Optimal control for a stochastic model of cancer chemotherapy
Optimal control for a stochastic model of cancer chemotherapy
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DOI：
10.1016/s0025-5564(00)00045-6
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发表时间：
2000-12-01
影响因子：
4.3
通讯作者：
Murray, JM
中科院分区：
文献类型：
--
作者：
Coldman, AJ;Murray, JM
化疗可用于许多癌症，以减少或消除残留疾病。当以这种方式使用时，目标是最大限度地提高消除癌症的可能性。在本文中，我们扩展了癌症化疗的随机模型，将其对正常系统的伴随影响纳入其中，并得出结果的总体衡量标准。该模型包括耐药性的发展，并且足够灵活，可以包括各种肿瘤和正常系统的生长功能。然后将该模型应用于文献中先前研究的情况，结果表明，在可能产生耐药性的情况下，早期强化是成功治疗方案的共同特征。该模型还适用于从临床试验中收集的数据，分析阿霉素、环磷酰胺、甲氨蝶呤和 5-氟尿嘧啶 (CMF) 疗法在治疗可手术乳腺癌中的效果。该模型能够模拟数据并提供最佳方案的描述。 (C) 2000 Elsevier Science Inc. 保留所有权利。
Chemotherapy is useful in a number of cancers to reduce or eliminate residual disease. When used in this way the objective is to maximise the likelihood that the cancer will be eliminated. In this article, we extend a stochastic model of chemotherapy for cancer to incorporate its concomitant effect on the normal system and derive overall measures of outcome. The model includes the development of drug resistance and is sufficiently flexible to include a variety of tumour and normal system growth functions. The model is then applied to situations previously examined in the literature and it is shown that early intensification is a common feature of successful regimens in situations where drug resistance is likely. The model is also applied to data collected from clinical trials analysing the effect of adriamycin, and cyclophosphamide, methotrexate and 5-flourouracil (CMF) therapy in the treatment of operable breast cancer. The model is able to mimic the data and provides a description of the optimal regimen. (C) 2000 Elsevier Science Inc. All rights reserved.