Optimization of individualized dynamic treatment regimes for recurrent diseases
Optimization of individualized dynamic treatment regimes for recurrent diseases
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DOI：
10.1002/sim.6104
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发表时间：
2014-06-30
影响因子：
2
通讯作者：
Wahed, Abdus S.
中科院分区：
文献类型：
--
作者：
Huang, Xuelin;Ning, Jing;Wahed, Abdus S.
患有癌症或其他复发性疾病的患者可能经历初始治疗、疾病复发和挽救治疗的漫长过程。在这一过程中，优化多阶段治疗顺序，最大限度地延长患者生存期至关重要。比较每个治疗阶段的无病生存率，过度惩罚疾病复发，但不足惩罚治疗相关死亡率。此外，实践中使用的治疗方案是动态的;也就是说，下一次治疗的选择取决于患者对先前治疗的反应。在这篇文章中，使用加速故障时间模型，我们开发了一种方法来优化这种动态处理制度。该方法利用在疾病复发和治疗的多阶段过程中收集的所有纵向数据，并通过最大化他或她的预期总生存率来确定每个患者的最佳动态治疗方案。我们说明了这种方法的应用，从急性髓系白血病的研究，确定不同的患者亚组的最佳治疗策略的数据。版权所有（c）2014约翰威利父子有限公司
Patients with cancer or other recurrent diseases may undergo a long process of initial treatment, disease recurrences, and salvage treatments. It is important to optimize the multi-stage treatment sequence in this process to maximally prolong patients' survival. Comparing disease-free survival for each treatment stage over penalizes disease recurrences but under penalizes treatment-related mortalities. Moreover, treatment regimes used in practice are dynamic; that is, the choice of next treatment depends on a patient's responses to previous therapies. In this article, using accelerated failure time models, we develop a method to optimize such dynamic treatment regimes. This method utilizes all the longitudinal data collected during the multi-stage process of disease recurrences and treatments, and identifies the optimal dynamic treatment regime for each individual patient by maximizing his or her expected overall survival. We illustrate the application of this method using data from a study of acute myeloid leukemia, for which the optimal treatment strategies for different patient subgroups are identified. Copyright (c) 2014 John Wiley & Sons, Ltd.