Xie Xianhe, Hu Yanfen, Jing Chao, Luo Shuimei, Lv Yunfu, Yang Haitao, Li Lina, Chen Huijuan, Lin Wanzun, Zheng Weili
Department of Chemotherapy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
Department of Internal Medicine Oncology, Hainan General Hospital, Haikou, Hainan, China. Email:xiexianhe@ yahoo.com
Asian Pac J Cancer Prev. 2017 Mar 1;18(3):727-733. doi: 10.22034/APJCP.2017.18.3.727.
We investigated relationships between clinical pathologic data, molecular biomarkers and prognosis of invasive breast cancer based on a Chinese population. Immunohistochemistry (IHC) was used to assess the status of ER, PR, HER-2 and Ki-67, with fluorescence in situ hybridization (FISH) performed to further confirm HER-2 positivity with an equivocal result (IHC 2+). Subsequently, Kaplan-Meier univariate and multivariate COX regression analyses of ER, PR, HER-2, Ki-67, clinical features, therapeutic status and follow-up data were performed according to the establishment principle of the Nottingham prognostic index (NPI). From this study, age, tumor size, lymph node status, ER, HER-2, Ki-67 status were found to be associated with prognosis. Eventually, a prognostic model of (PI= (1.5×age) - size + (0.1×lymph node status) - (0.5×ER) + (2×HER-2) - (0.2×Ki-67)) was established with 288 randomly selected patients and verified with another 100 cases with invasive breast cancer. Pearson correlation analysis demonstrated a significant positive correlation index of 0.376 (P=0.012<0.05) between the prognostic index (PI) and actual prognosis. Remarkably, the consistency with the model predicted recurrence was 93% in the validation set. Therefore, it appears feasible to predict the prognosis of individuals with invasive breast cancer and to determine optimal therapeutic strategy with this model.
我们基于中国人群研究了浸润性乳腺癌的临床病理数据、分子生物标志物与预后之间的关系。采用免疫组织化学(IHC)评估雌激素受体(ER)、孕激素受体(PR)、人表皮生长因子受体2(HER-2)和Ki-67的状态,对于结果不明确(IHC 2+)的情况,采用荧光原位杂交(FISH)进一步确认HER-2阳性。随后,根据诺丁汉预后指数(NPI)的建立原则,对ER、PR、HER-2、Ki-67、临床特征、治疗情况和随访数据进行了Kaplan-Meier单因素和多因素COX回归分析。通过本研究发现,年龄、肿瘤大小、淋巴结状态、ER、HER-2、Ki-67状态与预后相关。最终,利用288例随机选择的患者建立了预后模型(PI = (1.5×年龄) - 肿瘤大小 + (0.1×淋巴结状态) - (0.5×ER) + (2×HER-2) - (0.2×Ki-67)),并在另外100例浸润性乳腺癌患者中进行了验证。Pearson相关分析显示,预后指数(PI)与实际预后之间的显著正相关指数为0.376(P = 0.012<0.05)。值得注意的是,在验证集中,该模型预测复发的一致性为93%。因此,利用该模型预测浸润性乳腺癌患者的预后并确定最佳治疗策略似乎是可行的。