Methodology for Adaptive Treatment Strategies

描述(由申请人提供)： 这项申请提出了一个网络，以鼓励和促进合作，这些合作有可能导致开发和评估慢性疾病适应性治疗战略的新方法。这些策略是与临床实践的适应性相对应的个体化治疗方法。例如，在实践中，患有药物滥用、精神疾病和艾滋病毒感染等慢性疾病的患者是按顺序接受治疗的，根据临床医生和患者对持续反应、负担和依从性的评估，决定随着时间的推移修改或改变治疗。 告知和评估适应性治疗策略的数据分析方法和实验数据收集方法都处于初级阶段。从计算机科学家和控制工程师的角度来看，这个问题可以看作是一个多阶段决策问题；然而，参与这些疾病管理的临床医生、从事数据分析和设计工作的统计学家和计算机科学家之间几乎没有交流。来自所有这些领域的投入有可能以确保以最适当的方式查明和解决重大挑战的方式启动方法的发展。这个网络包括计算机科学家、精神病学家、心理学家、工程师和统计学家。我们将撰写一份联合立场文件，确定主要挑战和潜在的解决方案，我们将成立小型合作小组，努力应对这些方法挑战。

DESCRIPTION (provided by applicant): This application proposes a network to stimulate and foster collaborations that have the potential to lead to new methodology for the development and evaluation of adaptive treatment strategies for chronic disorders. These strategies are individually tailored approaches to treatment that correspond to the adaptive nature of clinical practice. For example, in practice, patients suffering from chronic disorders such as substance abuse, mental illness and HIV infection are treated sequentially, where decisions to modify or change treatment over time are made based on the clinician's and patient's evaluation of ongoing response, burden and adherence. Both data analysis methods and experimental data collection methods for informing and evaluating adaptive treatment strategies are in their infancy. This issue can be viewed from the perspective of computer scientists and control engineers as a multi-stage decision problem; however there has been little interchange between clinicians involved in the management of these disorders, statisticians who work in data analysis and design and computer scientists. Input from all of these areas has the potential to jump-start the methodological development in a manner that will ensure that major challenges will be identified and addressed in the most appropriate fashion. This network includes computer scientists, psychiatrists, psychologists, engineers and statisticians. We will write a joint position paper identifying the major challenges and potential solutions and we will form small collaborative groups that will work to address these methodological challenges.