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Structural Sensitivity of Control Models Arising in Combined Chemo-Radiotherapy

机译:化疗组合放射治疗中产生的控制模型的结构敏感性

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Simple mathematical models of tumor growth are commonly used to predict efficiency of different therapy protocols and to optimize therapy outcome. Nowadays, the focus is on personalized oncology, in which treatment strategy is tailored to an individual patient. Simple models with minimal number of parameters can be used to find appropriate treatment strategy. The main idea of this study is to describe effects of combined radio-chemotherapy by two control actions. In this work we compare results of different control strategies (treatment protocols) for a family of models of tumor growth. Using simulations in silico we analyse responses of a thousand patients to three possible therapy protocols. Comparing Kaplan-Meier survival curves obtained for two different tumor growth models indicates that while Gompertz model is slightly less sensitive to changes in control action than exponential and logistic models, the difference is negligible. The important finding is that the shapes of survival curves are similar in all cases. It suggests that the family of models is structurally insensitive. Obtained results imply that more attention should be paid on estimation of parameters for a tumor growth model, than on model selection.
机译:肿瘤生长的简单数学模型通常用于预测不同治疗方案的效率并优化治疗结果。如今,重点是个性化肿瘤,其中治疗策略针对个体患者量身定制。具有最小数量参数的简单模型可用于找到适当的治疗策略。本研究的主要思想是通过两个控制作用描述组合无线电化疗的影响。在这项工作中,我们对肿瘤生长模型的家族进行比较不同控制策略(治疗方案)的结果。在硅中使用模拟我们分析了一千名患者的响应到三种可能的治疗方案。比较两种不同肿瘤生长模型获得的Kaplan-Meier存活曲线表明,虽然Gompertz模型对控制动作的变化略微不那么敏感而不是指数和逻辑模型,但差异可以忽略不计。重要的发现是,在所有情况下,生存曲线的形状都是相似的。它表明,模型系列在结构上不敏感。获得的结果意味着应在肿瘤生长模型的参数估计比模型选择的估算中获得更多关注。

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