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Parameter estimation for leukocyte dynamics after chemotherapy

机译:化疗后白细胞动力学的参数估计

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Leukopenia is one of the most harmful side effects during chemotherapy treatment, since leukocytes (L) are crucial in protecting patients against bacteria and fungi. A personalized mathematical model of dynamics of L would allow a glimpse into the future and the initiation of tailored countermeasures. We propose such a mathematical model and calibrate it based on a parameter estimation with real world data. For our study we used data of L during and after consolidation chemotherapy treatment (cytarabine) of six patients contracting acute myeloid leukemia. We compare two different ways to treat the unknown initial values of the system of ordinary differential equations, discuss patient-specificity of parameter values, and different scalings of the least squares formulation. These three comparisons are necessary considerations for all modeling approaches to biomedicine, and have thus a methodological scope beyond the specific case of leukopenia. In summary, we show that our approach is able to simulate L dynamics in response to chemotherapy treatment and allows to take patient-specific characteristics into account.
机译:白细胞减少是化疗治疗期间最有害的副作用之一,因为白细胞(L)对保护针对细菌和真菌的患者至关重要。 L的个性化数学模型L将允许一瞥未来,并对定制对策开始。我们提出了这种数学模型,并根据具有现实世界数据的参数估计来校准它。对于我们的研究,我们在合并化疗处理期间和六个患者的合并化疗治疗(溶质)收缩急性髓性白血病的患者中的数据。我们比较两种不同的方法来处理常微分方程系统的未知初始值,讨论参数值的患者特异性,以及最小二乘法式的不同缩放。这三种比较是生物医学的所有建模方法的必要考虑因素,因此具有超出白细胞减少症特定情况的方法论范围。总之,我们表明我们的方法能够响应化疗处理来模拟L动态,并允许考虑患者特定的特征。

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