TY - JOUR
T1 - Assessment of systemic and gastrointestinal tissue damage biomarkers for GVHD risk stratification
AU - Etra, Aaron
AU - Gergoudis, Stephanie
AU - Morales, George
AU - Spyrou, Nikolaos
AU - Shah, Jay
AU - Kowalyk, Steven
AU - Ayuk, Francis
AU - Baez, Janna
AU - Chanswangphuwana, Chantiya
AU - Chen, Yi Bin
AU - Choe, Hannah
AU - DeFilipp, Zachariah
AU - Gandhi, Isha
AU - Hexner, Elizabeth
AU - Hogan, William J.
AU - Holler, Ernst
AU - Kapoor, Urvi
AU - Kitko, Carrie L.
AU - Kraus, Sabrina
AU - Lin, Jung Yi
AU - Al Malki, Monzr
AU - Merli, Pietro
AU - Pawarode, Attaphol
AU - Pulsipher, Michael A.
AU - Qayed, Muna
AU - Reshef, Ran
AU - Rösler, Wolf
AU - Schechter, Tal
AU - Van Hyfte, Grace
AU - Weber, Daniela
AU - Wölfl, Matthias
AU - Young, Rachel
AU - Özbek, Umut
AU - Ferrara, James L.M.
AU - Levine, John E.
N1 - Funding Information:
The authors thank the patients, their families, and the research staff for their participation, as well as Sigrun Gleich for coordinating the MAGIC database in Germany and Gilbert Eng for computer programming and database support. This work was supported by the National Institutes of Health, National Cancer Institute (grant PO1CA03942), the Pediatric Cancer Foundation, and the German Jose Carreras Leukemia Foundation (grants DJCLS 01 GVHD 2016 and DJCLS 01 GVHD 2020).
Funding Information:
This work was supported by the National Institutes of Health, National Cancer Institute (grant PO1CA03942), the Pediatric Cancer Foundation, and the German Jose Carreras Leukemia Foundation (grants DJCLS 01 GVHD 2016 and DJCLS 01 GVHD 2020).
Publisher Copyright:
© 2022 by The American Society of Hematology.
PY - 2022/6/28
Y1 - 2022/6/28
N2 - We used a rigorous PRoBE (prospective-specimen collection, retrospective-blinded-evaluation) study design to compare the ability of biomarkers of systemic inflammation and biomarkers of gastrointestinal (GI) tissue damage to predict response to corticosteroid treatment, the incidence of clinically severe disease, 6-month nonrelapse mortality (NRM), and overall survival in patients with acute graft-versus-host disease (GVHD). We prospectively collected serum samples of newly diagnosed GVHD patients (n = 730) from 19 centers, divided them into training (n = 352) and validation (n = 378) cohorts, and measured TNFR1, TIM3, IL6, ST2, and REG3a via enzyme-linked immunosorbent assay. Performances of the 4 strongest algorithms from the training cohort (TNFR1 + TIM3, TNFR1 + ST2, TNFR1 + REG3a, and ST2 + REG3a) were evaluated in the validation cohort. The algorithm that included only biomarkers of systemic inflammation (TNFR1 + TIM3) had a significantly smaller area under the curve (AUC; 0.57) than the AUCs of algorithms that contained ≥1 GI damage biomarker (TNFR1 + ST2, 0.70; TNFR1 + REG3a, 0.73; ST2 + REG3a, 0.79; all P < .001). All 4 algorithms were able to predict short-term outcomes such as response to systemic corticosteroids and severe GVHD, but the inclusion of a GI damage biomarker was needed to predict long-term outcomes such as 6-month NRM and survival. The algorithm that included 2 GI damage biomarkers was the most accurate of the 4 algorithms for all endpoints.
AB - We used a rigorous PRoBE (prospective-specimen collection, retrospective-blinded-evaluation) study design to compare the ability of biomarkers of systemic inflammation and biomarkers of gastrointestinal (GI) tissue damage to predict response to corticosteroid treatment, the incidence of clinically severe disease, 6-month nonrelapse mortality (NRM), and overall survival in patients with acute graft-versus-host disease (GVHD). We prospectively collected serum samples of newly diagnosed GVHD patients (n = 730) from 19 centers, divided them into training (n = 352) and validation (n = 378) cohorts, and measured TNFR1, TIM3, IL6, ST2, and REG3a via enzyme-linked immunosorbent assay. Performances of the 4 strongest algorithms from the training cohort (TNFR1 + TIM3, TNFR1 + ST2, TNFR1 + REG3a, and ST2 + REG3a) were evaluated in the validation cohort. The algorithm that included only biomarkers of systemic inflammation (TNFR1 + TIM3) had a significantly smaller area under the curve (AUC; 0.57) than the AUCs of algorithms that contained ≥1 GI damage biomarker (TNFR1 + ST2, 0.70; TNFR1 + REG3a, 0.73; ST2 + REG3a, 0.79; all P < .001). All 4 algorithms were able to predict short-term outcomes such as response to systemic corticosteroids and severe GVHD, but the inclusion of a GI damage biomarker was needed to predict long-term outcomes such as 6-month NRM and survival. The algorithm that included 2 GI damage biomarkers was the most accurate of the 4 algorithms for all endpoints.
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U2 - 10.1182/bloodadvances.2022007296
DO - 10.1182/bloodadvances.2022007296
M3 - Article
C2 - 35443021
AN - SCOPUS:85132076333
SN - 2473-9529
VL - 6
SP - 3707
EP - 3715
JO - Blood advances
JF - Blood advances
IS - 12
ER -