Data-driven grading of acute graft-versus-host disease

  • Evren Bayraktar (Shared first author)
  • Theresa Graf (Shared first author)
  • Francis A Ayuk
  • Gernot Beutel
  • Olaf Penack
  • Thomas Luft
  • Nicole Brueder
  • Gastone Castellani
  • H Christian Reinhardt
  • Nicolaus Kröger
  • Dietrich W Beelen
  • Amin T Turki


Despite advances in allogeneic hematopoietic cell transplantation, acute graft-versus-host disease (aGVHD) remains its leading complication, yet with heterogeneous outcomes. Here, we analyzed aGVHD phenotypes and clinical classifications in depth in large, multicenter cohorts involving 3019 patients and addressed prevailing gaps by developing data-driven models. We compared, tested and verified these along with all conventional classifications in independent cohorts and found that data-driven grading outperformed conventional grading in Akaike information criterion and concordance index metrics. Data-driven classifications refined aGVHD assessment with up to 12 severity grades, which were associated with distinct nonrelapse mortality (NRM) and confirmed the key role of intestinal aGVHD. We developed an online calculator for physicians to implement principal component-derived grading (PC1). These results provide substantial insight into the evaluation of aGVHD phenotypes and multiorgan involvement, which relegates the exclusive reporting of overall aGVHD severity grades in transplant registries and clinical trials. Data-driven aGVHD grading provides an expandable platform to refine classification and transplant risk assessment.

Bibliographical data

Original languageEnglish
Publication statusPublished - 28.11.2023

Comment Deanary

© 2023. The Author(s).

PubMed 38017035