Efficacy of an allogeneic transplant and understanding the complex competing risks and multistate structure of aftercare - Analysis of German transplant registry data -

同种异体移植的功效以及了解复杂的竞争风险和善后护理的多态结构 - 德国移植登记数据分析 -

• 批准号: 437606867
• 负责人: Professor Dr. Jan Beyersmann
• 金额: --
• 依托单位: Institut für Transfusionsmedizin
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/437606867?language=en
• 关键词: Efficacy; allogeneic; transplant; understanding; complex

This collaborative work aims to apply and further develop advanced biostatistical methods to data of the German Registry for Stem Cell Transplantation (DRST) with the desire to better understand the efficacy of allogeneic transplants and aftercare. The course of disease and treatment after allogeneic stem cell transplantation is a complex event history that shall be analysed using statistical competing risks and multistate methodology. Particular focus will lie on evaluating time-dependent effects, event-specific prediction and prediction assessment as well as understanding time-dependent effects via intermediate multistate events. One part of this effort is developing an updated EBMT risk score both accounting for specifics of German patients and allowing for more event-specific predictions of competing risks and multistate outcomes. Development of novel statistical methodology will include stabilized multistate inference for small intermediate risk sets.

这项合作旨在将先进的生物统计学方法应用于德国干细胞移植登记处（DRST）的数据，以更好地了解同种异体移植和术后护理的有效性。异基因干细胞移植后的病程和治疗是一个复杂的事件史，应使用统计竞争风险和多状态方法进行分析。特别侧重于评估随时间变化的影响，特定事件的预测和预测评估，以及通过中间多态事件了解随时间变化的影响。这项工作的一部分是开发一个更新的EBMT风险评分，既考虑到德国患者的具体情况，又允许对竞争风险和多状态结局进行更多的事件特异性预测。新的统计方法的发展将包括稳定的多状态推断小的中间风险集。