meta-analysis showed that the uPAR expression rate in GC and CRC tissues was higher than that in normal tissues (odds ratio [OR] =3.385; 95% confidence interval [CI] 2.605-4.400; P=0.000). Our meta-analysis also revealed a significant association between uPAR expression and lymph node metastasis (OR =1.366; 95% CI =1.086-1.718; P=0.008) and tumor stage (OR =3.076; 95% CI =2.330-4.061; P=0.000). Furthermore, we found that high uPAR expression correlated with poor OS (OR =1.937; 95% CI =1.570-2.930; P=0.000).

conclusionThe uPAR expression may serve as a novel disease marker in GC and CRC, as well as a therapeutic target.

Indexed as

colorectal cancergastric cancermeta-analysisuPAR

Identifiers

PMID26150727
PMCPMC4480592

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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.