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Data-driven grading of acute graft-versus-host disease
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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684603/ https://www.ncbi.nlm.nih.gov/pubmed/38017035 http://dx.doi.org/10.1038/s41467-023-43372-2 |
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author | Bayraktar, Evren Graf, Theresa Ayuk, Francis A. Beutel, Gernot Penack, Olaf Luft, Thomas Brueder, Nicole Castellani, Gastone Reinhardt, H. Christian Kröger, Nicolaus Beelen, Dietrich W. Turki, Amin T. |
author_facet | Bayraktar, Evren Graf, Theresa Ayuk, Francis A. Beutel, Gernot Penack, Olaf Luft, Thomas Brueder, Nicole Castellani, Gastone Reinhardt, H. Christian Kröger, Nicolaus Beelen, Dietrich W. Turki, Amin T. |
author_sort | Bayraktar, Evren |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10684603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106846032023-11-30 Data-driven grading of acute graft-versus-host disease Bayraktar, Evren Graf, Theresa Ayuk, Francis A. Beutel, Gernot Penack, Olaf Luft, Thomas Brueder, Nicole Castellani, Gastone Reinhardt, H. Christian Kröger, Nicolaus Beelen, Dietrich W. Turki, Amin T. Nat Commun Article 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. Nature Publishing Group UK 2023-11-28 /pmc/articles/PMC10684603/ /pubmed/38017035 http://dx.doi.org/10.1038/s41467-023-43372-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Bayraktar, Evren Graf, Theresa Ayuk, Francis A. Beutel, Gernot Penack, Olaf Luft, Thomas Brueder, Nicole Castellani, Gastone Reinhardt, H. Christian Kröger, Nicolaus Beelen, Dietrich W. Turki, Amin T. Data-driven grading of acute graft-versus-host disease |
title | Data-driven grading of acute graft-versus-host disease |
title_full | Data-driven grading of acute graft-versus-host disease |
title_fullStr | Data-driven grading of acute graft-versus-host disease |
title_full_unstemmed | Data-driven grading of acute graft-versus-host disease |
title_short | Data-driven grading of acute graft-versus-host disease |
title_sort | data-driven grading of acute graft-versus-host disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684603/ https://www.ncbi.nlm.nih.gov/pubmed/38017035 http://dx.doi.org/10.1038/s41467-023-43372-2 |
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