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Amphiregulin, ST2, and REG3α biomarker risk algorithms as predictors of nonrelapse mortality in patients with acute GVHD
•ST2, REG3α, and/or AREG at the time of acute GVHD diagnosis are excellent predictors of risk for 12-month NRM.•The best biomarker algorithm and threshold for risk stratification may depend on the target population. [Display omitted] Graft-versus-host disease (GVHD) is a major cause of nonrelapse mo...
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Published in: | Blood advances 2024-06, Vol.8 (12), p.3284-3292 |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
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Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | •ST2, REG3α, and/or AREG at the time of acute GVHD diagnosis are excellent predictors of risk for 12-month NRM.•The best biomarker algorithm and threshold for risk stratification may depend on the target population.
[Display omitted]
Graft-versus-host disease (GVHD) is a major cause of nonrelapse mortality (NRM) after allogeneic hematopoietic cell transplantation. Algorithms containing either the gastrointestinal (GI) GVHD biomarker amphiregulin (AREG) or a combination of 2 GI GVHD biomarkers (suppressor of tumorigenicity-2 [ST2] + regenerating family member 3 alpha [REG3α]) when measured at GVHD diagnosis are validated predictors of NRM risk but have never been assessed in the same patients using identical statistical methods. We measured the serum concentrations of ST2, REG3α, and AREG by enzyme-linked immunosorbent assay at the time of GVHD diagnosis in 715 patients divided by the date of transplantation into training (2004-2015) and validation (2015-2017) cohorts. The training cohort (n = 341) was used to develop algorithms for predicting the probability of 12-month NRM that contained all possible combinations of 1 to 3 biomarkers and a threshold corresponding to the concordance probability was used to stratify patients for the risk of NRM. Algorithms were compared with each other based on several metrics, including the area under the receiver operating characteristics curve, proportion of patients correctly classified, sensitivity, and specificity using only the validation cohort (n = 374). All algorithms were strong discriminators of 12-month NRM, whether or not patients were systemically treated (n = 321). An algorithm containing only ST2 + REG3α had the highest area under the receiver operating characteristics curve (0.757), correctly classified the most patients (75%), and more accurately risk-stratified those who developed Minnesota standard-risk GVHD and for patients who received posttransplant cyclophosphamide-based prophylaxis. An algorithm containing only AREG more accurately risk-stratified patients with Minnesota high-risk GVHD. Combining ST2, REG3α, and AREG into a single algorithm did not improve performance. |
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ISSN: | 2473-9529 2473-9537 2473-9537 |
DOI: | 10.1182/bloodadvances.2023011049 |