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Biomarker-based adaptive trials for patients with glioblastoma—lessons from I-SPY 2

Overview of attention for article published in Neuro-Oncology, July 2013
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  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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2 X users
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1 research highlight platform

Citations

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37 Dimensions

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43 Mendeley
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Title
Biomarker-based adaptive trials for patients with glioblastoma—lessons from I-SPY 2
Published in
Neuro-Oncology, July 2013
DOI 10.1093/neuonc/not088
Pubmed ID
Authors

Brian M Alexander, Patrick Y Wen, Lorenzo Trippa, David A Reardon, Wai-Kwan Alfred Yung, Giovanni Parmigiani, Donald A Berry

Abstract

The traditional clinical trials infrastructure may not be ideally suited to evaluate the numerous therapeutic hypotheses that result from the increasing number of available targeted agents combined with the various methodologies to molecularly subclassify patients with glioblastoma. Additionally, results from smaller screening studies are rarely translated to successful larger confirmatory studies, potentially related to a lack of efficient control arms or the use of unvalidated surrogate endpoints. Streamlining clinical trials and providing a flexible infrastructure for biomarker development is clearly needed for patients with glioblastoma. The experience developing and implementing the I-SPY studies in breast cancer may serve as a guide to developing such trials in neuro-oncology.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 5%
Unknown 41 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 21%
Student > Ph. D. Student 5 12%
Other 4 9%
Student > Bachelor 4 9%
Student > Postgraduate 3 7%
Other 10 23%
Unknown 8 19%
Readers by discipline Count As %
Medicine and Dentistry 17 40%
Agricultural and Biological Sciences 4 9%
Biochemistry, Genetics and Molecular Biology 2 5%
Mathematics 2 5%
Engineering 2 5%
Other 5 12%
Unknown 11 26%
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 17 September 2013.
All research outputs
#13,386,934
of 22,714,025 outputs
Outputs from Neuro-Oncology
#1,571
of 3,235 outputs
Outputs of similar age
#102,398
of 194,446 outputs
Outputs of similar age from Neuro-Oncology
#16
of 42 outputs
Altmetric has tracked 22,714,025 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,235 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one is in the 49th percentile – i.e., 49% 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 194,446 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.