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

我们的目标是通过更好地了解患者的表型，重新评估风险分类，并将早期事件与一年的结果联系起来，改善儿童急性肝功能衰竭(PALF)的短期和长期结果。我们将整合目前与PALF研究小组(NIH/NIDDK U01DK072146-05)合作的两项研究工作(Vodovotz-3U01DK-072146-05S1和Roberts-1R21DK084201-01)，这两项研究工作是：(1)使用生理和炎症生物标记物将PALF建模为复杂的生物系统；(2)开发模型来代表PALF中的肝脏移植(LT)决策。为了检验我们的假设，即PALF中的临床、生化、基因组、蛋白质、代谢学、免疫学和细胞因子分析可以用于准确定义对定向治疗(例如，免疫调节)有利的表型，以及预测疾病进展，包括自然恢复或死亡风险，所有这些都将提供一个平台，在此平台上，基于计算机/信息学的(例如，在计算机中)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；我们提出这些目标：目标1：利用免疫补充的传统临床、生化、诊断和管理特征来综合表征PALF的表型。炎症和肝再生标记物，以确定解释PALF表型预后差异的因素。结果包括存活率、LT、神经认知功能、健康相关生活质量(HRQOL)、抑郁和创伤后应激障碍(PTSD)。目的2：利用连续收集的临床、生理和生物标记物数据，模拟PALF在不同表型内和不同表型之间的动态。统计建模技术将用来表示复杂生物系统的模型加以补充，以更准确地反映PALF的动态性质。这些数据和模型将被用来创建一个基于计算机或“电子计算机”的PALF模拟，以模拟介入性研究，评估治疗，包括LT决策过程，并估计改进决策对器官分配的影响。

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.