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Mendeley readers
Attention Score in Context
| Title |
Exploration of the association between FOXE1 gene polymorphism and differentiated thyroid cancer: a meta-analysis
|
|---|---|
| Published in |
BMC Medical Genomics, May 2018
|
| DOI | 10.1186/s12881-018-0604-y |
| Pubmed ID | |
| Authors |
Yong-Hui Chen, Ying-Qiang Zhang |
| Abstract |
Several association analyses and linkage researches indicated that inherited genetic variations effectively influence differentiated thyroid carcinogenesis. The results from 15 published studies on differentiated thyroid carcinoma (DTC) were combined. The genetic model included rs965513, rs944289 and rs1867277. Meta-analyses were performed and cochran's χ2 based Q-statistic and I2 test were performed to assess heterogeneity using STATA software. Significant results were noticed for rs965513(Odds Ratio(OR) = 1.162(1.117, 1.208)), rs944289(OR = 1.082(1.035, 1.131)) and rs1867277(OR = 1.415(1.324, 1.512)). In the subgroup analysis by ethnicity, rs965513 polymorphism conferred that risk of Caucasians (OR = 1.168(1.122, 1.215)) was more than that of East Asians of 1.35 (OR = 0.897(0.680, 1.193)). This meta-analysis revealed that common variations of FOXE1 (rs965513, rs944289 and rs1867277) were risk factors associated with increased DTC susceptibility. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 21% |
| Student > Ph. D. Student | 3 | 16% |
| Student > Doctoral Student | 1 | 5% |
| Student > Bachelor | 1 | 5% |
| Professor | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 7 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 6 | 32% |
| Biochemistry, Genetics and Molecular Biology | 2 | 11% |
| Agricultural and Biological Sciences | 1 | 5% |
| Computer Science | 1 | 5% |
| Unknown | 9 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 23 May 2018.
All research outputs
#22,767,715
of 25,382,440 outputs
Outputs from BMC Medical Genomics
#2,010
of 2,444 outputs
Outputs of similar age
#302,081
of 343,970 outputs
Outputs of similar age from BMC Medical Genomics
#41
of 55 outputs
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So far Altmetric has tracked 2,444 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.