ArticlePloS one2022
Cancer prevention in cancer predisposition syndromes: A protocol for testing the feasibility of building a hereditary cancer research registry and nurse navigator follow up model.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 8 citations in OpenAlex.
- Canadian consensus for the assessment and testing of Lynch syndrome.Journal of medical genetics · 2025Article
- Germline sequence variation in cancer genes in Rwandan breast and prostate cancer cases.NPJ genomic medicine · 2024Article
- An integrative review on the oncology nurse navigator role in the Canadian context.Canadian oncology nursing journal = Revue canadienne de nursing oncologique · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 3 institutions in 1 country.
Funding
Abstract
Monogenic, high penetrance syndromes, conferring an increased risk of malignancies in multiple organs, are important contributors to the hereditary burden of cancer. Early detection and risk reduction strategies in patients with a cancer predisposition syndrome can save their lives. However, despite evidence supporting the benefits of early detection and risk reduction strategies, most Canadian jurisdictions have not implemented programmatic follow up of these patients. In our study site in the province of Newfoundland and Labrador (NL), Canada, there is no centralized, provincial registry of high-risk individuals. There is no continuity or coordination of care providing cancer genetics expertise and no process to ensure that patients are referred to the appropriate specialists or risk management interventions. This paper describes a study protocol to test the feasibility of obtaining and analyzing patient risk management data, specifically patients affected by hereditary breast ovarian cancer syndrome (HBOC; BRCA 1 and BRCA 2 genes) and Lynch syndrome (LS; MLH1, MSH2, MSH6, and PMS2 genes). Through a retrospective cohort study, we will describe these patients' adherence to risk management guidelines and test its relationship to health outcomes, including cancer incidence and stage. Through a qualitative interviews, we will determine the priorities and preferences of patients with any inherited cancer mutation for a follow up navigation model of risk management. Study data will inform a subsequent funding application focused on creating and evaluating a research registry and follow up nurse navigation model. It is not currently known what proportion of cancer mutation carriers are receiving care according to guidelines. Data collected in this study will provide clinical uptake and health outcome information so gaps in care can be identified. Data will also provide patient preference information to inform ongoing and planned research with cancer mutation carriers.
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.