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A semiquantitative metric for evaluating clinical actionability of incidental or secondary findings from genome-scale sequencing

Overview of attention for article published in Genetics in Medicine, August 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 (91st percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

news
1 news outlet
policy
1 policy source
twitter
15 X users

Citations

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78 Dimensions

Readers on

mendeley
56 Mendeley
Title
A semiquantitative metric for evaluating clinical actionability of incidental or secondary findings from genome-scale sequencing
Published in
Genetics in Medicine, August 2015
DOI 10.1038/gim.2015.104
Pubmed ID
Authors

Jonathan S. Berg, Ann Katherine M. Foreman, Julianne M. O'Daniel, Jessica K. Booker, Lacey Boshe, Timothy Carey, Kristy R. Crooks, Brian C. Jensen, Eric T. Juengst, Kristy Lee, Daniel K. Nelson, Bradford C. Powell, Cynthia M. Powell, Myra I. Roche, Cecile Skrzynia, Natasha T. Strande, Karen E. Weck, Kirk C. Wilhelmsen, James P. Evans

Abstract

As genome-scale sequencing is increasingly applied in clinical scenarios, a wide variety of genomic findings will be discovered as secondary or incidental findings, and there is debate about how they should be handled. The clinical actionability of such findings varies, necessitating standardized frameworks for a priori decision making about their analysis. We established a semiquantitative metric to assess five elements of actionability: severity and likelihood of the disease outcome, efficacy and burden of intervention, and knowledge base, with a total score from 0 to 15. The semiquantitative metric was applied to a list of putative actionable conditions, the list of genes recommended by the American College of Medical Genetics and Genomics (ACMG) for return when deleterious variants are discovered as secondary/incidental findings, and a random sample of 1,000 genes. Scores from the list of putative actionable conditions (median = 12) and the ACMG list (median = 11) were both statistically different than the randomly selected genes (median = 7) (P < 0.0001, two-tailed Mann-Whitney test). Gene-disease pairs having a score of 11 or higher represent the top quintile of actionability. The semiquantitative metric effectively assesses clinical actionability, promotes transparency, and may facilitate assessments of clinical actionability by various groups and in diverse contexts.Genet Med advance online publication 13 August 2015Genetics in Medicine (2015); doi:10.1038/gim.2015.104.

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
United States 1 2%
Unknown 54 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 20%
Other 8 14%
Student > Postgraduate 6 11%
Professor 5 9%
Student > Master 5 9%
Other 12 21%
Unknown 9 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 27%
Medicine and Dentistry 11 20%
Agricultural and Biological Sciences 6 11%
Social Sciences 4 7%
Business, Management and Accounting 1 2%
Other 4 7%
Unknown 15 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 14 October 2021.
All research outputs
#1,773,930
of 25,371,288 outputs
Outputs from Genetics in Medicine
#603
of 2,943 outputs
Outputs of similar age
#22,500
of 276,158 outputs
Outputs of similar age from Genetics in Medicine
#10
of 39 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,943 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.0. This one has done well, scoring higher than 79% 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 276,158 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 91% of its contemporaries.
We're also able to compare this research output to 39 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 74% of its contemporaries.