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Genet Med. 2017 Aug;19(8):918-925. doi: 10.1038/gim.2016.212. Epub 2017 Jan 19.

A taxonomy of medical uncertainties in clinical genome sequencing.

Author information

1
Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, Portland, Maine, USA.
2
Social and Behavioral Research Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, USA.
3
Division of Translational Medicine and Human Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
4
Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
5
Personalized Medicine, Partners Healthcare, Cambridge, Massachusetts, USA.
6
Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
7
Broad Institute of MIT and Harvard, Boston, Massachusetts, USA.
8
Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
9
Institute for Health &Aging, University of California, San Francisco, California, USA.
10
Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
11
Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.

Abstract

PURPOSE:

Clinical next-generation sequencing (CNGS) is introducing new opportunities and challenges into the practice of medicine. Simultaneously, these technologies are generating uncertainties of an unprecedented scale that laboratories, clinicians, and patients are required to address and manage. We describe in this report the conceptual design of a new taxonomy of uncertainties around the use of CNGS in health care.

METHODS:

Interviews to delineate the dimensions of uncertainty in CNGS were conducted with genomics experts and themes were extracted in order to expand on a previously published three-dimensional taxonomy of medical uncertainty. In parallel, we developed an interactive website to disseminate the CNGS taxonomy to researchers and engage them in its continued refinement.

RESULTS:

The proposed taxonomy divides uncertainty along three axes-source, issue, and locus-and further discriminates the uncertainties into five layers with multiple domains. Using a hypothetical clinical example, we illustrate how the taxonomy can be applied to findings from CNGS and used to guide stakeholders through interpretation and implementation of variant results.

CONCLUSION:

The utility of the proposed taxonomy lies in promoting consistency in describing dimensions of uncertainty in publications and presentations, to facilitate research design and management of the uncertainties inherent in the implementation of CNGS.Genet Med advance online publication 19 January 2017.

PMID:
28102863
PMCID:
PMC5517355
DOI:
10.1038/gim.2016.212
[Indexed for MEDLINE]
Free PMC Article

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