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Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?

Overview of attention for article published in Cellular & Molecular Biology Letters, September 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#11 of 225)
  • High Attention Score compared to outputs of the same age (80th percentile)

Mentioned by

blogs
1 blog
twitter
3 tweeters

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
33 Mendeley
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Title
Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?
Published in
Cellular & Molecular Biology Letters, September 2017
DOI 10.1186/s11658-017-0049-x
Pubmed ID
Authors

Umar Wazir, Kinan Mokbel, Amtul Carmichael, Kefah Mokbel

Abstract

Clinicians use clinical and pathological parameters, such as tumour size, grade and nodal status, to make decisions on adjuvant treatments for breast cancer. However, therapeutic decisions based on these features tend to vary due to their subjectivity. Computational and mathematical algorithms were developed using clinical outcome data from breast cancer registries, such as Adjuvant! Online and NHS PREDICT. More recently, assessments of molecular profiles have been applied in the development of better prognostic tools. Based on the available literature on online registry-based tools and genomic assays, we evaluated whether these online tools could be valid and accurate alternatives to genomic and molecular profiling of the individual breast tumour in aiding therapeutic decisions, particularly in patients with early ER-positive breast cancer. Early breast cancer is currently considered a systemic disease and a complex ecosystem with behaviour determined by the complex genetic and molecular signatures of the tumour cells, mammary stem cells, microenvironment and host immune system. We anticipate that molecular profiling will continue to evolve, expanding beyond the primary tumour to include the tumour microenvironment, cancer stem cells and host immune system. This should further refine therapeutic decisions and optimise clinical outcome. This article was specially invited by the editors and represents work by leading researchers.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 15%
Student > Master 5 15%
Student > Bachelor 4 12%
Student > Doctoral Student 3 9%
Other 3 9%
Other 8 24%
Unknown 5 15%
Readers by discipline Count As %
Medicine and Dentistry 16 48%
Biochemistry, Genetics and Molecular Biology 5 15%
Nursing and Health Professions 2 6%
Agricultural and Biological Sciences 2 6%
Decision Sciences 1 3%
Other 0 0%
Unknown 7 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 19 October 2018.
All research outputs
#1,895,056
of 13,644,952 outputs
Outputs from Cellular & Molecular Biology Letters
#11
of 225 outputs
Outputs of similar age
#52,069
of 268,264 outputs
Outputs of similar age from Cellular & Molecular Biology Letters
#1
of 1 outputs
Altmetric has tracked 13,644,952 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 225 research outputs from this source. They receive a mean Attention Score of 2.0. This one has done particularly well, scoring higher than 95% 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 268,264 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 80% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them