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Attention Score in Context
| Title |
Influence of CYP19A1 polymorphisms on the treatment of breast cancer with aromatase inhibitors: a systematic review and meta-analysis
|
|---|---|
| Published in |
BMC Medicine, June 2015
|
| DOI | 10.1186/s12916-015-0373-9 |
| Pubmed ID | |
| Authors |
Osvaldo Artigalás, Tazio Vanni, Mara Helena Hutz, Patricia Ashton-Prolla, Ida Vanessa Schwartz |
| Abstract |
Many clinical trials have shown the efficacy of aromatase inhibitors (AIs) in the management of breast cancer (BC). There is growing evidence that CYP19A1 single-nucleotide polymorphisms (SNPs) are associated with clinical response (CR) and adverse effects (AEs) among BC patients treated with AIs. The aim of this study was to analyze the association between CYP19A1 polymorphisms and AI treatment in BC patients. A systematic review was performed in MEDLINE, EMBASE, and LILACS. A meta-analysis was conducted to compare the association between CYP19A1 variants and treatment response among BC patients. A total of 12 studies were included in the final analysis. There was significant variation among the populations studied and the SNPs and outcomes investigated. A meta-analysis was only possible for the evaluation of SNP rs4646 vs. the wild-type variant with respect to time to progression (TTP) among metastatic BC patients treated with AI. TTP was significantly increased in patients with the rs4646 variant compared with the wild-type gene (hazard ratio (HR) = 0.51 [95 % confidence interval (CI), 0.33-0.78], P = 0.002). Seven studies analyzed the association between AEs with different polymorphisms of CYP19A1. Although there was a statistically significant association with musculoskeletal adverse events (rs934635, rs60271534, rs700518rs, and haplotype M_3_5) and with vasomotor symptoms (rs934635, rs1694189, rs7176005, and haplotype M_5_3) in individual studies, similar associations were not observed in further studies. No statistically significant association between musculoskeletal AEs and SNPs rs4646, rs10046, rs727479, and rs1062033 was found. These findings suggest that the presence of the rs4646 variant may be a predictive factor of the benefit of AI treatment for BC. The effects of CYP19A1 polymorphisms on clinical outcomes were most often detected in individual studies, suggesting that longer-term studies will better clarify these associations. Additional studies are needed to clarify the predictive value of other SNPs and whether CYP19A1 genotyping should be used to guide AI treatment. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 33% |
| Spain | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 17% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 83 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 12 | 14% |
| Researcher | 9 | 11% |
| Student > Ph. D. Student | 9 | 11% |
| Student > Bachelor | 9 | 11% |
| Other | 4 | 5% |
| Other | 16 | 19% |
| Unknown | 24 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 19 | 23% |
| Biochemistry, Genetics and Molecular Biology | 8 | 10% |
| Nursing and Health Professions | 8 | 10% |
| Agricultural and Biological Sciences | 8 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 7% |
| Other | 6 | 7% |
| Unknown | 28 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 24 September 2015.
All research outputs
#2,793,859
of 22,811,321 outputs
Outputs from BMC Medicine
#1,683
of 3,421 outputs
Outputs of similar age
#37,572
of 266,811 outputs
Outputs of similar age from BMC Medicine
#37
of 69 outputs
Altmetric has tracked 22,811,321 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,421 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.6. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,811 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.