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Evidence-based classification of recommendations on use of genomic tests in clinical practice: Dealing with insufficient evidence

Overview of attention for article published in Genetics in Medicine, October 2010
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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 (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
7 X users

Citations

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65 Dimensions

Readers on

mendeley
67 Mendeley
Title
Evidence-based classification of recommendations on use of genomic tests in clinical practice: Dealing with insufficient evidence
Published in
Genetics in Medicine, October 2010
DOI 10.1097/gim.0b013e3181f9ad55
Pubmed ID
Authors

Muin J Khoury, Ralph J Coates, James P Evans

Abstract

Numerous genomic tests continue to emerge as potential tools in the diagnosis, treatment, prognosis, and prevention for a wide variety of common human diseases. To date, most of these tests have "insufficient evidence" of clinical validity and utility for their use in clinical practice. Explicit and quantitative tools can be used in the evaluation of direct and indirect evidence on the utility of genomic tests. As suggested in an article in this month's issue by Veenstra et al., a recommendation matrix can be developed based on the amount of certainty of the evidence and the assessment of the risk-benefit profile. To supplement the current binary (up or down) evidence-based recommendation for use, it is worthwhile to explore all available data to develop a three-tier evidence-based recommendation classification of genomic tests ("use in practice," "promote informed decision-making," and "discourage use"). Promoting informed decision making may be a valuable recommendation for tests for which there is sufficient information on analytic and clinical validity and for which the risk/benefit analysis on clinical utility is promising but not definitive. This approach could provide interim guidance for clinical practice, while rigorous outcomes research is conducted to assess the impact of such tests on patients, families, and population health outcomes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Brazil 2 3%
Switzerland 1 1%
Unknown 62 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 27%
Student > Ph. D. Student 10 15%
Student > Master 6 9%
Student > Doctoral Student 6 9%
Other 4 6%
Other 15 22%
Unknown 8 12%
Readers by discipline Count As %
Medicine and Dentistry 23 34%
Agricultural and Biological Sciences 12 18%
Biochemistry, Genetics and Molecular Biology 8 12%
Social Sciences 4 6%
Business, Management and Accounting 3 4%
Other 6 9%
Unknown 11 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 01 January 2017.
All research outputs
#2,561,404
of 25,374,647 outputs
Outputs from Genetics in Medicine
#891
of 2,943 outputs
Outputs of similar age
#9,878
of 108,804 outputs
Outputs of similar age from Genetics in Medicine
#5
of 15 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% 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 gotten more attention than average, scoring higher than 69% 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 108,804 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 90% of its contemporaries.
We're also able to compare this research output to 15 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 66% of its contemporaries.