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Do we need biomarkers to predict the benefit of adding adjuvant taxanes for treatment of breast cancer?
The current understanding of the molecular biology of breast cancer presents an extremely complex portrait of the disease. Based on this knowledge, considerable efforts are being made to identify biomarkers that will predict the response to a specific treatment while minimizing the risk of unnecessa...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3496127/ https://www.ncbi.nlm.nih.gov/pubmed/22297134 http://dx.doi.org/10.1186/bcr3093 |
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author | Pérez-García, José Cortés, Javier |
author_facet | Pérez-García, José Cortés, Javier |
author_sort | Pérez-García, José |
collection | PubMed |
description | The current understanding of the molecular biology of breast cancer presents an extremely complex portrait of the disease. Based on this knowledge, considerable efforts are being made to identify biomarkers that will predict the response to a specific treatment while minimizing the risk of unnecessary side effects. In breast cancer, the Ki67 index has been associated with poor prognosis and might play a relevant role in predicting benefit from adjuvant docetaxel, as observed in the article accompanying this editorial. Taxanes are one of the most active cytotoxic agents for breast cancer. However, the role of taxane-based chemotherapy as adjuvant treatment of early breast cancer remains controversial in some subsets of patients. For this reason, the Ki67 index might help to better define the group of patients who could have the optimal benefit. |
format | Online Article Text |
id | pubmed-3496127 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34961272012-11-14 Do we need biomarkers to predict the benefit of adding adjuvant taxanes for treatment of breast cancer? Pérez-García, José Cortés, Javier Breast Cancer Res Editorial The current understanding of the molecular biology of breast cancer presents an extremely complex portrait of the disease. Based on this knowledge, considerable efforts are being made to identify biomarkers that will predict the response to a specific treatment while minimizing the risk of unnecessary side effects. In breast cancer, the Ki67 index has been associated with poor prognosis and might play a relevant role in predicting benefit from adjuvant docetaxel, as observed in the article accompanying this editorial. Taxanes are one of the most active cytotoxic agents for breast cancer. However, the role of taxane-based chemotherapy as adjuvant treatment of early breast cancer remains controversial in some subsets of patients. For this reason, the Ki67 index might help to better define the group of patients who could have the optimal benefit. BioMed Central 2012 2012-01-31 /pmc/articles/PMC3496127/ /pubmed/22297134 http://dx.doi.org/10.1186/bcr3093 Text en Copyright ©2012 BioMed Central Ltd |
spellingShingle | Editorial Pérez-García, José Cortés, Javier Do we need biomarkers to predict the benefit of adding adjuvant taxanes for treatment of breast cancer? |
title | Do we need biomarkers to predict the benefit of adding adjuvant taxanes for treatment of breast cancer? |
title_full | Do we need biomarkers to predict the benefit of adding adjuvant taxanes for treatment of breast cancer? |
title_fullStr | Do we need biomarkers to predict the benefit of adding adjuvant taxanes for treatment of breast cancer? |
title_full_unstemmed | Do we need biomarkers to predict the benefit of adding adjuvant taxanes for treatment of breast cancer? |
title_short | Do we need biomarkers to predict the benefit of adding adjuvant taxanes for treatment of breast cancer? |
title_sort | do we need biomarkers to predict the benefit of adding adjuvant taxanes for treatment of breast cancer? |
topic | Editorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3496127/ https://www.ncbi.nlm.nih.gov/pubmed/22297134 http://dx.doi.org/10.1186/bcr3093 |
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