Title |
A semiquantitative metric for evaluating clinical actionability of incidental or secondary findings from genome-scale sequencing
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Published in |
Genetics in Medicine, August 2015
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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
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 8 | 53% |
United Kingdom | 2 | 13% |
Canada | 1 | 7% |
Unknown | 4 | 27% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 7 | 47% |
Scientists | 4 | 27% |
Science communicators (journalists, bloggers, editors) | 2 | 13% |
Practitioners (doctors, other healthcare professionals) | 2 | 13% |
Mendeley readers
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% |