Because mutations in BRCA1 and BRCA2 in women with breast cancer are associated with an increased risk of ovarian cancer, analysis of these genes should be considered for women diagnosed with breast cancer who have a high probability of carrying a mutation according to the statistical model developed with these data.

Purpose Genomic microarrays can detect copy number variants not detectable by conventional cytogenetics. This technology is diffusing rapidly into prenatal settings even though the clinical implications of many copy number variants are currently unknown. We conducted a qualitative pilot study to explore the experiences of women receiving abnormal results from prenatal microarray testing performed in a research setting. Methods Participants were a subset of women participating in a multicenter prospective study “Prenatal Cytogenetic Diagnosis by Array-based Copy Number Analysis”. Telephone interviews were conducted with 23 women receiving abnormal prenatal microarray results. Results We found that five key elements dominated the experiences of women who had received abnormal prenatal microarray results: an offer too good to pass up, blindsided by the results, uncertainty and unquantifiable risks, need for support, and toxic knowledge. Conclusion As prenatal microarray testing is increasingly utilized, uncertain findings will be common resulting in greater need for careful pre and post test counseling, and more education of, and resources for providers so they can adequately support the women who are undergoing testing.

Background/Aims: To predict the potential public health impact of personal genomics, empirical research on public perceptions of these services is needed. In this study, ‘early adopters’ of personal genomics were surveyed to assess their motivations, perceptions and intentions. Methods: Participants were recruited from everyone who registered to attend an enrollment event for the Coriell Personalized Medicine Collaborative, a United States-based (Camden, N.J.) research study of the utility of personalized medicine, between March 31, 2009 and April 1, 2010 (n = 369). Participants completed an Internet-based survey about their motivations, awareness of personalized medicine, perceptions of study risks and benefits, and intentions to share results with health care providers. Results: Respondents were motivated to participate for their own curiosity and to find out their disease risk to improve their health. Fewer than 10% expressed deterministic perspectives about genetic risk, but 32% had misperceptions about the research study or personal genomic testing. Most respondents perceived the study to have health-related benefits. Nearly all (92%) intended to share their results with physicians, primarily to request specific medical recommendations. Conclusion: Early adopters of personal genomics are prospectively enthusiastic about using genomic profiling information to improve their health, in close consultation with their physicians. This suggests that early users (i.e. through direct-to-consumer companies or research) may follow up with the health care system. Further research should address whether intentions to seek care match actual behaviors.

Racial differences in health care system distrust are complex with far greater differences seen in the domain of values distrust than in competence distrust. This framework may be useful for explaining the mixed results of studies of race and health care-related distrust to date, for the design of future studies exploring the causes of racial disparities in health and health care, and for the development and testing of novel strategies for reducing these disparities.

BackgroundPatients, clinicians, researchers and payers are seeking to understand the value of using genomic information (as reflected by genotyping, sequencing, family history or other data) to inform clinical decision-making. However, challenges exist to widespread clinical implementation of genomic medicine, a prerequisite for developing evidence of its real-world utility.MethodsTo address these challenges, the National Institutes of Health-funded IGNITE (Implementing GeNomics In pracTicE; www.ignite-genomics.org) Network, comprised of six projects and a coordinating center, was established in 2013 to support the development, investigation and dissemination of genomic medicine practice models that seamlessly integrate genomic data into the electronic health record and that deploy tools for point of care decision making. IGNITE site projects are aligned in their purpose of testing these models, but individual projects vary in scope and design, including exploring genetic markers for disease risk prediction and prevention, developing tools for using family history data, incorporating pharmacogenomic data into clinical care, refining disease diagnosis using sequence-based mutation discovery, and creating novel educational approaches.ResultsThis paper describes the IGNITE Network and member projects, including network structure, collaborative initiatives, clinical decision support strategies, methods for return of genomic test results, and educational initiatives for patients and providers. Clinical and outcomes data from individual sites and network-wide projects are anticipated to begin being published over the next few years.ConclusionsThe IGNITE Network is an innovative series of projects and pilot demonstrations aiming to enhance translation of validated actionable genomic information into clinical settings and develop and use measures of outcome in response to genome-based clinical interventions using a pragmatic framework to provide early data and proofs of concept on the utility of these interventions. Through these efforts and collaboration with other stakeholders, IGNITE is poised to have a significant impact on the acceleration of genomic information into medical practice.

Most studies of outcomes of genetic counseling have focused on client knowledge, reproductive plans and behavior, or satisfaction. Other measures of the "value" of genetic counseling are needed to guide research assessing the impact of genetic counseling on individuals and populations, as well as to improve the process of providing care. To obtain input from providers, we conducted telephone interviews with six experienced genetic counselors, and then we held a focus group with 10 additional genetic counselors from a variety of practice settings. To obtain input from consumers, telephone interviews were also conducted with 19 past clients of these participating counselors. We found that counselor goals focus on meeting clients' needs, usually educating and providing psychosocial support. Clients often had few goals going into a session because they were unaware of what would be discussed or how the session would be structured. They usually did not expect to receive "counseling," and when they did, it was a welcome surprise. Both clients and counselors commented that a positive interpersonal interaction and "connecting" are primary measures of success. All clients appreciated the large amount of time spent with the counselor, and the manner (clear, comprehensive, and unhurried) of providing information. Many clients said that genetic counseling resulted in improved communication with their partners and other family members. Clients view the counselor as an "expert" and value the counselor as an on-going resource for both information and support. These "outcomes"f genetic counseling need to be assessed, and new measures must be developed.

PurposeClinical next generation sequencing (CNGS) is introducing new opportunities and challenges into the practice of medicine. Simultaneously, these technologies are generating uncertainties of 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.MethodsInterviews to delineate the dimensions of uncertainty in CNGS were conducted with genomics experts, and themes were extracted in order to expand upon 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.ResultsThe 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.ConclusionThe 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.

Purpose The increased sensitivity of chromosomal microarray (CMA) technology as compared with traditional cytogenetic analysis allows for improved detection of genomic alterations. However, there is potential for uncertainty in the interpretation of test results in some cases. This paper explores how families understand and make meaning of CMA test results, and identifies the needs of families undergoing CMA testing. Methods We conducted semistructured interviews with parents of 25 pediatric outpatients with CMA test results indicating either a pathogenic alteration or a variant of unknown significance (VUS). Interviews were analyzed qualitatively. Results Three domains of understanding were identified: comprehension of results, interpretations of scientific uncertainty, and personal meaning for the child and family. Incomplete comprehension of test results and scientific uncertainty were prominent themes for families receiving results in both the VUS and pathogenic categories. Receiving results from non-geneticists and by telephone, long waits to see a geneticist, and misleading Internet searches all contributed to misunderstandings. Conclusion Differentiating domains of understanding allows for the identification of uncertainties that can be reduced or managed in order to improve understanding of CMA results. Using this framework, we suggest interventions to promote clarity and address the informational needs of families undergoing CMA testing.