https://scholars.lib.ntu.edu.tw/handle/123456789/520919
標題: | A new clinical-genomic model to predict 10-year recurrence risk in primary operable breast cancer patients | 作者: | Huang T.-T. Lei L. Chen C.-H.A. TZU-PIN LU Jen C.-W. Cheng S.H.-C. |
公開日期: | 2020 | 出版社: | Nature Research | 卷: | 10 | 期: | 1 | 來源出版物: | Scientific Reports | 摘要: | This study aimed to validate the long-term prognostic value of a new clinical-genomic model, Distant Genetic Model-Clinical Variable Model 6 (DGM-CM6), developed in Asia as a prognostic panel for all subtypes of breast cancer. We included 752 operable stage I–III breast cancer patients representing all subtypes treated from 2005 to 2014 as the validation cohort. The median follow-up was 95.8?months. The low- and high-risk patients classified by DGM-CM6 (RI-DR) had significant differences in 10-year distant recurrence-free interval (DRFI) (94.1% vs. 85.0%, P < 0.0001) and relapse-free survival (RFS) (90.0% vs. 80.5%, P = 0.0003). External validation using EMTAB-365 dataset showed similar observation (P < 0.0001). DGM-CM6 was an independent prognostic factor by multivariate analysis with hazard ratios of 3.1 (1.6–6.0) for RFS (P = 0.0009) and 3.8 (1.6–9.0) for DRFI (P = 0.0028). Comparing the C-index of DGM-CM6 and PAM50-ROR scores, the former performed better than the latter in predicting long-term DRFI and RFS, especially in N0, ER/PR-positive, and HER2-negative patients. ? 2020, The Author(s). |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082068187&doi=10.1038%2fs41598-020-61535-9&partnerID=40&md5=e31d0b3778f3a146064f54b7f675af42 https://scholars.lib.ntu.edu.tw/handle/123456789/520919 |
ISSN: | 2045-2322 | DOI: | 10.1038/s41598-020-61535-9 | SDG/關鍵字: | adult; aged; biological model; breast tumor; cancer staging; female; gene regulatory network; genetics; human; middle aged; multivariate analysis; pathology; prognosis; survival analysis; very elderly; Adult; Aged; Aged, 80 and over; Breast Neoplasms; Female; Gene Regulatory Networks; Humans; Middle Aged; Models, Genetic; Multivariate Analysis; Neoplasm Staging; Prognosis; Survival Analysis |
顯示於: | 流行病學與預防醫學研究所 |
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