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Precision oncology for acute myeloid leukemia using a knowledge bank approach

Overview of attention for article published in Nature Genetics, January 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

news
16 news outlets
blogs
1 blog
policy
1 policy source
twitter
211 tweeters
facebook
10 Facebook pages
reddit
1 Redditor

Citations

dimensions_citation
70 Dimensions

Readers on

mendeley
309 Mendeley
citeulike
6 CiteULike
Title
Precision oncology for acute myeloid leukemia using a knowledge bank approach
Published in
Nature Genetics, January 2017
DOI 10.1038/ng.3756
Pubmed ID
Authors

Moritz Gerstung, Elli Papaemmanuil, Inigo Martincorena, Lars Bullinger, Verena I Gaidzik, Peter Paschka, Michael Heuser, Felicitas Thol, Niccolo Bolli, Peter Ganly, Arnold Ganser, Ultan McDermott, Konstanze Döhner, Richard F Schlenk, Hartmut Döhner, Peter J Campbell

Abstract

Underpinning the vision of precision medicine is the concept that causative mutations in a patient's cancer drive its biology and, by extension, its clinical features and treatment response. However, considerable between-patient heterogeneity in driver mutations complicates evidence-based personalization of cancer care. Here, by reanalyzing data from 1,540 patients with acute myeloid leukemia (AML), we explore how large knowledge banks of matched genomic-clinical data can support clinical decision-making. Inclusive, multistage statistical models accurately predicted likelihoods of remission, relapse and mortality, which were validated using data from independent patients in The Cancer Genome Atlas. Comparison of long-term survival probabilities under different treatments enables therapeutic decision support, which is available in exploratory form online. Personally tailored management decisions could reduce the number of hematopoietic cell transplants in patients with AML by 20-25% while maintaining overall survival rates. Power calculations show that databases require information from thousands of patients for accurate decision support. Knowledge banks facilitate personally tailored therapeutic decisions but require sustainable updating, inclusive cohorts and large sample sizes.

Twitter Demographics

The data shown below were collected from the profiles of 211 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 309 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 <1%
Qatar 1 <1%
Israel 1 <1%
United Kingdom 1 <1%
Australia 1 <1%
United States 1 <1%
Romania 1 <1%
Korea, Republic of 1 <1%
France 1 <1%
Other 1 <1%
Unknown 298 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 89 29%
Student > Ph. D. Student 65 21%
Unspecified 27 9%
Student > Master 27 9%
Student > Bachelor 20 6%
Other 81 26%
Readers by discipline Count As %
Medicine and Dentistry 74 24%
Biochemistry, Genetics and Molecular Biology 70 23%
Agricultural and Biological Sciences 62 20%
Unspecified 39 13%
Computer Science 29 9%
Other 35 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 242. 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 07 March 2018.
All research outputs
#53,808
of 13,763,391 outputs
Outputs from Nature Genetics
#125
of 6,243 outputs
Outputs of similar age
#2,720
of 345,390 outputs
Outputs of similar age from Nature Genetics
#10
of 74 outputs
Altmetric has tracked 13,763,391 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,243 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 32.4. This one has done particularly well, scoring higher than 97% 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 345,390 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.