ArticleJournal of genetic counseling2018
A Clinical Decision Support Tool to Predict Cancer Risk for Commonly Tested Cancer-Related Germline Mutations.
Article in Journal of genetic counseling, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 4 of them syntheses that pooled it.
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
31 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Bayesian meta-analysis of penetrance for cancer risk.Biometrics · 2024Pooled it
- Statistical approaches for meta-analysis of genetic mutation prevalence.Genetic epidemiology · 2021Pooled it
- Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes.JCO clinical cancer informatics · 2019Pooled it
- Validation of a Semiautomated Natural Language Processing-Based Procedure for Meta-Analysis of Cancer Susceptibility Gene Penetrance.JCO clinical cancer informatics · 2019Pooled it
- Genetic Testing for All Breast Cancer Patients: The GET FACTS Randomized Clinical Trial.JAMA network open · 2026Trial
- Breast cancer screening adherence after multigene panel testing among women with pathogenic variants in moderate-risk genes or with empirically increased breast cancer risk.Breast cancer research and treatment · 2026Article
- Age-based risk estimates for C9orf72RE-related diseases: Theoretical developments and added value for genetic counseling.PLoS genetics · 2026Article
- Evaluating a Mendelian Risk Prediction Model That Aggregates Across Genes and Cancers.Genetic epidemiology · 2026Article
- Review
- Evaluating the utility of multi-gene, multi-disease population-based panel testing accounting for uncertainty in penetrance estimates.NPJ genomic medicine · 2024Article
- Upgrade Rates and Breast Cancer Development Among Germline Pathogenic Variant Carriers with High-Risk Breast Lesions.Annals of surgical oncology · 2024Article
- Society of Surgical Oncology Breast Disease Site Working Group Statement on Contralateral Mastectomy: Indications, Outcomes, and Risks.Annals of surgical oncology · 2024Review
- Awareness and Candidacy for Endocrine Prevention and Risk Reducing Mastectomy in Unaffected High-Risk Women Referred for Breast Cancer Risk Assessment.Annals of surgical oncology · 2024Article
- Counselling Framework for GermlineCurrent oncology (Toronto, Ont.) · 2024Review
- MyLynch: A Patient-Facing Clinical Decision Support Tool for Genetically-Guided Personalized Medicine in Lynch Syndrome.Cancers · 2023Article
- Who Should Have Multigene Germline Testing for Hereditary Cancer?Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022Article
- Statistical methods for Mendelian models with multiple genes and cancers.Genetic epidemiology · 2022Article
- Universal Germline Genetic Testing for Hereditary Cancer Syndromes in Patients With Solid Tumor Cancer.JCO precision oncology · 2022Article
- Familial pancreatic cancer: who should be considered for genetic testing?Irish journal of medical science · 2022Article
- Non-medullary Thyroid Cancer Susceptibility Genes: Evidence and Disease Spectrum.Annals of surgical oncology · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The rapid drop in the cost of DNA sequencing led to the availability of multi-gene panels, which test 25 or more cancer susceptibility genes for a low cost. Clinicians and genetic counselors need a tool to interpret results, understand risk of various cancers, and advise on a management strategy. This is challenging as there are multiple studies regarding each gene, and it is not possible for clinicians and genetic counselors to be aware of all publications, nor to appreciate the relative accuracy and importance of each. Through an extensive literature review, we have identified reliable studies and derived estimates of absolute risk. We have also developed a systematic mechanism and informatics tools for (1) data curation, (2) the evaluation of quality of studies, and (3) the statistical analysis necessary to obtain risk. We produced the risk prediction clinical decision support tool ASK2ME (All Syndromes Known to Man Evaluator). It provides absolute cancer risk predictions for various hereditary cancer susceptibility genes. These predictions are specific to patients' gene carrier status, age, and history of relevant prophylactic surgery. By allowing clinicians to enter patient information and receive patient-specific cancer risks, this tool aims to have a significant impact on the quality of precision cancer prevention and disease management activities relying on panel testing. It is important to note that this tool is dynamic and constantly being updated, and currently, some of its limitations include (1) for many gene-cancer associations risk estimates are based on one study rather than meta-analysis, (2) strong assumptions on prior cancers, (3) lack of uncertainty measures, and (4) risk estimates for a growing set of gene-cancer associations which are not always variant specific. All of these concerns are being addressed on an ongoing basis, aiming to make the tool even more accurate.
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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.