ArticleJournal of genetic counseling2015
Personalized Medicine Through SNP Testing for Breast Cancer Risk: Clinical Implementation.
Article in Journal of genetic counseling, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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
8 citing papers in PubMed, 31 citations in OpenAlex.
- Psychosocial and behavioral impact of breast cancer risk assessed by testing for common risk variants: protocol of a prospective study.BMC cancer · 2017Trial
- A computational and structural approach to identify malignant non-synonymous FOXM1 single nucleotide polymorphisms in triple-negative breast cancer.Scientific reports · 2025Article
- Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data.BMC bioinformatics · 2023Article
- Patients' and professionals' views related to ethical issues in precision medicine: a mixed research synthesis.BMC medical ethics · 2021Review
- Clinical and Genetic Risk Prediction of Cognitive Impairment After Blood or Marrow Transplantation for Hematologic Malignancy.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2020Article
- Making Sense of SNPs: Women's Understanding and Experiences of Receiving a Personalized Profile of Their Breast Cancer Risks.Journal of genetic counseling · 2018Article
- Article
- Women's preferences, willingness-to-pay, and predicted uptake for single-nucleotide polymorphism gene testing to guide personalized breast cancer screening strategies: a discrete choice experiment.Patient preference and adherence · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 6 institutions in 3 countries.
Funding
Abstract
Single nucleotide polymorphisms (SNPs) have the potential to improve personalized medicine in breast cancer care. As new SNPs are discovered, further enhancing risk classification, SNP testing may serve to complement family history and phenotypic risk factors when assessed in a clinical setting. SNP analysis is particularly relevant to high-risk women who may seek out such information to guide their decision-making around risk-reduction. However, little is known about how high-risk women may respond to SNP testing with regard to clinical decision-making. We examined high-risk women's interest in SNP testing for breast cancer risk through an online survey of hypothetical testing scenarios. Women stated their preferences for sharing test results and selected the most likely follow-up action they would pursue in each of the test result scenarios (above average and below average risk for breast cancer). Four hundred seventy-eight women participated. Most women (89 %) did not know what a SNP was prior to the study. Once SNP testing was described, 75 % were interested in SNP testing. Participants stated an interest in lifestyle interventions for risk-reduction and wanted to discuss their testing results with their doctor or a genetic counselor. Women are interested in SNP testing and are prepared to make lifestyle changes based on testing results. Women's preference for discussing testing results with a healthcare provider aligns with the current trend towards SNP testing in a clinical setting.
Indexed as
Identifiers
What OpenQuestion holds
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.