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Integrating precision cancer medicine into healthcare—policy, practice, and research challenges

Overview of attention for article published in Genome Medicine, October 2016
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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9 X users

Citations

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47 Dimensions

Readers on

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159 Mendeley
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Title
Integrating precision cancer medicine into healthcare—policy, practice, and research challenges
Published in
Genome Medicine, October 2016
DOI 10.1186/s13073-016-0362-4
Pubmed ID
Authors

Gabrielle Bertier, Jian Carrot-Zhang, Vassilis Ragoussis, Yann Joly

Abstract

Precision medicine (PM) can be defined as a predictive, preventive, personalized, and participatory healthcare service delivery model. Recent developments in molecular biology and information technology make PM a reality today through the use of massive amounts of genetic, 'omics', clinical, environmental, and lifestyle data. With cancer being one of the most prominent public health threats in developed countries, both the research community and governments have been investing significant time, money, and efforts in precision cancer medicine (PCM). Although PCM research is extremely promising, a number of hurdles still remain on the road to an optimal integration of standardized and evidence-based use of PCM in healthcare systems. Indeed, PCM raises a number of technical, organizational, ethical, legal, social, and economic challenges that have to be taken into account in the development of an appropriate health policy framework. Here, we highlight some of the more salient issues regarding the standards needed for integration of PCM into healthcare systems, and we identify fields where more research is needed before policy can be implemented. Key challenges include, but are not limited to, the creation of new standards for the collection, analysis, and sharing of samples and data from cancer patients, and the creation of new clinical trial designs with renewed endpoints. We believe that these issues need to be addressed as a matter of priority by public health policymakers in the coming years for a better integration of PCM into healthcare.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 159 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 <1%
Unknown 158 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 14%
Student > Bachelor 22 14%
Student > Ph. D. Student 17 11%
Researcher 16 10%
Other 15 9%
Other 32 20%
Unknown 35 22%
Readers by discipline Count As %
Medicine and Dentistry 39 25%
Biochemistry, Genetics and Molecular Biology 17 11%
Computer Science 13 8%
Agricultural and Biological Sciences 11 7%
Social Sciences 7 4%
Other 32 20%
Unknown 40 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 12 April 2017.
All research outputs
#6,233,117
of 24,960,237 outputs
Outputs from Genome Medicine
#1,053
of 1,539 outputs
Outputs of similar age
#87,826
of 320,733 outputs
Outputs of similar age from Genome Medicine
#22
of 31 outputs
Altmetric has tracked 24,960,237 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,539 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.1. This one is in the 31st percentile – i.e., 31% 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 320,733 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.