Novel Longitudinal Methods for SMART Studies of Drug Abuse and HIV

药物滥用和艾滋病毒 SMART 研究的新纵向方法

• 批准号: 9130143
• 负责人: Daniel Almirall
• 金额: $ 48.76万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9130143
• 关键词: AIDS prevention; Alcohol or Other Drugs use; Behavior Therapy; Behavioral Sciences; Clinical; Cocaine; Data; Data Analyses; Data Analytics; Decision Making; Development; Drug abuse; Drug usage; Experimental Designs; Future; HIV; HIV risk; Hand; Health; Individual; Intervention; Journals; Lead; Methods; Modeling; Opioid; Outcome; Outcome Measure; Outcome Study; Patients; Peer Review; Pregnant Women; Procedures; Property; Psychological reinforcement; Public Health; Publishing; Reporting; Research; Research Design; Research Personnel; Resources; Risk Behaviors; Sample Size; Sampling; Science; Scientist; Testing; Time; Woman; Work; base; cost; drug use screening; effective intervention; improved; innovation; method development; multilevel analysis; novel; personalized decision; randomized trial; response; therapy design; treatment program; trial design; user friendly software; user-friendly

 DESCRIPTION (provided by applicant): The treatment of drug use and HIV often requires sequential, individualized decision-making concerning the type or delivery of treatment. An adaptive intervention is a treatment design that uses ongoing information from the patient to guide whether, and how to modify the treatment over time. By providing the appropriate treatment to those who need it, when they need it, adaptive interventions hold the promise of improving long-term outcomes for greater numbers of people, thereby increasing the reach and impact of drug use and HIV treatments in real-world settings. The sequential multiple assignment randomized trial (SMART), a major step forward in the science of adaptive interventions, is an experimental design explicitly for identifying and constructing efficacious adaptive interventions. However, in order to make the SMART maximally useful to drug use and HIV intervention scientists, methodological work is needed to expand the options for analyzing data that arise from a SMART, which are limited in important ways. In particular, modern longitudinal data analysis methods that are used by the great majority of studies in today's drug use and HIV research do not accommodate and cannot be used to take advantage of the unique features of a SMART, hence their application can lead to greatly reduced statistical power or even incorrect conclusions. This makes it impossible for investigators using SMARTs to scientifically benefit from the power, elegance, and nuance afforded by longitudinal data. Our objective is to bridge this critical gap by developing and evaluating new multilevel methods for analyzing longitudinal continuous, binary, and zero- inflated drug-use and HIV outcome measures arising from a SMART; developing new sample size calculators for planning SMART studies with longitudinal continuous, binary or zero- inflated outcome measures; applying and illustrating these methods using data from three SMART studies in drug abuse and HIV; and developing free, user-friendly resources to implement these methods. The methods developed in this project will improve clinical and public health outcomes by enabling drug use and HIV scientists to develop more potent adaptive interventions to guide the individualization of drug use and HIV treatments.

 描述（由适用提供）：毒品使用和HIV的治疗通常需要有关治疗类型或提供的顺序，个性化的决策。自适应干预是一种治疗设计，它使用患者的持续信息来指导是否以及如何随着时间的推移修改治疗。通过向需要它的人提供适当的待遇，在需要时，自适应干预措施有望改善更多人的长期结局，从而增加了在现实世界中吸毒和艾滋病毒治疗的影响力和影响。顺序多重分配随机试验（SMART）是适应性干预科学的主要一步，是一种实验性设计，可显式设计，用于识别和构建有效的自适应干预措施。但是，为了使智能对药物使用和艾滋病毒干预科学家最大程度地有用，需要方法学工作来扩展源自智能的分析数据的选项，而这些数据以智能的方式有限。特别是，在当今药物使用和艾滋病毒研究中，绝大多数研究使用的现代纵向数据分析方法不适应，不能用于利用智能的独特特征，因此它们的应用可以大大降低统计能力甚至不正确的结论。这使得使用Smarts的研究人员无法科学地从纵向数据提供的力量，优雅和细微差别中受益。我们的目标是通过开发和评估新的多级方法来分析纵向连续，二进制和零膨胀的药物使用和HIV结果指标来弥合这一关键差距；开发新的样本量计算器，以计划纵向连续，二元或零泄漏的结果指标的智能研究；使用来自药物滥用和艾滋病毒的三项智能研究的数据应用和说明这些方法；并开发免费的，用户友好的资源来实施这些方法。该项目开发的方法将通过促进药物使用和艾滋病毒科学家来开发更多潜在的适应性干预措施来指导吸毒和艾滋病毒治疗的个性化，从而改善临床和公共卫生结果。