ArticleBreast cancer research and treatment2012
Improving communication of breast cancer recurrence risk.
Article in Breast cancer research and treatment, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 3 of them syntheses that pooled it.
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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
43 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Pooled it
- The Patient in Precision Medicine: A Systematic Review Examining Evaluations of Patient-Facing Materials.Journal of healthcare engineering · 2018Pooled it
- Recommendations from the EGAPP Working Group: does the use of Oncotype DX tumor gene expression profiling to guide treatment decisions improve outcomes in patients with breast cancer?Genetics in medicine : official journal of the American College of Medical Genetics · 2016Guideline
- A randomized experimental study to test the effects of discussing uncertainty during cancer genetic counseling: different strategies, different outcomes?European journal of human genetics : EJHG · 2021Trial
- A signal detection analysis of gist-based discrimination of genetic breast cancer risk.Behavior research methods · 2013Trial
- Tables or bar graphs? Presenting test results in electronic medical records.Medical decision making : an international journal of the Society for Medical Decision MakingTrial
- What do women want to see in a personalized breast cancer risk report? A qualitative study of Asian women of two countries.Journal of community genetics · 2024Article
- Article
- Visualizing machine learning-based predictions of postpartum depression risk for lay audiences.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Do you want to promote recall, perceptions, or behavior? The best data visualization depends on the communication goal.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Healthcare providers' understanding of data displays of clinical trial information: a scoping review of the literature.Journal of communication in healthcare · 2023Article
- Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breast cancer.NPJ breast cancer · 2023Article
- Investigating the presentation of uncertainty in an icon array: A randomized trial.PEC innovation · 2022Article
- Using Breast Cancer Gene Expression Signatures in Clinical Practice: Unsolved Issues, Ongoing Trials and Future Perspectives.Cancers · 2021Review
- How Canadian Oncologists Use Oncotype DX for Treatment of Breast Cancer Patients.Current oncology (Toronto, Ont.) · 2021Article
- Effects of health literacy skills, educational attainment, and level of melanoma risk on responses to personalized genomic testing.Patient education and counseling · 2021Article
- Question Prompt List to Support Patient-Provider Communication in the Use of the 21-Gene Recurrence Test: Feasibility, Acceptability, and Outcomes.JCO oncology practice · 2020Article
- Return-to-Player Percentage in Gaming Machines: Impact of Informative Materials on Player Understanding.Journal of gambling studies · 2020Article
- Illustrating Cancer Risk: Patient Risk Communication Preferences and Interest regarding a Novel BRCA1/2 Genetic Risk Modifier Test.Public health genomics · 2020Article
- Improving Communication in Breast Cancer Treatment Consultation: Use of a Computer Test of Health Numeracy.Journal of women's health (2002) · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Doctors commonly use genomic testing for breast cancer recurrence risk. We sought to assess whether the standard genomic report provided to doctors is a good approach for communicating results to patients. During 2009-2010, we interviewed 133 patients with stages I or II, node-negative, hormone receptor-positive breast cancer and eligible for the Oncotype DX genomic test. In a randomized experiment, patients viewed six vignettes that presented hypothetical recurrence risk test results. Each vignette described a low, intermediate, or high chance of breast cancer recurrence in 10 years. Vignettes used one of five risk formats of increasing complexity that we derived from the standard report that accompanies the commercial assay or a sixth format that used an icon array. Among women who received the genomic recurrence risk test, 63% said their doctors showed them the standard report. The standard report format yielded among the most errors in identification of whether a result was low, intermediate, or high risk (i.e., the gist of the results), whereas a newly developed risk continuum format yielded the fewest errors (17% vs. 5%; OR 0.23; 95% CI 0.10-0.52). For high recurrence risk results presented in the standard format, women made errors 35% of the time. Women rated the standard report as one of the least understandable and least-liked formats, but they rated the risk continuum format as among the most understandable and most liked. Results differed little by health literacy, numeracy, prior receipt of genomic test results during clinical care, and actual genomic test results. The standard genomic recurrence risk report was more difficult for women to understand and interpret than the other formats. A less complex report, potentially including the risk continuum format, would be more effective in communicating test results to patients.
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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.