用疗效-毒性数学模型优化肿瘤化疗药物方案

Athanassios Iliadis , Dominique Barbolosi
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引用次数: 90

摘要

在癌症化疗中,重要的是设计治疗策略,以确保理想的肿瘤细胞杀伤率而不产生不可接受的毒性。为了优化治疗,我们使用了一个数学模型来描述抗癌药物的药代动力学、抗肿瘤疗效和药物毒性。该模型与允许的血浆浓度、药物暴露和白细胞减少有关。给定给药时间表,数学模型优化药物剂量,使肿瘤负担最小化,同时在白细胞水平上限制毒性。主要结果是,最佳给药方式是初始高剂量化疗,直至与正常细胞毒性相关的限制饱和,并以中等速率维持持续输注。与依托泊苷调查相关的数据用于可行性研究。结果表明,优化方案的模拟效果优于常规临床方案。基于模型的最佳药物剂量提供了更大的细胞减少,同时限制了不可接受的毒性风险。
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Optimizing Drug Regimens in Cancer Chemotherapy by an Efficacy–Toxicity Mathematical Model

In cancer chemotherapy, it is important to design treatment strategies that ensure a desired rate of tumor cell kill without unacceptable toxicity. To optimize treatment, we used a mathematical model describing the pharmacokinetics of anticancer drugs, antitumor efficacy, and drug toxicity. This model was associated with constraints on the allowed plasma concentrations, drug exposure, and leukopenia. Given a schedule of drug administrations, the mathematical model optimized the drug doses that can minimize the tumor burden while limiting toxicity at the level of the white blood cells. The main result is that the optimal drug administration is an initial high-dose chemotherapy up to saturation of constraints associated with normal cell toxicity and a maintenance continuous infusion at a moderate rate. Data related to etoposide investigations were used in a feasibility study. Simulations with the optimized protocol showed better performances than usual clinical protocols. Model-based optimal drug doses provide for greater cytoreduction, while limiting the risk of unacceptable toxicity.

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