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

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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; Hogan, William J; Ayuketang, Francis; Efebera, Yvonne A; Hexner, Elizabeth O; Bunworasate, Udomsak; Qayed, Muna; Ordemann, Rainer; Wölfl, Matthias; Mielke, Stephan; Pawarode, Attaphol; Chen, Yi-Bin; Devine, Steven; Harris, Andrew C; Jagasia, Madan; Kitko, Carrie L; Litzow, Mark R; Kröger, Nicolaus; Locatelli, Franco; Morales, George; Nakamura, Ryotaro; Reshef, Ran; Rösler, Wolf; Weber, Daniela; Wudhikarn, Kitsada; Yanik, Gregory A; Levine, John E; Ferrara, James L M.

In: JCI INSIGHT, Vol. 2, No. 3, 09.02.2017, p. e89798.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Hartwell, MJ, Özbek, U, Holler, E, Renteria, AS, Major-Monfried, H, Reddy, P, Aziz, M, Hogan, WJ, Ayuketang, F, Efebera, YA, Hexner, EO, Bunworasate, U, Qayed, M, Ordemann, R, Wölfl, M, Mielke, S, Pawarode, A, Chen, Y-B, Devine, S, Harris, AC, Jagasia, M, Kitko, CL, Litzow, MR, Kröger, N, Locatelli, F, Morales, G, Nakamura, R, Reshef, R, Rösler, W, Weber, D, Wudhikarn, K, Yanik, GA, Levine, JE & Ferrara, JLM 2017, 'An early-biomarker algorithm predicts lethal graft-versus-host disease and survival', JCI INSIGHT, vol. 2, no. 3, pp. e89798. https://doi.org/10.1172/jci.insight.89798

APA

Hartwell, M. J., Özbek, U., Holler, E., Renteria, A. S., Major-Monfried, H., Reddy, P., Aziz, M., Hogan, W. J., Ayuketang, F., Efebera, Y. A., Hexner, E. O., Bunworasate, U., Qayed, M., Ordemann, R., Wölfl, M., Mielke, S., Pawarode, A., Chen, Y-B., Devine, S., ... Ferrara, J. L. M. (2017). An early-biomarker algorithm predicts lethal graft-versus-host disease and survival. JCI INSIGHT, 2(3), e89798. https://doi.org/10.1172/jci.insight.89798

Vancouver

Hartwell MJ, Özbek U, Holler E, Renteria AS, Major-Monfried H, Reddy P et al. An early-biomarker algorithm predicts lethal graft-versus-host disease and survival. JCI INSIGHT. 2017 Feb 9;2(3):e89798. https://doi.org/10.1172/jci.insight.89798

Bibtex

@article{1d3c6fc9101f46c1811319af5b65b709,
title = "An early-biomarker algorithm predicts lethal graft-versus-host disease and survival",
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.",
keywords = "Journal Article",
author = "Hartwell, {Matthew J} and Umut {\"O}zbek and Ernst Holler and Renteria, {Anne S} and Hannah Major-Monfried and Pavan Reddy and Mina Aziz and Hogan, {William J} and Francis Ayuketang and Efebera, {Yvonne A} and Hexner, {Elizabeth O} and Udomsak Bunworasate and Muna Qayed and Rainer Ordemann and Matthias W{\"o}lfl and Stephan Mielke and Attaphol Pawarode and Yi-Bin Chen and Steven Devine and Harris, {Andrew C} and Madan Jagasia and Kitko, {Carrie L} and Litzow, {Mark R} and Nicolaus Kr{\"o}ger and Franco Locatelli and George Morales and Ryotaro Nakamura and Ran Reshef and Wolf R{\"o}sler and Daniela Weber and Kitsada Wudhikarn and Yanik, {Gregory A} and Levine, {John E} and Ferrara, {James L M}",
year = "2017",
month = feb,
day = "9",
doi = "10.1172/jci.insight.89798",
language = "English",
volume = "2",
pages = "e89798",
journal = "JCI INSIGHT",
issn = "2379-3708",
publisher = "The American Society for Clinical Investigation",
number = "3",

}

RIS

TY - JOUR

T1 - An early-biomarker algorithm predicts lethal graft-versus-host disease and survival

AU - Hartwell, Matthew J

AU - Özbek, Umut

AU - Holler, Ernst

AU - Renteria, Anne S

AU - Major-Monfried, Hannah

AU - Reddy, Pavan

AU - Aziz, Mina

AU - Hogan, William J

AU - Ayuketang, Francis

AU - Efebera, Yvonne A

AU - Hexner, Elizabeth O

AU - Bunworasate, Udomsak

AU - Qayed, Muna

AU - Ordemann, Rainer

AU - Wölfl, Matthias

AU - Mielke, Stephan

AU - Pawarode, Attaphol

AU - Chen, Yi-Bin

AU - Devine, Steven

AU - Harris, Andrew C

AU - Jagasia, Madan

AU - Kitko, Carrie L

AU - Litzow, Mark R

AU - Kröger, Nicolaus

AU - Locatelli, Franco

AU - Morales, George

AU - Nakamura, Ryotaro

AU - Reshef, Ran

AU - Rösler, Wolf

AU - Weber, Daniela

AU - Wudhikarn, Kitsada

AU - Yanik, Gregory A

AU - Levine, John E

AU - Ferrara, James L M

PY - 2017/2/9

Y1 - 2017/2/9

N2 - 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.

AB - 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.

KW - Journal Article

U2 - 10.1172/jci.insight.89798

DO - 10.1172/jci.insight.89798

M3 - SCORING: Journal article

C2 - 28194439

VL - 2

SP - e89798

JO - JCI INSIGHT

JF - JCI INSIGHT

SN - 2379-3708

IS - 3

ER -