| Title |
Recommendations for biomarker testing in epithelial ovarian cancer: a National Consensus Statement by the Spanish Society of Pathology and the Spanish Society of Medical Oncology
|
|---|---|
| Published in |
Clinical and Translational Oncology, August 2017
|
| DOI | 10.1007/s12094-017-1719-x |
| Pubmed ID | |
| Authors |
A. Oaknin, R. Guarch, P. Barretina, D. Hardisson, A. González-Martín, X. Matías-Guiu, A. Pérez-Fidalgo, B. Vieites, I. Romero, J. Palacios |
| Abstract |
Because of advances in the understanding of histological and molecular characteristics in ovarian cancer, it is now possible to recognize the existence of five subtypes, which in turn has allowed a more refined therapeutic approach and better design of clinical trials. Each of these five subtypes has specific histological features and a particular biomarker expression, as well as mutations in different genes, some of which have prognostic and predictive value. CA125 and HE4 are examples of ovarian cancer biomarkers used in the diagnosis and follow-up of these malignancies. Currently, somatic or germinal mutations on BRCA1 and BRCA2 genes are the most important biomarkers in epithelial ovarian cancer having prognostic and predictive value. This article will review the histological and molecular characteristics of the five subtypes of ovarian cancer, describing the most important biomarkers and mutations that can guide in diagnosis, screening and tailored treatment strategy. |
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 % |
|---|---|---|
| Mexico | 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 55 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 20% |
| Other | 8 | 15% |
| Student > Bachelor | 8 | 15% |
| Student > Doctoral Student | 4 | 7% |
| Student > Postgraduate | 4 | 7% |
| Other | 11 | 20% |
| Unknown | 9 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 20 | 36% |
| Biochemistry, Genetics and Molecular Biology | 14 | 25% |
| Agricultural and Biological Sciences | 4 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 5% |
| Engineering | 2 | 4% |
| Other | 2 | 4% |
| Unknown | 10 | 18% |
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 05 March 2018.
All research outputs
#18,589,103
of 23,025,074 outputs
Outputs from Clinical and Translational Oncology
#863
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#221,330
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Outputs of similar age from Clinical and Translational Oncology
#15
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