Permanence of the information given during oncogenetic counseling to persons at familial risk of breast/ovarian and/or colon cancer

How long counselees retain the information given during their genetic consultation is of major importance. To address this issue, we conducted a survey among the 3500 families that have been offered genetic counseling at our Center since 1988. In August 2007, we mailed a questionnaire to a representative subset of 579 persons belonging to breast/ovarian or colon cancer families seen in the last 10 years, either carrying an identified mutation or not. Targeted topics included the meaning of hereditary predisposition, the medical prevention related to the familial risk, the steps to undertake for a new family member to enter the genetic testing program and general knowledge of hereditary predisposition to cancer. A total of 91 randomized non-respondents were sent a second, more inciting letter, in order to assess any non-response bias. Overall, 337 questionnaires were collected: response rate was 58%. Standardized average knowledge was 7.28±1.52 of 10. Scores were lowest concerning medical prevention. The level of knowledge decreased with age (P<10−6), but increased with educational level (P<10−5) and mutation status (P=0.01). Surprisingly, no erosion of patients' knowledge over the time was observed (P=0.41). Among persons at hereditary risk of colon cancer, the level of knowledge tended to improve with time, in contrast to the breast/ovarian group (P=0.017). Among persons with a familial risk of breast/ovarian or colon cancer, a renewal of oncogenetic counseling does not seem necessary to maintain the level of specific knowledge. Measures to help patients follow their medical prevention, as organizing or checking their medical examinations, seem indicated

A systematic review of communication interventions to help healthcare professionals discuss genetic testing for breast cancer

Purpose This systematic review examined educational training interventions for healthcare professionals (HCPs) discussing genetic testing and risk for hereditary breast cancer. There was a particular focus on the presence, and content, of communication elements within these packages. Methods Searches were run via CINAHL, EMBASE, PUBMED, and PsychInfo in February 2019 to identify training interventions available to HCPs with reference to communication skills. Studies were assessed for quality, with relevant intervention and outcome data extracted and synthesized. This review followed the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) statement and was registered on the PROSPERO database (CRD42019124010). Results of 3,988 items, seven papers, two of which were linked, were eligible for inclusion. There was a mix of randomized and single arm studies with web-based and face-to-face interventions. Content included an overview of genetics, hereditary and familial background, and recommended practice techniques. Outcomes focused on communication, self-efficacy, knowledge, and satisfaction. Interventions were designed for genetic counselors, physicians, primary care physicians (PCPs), medical students, and nurses. None of the papers featured oncologists or surgeons. Conclusions This review revealed an overall lack of publications which evaluated interventions to assist HCPs discussing hereditary breast cancer risk and testing. Studies failed to operationalize which ‘communication skills’ they included, nor did they consistently report randomization, outcome measures, or analysis. Discussing the need for, and management of, genetic testing for inherited cancer risk with individuals and their families can be challenging. As genetic testing in breast cancer becomes more common, the provision of specific communication-based training programs, with reference to genetic testing, risk assessments, and counseling skills is warranted

Responsible sharing of biomedical data and biospecimens via the "Automatable Discovery and Access Matrix" (ADA-M)

Given the data-rich nature of modern biomedical research, there is a pressing need for a systematic, structured, computer-readable way to capture, communicate, and manage sharing rules that apply to biomedical resources. This is essential for responsible recording, versioning, communication, querying, and actioning of resource sharing plans. However, lack of a common "information model" for rules and conditions that govern the sharing of materials, methods, software, data, and knowledge creates a fundamental barrier. Without this, it can be virtually impossible for Research Ethics Committees (RECs), Institutional Review Boards (IRBs), Data Access Committees (DACs), biobanks, and end users to confidently track, manage, and interpret applicable legal and ethical requirements. This raises costs and burdens of data stewardship and decreases efficient and responsible access to data, biospecimens, and other resources. To address this, the GA4GH and IRDiRC organizations sponsored the creation of the Automatable Discovery and Access Matrix (ADA-M, read simply as "Adam"). ADA-M is a comprehensive information model that provides the basis for producing structured metadata "Profiles" of regulatory conditions, thereby enabling efficient application of those conditions across regulatory spheres. Widespread use of ADA-M will aid researchers in globally searching and prescreening potential data and/or biospecimen resources for compatibility with their research plans in a responsible and efficient manner, increasing likelihood of timely DAC approvals while also significantly reducing time and effort DACs, RECs, and IRBs spend evaluating resource requests and research proposals. Extensive online documentation, software support, video guides, and an Application Programming Interface (API) for ADA-M have been made available

Responsible sharing of biomedical data and biospecimens via the "Automatable Discovery and Access Matrix" (ADA-M).

Given the data-rich nature of modern biomedical research, there is a pressing need for a systematic, structured, computer-readable way to capture, communicate, and manage sharing rules that apply to biomedical resources. This is essential for responsible recording, versioning, communication, querying, and actioning of resource sharing plans. However, lack of a common "information model" for rules and conditions that govern the sharing of materials, methods, software, data, and knowledge creates a fundamental barrier. Without this, it can be virtually impossible for Research Ethics Committees (RECs), Institutional Review Boards (IRBs), Data Access Committees (DACs), biobanks, and end users to confidently track, manage, and interpret applicable legal and ethical requirements. This raises costs and burdens of data stewardship and decreases efficient and responsible access to data, biospecimens, and other resources. To address this, the GA4GH and IRDiRC organizations sponsored the creation of the Automatable Discovery and Access Matrix (ADA-M, read simply as "Adam"). ADA-M is a comprehensive information model that provides the basis for producing structured metadata "Profiles" of regulatory conditions, thereby enabling efficient application of those conditions across regulatory spheres. Widespread use of ADA-M will aid researchers in globally searching and prescreening potential data and/or biospecimen resources for compatibility with their research plans in a responsible and efficient manner, increasing likelihood of timely DAC approvals while also significantly reducing time and effort DACs, RECs, and IRBs spend evaluating resource requests and research proposals. Extensive online documentation, software support, video guides, and an Application Programming Interface (API) for ADA-M have been made available

Responsible sharing of biomedical data and biospecimens via the "Automatable Discovery and Access Matrix" (ADA-M).

Given the data-rich nature of modern biomedical research, there is a pressing need for a systematic, structured, computer-readable way to capture, communicate, and manage sharing rules that apply to biomedical resources. This is essential for responsible recording, versioning, communication, querying, and actioning of resource sharing plans. However, lack of a common "information model" for rules and conditions that govern the sharing of materials, methods, software, data, and knowledge creates a fundamental barrier. Without this, it can be virtually impossible for Research Ethics Committees (RECs), Institutional Review Boards (IRBs), Data Access Committees (DACs), biobanks, and end users to confidently track, manage, and interpret applicable legal and ethical requirements. This raises costs and burdens of data stewardship and decreases efficient and responsible access to data, biospecimens, and other resources. To address this, the GA4GH and IRDiRC organizations sponsored the creation of the Automatable Discovery and Access Matrix (ADA-M, read simply as "Adam"). ADA-M is a comprehensive information model that provides the basis for producing structured metadata "Profiles" of regulatory conditions, thereby enabling efficient application of those conditions across regulatory spheres. Widespread use of ADA-M will aid researchers in globally searching and prescreening potential data and/or biospecimen resources for compatibility with their research plans in a responsible and efficient manner, increasing likelihood of timely DAC approvals while also significantly reducing time and effort DACs, RECs, and IRBs spend evaluating resource requests and research proposals. Extensive online documentation, software support, video guides, and an Application Programming Interface (API) for ADA-M have been made available