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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\u2019 gene carrier status, age, and history of relevant prophylactic surgery. By allowing clinicians to enter patient information and receive patient\u2010specific 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\u2010cancer associations risk estimates are based on one study rather than meta\u2010analysis, (2) strong assumptions on prior cancers, (3) lack of uncertainty measures, and (4) risk estimates for a growing set of gene\u2010cancer 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.<\/jats:p>","DOI":"10.1007\/s10897-018-0238-4","type":"journal-article","created":{"date-parts":[[2018,3,2]],"date-time":"2018-03-02T05:31:57Z","timestamp":1519968717000},"page":"1187-1199","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["A Clinical Decision Support Tool to Predict Cancer Risk for Commonly Tested Cancer\u2010Related Germline Mutations"],"prefix":"10.1002","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5177-8598","authenticated-orcid":false,"given":"Danielle","family":"Braun","sequence":"first","affiliation":[{"name":"Department of Biostatistics Harvard T.H. 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Chan School of Public Health Boston MA USA"},{"name":"Department of Biostatistics and Computational Biology Dana\u2010Farber Cancer Institute 450 Brookline Ave, CLSB 11051 Boston MA 02215 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin S.","family":"Hughes","sequence":"additional","affiliation":[{"name":"Division of Surgical Oncology Massachusetts General Hospital Boston MA USA"},{"name":"Surgery, Harvard Medical School Boston MA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2018,3,2]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1400382"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1399-0004.2008.01125.x"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2011.743"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10549-011-1791-9"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2006.09.1066"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2014.57.1414"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/sj.ejhg.5201734"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/bjc.2012.486"},{"key":"e_1_2_10_10_1","first-page":"181","article-title":"Better contralateral breast cancer risk estimation and alternative options to contralateral prophylactic mastectomy","volume":"7","author":"Davies K. 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