Etra, Aaron and Gergoudis, Stephanie and Morales, George and Spyrou, Nikolaos and Shah, Jay and Kowalyk, Steven and Ayuk, Francis and Baez, Janna and Chanswangphuwana, Chantiya and Chen, Yi-Bin and Choe, Hannah and DeFilipp, Zachariah and Gandhi, Isha and Hexner, Elizabeth and Hogan, William J. and Holler, Ernst and Kapoor, Urvi and Kitko, Carrie L. and Kraus, Sabrina and Lin, Jung-Yi and Al Malki, Monzr and Merli, Pietro and Pawarode, Attaphol and Pulsipher, Michael A. and Qayed, Muna and Reshef, Ran and Rosler, Wolf and Schechter, Tal and Van Hyfte, Grace and Weber, Daniela and Wolfl, Matthias and Young, Rachel and Ozbek, Umut and Ferrara, James L. M. and Levine, John E. (2022) Assessment of systemic and gastrointestinal tissue damage biomarkers for GVHD risk stratification. BLOOD ADVANCES, 6 (12). pp. 3707-3715. ISSN 2473-9529, 2473-9537
Full text not available from this repository. (Request a copy)Abstract
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 REG3 alpha via enzyme-linked immunosorbent assay. Performances of the 4 strongest algorithms from the training cohort (TNFR1 + TIM3, TNFR1 + ST2, TNFR1 + REG3 alpha, and ST2 + REG3 alpha) 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 + REG3 alpha, 0.73; ST2 + REG3 alpha, 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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | VERSUS-HOST-DISEASE; PLASMA BIOMARKERS; PREDICTIVE-VALUE; OUTCOMES; THERAPY; TRANSPLANTATION; MARKER; BLOOD; TIM-3; SCORE; |
| Subjects: | 600 Technology > 610 Medical sciences Medicine |
| Divisions: | Medicine > Lehrstuhl für Innere Medizin III (Hämatologie und Internistische Onkologie) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 12 Dec 2023 14:23 |
| Last Modified: | 12 Dec 2023 14:23 |
| URI: | https://pred.uni-regensburg.de/id/eprint/58743 |
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