ArticleThe oncologist2024
Development of an Electronic Decision Aid Tool to Facilitate Mainstream Genetic Testing in Ovarian Cancer Patients.
Article in The oncologist, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Healthcare professional perspectives on hereditary breast cancer risk assessment prior to gender-affirming mastectomy.Breast cancer research and treatment · 2026Article
- Digital genetic counseling services for cascade cardiogenetic testing.Journal of genetic counseling · 2026Article
- Feasibility and acceptability of an electronic decision aid for genetic testing in ovarian and pancreatic cancer patients.Research connections · 2026Article
- Awareness, uptake, and determinants of germline genetic testing in Chinese epithelial ovarian cancer patients: a cross-sectional study.Frontiers in oncology · 2026Article
- The development and usability of 'The Genetics Navigator': a digital solution for adult and paediatric clinical genetics services.European journal of human genetics : EJHG · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
backgroundMultigene panel testing is an important component of cancer treatment plans and risk assessment, but there are many different panel options and choosing the most appropriate panel can be challenging for health care providers and patients. Electronic tools have been proposed to help patients make informed decisions about which gene panel to choose by considering their preferences and priorities. MATERIALS AND
methodsAn electronic decision aid (DA) tool was developed in line with the International Patient Decision Aids Standards collaboration. The multidisciplinary project team collaborated with an external health care communications agency and the MGH Cancer Center Patient and Family Advisory Council (PFAC) to develop the DA. Surveys of genetic counselors and patients were used to scope the content, and alpha testing was used to refine the design and content.
resultsSurveys of genetic counselors (n = 12) and patients (n = 228) identified common themes in discussing panel size and strategies for helping patients decide between panels and in identifying confusing terms for patients and distribution of patients' choices. The DA, organized into 2 major sections, provides educational text, graphics, and videos to guide patients through the decision-making process. Alpha testing feedback from the PFAC (n = 4), genetic counselors (n = 3) and a group of lay people (n = 8) identified areas to improve navigation, simplify wording, and improve layout.
conclusionThe DA developed in this study has the potential to facilitate informed decision-making by patients regarding cancer genetic testing. The distinctive feature of this DA is that it addresses the specific question of which multigene panel may be most suitable for the patient. Its acceptability and effectiveness will be evaluated in future studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.