癌症最佳疗法中时间估值的影响:慢性骨髓性白血病研究。

Q1 Mathematics
Pedro José Gutiérrez-Diez, Miguel Ángel López-Marcos, Julia Martínez-Rodríguez, Jose Russo
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引用次数: 0

摘要

背景:抗癌最佳疗法的数学设计是当今生物数学和生物医学的一个重要研究领域,因为它与制定针对病人的治疗方案息息相关。然而,迄今为止,癌症优化疗法一直认为恶性程度完全取决于药物浓度和癌细胞数量,而忽视了癌症生长越快,病情越严重,以及早期用药剂量更不利的事实。在此,我们分析了当把治疗癌症的时间演变视为决定恶性程度的额外因素时,最佳疗法会受到怎样的影响,并详细分析了伊马替尼治疗慢性粒细胞白血病的影响:方法:以描述慢性粒细胞白血病动态的数学模型为参考,我们通过修改通常的恶性肿瘤目标函数,设计了一个最佳治疗问题,而不考虑癌症恶性肿瘤的任何时间维度。特别是,我们引入了一个时间估值因子,以捕捉与疾病快速发展和初始药物剂量的持续负面影响相关的恶性程度的增加。在为相关参数赋值后,我们求解并模拟了有无新时间估值因子的模型,比较了药物剂量和疾病演变的结果:结果:我们的计算模拟明确显示,考虑到癌症早期生长和用药相关的恶性程度较高的时间估值因子,可以设计出更有效的疗法。更具体地说,当目标函数中包含时间估值因子时,最佳药物剂量更低,并且不会导致癌细胞数量或病程的医学相关性增加:根据我们的模拟结果以及生物医学证据的有力证明,在设计癌症最佳疗法时,不能忽视影响癌症恶性程度的时间估值因素的存在。事实上,考虑时间估值因素对恶性程度的影响会显著提高最佳疗法的效率,这从生物医学角度看具有重要意义,特别是在设计针对病人的治疗方法时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The effects of time valuation in cancer optimal therapies: a study of chronic myeloid leukemia.

The effects of time valuation in cancer optimal therapies: a study of chronic myeloid leukemia.

The effects of time valuation in cancer optimal therapies: a study of chronic myeloid leukemia.

The effects of time valuation in cancer optimal therapies: a study of chronic myeloid leukemia.

Background: The mathematical design of optimal therapies to fight cancer is an important research field in today's Biomathematics and Biomedicine given its relevance to formulate patient-specific treatments. Until now, however, cancer optimal therapies have considered that malignancy exclusively depends on the drug concentration and the number of cancer cells, ignoring that the faster the cancer grows the worse the cancer is, and that early drug doses are more prejudicial. Here, we analyze how optimal therapies are affected when the time evolution of treated cancer is envisaged as an additional element determining malignancy, analyzing in detail the implications for imatinib-treated Chronic Myeloid Leukemia.

Methods: Taking as reference a mathematical model describing Chronic Myeloid Leukemia dynamics, we design an optimal therapy problem by modifying the usual malignancy objective function, unaware of any temporal dimension of cancer malignance. In particular, we introduce a time valuation factor capturing the increase of malignancy associated to the quick development of the disease and the persistent negative effects of initial drug doses. After assigning values to the parameters involved, we solve and simulate the model with and without the new time valuation factor, comparing the results for the drug doses and the evolution of the disease.

Results: Our computational simulations unequivocally show that the consideration of a time valuation factor capturing the higher malignancy associated with early growth of cancer and drug administration allows more efficient therapies to be designed. More specifically, when this time valuation factor is incorporated into the objective function, the optimal drug doses are lower, and do not involve medically relevant increases in the number of cancer cells or in the disease duration.

Conclusions: In the light of our simulations and as biomedical evidence strongly suggests, the existence of a time valuation factor affecting malignancy in treated cancer cannot be ignored when designing cancer optimal therapies. Indeed, the consideration of a time valuation factor modulating malignancy results in significant gains of efficiency in the optimal therapy with relevant implications from the biomedical perspective, specially when designing patient-specific treatments.

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来源期刊
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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