Evidence map›Paper›PMID 25555557›Full record

SynthesisFamilial cancer2015

A risk of digestive tract neoplasms susceptibility in miR-146a and miR-196a2.

Mingkun Xie, Yating Li, Jing Wu, Jin Wu

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Familial cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 36% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
  6. MiR-146a rs2910164 polymorphism is associated with hepatocellular carcinoma: a meta-analysis.International journal of clinical and experimental medicine · 2015
    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

4 authors at 1 institution in 1 country.

Mingkun XieDepartment of Forensic Biology, West China School of Preclinical and Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, People's Republic of China.
Yating Li
Jing Wu
Jin Wu
Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies have identified many genes associated with digestive tract neoplasms. However, the published findings have been conflicting. The aim of our study was to evaluate the involvement of two polymorphisms (miR-146a rs2910164, miR-196a2 rs11614913) in digestive tract neoplasms risk and explore how miR-146a and miR-196a2 influence this risk. Systemic research of the PubMed, EBSCO, CBM and VIP databases was performed. The software STATA 12.0 was used to calculate odd ratios and 95% confidence intervals. There were 14 studies (6,053 cases and 6,527 controls) available for rs2910164 and 15 studies (5,648 cases and 6,607 controls) involved in rs11614913. Rs2910164G>C was statistically significantly associated with digestive tract neoplasms (OR 1.134, 95% CI 1.076-1.194, P < 0.001). In the subgroup analysis by ethnicity, significant association was observed in Asian individuals (OR 1.145, 95% CI 1.084-1.209, P < 0.001). We found a correlation between rs11614913 and only colorectal cancer (OR 1.325, 95% CI 1.102-1.594, P = 0.003). This study suggested that digestive tract neoplasms might associate with miR-146a variants, but not miR-196a2 variants.

Indexed as

Genetic Predisposition to DiseaseGastrointestinal NeoplasmsHumansMicroRNAsPolymorphism, GeneticPublication BiasRiskMicroRNAsMIRN146 microRNA, humanMIRN196 microRNA, human

Identifiers

PMID25555557
OpenAlexW2040326048

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.