Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer-025EFcomparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial
Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer-025EFcomparison 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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DOI：
10.1093/annonc/mdn590
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发表时间：
2009-02-01
影响因子：
50.5
通讯作者：
Thomssen, C.
中科院分区：
文献类型：
--
作者：
Schmidt, M.;Victor, A.;Thomssen, C.
背景：定义乳腺癌的风险类别具有相当大的临床意义。我们开发了一种新颖的风险分类算法，并将其预测实用性与基于网络的工具 Adjuvant!患者和方法：经过 10 年的中位随访，我们回顾性分析了 410 名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 < 35 岁，(ii) 3 级，(iii) 人上皮生长因子受体 2 阳性，(iv) 血管侵犯，(v) 黄体酮受体阴性，(vi) 2 级肿瘤 > 2 cm。所有患者均使用佐剂进行表征！以及圣加仑 2007 年风险类别。我们分析了无病生存期 (DFS) 和总生存期 (OS)。结果：与佐剂相比，淋巴结阴性乳腺癌 3 (NNBC-3) 算法将低风险组扩大至 37%！分别为（17%）和圣加仑（18%）。在多变量分析中，两者都是佐剂！ [P = 0.027，风险比 (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 OS，但只有 NNBC-3 算法在 DFS 多变量分析中保留其预后意义（P < 0.0005)。结论：新型 NNBC-3 风险算法是唯一能显着预测 DFS 和 OS 的临床病理风险分类算法。
Background: 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.Patients and methods: 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).Results: 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).Conclusion: The novel NNBC-3 risk algorithm is the only clinicopathological risk classification algorithm significantly predicting DFS as well as OS.