首页> 外文OA文献 >Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer--comparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial.
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Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer--comparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial.

机译:通过淋巴结阴性乳腺癌的临床病理风险分类算法进行长期结果预测-比较佐剂,St Gallen和前瞻性随机淋巴结阴性乳腺癌3(NNBC-3)试验中使用的新型风险算法。

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摘要

Defining risk categories in breast cancer is of considerable clinical significance. We have developed a novel risk classification algorithm and compared its prognostic utility to the Web-based tool Adjuvant! and to the St Gallen risk classification.After a median follow-up of 10 years, we retrospectively analyzed 410 consecutive node-negative breast cancer patients who had not received adjuvant systemic therapy. High risk was defined by any of the following criteria: (i) age <35 years, (ii) grade 3, (iii) human epithelial growth factor receptor-2 positivity, (iv) vascular invasion, (v) progesterone receptor negativity, (vi) grade 2 tumors >2 cm. All patients were also characterized using Adjuvant! and the St Gallen 2007 risk categories. We analyzed disease-free survival (DFS) and overall survival (OS).The Node-Negative-Breast Cancer-3 (NNBC-3) algorithm enlarged the low-risk group to 37% as compared with Adjuvant! (17%) and St Gallen (18%), respectively. In multivariate analysis, both Adjuvant! [P = 0.027, hazard ratio (HR) 3.81, 96% confidence interval (CI) 1.16-12.47] and the NNBC-3 risk classification (P = 0.049, HR 1.95, 95% CI 1.00-3.81) significantly predicted OS, but only the NNBC-3 algorithm retained its prognostic significance in multivariate analysis for DFS (P < 0.0005).The novel NNBC-3 risk algorithm is the only clinicopathological risk classification algorithm significantly predicting DFS as well as OS.
机译:在乳腺癌中定义风险类别具有重要的临床意义。我们开发了一种新颖的风险分类算法,并将其预后效用与基于Web的工具Adjuvant!进行了比较。中位随访10年后,我们回顾性分析了410例未接受辅助全身治疗的连续淋巴结阴性乳腺癌患者。高风险由以下任何标准定义:(i)年龄小于35岁,(ii)3级,(iii)人上皮生长因子受体2阳性,(iv)血管浸润,(v)孕激素受体阴性, (vi)> 2 cm的2级肿瘤。还使用佐剂对所有患者进行了表征!以及St Gallen 2007风险类别。我们分析了无病生存期(DFS)和总体生存期(OS)。与佐剂相比,Node-Negative-Breast Cancer-3(NNBC-3)算法将低风险组扩大到37%! (17%)和圣加仑(18%)。在多变量分析中,两者都是佐剂! [P = 0.027,危险比(HR)3.81,96%置信区间(CI)1.16-12.47]和NNBC-3风险分类(P = 0.049,HR 1.95,95%CI 1.00-3.81)显着预测了OS,但只有NNBC-3算法在DFS的多变量分析中保留了其预后意义(P <0.0005)。新颖的NNBC-3风险算法是唯一能够显着预测DFS和OS的临床病理风险分类算法。

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