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Lost in translation: returning germline genetic results in genome-scale cancer research

Overview of attention for article published in Genome Medicine, April 2017
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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 (88th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

policy
1 policy source
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24 X users

Citations

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26 Dimensions

Readers on

mendeley
60 Mendeley
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1 CiteULike
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Title
Lost in translation: returning germline genetic results in genome-scale cancer research
Published in
Genome Medicine, April 2017
DOI 10.1186/s13073-017-0430-4
Pubmed ID
Authors

Amber L. Johns, Skye H. McKay, Jeremy L. Humphris, Mark Pinese, Lorraine A. Chantrill, R. Scott Mead, Katherine Tucker, Lesley Andrews, Annabel Goodwin, Conrad Leonard, Hilda A. High, Katia Nones, Ann-Marie Patch, Neil D. Merrett, Nick Pavlakis, Karin S. Kassahn, Jaswinder S. Samra, David K. Miller, David K. Chang, Marina Pajic, Australian Pancreatic Cancer Genome Initiative, John V. Pearson, Sean M. Grimmond, Nicola Waddell, Nikolajs Zeps, Anthony J. Gill, Andrew V. Biankin

Abstract

The return of research results (RoR) remains a complex and well-debated issue. Despite the debate, actual data related to the experience of giving individual results back, and the impact these results may have on clinical care and health outcomes, is sorely lacking. Through the work of the Australian Pancreatic Cancer Genome Initiative (APGI) we: (1) delineate the pathway back to the patient where actionable research data were identified; and (2) report the clinical utilisation of individual results returned. Using this experience, we discuss barriers and opportunities associated with a comprehensive process of RoR in large-scale genomic research that may be useful for others developing their own policies. We performed whole-genome (n = 184) and exome (n = 208) sequencing of matched tumour-normal DNA pairs from 392 patients with sporadic pancreatic cancer (PC) as part of the APGI. We identified pathogenic germline mutations in candidate genes (n = 130) with established predisposition to PC or medium-high penetrance genes with well-defined cancer associated syndromes or phenotypes. Variants from candidate genes were annotated and classified according to international guidelines. Variants were considered actionable if clinical utility was established, with regard to prevention, diagnosis, prognostication and/or therapy. A total of 48,904 germline variants were identified, with 2356 unique variants undergoing annotation and in silico classification. Twenty cases were deemed actionable and were returned via previously described RoR framework, representing an actionable finding rate of 5.1%. Overall, 1.78% of our cohort experienced clinical benefit from RoR. Returning research results within the context of large-scale genomics research is a labour-intensive, highly variable, complex operation. Results that warrant action are not infrequent, but the prevalence of those who experience a clinical difference as a result of returning individual results is currently low.

X Demographics

X Demographics

The data shown below were collected from the profiles of 24 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 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 18%
Professor > Associate Professor 8 13%
Student > Bachelor 6 10%
Student > Master 6 10%
Student > Postgraduate 5 8%
Other 14 23%
Unknown 10 17%
Readers by discipline Count As %
Medicine and Dentistry 17 28%
Biochemistry, Genetics and Molecular Biology 12 20%
Agricultural and Biological Sciences 8 13%
Engineering 4 7%
Business, Management and Accounting 1 2%
Other 6 10%
Unknown 12 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 08 November 2023.
All research outputs
#2,017,164
of 25,775,807 outputs
Outputs from Genome Medicine
#447
of 1,612 outputs
Outputs of similar age
#36,984
of 325,492 outputs
Outputs of similar age from Genome Medicine
#9
of 31 outputs
Altmetric has tracked 25,775,807 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,612 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.1. This one has gotten more attention than average, scoring higher than 72% 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 325,492 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% 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 has gotten more attention than average, scoring higher than 70% of its contemporaries.