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Accurate Prediction and Validation of Response to Endocrine Therapy in Breast Cancer

Overview of attention for article published in Journal of Clinical Oncology, June 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

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11 X users
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1 patent
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1 Facebook page

Readers on

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148 Mendeley
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Article details
Title
Accurate Prediction and Validation of Response to Endocrine Therapy in Breast Cancer
Published in
Journal of Clinical Oncology, June 2015
DOI 10.1200/jco.2014.57.8963
Pubmed ID
Authors
Abstract

Aromatase inhibitors (AIs) have an established role in the treatment of breast cancer. Response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. Pretreatment and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 postmenopausal women who had estrogen receptor-alpha positive breast cancer and were receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed with use of three-dimensional ultrasound measurements. The molecular response to letrozole was characterized and a four-gene classifier of clinical response was established (accuracy of 96%) on the basis of the level of two genes before treatment (one gene [IL6ST] was associated with immune signaling, and the other [NGFRAP1] was associated with apoptosis) and the level of two proliferation genes (ASPM, MCM4) after 2 weeks of therapy. The four-gene signature was found to be 91% accurate in a blinded, completely independent validation data set of patients treated with anastrozole. Matched 2-week on-treatment biopsies were associated with improved predictive power as compared with pretreatment biopsies alone. This signature also significantly predicted recurrence-free survival (P = .029) and breast cancer -specific survival (P = .009). We demonstrate that the test can also be performed with use of quantitative polymerase chain reaction or immunohistochemistry. A four-gene predictive model of clinical response to AIs by 2 weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and cell proliferation that is not reduced 2 weeks after initiation of treatment are functional characteristics of breast tumors that do not respond to AIs.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 148 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United Kingdom 3 2%
United States 1 <1%
Netherlands 1 <1%
Unknown 143 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 32 22%
Student > Ph. D. Student 29 20%
Student > Master 14 9%
Other 8 5%
Student > Doctoral Student 8 5%
Other 21 14%
Unknown 36 24%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 42 28%
Biochemistry, Genetics and Molecular Biology 31 21%
Agricultural and Biological Sciences 12 8%
Nursing and Health Professions 5 3%
Computer Science 4 3%
Other 12 8%
Unknown 42 28%
Attention Score in Context

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 16 June 2016.
All research outputs
#4,505,860
of 34,350,842 outputs
Outputs from Journal of Clinical Oncology
#11,225
of 32,292 outputs
Outputs of similar age
#45,672
of 309,510 outputs
Outputs of similar age from Journal of Clinical Oncology
#110
of 461 outputs
Altmetric has tracked 34,350,842 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 32,292 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 65% 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 309,510 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 461 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.