Evidence map›Paper›PMID 26622695›Full record

ArticleOncology letters2015

Role of five small nucleotide polymorphisms in the VEGF gene on the susceptibility to osteosarcoma and overall survival of patients.

Jian-Qiang Liu, Xia Bai, DE-Chen Duan, Ai-Xia Dou

Open access · diamondAbstract read
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 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 pooled it
1.0field-weighted citation impact, top 22% 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

9 citing papers in PubMed, 3 syntheses or guidelines pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  4. Article
  5. Review
  6. Article
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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

4 authors at 1 institution in 1 country.

Jian-Qiang LiuDepartment of Orthopaedics, Jinan No. 4 Hospital, Jinan, Shandong, P.R. China.
Xia BaiDepartment of Orthopaedics, Jinan No. 4 Hospital, Jinan, Shandong, P.R. China.
DE-Chen DuanDepartment of Orthopaedics, Jinan No. 4 Hospital, Jinan, Shandong, P.R. China.
Ai-Xia DouDepartment of Hematology and Oncology, The Second Hospital of Shandong University, Jinan, Shandong, P.R. China.
Second Hospital of Shandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study aimed to investigate the association between five common small nucleotide polymorphisms (SNPs) in the VEGF gene and the risk of osteosarcoma. An additional aim was to investigate the role of these five SNPs on the prognosis of osteosarcoma. A total of 186 patients with osteosarcoma and 186 age- and sex-matched healthy controls were enrolled into the present study. A polymerase chain reaction-restriction fragment length polymorphism assay was conducted to determine the incidence of the VEGF-2578 C/A, -1156 G/A, +1612 G/A, +936 C/T and -634 G/C polymorphisms. Conditional logistic regression analyses revealed that individuals carrying the -634 GG genotype possessed a significantly increased risk of osteosarcoma, with an adjusted odds ratio [(95% confidence interval (CI)] of 2.00 (1.07-3.75). In the Cox proportional hazards model, subsequent to adjusting for potential confounding factors, patients with osteosarcoma carrying the -634 GG genotype were found to demonstrate a shorter overall survival time (hazard ratio, 3.10; 95% CI, 1.17-8.38). The VEGF-634 G/C polymorphism may therefore be used as a genetic marker for the prediction of the risk and clinical outcome of osteosarcoma.

Indexed as

clinical outcomeosteosarcomasingle nucleotide polymorphismsusceptibilityvascular endothelial growth factor

Identifiers

PMID26622695
PMCPMC4533749
OpenAlexW2140679137

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.