論文

国際誌
2021年5月25日

Optimization of prediction methods for risk assessment of pathogenic germline variants in the Japanese population.

Cancer science
  • Noriko Senda
  • Nobuko Kawaguchi-Sakita
  • Masahiro Kawashima
  • Yukiko Inagaki-Kawata
  • Kenichi Yoshida
  • Masahiro Takada
  • Masako Kataoka
  • Masae Torii
  • Tomomi Nishimura
  • Kosuke Kawaguchi
  • Eiji Suzuki
  • Yuki Kataoka
  • Yoshiaki Matsumoto
  • Hiroshi Yoshibayashi
  • Kazuhiko Yamagami
  • Shigeru Tsuyuki
  • Sachiko Takahara
  • Akira Yamauchi
  • Nobuhiko Shinkura
  • Hironori Kato
  • Yoshio Moriguchi
  • Ryuji Okamura
  • Norimichi Kan
  • Hirofumi Suwa
  • Shingo Sakata
  • Susumu Mashima
  • Fumiaki Yotsumoto
  • Tsuyoshi Tachibana
  • Mitsuru Tanaka
  • Kaori Togashi
  • Hironori Haga
  • Takahiro Yamada
  • Shinji Kosugi
  • Takashi Inamoto
  • Masahiro Sugimoto
  • Seishi Ogawa
  • Masakazu Toi
  • 全て表示

112
8
開始ページ
3338
終了ページ
3348
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1111/cas.14986

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-Cuzick (TC) breast cancer risk evaluation tool to predict BRCA PGVs in unselected Japanese breast cancer patients (n = 1,995). Eleven breast cancer susceptibility genes were analyzed using target-capture sequencing in a previous study; the PGV prevalence in BRCA1, BRCA2, and PALB2 was 0.75%, 3.1%, and 0.45%, respectively. Significant associations were found between the presence of BRCA PGVs and early disease onset, number of familial cancer cases (up to third-degree relatives), triple-negative breast cancer patients under the age of 60, and ovarian cancer history (all P < .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 BRCA PGVs (area under the curve, 0.75; 95% confidence interval, 0.69-0.81). Furthermore, use of the TC model with an optimized cutoff of TC score ≥0.16% in addition to the NCCN guidelines improved the predictive efficiency for high-risk 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.

リンク情報
DOI
https://doi.org/10.1111/cas.14986
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/34036661
PubMed Central
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353892
ID情報
  • DOI : 10.1111/cas.14986
  • PubMed ID : 34036661
  • PubMed Central 記事ID : PMC8353892

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