Evidence map›Paper›PMID 25053593›Full record

SynthesisTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2014

Meta-analyses of methylation markers for prostate cancer.

Danjie Jiang, Yusheng Shen, Dongjun Dai, Yan Xu, Chunjing Xu, Huangkai Zhu, Tao Huang, Shiwei Duan

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
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  7. Oncology letters · 2016
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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

8 authors.

Danjie JiangZhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang, China.
Yusheng Shen
Dongjun Dai
Yan Xu
Chunjing Xu
Huangkai Zhu
Tao Huang
Shiwei Duan

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer (PCa) is the most frequently diagnosed non-cutaneous cancer that has become the sixth leading cause of mortality in both the developed and developing countries. Accumulating evidence showed a number of genes with aberrant DNA methylation in the pathogenesis of PCa. Here, we conducted a systematic meta-analysis to evaluate the contribution of aberrantly methylated genes to the risk of PCa. Relevant methylation studies were retrieved from PubMed and Wanfang literature databases. In the meta-analysis, Mantel-Haenszel odds ratios (ORs) and 95 % confidence intervals (CIs) were calculated for each methylation event under appropriate models. A total of 594 publications were initially retrieved from PubMed and Wanfang literature database. After a three-step filtration, we harvested 39 case-control articles investigating the role of gene methylation in the prediction of PCa risk. Among the 31 genes involved, 24 genes were shown to be significantly hypermethylated in the PCa patients. Our meta-analyses identified strong associations of four aberrantly methylated genes (GSTP1, RASSF1, p16, and RARB) with PCa. Further research is needed to strengthen our findings in the future.

Indexed as

AdenocarcinomaBiomarkers, TumorDNA MethylationGenes, p16Glutathione S-Transferase piHumansMaleProstatic NeoplasmsReceptors, Retinoic AcidTumor Suppressor ProteinsBiomarkers, TumorGlutathione S-Transferase piGSTP1 protein, humanRASSF1 protein, humanReceptors, Retinoic Acidretinoic acid receptor betaTumor Suppressor Proteins

Identifiers

What OpenQuestion holds

Textmetadata
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.