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.

Hartwell, M. J., Ozbek, U., Holler, E., Renteria, A. S., Major-Monfried, H., Reddy, P., Aziz, M., Hogan, W. J., Ayuk, F., Efebera, Y. A., Hexner, E. O., Bunworasate, U., Qayed, M., Ordemann, R., Wolfl, M., Mielke, S., Pawarode, A., Chen, Y. -., Devine, S., Harris, A. C., Jagasia, M., Kitko, C. L., Litzow, M. R., Kroger, N., Locatelli, F., Morales, G., Nakamura, R., Reshef, R., Rosler, W., Weber, D., Wudhikarn, K., Yanik, G. A., Levine, J. E., Ferrara, J. L. M., An early-biomarker algorithm predicts lethal graft-versus-host disease and survival, <<JCI INSIGHT>>, 2017; 2 (3): 1-10. [doi:10.1172/JCI.INSIGHT.89798] [https://hdl.handle.net/10807/230024]

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

Locatelli, Franco
Writing – Review & Editing
;
2017

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.
2017
Inglese
Hartwell, M. J., Ozbek, U., Holler, E., Renteria, A. S., Major-Monfried, H., Reddy, P., Aziz, M., Hogan, W. J., Ayuk, F., Efebera, Y. A., Hexner, E. O., Bunworasate, U., Qayed, M., Ordemann, R., Wolfl, M., Mielke, S., Pawarode, A., Chen, Y. -., Devine, S., Harris, A. C., Jagasia, M., Kitko, C. L., Litzow, M. R., Kroger, N., Locatelli, F., Morales, G., Nakamura, R., Reshef, R., Rosler, W., Weber, D., Wudhikarn, K., Yanik, G. A., Levine, J. E., Ferrara, J. L. M., An early-biomarker algorithm predicts lethal graft-versus-host disease and survival, <<JCI INSIGHT>>, 2017; 2 (3): 1-10. [doi:10.1172/JCI.INSIGHT.89798] [https://hdl.handle.net/10807/230024]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/230024
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