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

• Applicants: Professor Dr. Jan Beyersmann; Privatdozent Dr. Daniel Fürst; Privatdozent Dr. Joannis Mytilineos
• Subject Area: Epidemiology and Medical Biometry/Statistics
• Term: since 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 437606867

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.

• DFG Programme: Research Grants