↓ Skip to main content

Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers

Overview of attention for article published in Breast Cancer Research, December 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users

Citations

dimensions_citation
73 Dimensions

Readers on

mendeley
160 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers
Published in
Breast Cancer Research, December 2016
DOI 10.1186/s13058-016-0779-0
Pubmed ID
Authors

Cigdem Selli, J. Michael Dixon, Andrew H. Sims

Abstract

Approximately 70% of patients have breast cancers that are oestrogen receptor alpha positive (ER+) and are therefore candidates for endocrine treatment. Many of these patients relapse in the years during or following completion of adjuvant endocrine therapy. Thus, many ER+ cancers have primary resistance or develop resistance to endocrine therapy during treatment. Recent improvements in our understanding of how tumours evolve during treatment with endocrine agents have identified both changes in gene expression and mutational profiles, in the primary cancer as well as in circulating tumour cells. Analysing these changes has the potential to improve the prediction of which specific patients will respond to endocrine treatment. Serially profiled biopsies during treatment in the neoadjuvant setting offer promise for accurate and early prediction of response to both current and novel drugs and allow investigation of mechanisms of resistance. In addition, recent advances in monitoring tumour evolution through non-invasive (liquid) sampling of circulating tumour cells and cell-free tumour DNA may provide a method to detect resistant clones and allow implementation of personalized treatments for metastatic breast cancer patients. This review summarises current and future biomarkers and signatures for predicting response to endocrine treatment, and discusses the potential for using approved drugs and novel agents to improve outcomes. Increased prediction accuracy is likely to require sequential sampling, utilising preoperative or neoadjuvant treatment and/or liquid biopsies and an improved understanding of both the dynamics and heterogeneity of breast cancer.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 160 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 18%
Student > Master 23 14%
Student > Bachelor 18 11%
Researcher 17 11%
Student > Postgraduate 10 6%
Other 24 15%
Unknown 40 25%
Readers by discipline Count As %
Medicine and Dentistry 41 26%
Biochemistry, Genetics and Molecular Biology 35 22%
Agricultural and Biological Sciences 12 8%
Pharmacology, Toxicology and Pharmaceutical Science 8 5%
Nursing and Health Professions 4 3%
Other 13 8%
Unknown 47 29%
Attention Score in Context

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 14 July 2017.
All research outputs
#15,740,505
of 25,374,917 outputs
Outputs from Breast Cancer Research
#1,387
of 2,053 outputs
Outputs of similar age
#231,320
of 416,453 outputs
Outputs of similar age from Breast Cancer Research
#15
of 24 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,053 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.2. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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 416,453 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.