Citations 22
MAGIC biomarkers predict long-term outcomes for steroid-resistant acute GVHD
Major-Monfried, Hannah , Renteria, Anne S. , Pawarode, Attaphol , Reddy, Pavan , Ayuk, Francis , Holler, Ernst , Efebera, Yvonne A. , Wölfl, Matthias , Wudhikarn, Kitsada , Ordemann, Rainer, Young, Rachel , Hartwell, Matthew J. , Chaudhry, Mohammed S., Aziz, Mina, Etra, Aaron , Yanik, Gregory A. , Kröger, Nicolaus , Weber, Daniela , Chen, Yi‐Bin , Nakamura, Ryotaro , Rösler, Wolf, Kitko, Carrie L. , Harris, Andrew C. , Kowalyk, Steven, Morales, George , Torres, I.M., Özbek, Umut , Ferrara, James L.M. , Levine, John E. , Kroger, Nicolaus , Kroger, Nicolaus , Levine, John E , Hogan, William J. , Qayed, Muna , Hexner, Elizabeth O. , Shah, Jay Narayan , Pulsipher, Michael A. , Reshef, Ran , Kröger, Nicolaus
Blood | March 15, 2018 | Volume: 131 | Issue: 25 | Pages: 2846-2855
Key Points Biomarker scores generated after 1 week of steroid treatment of GVHD are prognostic. Biomarkers reflect prognosis better than early clinical response to GVHD treatment.
An early-biomarker algorithm predicts lethal graft-versus-host disease and survival
Hartwell, Matthew J. , Özbek, Umut , Holler, Ernst , Renteria, Anne S. , Major-Monfried, Hannah , Reddy, Pavan , Aziz, Mina, Ayuk, Francis , Efebera, Yvonne A. , Bunworasate, Udomsak , Ordemann, Rainer, Wölfl, Matthias , Mielke, Stephan , Pawarode, Attaphol , Chen, Yi‐Bin , Harris, Andrew C. , Jagasia, Madan , Kitko, Carrie L. , Litzow, Mark R. , Morales, George , Nakamura, Ryotaro , Rösler, Wolf, Weber, Daniela , Yanik, Gregory A. , Levine, John E. , Ferrara, James L.M. , Hogan, William J. , Hexner, Elizabeth O. , Qayed, Muna , Mielke, Stephan , Devine, Steven M. , Kröger, Nicolaus , Locatelli, Franco , Reshef, Ran , Wudhikarn, Kitsada , Levine, John E
JCI Insight | February 8, 2017 | Volume: 2 | Issue: 3 | Pages: No page available
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.