Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Med Oncol. 2013 Mar;30(1):337. doi: 10.1007/s12032-012-0337-2. Epub 2013 Feb 12.
The aim of this study is to determine the risk factors associated with metastasis to the brain of primary breast cancer patients and evaluate a predictive model. The clinicopathological characteristics of 206 patients with primary breast cancer were analyzed retrospectively with a univariate and multivariate logistic regression model. A predictive model was generated, and its validity evaluated with a receiver operating characteristic (ROC) curve. Independent risk factors for brain metastasis in patients with primary breast cancer were: being younger than 35 years old at the time of diagnosis, having four or more metastatic axillary nodes, being estrogen receptor-negative, and with 24 months of metastasis-free survival. The predictive value of the brain metastasis risk model, measured as the area under the ROC curve, was 0.765 ± 0.040 (95 % CI 0.688-0.842). When 0.8 was considered the cutoff point of probability calculated by the model, the sensitivity and specificity for predicting the occurrence of brain metastases in these patients were 0.769 and 0.713, respectively. The predictive model constructed in this study can be used to forecast brain metastasis in breast cancer. Patients with a predictive level ≥0.8 could be treated preventively for brain metastases.
本研究旨在确定与原发性乳腺癌患者脑转移相关的风险因素，并评估预测模型。回顾性分析了 206 例原发性乳腺癌患者的临床病理特征，采用单因素和多因素逻辑回归模型进行分析。生成了预测模型，并通过接收者操作特征（ROC）曲线评估其有效性。原发性乳腺癌患者脑转移的独立危险因素为：诊断时年龄小于 35 岁、腋窝转移淋巴结 4 个或以上、雌激素受体阴性以及无转移生存时间 24 个月。ROC 曲线下面积（AUC）衡量脑转移风险模型的预测价值，为 0.765±0.040（95%CI 0.688-0.842）。当模型计算的概率截断值为 0.8 时，预测这些患者发生脑转移的敏感性和特异性分别为 0.769 和 0.713。本研究构建的预测模型可用于预测乳腺癌脑转移。预测值≥0.8 的患者可预防性地进行脑转移治疗。
