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Optimal design of personalized prostate cancer therapy using Infinitesimal Perturbation Analysis

机译:使用无限扰动分析的个性化前列腺癌治疗的最佳设计

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The standard treatment for advanced prostate cancer is hormone therapy in the form of continuous androgen suppression (CAS), which unfortunately frequently leads to resistance and relapse. An alternative scheme is intermittent androgen suppression (IAS), in which patients are submitted to cycles of treatment (in the form of androgen deprivation) and off-treatment periods in an alternating manner. In spite of extensive recent clinical experience with IAS, the design of ideal protocols for any given patient remains a challenge. The level of prostate specific antigen (PSA) is frequently monitored to determine when patients will be taken off therapy and when therapy will resume. In this work, we propose a threshold-based policy for optimal IAS therapy design that is parameterized by lower and upper PSA threshold values and is associated with a cost metric that combines clinically relevant measures of therapy success. We use a Stochastic Hybrid Automaton (SHA) model of prostate cancer evolution under IAS and perform Infinitesimal Perturbation Analysis (IPA) to adaptively adjust PSA threshold values so as to improve therapy outcomes. We also apply this methodology to clinical data from real patients, and obtain promising results and valuable insights for personalized IAS therapy design. (C) 2016 Elsevier Ltd. All rights reserved.
机译:晚期前列腺癌的标准治疗是一种激素治疗,以连续的雄激素抑制(CAS)的形式,这不幸的是经常导致抗性和复发。替代方案是间歇性雄激素抑制(IAS),其中患者以交替的方式提交治疗循环(以雄激素剥夺的形式)和离处理期。尽管最近有广泛的IAS临床经验,但任何给定的患者的理想协议的设计仍然是一个挑战。经常监测前列腺特异性抗原(PSA)的水平以确定患者是否会何时将被疗法和恢复治疗时。在这项工作中,我们提出了一种基于阈值的策略,用于最佳IAS治疗设计,其通过较低和上部PSA阈值参数化,并且与结合临床相关的治疗措施的成本度量相关联。我们在IAS下使用了随机混合自动机(SHA)前列腺癌演化模型,并进行了无限的扰动分析(IPA)以自适应地调整PSA阈值,以改善治疗结果。我们还将这种方法应用于来自真实患者的临床数据,并获得了对个性化IAS治疗设计的有希望和有价值的见解。 (c)2016 Elsevier Ltd.保留所有权利。

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