Evidence map›Paper›PMID 25788990›Full record

ArticleOncology letters2015

Biomarkers for gastric cancer: Progression in early diagnosis and prognosis (Review).

Ziliang Jin, Weihua Jiang, Liwei Wang

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncology letters, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 1 pooled it
5.2field-weighted citation impact, top 4% 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

62 citing papers in PubMed, 1 synthesis or guideline pooled it, 106 citations in OpenAlex.

  1. Pooled it
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  15. SustainedLife science alliance · 2021
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  20. Prediction of Gastric Cancer-Related Proteins Based on Graph Fusion Method.Frontiers in cell and developmental biology · 2021
    Article

2 more citing papers are in PubMed but not listed here.

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 1 institution in 1 country.

Ziliang JinDepartment of Oncology, Shanghai Key Laboratory of Pancreatic Diseases, Shanghai Jiaotong University Affiliated First People's Hospital, Shanghai 200080, P.R. China.
Weihua JiangDepartment of Oncology, Shanghai Key Laboratory of Pancreatic Diseases, Shanghai Jiaotong University Affiliated First People's Hospital, Shanghai 200080, P.R. China.
Liwei WangDepartment of Oncology, Shanghai Key Laboratory of Pancreatic Diseases, Shanghai Jiaotong University Affiliated First People's Hospital, Shanghai 200080, P.R. China.
Shanghai First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancer is one of leading causes of cancer-related mortality worldwide and is a notable disease due to its heterogeneity. Recently, numerous studies have investigated the molecular basis of gastric cancer, involving the alteration of pathogenesis, and invasion and metastasis. With the development of modern technologies, various novel biomarkers had been identified that appear to possess diagnostic and prognostic value; therefore, the present review describes our current knowledge of biomarkers for the early diagnosis and prognosis of gastric cancer. Classic biomarkers for gastric cancer diagnosis include carcinoembryonic antigen and cancer antigen 19-9, while microRNA and DNA hypomethylation are proposed as novel biomarkers. Excluding classical biomarkers, biomarkers for determining the progression and prognosis of gastric cancer focus on targeting microRNAs, epigenetic alterations and genetic polymorphisms.

Indexed as

biological markerearly diagnosisgastric cancerprognosis

Identifiers

PMID25788990
PMCPMC4356326
OpenAlexW2018928655

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.