A Clinical Decision Support Tool to Predict Cancer Risk for Commonly Tested Cancer‐Related Germline Mutations. Issue 5 (2nd March 2018)

• Record Type: Journal Article
• Authors: Braun, Danielle; Yang, Jiabei; Griffin, Molly; Parmigiani, Giovanni; Hughes, Kevin S.
• Is Part Of: Journal of genetic counseling. Volume 27:Issue 5(2018)
• Page Start: 1187
• Page End: 1199
• Publication Date: 2018-03-02
• Subjects: Germline mutation -- Disease susceptibility -- Genetic predisposition to disease -- Risk assessment -- Risk management; Genetic counseling -- Periodicals; 616.042
• DOI: 10.1007/s10897-018-0238-4
• Languages: English
• ISSNs: 1059-7700

Abstract

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.