Measurement of Individualized Factors Associated with Tinnitus Burden

项目总结/摘要 根据PAR-18-352资助机会公告的指导方针，该项目 提出了一种数据和分析方法，用于耳鸣的可靠和准确的个性化表征。 耳鸣的危害有哪些？耳鸣的危害有哪些？据估计，近15%的 一般公众-超过5000万美国人-经历某种形式的耳鸣。拟定的研究将 评估一种新方法，将基于生态瞬时评估（EMA）的、强烈纵向的联合收割机结合起来 新的数据分析技术。本研究假设耳鸣患者个体的捕获 曲线将允许预测目前令人困惑的治疗反应和 神经影像学发现。这将是一项重复评估的单组纵向研究设计， 参与者将从华盛顿大学招募。预计参与者将完成4个EMA 每天通过智能手机进行调查，持续3周，共进行84次CBT前调查。参与者还将接受 静息状态功能连接MRI（rs-fcMRI）。Tinnut提供了一个 特别适当的条件来说明改进的和可靠的个性化的实用性， 由于神经影像学和治疗结果的异质性，因此无法进行评估。 具体目标是： (1)通过个性化的动态评估和ML获得耳鸣的个人特定驱动因素- DSEM分析。 (2)研究ML-DSEM定义的耳鸣驱动因素与患者对耳鸣的反应之间的关系， 认知行为疗法（CBT） (3)研究ML-DSEM定义的耳鸣驱动因素、治疗反应和 神经成像 建议的研究的成功进行将通过改善耳鸣的研究 患者评估和数据分析技术，这将导致临床试验的更大功效， 将患者护理转向个性化医疗。这种方法广泛适用于健康 条件是异质的，随着时间的推移变化很大。最终，临床医生可以 通过网站或应用程序获取纵向数据，然后提供信息 个性化模型的基础上，在这项研究中所描述的新的分析技术。就这样， 本研究的结果可能是个性化医疗在临床上的真正实现 实践

PROJECT SUMMARY/ABSTRACT In response to the guidelines of the PAR-18-352 Funding Opportunity Announcement, this project is proposing a data and analysis method for the reliable and accurate personalized characterization of tinnitus. Bothersome tinnitus is an enormous source of suffering and disability. It is estimated that nearly 15% of the general public — over 50 million Americans — experience some form of tinnitus. The proposed study will assess a new methodology to combine ecological momentary assessment (EMA)-based, intensely longitudinal data with new analytical techniques. The study hypothesis is that the capture of tinnitus patients’ individual profiles will allow prediction of the currently puzzling heterogeneity of both treatment response and neuroimaging findings. This will be a single arm, longitudinal study design with repeat assessments, and 110 participants will be recruited from Washington University. Participants will be expected to complete 4 EMA surveys via smartphone every day for 3 weeks for a total of 84 pre-CBT surveys. Participants will also undergo resting-state functional connectivity MRI (rs-fcMRI) prior to the start of CBT. Tinnitus offers a particularly appropriate condition to illustrate the utility of improved and reliable personalized assessment because of the heterogeneity in both neuroimaging and treatment findings. The Specific Aims are: (1) To obtain person-specific drivers of tinnitus through personalized ambulatory assessment and ML- DSEM analyses. (2) To examine the relationship between ML-DSEM-defined drivers of tinnitus and patient response to cognitive behavioral therapy (CBT). (3) To examine the association between ML-DSEM-defined drivers of tinnitus, treatment response, and neuroimaging. The successful conduct of the proposed research will advance tinnitus research through improved patient assessment and data analytical techniques, which will result in greater efficacy of clinical trials and move patient care toward personalized medicine. Such an approach is widely applicable to health conditions that are heterogeneous and widely variable over time. Eventually, a clinician could order the acquisition of longitudinal data through a website or app, which would then render an informative personalized model based on the new analytical techniques described in this research. In this way, the end result of this research could be the true realization of personalized medicine in clinical practice.