Methods to improve the detection of treatment effects in ARDS clinical trials

改善 ARDS 临床试验中治疗效果检测的方法

基本信息

批准号：
8907567
负责人：
Michael Oscar Harhay
金额：
$ 4.31万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-03-12 至 2017-03-11
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8907567
关键词：
Accounting Active Learning Address Adult Respiratory Distress Syndrome American Caring Cessation of life Clinical Clinical Trials Clinical Trials Design Clinical Trials Network Cognitive Communities Critical Care Data Death Rate Detection Development Doctor of Philosophy Dropout Educational Curriculum Educational workshop Enrollment Environmental air flow Epidemiology Event Faculty Failure Funding Future Goals Grant Health Individual Intensive Care Units Intervention Joints Measures Mechanical ventilation Medical Methods Modeling Morbidity - disease rate National Heart, Lung, and Blood Institute Outcome Outcome Measure Patient Care Patient-Focused Outcomes Patients Physical Function Physicians Population Heterogeneity Postdoctoral Fellow Quality of life Randomized Clinical Trials Recommendation Reporting Research Research Personnel Research Training Risk Sample Size Solutions Statistical Models Students Subgroup Surrogate Endpoint Survivors Techniques Time Training United States Ventilator Work base career career development clinical epidemiology cognitive function comparative follow-up improved individualized medicine innovation insight intervention effect mortality novel patient oriented psychologic simulation statistics successful intervention treatment effect

Accounting Active Learning Address Adult Respiratory Distress Syndrome American Caring Cessation of life Clinical Clinical Trials Clinical Trials Design Clinical Trials Network Cognitive Communities Critical Care Data Death Rate Detection Development Doctor of Philosophy Dropout Educational Curriculum Educational workshop Enrollment Environmental air flow Epidemiology Event Faculty Failure Funding Future Goals Grant Health Individual Intensive Care Units Intervention Joints Measures Mechanical ventilation Medical Methods Modeling Morbidity - disease rate National Heart, Lung, and Blood Institute Outcome Outcome Measure Patient Care Patient-Focused Outcomes Patients Physical Function Physicians Population Heterogeneity Postdoctoral Fellow Quality of life Randomized Clinical Trials Recommendation Reporting Research Research Personnel Research Training Risk Sample Size Solutions Statistical Models Students Subgroup Surrogate Endpoint Survivors Techniques Time Training United States Ventilator Work base career career development clinical epidemiology cognitive function comparative follow-up improved individualized medicine innovation insight intervention effect mortality novel patient oriented psychologic simulation statistics successful intervention treatment effect

展开

项目摘要

DESCRIPTION (provided by applicant): Each year, approximately 140,000 Americans develop acute respiratory distress syndrome (ARDS), and 40% of these patients die. Yet, only 5% of all ARDS randomized clinical trials (RCTs) designed to detect reductions in mortality have been able to identify new, successful interventions. In addition to improving survival, a 2009 NHLBI workshop identified several priorities for future ARDS RCTs, including the development of strategies to enroll fewer patients and a focus on longer-term patient-centered endpoints for ARDS survivors. Although the critical care community has sought to identify interventions' effects on post intensive care unit (ICU) endpoints such as quality of life (QOL) and physical and cognitive functioning, there are several methodological challenges in assessing non-mortal endpoints among ARDS patients. These include missing data resulting from high patient mortality rates (i.e., censoring from death), heterogeneous treatment effects among subsets of ARDS patients, and the lack of validated, early surrogate endpoints for long-term patient-centered outcomes. The overall goal of this research and training plan is to execute three interrelated studies as the subject of a doctoral dissertation in clinical epidemiology that will have immediate relevance in improving the conduct, analysis and application of findings from RCTs for ARDS patients. First, in Aim 1, we will advance an innovative statistical framework for the analysis of short- and long-term non-mortal outcomes that addresses the biases resulting from death-induced missing data. Specifically, we will utilize a joint modeling framework with longitudinal and survival components, resulting in gains in statistical power (potentially reducing the needed sample sizes in RCTs), while offering greater clinical and statistical inference than current methods commonly used in RCTs. Next, in Aim 2, we will generate a multivariable risk score based on patient-level data that can be used to guide more individualized treatment recommendations among heterogeneous ARDS patients, and integrate it into our joint modeling framework. Finally, in Aim 3, we will seek to identify threshold effects of ICU ventilation exposure (e.g., time requiring mechanical ventilation, ventilator-free days) that predict long-term mortality and post-ICU QOL. A rigorous curriculum including didactic and experiential learning in critical care, statistics, and advanced epidemiology will round out the applicant's training, preparing him to be an independent and collaborative faculty investigator and critical care trialis at the completion of his PhD.

描述（由适用提供）：每年，大约有14万美国人患上急性呼吸窘迫综合征（ARDS），其中40％的患者死亡。然而，旨在检测死亡率降低的所有ARDS随机临床试验（RCT）中，只有5％能够识别新的成功干预措施。除了提高生存期外，2009年的NHLBI研讨会还确定了未来ARDS RCT的几个优先事项，包括制定了少数患者的策略，并专注于以长期以患者为中心的ARDS生存的终点。尽管重症监护群社区已经感觉到要确定干预措施对重症监护病房（ICU）终点（例如生活质量（QOL）以及身体和认知功能）的影响，但评估ARDS患者的非年龄终点方面存在一些方法上的挑战。其中包括由于高患者死亡率（即死亡审查），ARDS患者亚群的异质治疗效应以及缺乏经过验证的长期以患者以患者为中心结果的验证的早期替代终点所产生的数据。该研究和培训计划的总体目标是执行三项相互关联的研究，作为临床流行病学博士学位论文的主题，这些研究将在改善ARDS患者的RCT的行为，分析和应用中具有直接相关性。首先，在AIM 1中，我们将推进一个创新的统计框架，以分析短期和长期非质量结果，以解决因死亡引起的丢失数据而产生的偏见。具体而言，我们将利用具有纵向和生存成分的联合建模框架，从而获得统计能力的提高（可能会降低与RCT相比，RCT中所需的样本大小），同时提供的临床和统计推断更大。接下来，在AIM 2中，我们将基于患者级数据产生多变量的风险评分，该数据可用于指导异质ARDS患者中更多个性化的治疗建议，并将其集成到我们的关节建模框架中。最后，在AIM 3中，我们将寻求确定ICU通风暴露的阈值效应（例如，需要机械通气的时间，无通风机的时间），以预测长期的长期死亡率和ICU后QoL。一项严格的课程，包括重症监护，统计和高级流行病学中的教学和经验丰富的学习，将在申请的培训中进行完整的培训，这使他成为一名独立且协作的教师调查员，并在博士学位完成后成为重症监护室。