An early-biomarker algorithm predicts lethal graft-versus-host disease and survival
Standard
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, Jahrgang 2, Nr. 3, 09.02.2017, S. e89798.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
Harvard
APA
Vancouver
Bibtex
}
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 -