Individualized Survival and Treatment Response Predictions in Breast Cancer Patients: Involvements of Phospho-EGFR and Phospho-Her2/neu Proteins.
Individualized Survival and Treatment Response Predictions in Breast Cancer Patients: Involvements of Phospho-EGFR and Phospho-Her2/neu Proteins.
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DOI：
10.2174/1874189400802010018
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发表时间：
2008-05-27
期刊：
影响因子：
--
通讯作者：
Qian, Yong
中科院分区：
文献类型：
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作者：
Guo, Lan;Abraham, Jame;Qian, Yong
我们针对个体乳腺癌患者的强大预测系统结合了三种知名的机器学习分类器，以提供稳定准确的临床结果预测（N=269）。所选分类器的平均性能被用作乳腺癌预后预测的评价标准。一个概况（包括组织学，淋巴结状态，肿瘤分级，肿瘤分期，ER，PR，Her 2/neu，患者年龄和吸烟状况）在个体化无病生存和治疗反应预测中产生了超过95%的准确性。此外，我们的分析表明，磷酸化EGFR和磷酸化Her 2/neu的测量比总EGFR和总Her 2/neu的测量在乳腺癌生存预测中更有效（p < 0.05）。将激素受体状态、Her 2/neu、患者的年龄和吸烟状态并入传统病理标志物中，创建了一个强大的标准，以进行乳腺癌患者的个体化生存和治疗结果预测。
Our robust prediction system for individual breast cancer patients combines three well-known machine-learning classifiers to provide stable and accurate clinical outcome prediction (N=269). The average performance of the selected classifiers is used as the evaluation criterion in breast cancer outcome predictions. A profile (incorporating histology, lymph node status, tumor grade, tumor stage, ER, PR, Her2/neu, patient's age and smoking status) generated over 95% accuracy in individualized disease-free survival and treatment response predictions. Furthermore, our analysis demonstrated that the measurement of phospho-EGFR and phospho-Her2/neu is more powerful in breast cancer survival prediction than that of total EGFR and total Her2/neu (p < 0.05). The incorporation of hormone receptor status, Her2/neu, patient's age and smoking status into the traditional pathologic markers creates a powerful standard to perform individualized survival and treatment outcome predictions for breast cancer patients.