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  4. A dynamic time‐to‐event model for prediction of acute graft‐versus‐host disease in patients after allogeneic hematopoietic stem cell transplantation
 
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2024
Journal Article
Title

A dynamic time‐to‐event model for prediction of acute graft‐versus‐host disease in patients after allogeneic hematopoietic stem cell transplantation

Abstract
Background:
Acute graft-versus-host disease (aGvHD) is a major cause of death for patients following allogeneic hematopoietic stem cell transplantation (HSCT). Effective management of moderate to severe aGvHD remains challenging despite recent advances in HSCT, emphasizing the importance of prophylaxis and risk factor identification.
Methods:
In this study, we analyzed data from 1479 adults who underwent HSCT between 2005 and 2017 to investigate the effects of aGvHD prophylaxis and time-dependent risk factors on the development of grades II-IV aGvHD within 100 days post-HSCT.
Results:
Using a dynamic longitudinal time-to-event model, we observed a non-monotonic baseline hazard overtime with a low hazard during the first few days and a maximum hazard at day 17, described by Bateman function with a mean transit time of approximately 11 days. Multivariable analysis revealed significant time-dependent effects of white blood cell counts and cyclosporine A exposure as well as static effects of female donors for male recipients, patients with matched related donors, conditioning regimen consisting of fludarabine plus total body irradiation, and patient age in recipients of grafts from related donors on the risk to develop grades II-IV aGvHD. Additionally, we found that higher cumulative hazard on day 7 after allo-HSCT are associated with an increased incidence of grades II-IV aGvHD within 100 days indicating that an individual assessment of the cumulative hazard on day 7 could potentially serve as valuable predictor for later grades II-IV aGvHD development. Using the final model, stochastic simulations were performed to explore covariate effects on the cumulative incidence over time and to estimate risk ratios.
Conclusion:
Overall, the presented model showed good descriptive and predictive performance and provides valuable insights into the interplay of multiple static and time-dependent risk factors for the prediction of aGvHD.
Author(s)
Och, Katharina
Turki, Amin T.
Götz, Katharina M.
Selzer, Dominik
Brossette, Christian
Theobald, Stefan
Braun, Yvonne
Graf, Norbert
Rauch, Jochen
Fraunhofer-Institut für Biomedizinische Technik IBMT  
Rohm, Kerstin
Fraunhofer-Institut für Biomedizinische Technik IBMT  
Weiler, Gabriele
Fraunhofer-Institut für Biomedizinische Technik IBMT  
Schwarz, Ulf
Kiefer, Stephan
Fraunhofer-Institut für Biomedizinische Technik IBMT  
Eisenberg, Lisa
Pfeifer, Nico
Ihle, Matthias
Grandjean, Andrea
Fix, Sonja
Riede, Claudia
Rissland, Jürgen
Smola, Sigrun
Beelen, Dietrich W.
Kaddu-Mulindwa, Dominic
Bittenbring, Jörg
Lehr, Thorsten
Journal
Cancer medicine  
Open Access
DOI
10.1002/cam4.6833
Language
English
Fraunhofer-Institut für Biomedizinische Technik IBMT  
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