| Title |
Association of telomerase reverse transcriptase promoter mutations with clinicopathological features and prognosis of thyroid cancer: a meta-analysis
|
|---|---|
| Published in |
OncoTargets and therapy, November 2016
|
| DOI | 10.2147/ott.s116594 |
| Pubmed ID | |
| Authors |
Xingyun Su, Xiaoxia Jiang, Weibin Wang, Haiyong Wang, Xin Xu, Aihui Lin, Xiaodong Teng, Huiling Wu, Lisong Teng |
| Abstract |
The clinicopathological and prognostic significance of telomerase reverse transcriptase (TERT) promoter mutations have been widely investigated in thyroid cancer; however, the results are still discrepant. Systematic searches were performed in PubMed, Web of Science, Scopus, Ovid, and the Cochran Library databases for relevant articles prior to April 2016. Mutation rates were synthesized by R statistical software. The odds ratio or standardized mean difference with 95% confidence interval was pooled by Stata. A total of 22 studies with 4,907 cases were included in this meta-analysis. TERT promoter mutations tended to present in aggressive histological types including poorly differentiated thyroid cancer (33.37%), anaplastic thyroid cancer (38.69%), and tall-cell variant papillary thyroid cancer (30.23%). These promoter mutations were likely to exist in older patients and males and were well associated with larger tumor size, extrathyroidal extension, vascular invasion, lymph node metastasis, distant metastasis, advanced tumor stage, disease recurrence/persistence, and mortality. In addition, TERT promoter mutations (especially C228T) tended to coexist with BRAF(V600E) mutation, which indicated more aggressive tumor behavior. Therefore, TERT promoter mutations may be promising biomarkers for early diagnosis, risk stratification, prognostic prediction, and management of thyroid cancer. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 5 | 19% |
| Researcher | 4 | 15% |
| Student > Master | 3 | 11% |
| Student > Ph. D. Student | 3 | 11% |
| Other | 2 | 7% |
| Other | 3 | 11% |
| Unknown | 7 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 33% |
| Biochemistry, Genetics and Molecular Biology | 6 | 22% |
| Environmental Science | 1 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 4% |
| Computer Science | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 8 | 30% |
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 22 February 2018.
All research outputs
#16,722,190
of 25,374,917 outputs
Outputs from OncoTargets and therapy
#982
of 3,016 outputs
Outputs of similar age
#196,502
of 317,812 outputs
Outputs of similar age from OncoTargets and therapy
#32
of 74 outputs
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