| Title |
The association between XRCC1 Arg399Gln polymorphism and risk of leukemia in different populations: a meta-analysis of case-control studies
|
|---|---|
| Published in |
OncoTargets and therapy, November 2015
|
| DOI | 10.2147/ott.s92752 |
| Pubmed ID | |
| Authors |
Fang Wang, Qian Zhao, Hai-rong He, Ya-jing Zhai, Jun Lu, Hai-bo Hu, Jin-song Zhou, Yong-hua Yang, Yuan-jie Li |
| Abstract |
Associations between Arg399Gln single-nucleotide polymorphism (SNP) in the XRCC1 gene and leukemia susceptibility have been studied extensively, however, the results are inconsistent. The aim of this study was to determine these associations using meta-analytical methods. A meta-analysis was performed to examine the associations between XRCC1 Arg399-Gln SNP and leukemia risk. A literature search of PubMed and Web of Science databases was conducted to identify relevant studies published up to March 10, 2015. The references of the retrieved articles were also screened. All the statistical analyses were conducted using Review Manager software. The XRCC1 Arg399Gln SNP was found to be associated with increased childhood risk of acute lymphoblastic leukemia among Asians under the dominant (odds ratio [OR] 2.11, 95% confidence interval [CI] 1.50-2.97, P<0.0001), allele contrast (OR 1.72, 95% CI 1.33-2.23, P<0.0001), and homozygote contrast (OR 2.34, 95% CI 1.25-4.36, P=0.008) models. However, no association was found in Caucasians between the SNP and risk of either chronic myeloid leukemia or chronic lymphocytic leukemia under any contrast model. The findings of the current meta-analysis indicate that the XRCC1 Arg399Gln SNP is a risk factor for childhood lymphoblastic leukemia in Asians. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 25% |
| Lecturer | 1 | 8% |
| Student > Ph. D. Student | 1 | 8% |
| Professor | 1 | 8% |
| Researcher | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 4 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 25% |
| Biochemistry, Genetics and Molecular Biology | 3 | 25% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
| Computer Science | 1 | 8% |
| Agricultural and Biological Sciences | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 3 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 November 2015.
All research outputs
#16,721,208
of 25,373,627 outputs
Outputs from OncoTargets and therapy
#982
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Outputs of similar age
#167,047
of 294,811 outputs
Outputs of similar age from OncoTargets and therapy
#25
of 104 outputs
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We're also able to compare this research output to 104 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.