A Multi-Center Group to Study Acute Liver Failure in Children

研究儿童急性肝衰竭的多中心小组

• 批准号: 8541812
• 负责人: ROBERT H SQUIRES
• 金额: $ 376.74万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8541812
• 关键词: Acute Liver Failure; Adrenal Cortex Hormones; Benefits and Risks; Biochemical; Biological Markers; Cessation of life; Characteristics; Child; Childhood; Classification; Clinical; Clinical Trials; Clinical Trials Design; Collaborations; Complex; Computer Simulation; Computers; Conduct Clinical Trials; Coupled; Data; Decision Making; Diagnosis; Diagnostic; Disease; Disease Progression; Enrollment; Ensure; Etiology; Event; Foundations; Functional disorder; Genomics; Goals; Heterogeneity; Immune; Immunologic Markers; Immunologics; Infant; Inflammatory; Informatics; Intervention; Knowledge; Liver Regeneration; Medical; Mental Depression; Methodology; Modeling; Monitor; National Institute of Diabetes and Digestive and Kidney Diseases; Natural Killer Cells; Nature; Nervous System Trauma; Neurocognitive; Organ; Organ Donations; Outcome; Patients; Phase II Clinical Trials; Phenotype; Physiological; Policies; Post-Traumatic Stress Disorders; Process; Proteomics; Randomized Controlled Trials; Recovery; Registries; Research; Research Infrastructure; Resources; Risk; Severity of illness; Simulate; Site; Statistical Models; Structure; Systems Biology; Techniques; Testing; Therapeutic; Uncertainty; United States National Institutes of Health; Universities; Variant; Work; analog; base; cohort; complex biological systems; cytokine; data modeling; design; experience; health related quality of life; immunoregulation; improved; liver transplantation; metabolomics; novel; organ allocation; outcome forecast; patient oriented; phase 2 study; prospective; treatment strategy

Our goal is to improve short- and long-term outcomes for pediatric acute liver failure (PALF) through a better understanding of patient phenotypes, reassessment of risk classifications, and associating early events to outcome at one year. We will integrate two research efforts (Vodovotz-3U01 DK- 072146-05S1 and Roberts-1R21DK084201-01) currently collaborating with the PALF Study Group (NIH/NIDDK U01 DK072146-05) which are (1) modeling PALF as a complex biological system using physiological and inflammatory biomarkers and (2) developing models to represent the liver transplant (LT) decisions In PALF. To examine our hypotheses that clinical, biochemical, genomic, proteomic, metabolomic, immunologic, and cytokine analyses in PALF can be used to accurately define phenotypes that respond favorably to directed therapy (e.g., immunomodulation) as well as predict disease progression, including potential for spontaneous recovery or risk of death, all of which will provide a platform on which computer/informatics-based (e.g., in silico) studies can inform the design and conduct of clinical trials, and evaluate the impact of therapeutic decisions, including LT; we propose these Aims: Aim 1: To comprehensively characterize PALF phenotypes utilizing traditional clinical, biochemical, diagnostic, and management profiles supplemented by immune. Inflammatory and liver regeneration markers to identify factors that explain variations in outcomes for PALF phenotypes. Outcomes Include survival, LT, neurocognitive function, health-related quality of life (HRQOL), depression and post-traumatic stress disorder (PTSD) 6 months and 1 year after enrollment. Aim 2: To model the dynamics of PALF within and between distinct phenotypes using serially collected clinical, physiological, and biomarker data. Statistical modeling techniques will be augmented with models used to represent complex biological systems to more accurately reflect the dynamic nature of PALF. The data and models will be utilized to create a computer-based or "in silico" analog of PALF to simulate interventional studies and to assess treatment, including LT decision processes and to estimate the impact of improved decision-making on organ allocation.

我们的目标是通过更好地了解患者表型，重新评估风险分类，并将早期事件与1年时的结局相关联，改善儿科急性肝衰竭（PALF）的短期和长期结局。我们将整合两项研究成果（Vodovotz-3U 01 DK- 072146- 05 S1和Roberts-1 R21 DK 084201 -01）目前与PALF研究组合作（NIH/NIDDK U 01 DK 072146 -05），其（1）使用生理和炎症生物标志物将PALF建模为复杂的生物系统，和（2）开发模型以代表肝移植（LT）。在PALF的决定。为了检验我们的假设，即PALF中的临床、生化、基因组学、蛋白质组学、代谢组学、免疫学和细胞因子分析可用于准确定义对定向治疗有利的表型（例如，免疫调节）以及预测疾病进展，包括自发恢复或死亡风险的可能性，所有这些都将提供一个平台，在该平台上基于计算机/信息学（例如，计算机模拟）研究可以为临床试验的设计和实施提供信息，并评估包括LT在内的治疗决策的影响;我们提出了以下目标：目标1：利用传统的临床、生化、诊断和管理概况，辅以免疫，全面表征PALF表型。炎症和肝再生标志物，以确定解释PALF表型结果变化的因素。结果包括生存率，LT，神经认知功能，健康相关的生活质量（HRQOL），抑郁症和创伤后应激障碍（PTSD）6个月和1年后登记。目的2：使用连续收集的临床、生理和生物标志物数据，对不同表型内和表型之间的PALF动力学进行建模。统计建模技术将被用来表示复杂的生物系统，以更准确地反映PALF的动态性质的模型。这些数据和模型将用于创建基于计算机或“计算机模拟”的PALF模拟物，以模拟干预性研究和评估治疗，包括LT决策过程，并估计改善决策对器官分配的影响。