Dataset Information

Navigating the research-clinical interface in genomic medicine: analysis from the CSER Consortium.

ABSTRACT: PurposeThe Clinical Sequencing Exploratory Research (CSER) Consortium encompasses nine National Institutes of Health-funded U-award projects investigating translation of genomic sequencing into clinical care. Previous literature has distinguished norms and rules governing research versus clinical care. This is the first study to explore how genomics investigators describe and navigate the research-clinical interface.MethodsA CSER working group developed a 22-item survey. All nine U-award projects participated. Descriptive data were tabulated and qualitative analysis of text responses identified themes and characterizations of the research-clinical interface.ResultsSurvey responses described how studies approached the research-clinical interface, including in consent practices, recording results, and using a research versus clinical laboratory. Responses revealed four characterizations of the interface: clear separation between research and clinical care, interdigitation of the two with steps to maintain separation, a dynamic interface, and merging of the two. All survey respondents utilized at least two different characterizations. Although research has traditionally been differentiated from clinical care, respondents pointed to factors blurring the distinction and strategies to differentiate the domains.ConclusionThese results illustrate the difficulty in applying the traditional bifurcation of research versus clinical care to translational models of clinical research, including in genomics. Our results suggest new directions for ethics and oversight.

SUBMITTER: Wolf SM

PROVIDER: S-EPMC5832495 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Clinical and research settings are increasingly incorporating genomic sequencing (GS) technologies. Previous research has explored reasons for declining genetic testing and participation in genetic studies; however, there is a dearth of literature regarding why potential participants decline participation in GS research, and if any of these reasons are unique to GS. This knowledge is essential to promote informed decision-making and identify potential barriers to research participation and clinical implementation. We aggregated data from seven sites across the National Institutes of Health's Clinical Sequencing Exploratory Research (CSER) consortium on each project's procedures for recruitment, and rates of and reasons for decline. Data were analyzed using descriptive statistics. The decline rate for enrollment at the seven CSER sites ranged from 12 to 64% (median 28%) and varied based on age and disease status. Projects differed in their protocols for approaching potential participants and obtaining informed consent. Reasons for declining GS research were reported for 1088 potential participants. Commonly cited reasons were similar to those reported for clinical single gene testing and non-GS genetic research. The most frequently cited reason for decline was study logistics (35%); thus, addressing logistical barriers to enrollment may positively impact GS study recruitment. Privacy and discrimination concerns were cited by 13% of decliners, highlighting the need for researchers and providers to focus educational efforts in this area. The potential psychological burden of pursuing and receiving results from GS and not wanting to receive secondary findings, a concern specific to GS, have been cited as concerns in the literature. A minority of potential participants cited psychological impact (8%) or not wanting to receive secondary findings (2%) as reasons for decline, suggesting that these concerns were not major barriers to participation in these GS studies. Further research is necessary to explore the impact, if any, of different participant groups or study protocols on rates of decline for GS studies. Future studies exploring GS implementation should consider using standardized collection methods to examine reasons for decline in larger populations and more diverse healthcare settings.

Project description:BackgroundIncreasing diversity in clinical trial participation is necessary to improve health outcomes and requires addressing existing social, structural, and geographic barriers. The Clinical Sequencing Evidence-Generating Research Consortium (CSER) included six research projects to enroll historically underrepresented/underserved (UR/US) populations in clinical genomics research. Delays and project re-designs emerged shortly after work began. Understanding common experiences of these projects may inform future trial implementation.MethodsSemi-structured interviews with six CSER principal investigators and seven project managers were performed. An interview guide included questions of research/clinical infrastructure, logistics across sites, language, communication, and allocation of grant-related resources. Interviews were recorded, transcribed verbatim; transcripts were analyzed using inductive coding, thematic analysis and consensus building.ResultsAll projects collaborating with new clinical sub-sites to recruit UR/US populations. Refining trial logistics continued long after enrollment for all projects. Themes of challenges included: sub-site customization for workflow and genetics support, conflicting input from participant advisory groups and approval bodies, developing research personnel, complex data management structures, and external changes (e.g. subcontractors ending contracts) that required redesign. Themes of beneficial lessons included: domains with prior experience were easier, develop project champions at each sub-site, structure communication within the research team, and simplify research design when possible.ConclusionsThe operational aspects of expanding clinical research into novel sub-sites are significant and require investment of time and resources. The themes arising from these interviews suggest priority areas for more quantitative analyses in the future including multi-institutional approval policies and processes, data management structures, and incremental research complexity.

Dataset Information

Navigating the research-clinical interface in genomic medicine: analysis from the CSER Consortium.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets