Artificial neural network analysis of circulating tumor cells in metastatic breast cancer patients
Artificial neural network analysis of circulating tumor cells in metastatic breast cancer patients
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DOI：
10.1007/s10549-011-1645-5
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发表时间：
2011-09-01
影响因子：
3.8
通讯作者：
Reuben, James M.
中科院分区：
文献类型：
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作者：
Giordano, Antonio;Giuliano, Mario;Reuben, James M.
在转移性乳腺癌（MBC）患者中，每7.5毫升血液中有5个循环肿瘤细胞（ctc）的临界值可以高度预测预后。我们使用人工神经网络（ANN）预测工具分析了免疫组织化学定义的原发性肿瘤分子亚型中作为连续变量的CTC与总生存率之间的关系，以确定死亡风险与CTC计数之间的关系，并预测个体生存率。我们分析了2004年9月至2009年在MD安德森癌症中心接受治疗并接受治疗前CTC计数的517例（60%）连续MBC患者中的311例(CellSearch（a (R)）的训练数据集。年龄;雌激素、孕激素受体和HER2状态；内脏转移;转移性疾病部位；治疗类型和治疗线；使用人工神经网络对连续值ctc进行评价。在剩余206例（40%）患者的验证集中测试了从训练数据中获得的参数估计模型。模型估计准确，具有良好的判别性和校正性。ANN估计的死亡风险在所有分子肿瘤亚型中随着CTC计数的增加而线性增加，但ER+和三阴性MBC的死亡风险高于HER2+。4种CTC为0亚型的生存概率分别为：ER+/HER2- 0.947、ER+/HER2+ 0.959、ER-/HER2+ 0.902和ER-/HER2- 0.875。在200例CTCs患者中，ER+/HER2- 0.439, ER+/HER2+ 0.621, ER-/HER2+ 0.307, ER-/HER2- 0.130。在这项大型研究中，ANN揭示了在所有肿瘤亚型中，随着CTC计数的增加，MBC患者死亡风险呈线性增加。CTCs对HER2+ MBC患者的预后影响在靶向治疗中不太明显。这项研究可能支持这样一个概念，即在未来的分析中，需要仔细考虑ctc的数量以及生物学特性。
A cut-off of 5 circulating tumor cells (CTCs) per 7.5 ml of blood in metastatic breast cancer (MBC) patients is highly predictive of outcome. We analyzed the relationship between CTCs as a continuous variable and overall survival in immunohistochemically defined primary tumor molecular subtypes using an artificial neural network (ANN) prognostic tool to determine the shape of the relationship between risk of death and CTC count and to predict individual survival. We analyzed a training dataset of 311 of 517 (60%) consecutive MBC patients who had been treated at MD Anderson Cancer Center from September 2004 to 2009 and who had undergone pre-therapy CTC counts (CellSearch(A (R))). Age; estrogen, progesterone receptor, and HER2 status; visceral metastasis; metastatic disease sites; therapy type and line; and CTCs as a continuous value were evaluated using ANN. A model with parameter estimates obtained from the training data was tested in a validation set of the remaining 206 (40%) patients. The model estimates were accurate, with good discrimination and calibration. Risk of death, as estimated by ANN, linearly increased with increasing CTC count in all molecular tumor subtypes but was higher in ER+ and triple-negative MBC than in HER2+. The probabilities of survival for the four subtypes with 0 CTC were as follows: ER+/HER2- 0.947, ER+/HER2+ 0.959, ER-/HER2+ 0.902, and ER-/HER2- 0.875. For patients with 200 CTCs, they were ER+/HER2- 0.439, ER+/HER2+ 0.621, ER-/HER2+ 0.307, ER-/HER2- 0.130. In this large study, ANN revealed a linear increase of risk of death in MBC patients with increasing CTC counts in all tumor subtypes. CTCs' prognostic effect was less evident in HER2+ MBC patients treated with targeted therapy. This study may support the concept that the number of CTCs, along with the biologic characteristics, needs to be carefully taken into account in future analysis.