{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T21:52:38Z","timestamp":1788558758593,"version":"build-2803163510"},"reference-count":37,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T00:00:00Z","timestamp":1768780800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:p>\n                    Accurate prediction of mortality after allogeneic hematopoietic stem cell transplantation (alloHCT) is essential for individualized treatment decisions, yet existing clinical risk scores capture only a limited number of variables and show modest predictive performance. In our single-center retrospective analysis, we included data from 909 adult patients with hematologic malignancies undergoing alloHCT. We used 31 features to build machine-learning models to predict death within the first year after alloHCT. These features included established clinical risk factors together with pre-transplant lymphocyte subsets and inflammatory markers. Among four models, a random forest algorithm showed the best performance (AUC = 0.773) and retained good generalizability in an independent test set (AUC = 0.748). SHapley Additive exPlanations (SHAP)-based interpretation of the machine-learning models showed that age together with five easily measurable pre-transplant immunological and inflammatory parameters influenced the outcome: pre-transplant CD4\n                    <jats:sup>+<\/jats:sup>\n                    , CD8\n                    <jats:sup>+<\/jats:sup>\n                    , and B-lymphocyte counts, albumin, and C-reactive protein (CRP) levels. Based on these features, our random forest approach outperformed established clinical risk scores (HCT-CI, EASIX, rDRI, mGPS) in predicting one-year mortality after alloHCT and more effectively distinguished patients at low and high risk of an adverse outcome. Our study shows that machine-learning-based models can not only predict patient outcomes after alloHCT but also serve as powerful tools for data exploration, confirming the prognostic relevance of pre-transplant inflammation while uncovering the critical role of lymphocyte subsets as previously unknown risk factors. External validation in independent multicenter cohorts will be required to confirm generalizability.\n                  <\/jats:p>","DOI":"10.3389\/fimmu.2025.1745873","type":"journal-article","created":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T05:28:03Z","timestamp":1768800483000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Machine learning-based prediction of one-year mortality after alloHCT identifies the impact of pre-transplant immunity and inflammation"],"prefix":"10.3389","volume":"16","author":[{"given":"Thomas","family":"Meyer","sequence":"first","affiliation":[{"name":"Department of Internal Medicine I, Hematology, Oncology and Stem Cell Transplantation, Medical Center - University of Freiburg, Faculty of Medicine","place":["Freiburg, Germany"]},{"name":"Collaborative Research Institute Intelligent Oncology (CRIION)","place":["Freiburg, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Meyer","sequence":"additional","affiliation":[{"name":"Alcemy GmbH","place":["Berlin, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maren","family":"Hackenberg","sequence":"additional","affiliation":[{"name":"Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg","place":["Freiburg, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniela","family":"Oelke","sequence":"additional","affiliation":[{"name":"Offenburg University of Applied Sciences","place":["Offenburg, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Gengenbach","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine I, Hematology, Oncology and Stem Cell Transplantation, Medical Center - University of Freiburg, Faculty of Medicine","place":["Freiburg, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christoph","family":"Rummelt","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine I, Hematology, Oncology and Stem Cell Transplantation, Medical Center - University of Freiburg, Faculty of Medicine","place":["Freiburg, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hauke","family":"Wilcken","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine I, Hematology, Oncology and Stem Cell Transplantation, Medical Center - University of Freiburg, Faculty of Medicine","place":["Freiburg, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristina","family":"Maas-Bauer","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine I, Hematology, Oncology and Stem Cell Transplantation, Medical Center - University of Freiburg, Faculty of Medicine","place":["Freiburg, Germany"]},{"name":"IMMediate Advanced Clinician Scientist-Program, Department of Medicine II, Medical Center \u2013 University of Freiburg and Faculty of Medicine, University of Freiburg","place":["Freiburg, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ralph","family":"W\u00e4sch","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine I, Hematology, Oncology and Stem Cell Transplantation, Medical Center - University of Freiburg, Faculty of Medicine","place":["Freiburg, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Justus","family":"Duyster","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine I, Hematology, Oncology and Stem Cell Transplantation, Medical Center - University of Freiburg, Faculty of Medicine","place":["Freiburg, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hartmut","family":"Bertz","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine I, Hematology, Oncology and Stem Cell Transplantation, Medical Center - University of Freiburg, Faculty of Medicine","place":["Freiburg, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jes\u00fas","family":"Duque-Afonso","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine I, Hematology, Oncology and Stem Cell Transplantation, Medical Center - University of Freiburg, Faculty of Medicine","place":["Freiburg, Germany"]},{"name":"Collaborative Research Institute Intelligent Oncology (CRIION)","place":["Freiburg, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J\u00fcrgen","family":"Finke","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine I, Hematology, Oncology and Stem Cell Transplantation, Medical Center - 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