{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T19:32:22Z","timestamp":1783971142447,"version":"3.55.0"},"reference-count":41,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2021,6,28]],"date-time":"2021-06-28T00:00:00Z","timestamp":1624838400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100004325","name":"AstraZeneca","doi-asserted-by":"publisher","award":["NCR\u201017\u201012919"],"award-info":[{"award-number":["NCR\u201017\u201012919"]}],"id":[{"id":"10.13039\/100004325","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Science"],"published-print":{"date-parts":[[2021,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Predicting pathogenic germline variants (PGVs) in breast cancer patients is important for selecting optimal therapeutics and implementing risk reduction strategies. However, PGV risk factors and the performance of prediction methods in the Japanese population remain unclear. We investigated clinicopathological risk factors using the Tyrer\u2010Cuzick (TC) breast cancer risk evaluation tool to predict <jats:italic>BRCA<\/jats:italic> PGVs in unselected Japanese breast cancer patients (n\u00a0=\u00a01,995). Eleven breast cancer susceptibility genes were analyzed using target\u2010capture sequencing in a previous study; the PGV prevalence in <jats:italic>BRCA1<\/jats:italic>, <jats:italic>BRCA2<\/jats:italic>, and <jats:italic>PALB2<\/jats:italic> was 0.75%, 3.1%, and 0.45%, respectively. Significant associations were found between the presence of <jats:italic>BRCA<\/jats:italic> PGVs and early disease onset, number of familial cancer cases (up to third\u2010degree relatives), triple\u2010negative breast cancer patients under the age of 60, and ovarian cancer history (all <jats:italic>P<\/jats:italic>\u00a0&lt;\u00a0.0001). In total, 816 patients (40.9%) satisfied the National Comprehensive Cancer Network (NCCN) guidelines for recommending multigene testing. The sensitivity and specificity of the NCCN criteria for discriminating PGV carriers from noncarriers were 71.3% and 60.7%, respectively. The TC model showed good discrimination for predicting <jats:italic>BRCA<\/jats:italic> PGVs (area under the curve, 0.75; 95% confidence interval, 0.69\u20100.81). Furthermore, use of the TC model with an optimized cutoff of TC score \u22650.16% in addition to the NCCN guidelines improved the predictive efficiency for high\u2010risk groups (sensitivity, 77.2%; specificity, 54.8%; about 11 genes). Given the influence of ethnic differences on prediction, we consider that further studies are warranted to elucidate the role of environmental and genetic factors for realizing precise prediction.<\/jats:p>","DOI":"10.1111\/cas.14986","type":"journal-article","created":{"date-parts":[[2021,5,26]],"date-time":"2021-05-26T01:07:17Z","timestamp":1621991237000},"page":"3338-3348","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Optimization of prediction methods for risk assessment of pathogenic germline variants in the Japanese population"],"prefix":"10.1111","volume":"112","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5836-7556","authenticated-orcid":false,"given":"Noriko","family":"Senda","sequence":"first","affiliation":[{"name":"Department of Breast Surgery Kyoto University Kyoto 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