Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Physician-Scientist Development
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • In-Press Preview
    • Resource and Technical Advances
    • Clinical Research and Public Health
    • Research Letters
    • Editorials
    • Perspectives
    • Physician-Scientist Development
    • Reviews
    • Top read articles

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Resource and Technical Advances
  • Clinical Research and Public Health
  • Research Letters
  • Editorials
  • Perspectives
  • Physician-Scientist Development
  • Reviews
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact

Usage Information

An early-biomarker algorithm predicts lethal graft-versus-host disease and survival
Matthew J. Hartwell, Umut Özbek, Ernst Holler, Anne S. Renteria, Hannah Major-Monfried, Pavan Reddy, Mina Aziz, William J. Hogan, Francis Ayuk, Yvonne A. Efebera, Elizabeth O. Hexner, Udomsak Bunworasate, Muna Qayed, Rainer Ordemann, Matthias Wölfl, Stephan Mielke, Attaphol Pawarode, Yi-Bin Chen, Steven Devine, Andrew C. Harris, Madan Jagasia, Carrie L. Kitko, Mark R. Litzow, Nicolaus Kröger, Franco Locatelli, George Morales, Ryotaro Nakamura, Ran Reshef, Wolf Rösler, Daniela Weber, Kitsada Wudhikarn, Gregory A. Yanik, John E. Levine, James L.M. Ferrara
Matthew J. Hartwell, Umut Özbek, Ernst Holler, Anne S. Renteria, Hannah Major-Monfried, Pavan Reddy, Mina Aziz, William J. Hogan, Francis Ayuk, Yvonne A. Efebera, Elizabeth O. Hexner, Udomsak Bunworasate, Muna Qayed, Rainer Ordemann, Matthias Wölfl, Stephan Mielke, Attaphol Pawarode, Yi-Bin Chen, Steven Devine, Andrew C. Harris, Madan Jagasia, Carrie L. Kitko, Mark R. Litzow, Nicolaus Kröger, Franco Locatelli, George Morales, Ryotaro Nakamura, Ran Reshef, Wolf Rösler, Daniela Weber, Kitsada Wudhikarn, Gregory A. Yanik, John E. Levine, James L.M. Ferrara
View: Text | PDF | Corrigendum
Clinical Research and Public Health Oncology Transplantation

An early-biomarker algorithm predicts lethal graft-versus-host disease and survival

  • Text
  • PDF
Abstract

BACKGROUND. No laboratory test can predict the risk of nonrelapse mortality (NRM) or severe graft-versus-host disease (GVHD) after hematopoietic cellular transplantation (HCT) prior to the onset of GVHD symptoms. METHODS. Patient blood samples on day 7 after HCT were obtained from a multicenter set of 1,287 patients, and 620 samples were assigned to a training set. We measured the concentrations of 4 GVHD biomarkers (ST2, REG3α, TNFR1, and IL-2Rα) and used them to model 6-month NRM using rigorous cross-validation strategies to identify the best algorithm that defined 2 distinct risk groups. We then applied the final algorithm in an independent test set (n = 309) and validation set (n = 358). RESULTS. A 2-biomarker model using ST2 and REG3α concentrations identified patients with a cumulative incidence of 6-month NRM of 28% in the high-risk group and 7% in the low-risk group (P < 0.001). The algorithm performed equally well in the test set (33% vs. 7%, P < 0.001) and the multicenter validation set (26% vs. 10%, P < 0.001). Sixteen percent, 17%, and 20% of patients were at high risk in the training, test, and validation sets, respectively. GVHD-related mortality was greater in high-risk patients (18% vs. 4%, P < 0.001), as was severe gastrointestinal GVHD (17% vs. 8%, P < 0.001). The same algorithm can be successfully adapted to define 3 distinct risk groups at GVHD onset. CONCLUSION. A biomarker algorithm based on a blood sample taken 7 days after HCT can consistently identify a group of patients at high risk for lethal GVHD and NRM. FUNDING. The National Cancer Institute, American Cancer Society, and the Doris Duke Charitable Foundation.

Authors

Matthew J. Hartwell, Umut Özbek, Ernst Holler, Anne S. Renteria, Hannah Major-Monfried, Pavan Reddy, Mina Aziz, William J. Hogan, Francis Ayuk, Yvonne A. Efebera, Elizabeth O. Hexner, Udomsak Bunworasate, Muna Qayed, Rainer Ordemann, Matthias Wölfl, Stephan Mielke, Attaphol Pawarode, Yi-Bin Chen, Steven Devine, Andrew C. Harris, Madan Jagasia, Carrie L. Kitko, Mark R. Litzow, Nicolaus Kröger, Franco Locatelli, George Morales, Ryotaro Nakamura, Ran Reshef, Wolf Rösler, Daniela Weber, Kitsada Wudhikarn, Gregory A. Yanik, John E. Levine, James L.M. Ferrara

×

Usage data is cumulative from May 2025 through May 2026.

Usage JCI PMC
Text version 2,148 315
PDF 288 68
Figure 476 4
Table 96 0
Supplemental data 195 38
Citation downloads 205 0
Totals 3,408 425
Total Views 3,833
(Click and drag on plot area to zoom in. Click legend items above to toggle)

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement

Copyright © 2026 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts