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Nomogram Model of LNR Predicts Survival in Premenopausal Patients with Node-positive Luminal Breast Cancer

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机构: [1]Sun Yat Sen Univ, Ctr Canc, State Key Lab Oncol South China, Collaborat Innovat Ctr Canc Med, 651 Dongfeng Rd East, Guangzhou 510060, Guangdong, Peoples R China; [2]Sun Yat Sen Univ, Sun Yat Sen Mem Hosp, Breast Tumor Ctr, Guangzhou, Guangdong, Peoples R China
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关键词: Lymph node ratio breast cancer luminal subtype prognosis nomogram

摘要:
Aim: The aim of this study was to assess the prognostic value of lymph node ratio (LNR) in premenopausal patients with luminal breast carcinoma. Materials and Methods: A total of 885 female patients who presented with axillary lymph node-positive luminal breast cancer between 2000 and 2009 were investigated. Using X-tile, we classified patients into low-, intermediate-and high-risk groups based on LNR. The Kaplan-Meier method was used to determine cumulative survival curves. Cox proportional hazards analyses were used to identify the factors that contributed to disease-free (DFS) and overall (OS) survival. Results: The median age of patients was 42 years (range=21-58 years). A training set of 295 patients and a validation set of 590 patients were used to determine the optimal LNR cut-off points (0.20 and 0.63). DFS was 87.7%, 77.4% and 53.9% (p<0.001) and OS was 91.5%, 76.7% and 50.9% (p<0.0001) for the low- (<= 0.20), intermediate- (0.21-0.63) and high-risk (>0.63) groups, respectively. The 10-year DFS and OS rates were significantly longer in the low-risk group than in the high-risk group. Nomogram analysis demonstrated that LNR contributed more compared to nodal stage in predicting both DFS and OS. Conclusion: We conclude that LNR strongly predicts prognosis in premenopausal patients with lymph node-positive luminal breast cancer.

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出版当年[2017]版:
大类 | 4 区 医学
小类 | 4 区 肿瘤学
最新[2023]版:
大类 | 4 区 医学
小类 | 4 区 肿瘤学
第一作者:
第一作者机构: [1]Sun Yat Sen Univ, Ctr Canc, State Key Lab Oncol South China, Collaborat Innovat Ctr Canc Med, 651 Dongfeng Rd East, Guangzhou 510060, Guangdong, Peoples R China; [2]Sun Yat Sen Univ, Sun Yat Sen Mem Hosp, Breast Tumor Ctr, Guangzhou, Guangdong, Peoples R China
通讯作者:
通讯机构: [1]Sun Yat Sen Univ, Ctr Canc, State Key Lab Oncol South China, Collaborat Innovat Ctr Canc Med, 651 Dongfeng Rd East, Guangzhou 510060, Guangdong, Peoples R China;
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