The graft-versus-leukemia (GVL) effect after allogeneic hematopoietic cell transplant (HCT) can prevent relapse but the risk of severe graft-vs-host disease (GVHD) leads to prolonged intensive ...immunosuppression and possible blunting of the GVL effect. Strategies to reduce immunosuppression in order to prevent relapse have been offset by increases in severe GVHD and non-relapse mortality (NRM). We recently validated the MAGIC algorithm probability (MAP) that predicts the risk for severe GVHD and NRM in asymptomatic patients using serum biomarkers. In this study we tested whether the MAP could identify patients whose risk for relapse is higher than their risk for severe GVHD and NRM. The multicenter study population (n=1604) was divided into two cohorts: historical (2006–2015, n=702) and current (2015–2017, n=902) with similar non-relapse mortality, relapse, and survival. On day 28 post-HCT, patients who had not developed GVHD (75% of the population) and who possessed a low MAP were at much higher risk for relapse (24%) than severe GVHD and NRM (16% and 9%); this difference was even more pronounced in patients with a high disease risk index (relapse 33%, NRM 9%). Such patients are good candidates to test relapse prevention strategies that might enhance GVL.
Systemic glucocorticoids are the principal treatment for acute graft-versus-host disease (GVHD), which remains the major cause of non-relapse mortality (NRM) after allogeneic hematopoietic cell ...transplantation (HCT). However, there are no validated biomarkers that measure a patient's response to glucocorticoid therapy, and thus response is evaluated by the change in clinical symptom severity. A major weakness in the predictive power of clinical responses is that changes to all organs are weighted equally even though the major driver of NRM is irreversible damage to the crypts of the GI tract. Recent studies from the Mount Sinai Acute GVHD International Consortium (MAGIC) have validated an algorithm probability (MAP) that combines serum concentrations of two biomarkers of GVHD (REG3α and ST2) to generate an estimated probability of 6 month NRM for individual patients. The MAP has been considered a “liquid biopsy” that estimates the damage caused by GVHD to crypts throughout the lower GI tract (Hartwell et al., JCI Insight, 2017; Major-Monfried et al., Blood, 2018). We hypothesized that the change in MAP between start of treatment and 28 days later could serve as a response biomarker for GVHD and might compare favorably to the change in clinical symptoms that measures response to GVHD treatment, which is widely used as a surrogate for long term survival and is the primary endpoint in most GVHD treatment trials (Martin et al., BBMT, 2009; MacMillan et al., Blood, 2010).
We prospectively collected serum samples and clinical staging from 368 sequential HCT patients who received systemic treatment for acute GVHD in one of 20 MAGIC centers between January 2016 and February 2018. We measured the serum concentrations of REG3α and ST2 before and after systemic therapy for acute GVHD and computed MAPs, the changes in MAPs, and clinical responses for each patient.
MAPs of patients who experienced 6 month NRM showed significantly greater increases than MAPs of patients who survived (p=0.0004). In patients whose MAPs at the start of treatment were low (Ann Arbor 1, MAP < 0.141) or intermediate (Ann Arbor 2, 0.141 ≤ MAP ≤ 0.290), 6 month NRM clustered among those who had the greatest increases in MAP after 28 days (Fig 1A,B). In patients with high MAPs at the start of treatment (Ann Arbor 3, MAP > 0.290), those who survived tended to have the largest decreases in MAP (Fig 1C). These changes in MAP suggested crossing a single threshold could predict risk of mortality. We found that patients whose MAPs rose above a threshold MAP of 0.290 (5% of Ann Arbor 1, 27% of Ann Arbor 2) had significantly worse survival compared to those who remained below it, whereas the large number patients with initially high MAPs that remained above the threshold (66% of Ann Arbor 3) had a large increases in mortality (Fig 2).
When measured at day 28, the MAP was significantly more accurate in predicting NRM than the gold standard of the clinical response, with areas under the receiver operating characteristic curve (AUC) of 0.86 and 0.70, respectively (p<0.0001). An algorithm that combined clinical response with biomarkers generated the same AUC as the MAP alone (0.83 v 0.86, p = NS). We next tested whether the same MAP threshold of 0.290 could predict risk within clinical response subsets. A significant minority (10%) of clinical responders had high MAPs and experienced three-fold greater NRM than those with low MAPs (40% v 12%, p<0.0001) whereas the majority (57%) of non-responders had low MAPs and experienced almost three-fold lower NRM than those with high MAPs (24% v 65%, p<0.0001) (Fig 3). Thus the MAP provides important prognostic information over and above the change in clinical symptoms, further stratifying both responders and non-responders at four weeks of treatment. The MAP threshold classified patients both with and without significant lower GI symptoms because the MAP is a more specific measure of irreversible cryptic damage in patients with copious diarrhea and more sensitive in patients with less than 0.5 liters of daily diarrhea (Fig 4).
We conclude that the MAP is, to our knowledge, the first validated laboratory test to serve as response biomarker for the treatment for acute GVHD and a more accurate predictor of survival than clinical response after four weeks of treatment. The MAP may serve as a novel endpoint and an important complement to changes in clinical symptom severity in future trials of GVHD treatment.
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Srinagesh:National Institutes of Health: Research Funding. Ozbek:Viracor: Patents & Royalties: Biomarker Patent. Ayuk:Novartis: Honoraria, Other: Advisory Board, Research Funding. Aziz:Doris Duke Charitable Foundation: Research Funding. Defilipp:Incyte: Research Funding. Grupp:Novartis: Consultancy, Research Funding; Roche: Consultancy; GSK: Consultancy; CBMG: Consultancy; Novartis: Research Funding; Kite: Research Funding; Servier: Research Funding; Jazz: Other: study steering committees or scientific advisory boards; Adaptimmune: Other: study steering committees or scientific advisory boards; Cure Genetics: Consultancy; Humanigen: Consultancy. Hexner:novartis: Research Funding. Kitko:Mallinckrodt: Honoraria; Novartis: Consultancy, Honoraria. Mielke:EBMT/EHA: Other: Travel support; ISCT: Other: Travel support; Miltenyi: Consultancy, Honoraria, Other: Travel and speakers fee (via institution), Speakers Bureau; Jazz Pharma: Honoraria, Other: Travel support, Speakers Bureau; IACH: Other: Travel support; Kiadis Pharma: Consultancy, Honoraria, Other: Travel support (via institution), Speakers Bureau; DGHO: Other: Travel support; Bellicum: Consultancy, Honoraria, Other: Travel (via institution); GILEAD: Consultancy, Honoraria, Other: travel (via institution), Speakers Bureau; Celgene: Honoraria, Other: Travel support (via institution), Speakers Bureau. Merli:Sobi: Consultancy; Amgen: Honoraria; Novartis: Honoraria; Bellicum: Consultancy. Pulsipher:Amgen: Other: Lecture; Miltenyi: Research Funding; Bellicum: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz: Other: Education for employees; CSL Behring: Membership on an entity's Board of Directors or advisory committees; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Medac: Honoraria. Qayed:Bristol-Myers Squibb: Honoraria. Reshef:Pfizer: Consultancy; Magenta: Consultancy; Kite: Consultancy, Research Funding; Atara: Consultancy, Research Funding; BMS: Consultancy; Pharmacyclics: Consultancy, Research Funding; Incyte: Consultancy, Research Funding; Celgene: Research Funding; Shire: Research Funding. Levine:Incyte: Consultancy, Research Funding; Biogen: Other: non-financial support; Viracor: Patents & Royalties: biomarker patent; Ironwood: Honoraria; bluebird bio: Consultancy; National Cancer Institute: Research Funding; Novartis: Honoraria; Kamada: Research Funding. Ferrara:National Institutes of Health: Research Funding; ViraCor: Consultancy; Incyte: Consultancy; Kamada: Consultancy; Mallinckrodt: Consultancy; Enlivex: Consultancy; Xenikos: Consultancy; CSL Behring: Consultancy.
Relapse of malignancy and lethal graft versus host disease (GVHD) are the principal causes of failure of allogeneic hematopoietic cell transplant (HCT). Recently we have shown that at seven days ...after HCT an algorithm using two serum biomarkers (ST2 and REG3α) can predict severe GVHD (Hartwell et al. JCI Insight 2017). We determined whether serial testing (in the first month following HCT) of patients with low probability biomarkers would improve the predictive accuracy of the algorithm and identify patients with different risks of relapse and lethal GVHD. Patients who received an HCT at 18 centers in the Mount Sinai Acute GVHD International Consortium (MAGIC) for hematologic malignancy and who supplied three blood samples were divided into a training set and validation set with equal numbers of lethal GVHD events, which was defined as death from GVHD or infection during treatment for GVHD. Patients in the training set (n=702) underwent HCT from January 1, 2006 until June 30, 2015, whereas patients in the validation set (n=906) underwent HCT from July 1, 2015 to May 1, 2017. Serum samples were analyzed using the previously published algorithm of two biomarkers up to three times (day 7, day 14, day 28 or GVHD onset, if onset occurred within the first 28 days). The algorithm generates a predicted probability of lethal GVHD between 0 and 1 for each patient. Patients were categorized as either low probability (LP) or high probability (HP) for lethal GVHD. HP thresholds of 0.20 and 0.16 were used to classify patients with and without GVHD symptoms, respectively (once categorized as HP, patients remained in that category and were not retested). All results were similar between training and validation sets, and we present here the validation set results.
Serial testing identified 28% of patients as HP with a three-fold greater cumulative incidence of lethal GVHD at one year (13% vs 4%, p<0.001, Figure 1). Relapse rates were the same in both probability groups, and thus LP patients experienced significantly better relapse free survival (RFS) (69% vs 53%, p<0.001). As expected, significantly fewer LP patients experienced severe GVHD at onset (as measured by Minnesota risk), maximum grade III/IV GVHD, or steroid resistant GVHD by day 180 after HCT (Figure 2, p<0.001 for all three parameters). To measure the accuracy of prediction, at each timepoint we calculated the area under the curve (AUC) of receiver operating characteristic curves; the AUC increased significantly with each subsequent evaluation, from 0.59 at one timepoint (dotted line) to 0.74 at the third timepoint (solid line) (p<0.001), with a final sensitivity of 65% and specificity of 74% (Figure 3A).
Early development of GVHD (by day 28) is a risk factor for lethal GVHD. Therefore, we next plotted RFS (dashed line), relapse (solid line), and lethal GVHD (dotted line) rates in patients who developed GVHD by day 28. 25% of patients with GVHD were categorized as HP and had a cumulative incidence of lethal GVHD more than four times higher (28%) than that of relapse (6%); however the risks were reversed for the 75% of patients who were LP, where relapse (15%) occurred twice as often as lethal GVHD (7%) (Figure 3B). In patients who did not develop GVHD in the first month, this reversal of risks was even more dramatic. Approximately half (53%) of the entire validation cohort did not develop GVHD by day 28 and was LP at all three evaluations. These patients had an exceptionally low risk of lethal GVHD and thus they relapsed (25%) much more often than they died from GVHD (3%). When malignancies were classified according to risk for relapse by the disease risk index (DRI) (Figure 3C), the probability of relapse was three fold higher than lethal GVHD in malignancies with a low DRI (12%), six fold higher for intermediate DRI (20%), and eleven fold higher for high/very high DRI (33%).
We conclude that a serial monitoring strategy using GVHD biomarkers for one month after HCT is able to identify two groups of patients with very different risks of lethal GVHD and relapse. For these patients, the intensity of immunosuppression after day 28 could be tailored according to the probabilities of developing lethal GVHD and relapse in the context of clinical trials.
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Aziz:Doris Duke Charitable Foundation: Research Funding. Ayuk:Therakos (Mallinckrodt): Honoraria; Novartis: Honoraria; Celgene: Consultancy; Gilead: Consultancy. Chen:REGiMMUNE: Consultancy; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees; Magenta Therapeutics: Consultancy; Takeda Pharmaceuticals: Consultancy. Merli:Neovii Biotech: Honoraria; AMGEN: Honoraria. Roesler:Sanofi: Other: Travel, Accommodations, Expenses; Amgen: Equity Ownership; Jazz Pharmaceuticals: Other: Travel, Accommodations, Expenses; Immunomedics: Equity Ownership; Biogen: Equity Ownership; Merck: Consultancy; Pfizer: Consultancy. Kitko:Novartis: Consultancy, Honoraria; Mallinckrodt: Honoraria, Other: Travel, Accommodations, Expenses. Qayed:Novartis: Consultancy. Wölfl:Bristol-myers Squibb: Equity Ownership; Novartis: Equity Ownership; Taheda: Equity Ownership; Juno: Equity Ownership; Neovii: Other: Travel, Accommodations, Expenses. Mielke:Celgene: Speakers Bureau; DGHO: Speakers Bureau; EHA: Speakers Bureau; Kiadis Pharma: Speakers Bureau; Miltenyi: Speakers Bureau. Wudhikarn:Takeda Oncology: Other: Travel, Accommodations, Expenses. Nakamura:Celgene: Honoraria; Molmed: Honoraria; Merck: Consultancy; Pharmacyclics: Consultancy; Atara: Consultancy; Jazz Pharmaceuticals: Consultancy. Pulsipher:CSL Behring: Consultancy; Novartis: Consultancy, Honoraria, Speakers Bureau; Adaptive Biotech: Consultancy, Research Funding; Amgen: Honoraria. Reshef:Pfizer: Consultancy; Atara Biotherapeutics: Consultancy; Kite Pharma: Consultancy; Takeda Pharmaceuticals: Consultancy; Bristol-Myers Squibb: Consultancy; Incyte: Consultancy. Levine:Therakos: Consultancy; Novartis: Consultancy; Bluebird: Consultancy; Incyte: Consultancy; Kamada: Research Funding; Viracor: Patents & Royalties. Ferrara:Incyte: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses; Xenikos: Consultancy, Other: Travel, Accommodations, Expenses; Kamada: Consultancy, Research Funding; Viracor: Consultancy, Patents & Royalties.
•Biomarker scores are a feasible eligibility criterion for high-risk GVHD in which the prompt initiation of treatment is a priority.•The combination of natalizumab with corticosteroids was not ...effective in improving outcomes for patients with high-risk GVHD.
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Graft-versus-host disease (GVHD) of the gastrointestinal (GI) tract is the main cause of nonrelapse mortality (NRM) after allogeneic hematopoietic cell transplantation. Ann Arbor (AA) scores derived from serum biomarkers at onset of GVHD quantify GI crypt damage; AA2/3 scores correlate with resistance to treatment and higher NRM. We conducted a multicenter, phase 2 study using natalizumab, a humanized monoclonal antibody that blocks T-cell trafficking to the GI tract through the α4 subunit of α4β7 integrin, combined with corticosteroids as primary treatment for patients with new onset AA2/3 GVHD. Seventy-five patients who were evaluable were enrolled and treated; 81% received natalizumab within 2 days of starting corticosteroids. Therapy was well tolerated with no treatment emergent adverse events in >10% of patients. Outcomes for patients treated with natalizumab plus corticosteroids were compared with 150 well-matched controls from the MAGIC database whose primary treatment was corticosteroids alone. There were no significant differences in overall or complete response between patients treated with natalizumab plus corticosteroids and those treated with corticosteroids alone (60% vs 58%; P = .67% and 48% vs 48%; P = 1.0, respectively) including relevant subgroups. There were also no significant differences in NRM or overall survival at 12 months in patients treated with natalizumab plus corticosteroids compared with controls treated with corticosteroids alone (38% vs 39%; P = .80% and 46% vs 54%; P = .48, respectively). In this multicenter biomarker–based phase 2 study, natalizumab combined with corticosteroids failed to improve outcome of patients with newly diagnosed high-risk GVHD. This trial was registered at www.clinicaltrials.gov as # NCT02133924.
Steroid-refractory (SR) acute graft-versus-host disease (GVHD) remains a major cause of nonrelapse mortality (NRM) after allogeneic hematopoietic cell transplantation (HCT), but its occurrence is not ...accurately predicted by pre-HCT clinical risk factors. The Mount Sinai Acute GVHD International Consortium (MAGIC) algorithm probability (MAP) identifies patients who are at high risk for developing SR GVHD as early as 7 days after HCT based on the extent of intestinal crypt damage as measured by the concentrations of 2 serum biomarkers, suppressor of tumorigenesis 2 and regenerating islet-derived 3α. We conducted a multicenter proof-of-concept “preemptive” treatment trial of α-1-antitrypsin (AAT), a serine protease inhibitor with demonstrated activity against GVHD, in patients at high risk for developing SR GVHD. Patients were eligible if they possessed a high-risk MAP on day 7 after HCT or, if initially low risk, became high risk on repeat testing at day 14. Thirty high-risk patients were treated with twice-weekly infusions of AAT for a total of 16 doses, and their outcomes were compared with 90 high-risk near-contemporaneous MAGIC control patients. AAT treatment was well tolerated with few toxicities, but it did not lower the incidence of SR GVHD compared with controls (20% vs 14%, P = .56). We conclude that real-time biomarker-based risk assignment is feasible early after allogeneic HCT but that this dose and schedule of AAT did not change the incidence of SR acute GVHD. This trial was registered at www.clinicaltrials.gov as #NCT03459040.
•GVHD biomarkers can be used as real-time inclusion criteria to selectively target asymptomatic, high-risk patients for intervention.•Preemptive treatment with αατ did not improve GVHD outcomes.
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•After initial clinical response, flares of acute GVHD are common and associated with higher NRM.•MAGIC biomarkers at first CR/VGPR can predict GVHD flares.
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The absence of a ...standardized definition for graft-versus-host disease (GVHD) flares and data on its clinical course are significant concerns. We retrospectively evaluated 968 patients across 23 Mount Sinai Acute GVHD International Consortium (MAGIC) transplant centers who achieved complete response (CR) or very good partial response (VGPR) within 4 weeks of treatment. The cumulative incidence of flares within 6 months was 22%, and flares were associated with a higher risk of nonrelapse mortality (NRM; adjusted hazard ratio aHR, 4.84; 95% confidence interval CI, 3.19-7.36; P < .001). Flares were more severe (grades 3/4, 41% vs 16%; P < .001) and had more frequent lower gastrointestinal (LGI) involvement (55% vs 32%; P < .001) than the initial GVHD. At CR/VGPR, elevated MAGIC biomarkers predicted the future occurrence of a flare, along with its severity and LGI involvement. In multivariate analyses, higher Ann Arbor (AA) biomarker scores at CR/VGPR were significant risk factors for flares (AA2 vs AA1: aHR, 1.81 95% CI, 1.32-2.48; P = .001; AA3 vs AA1: aHR, 3.14 95% CI, 1.98-4.98; P < .001), as were early response to initial treatment (aHR, 1.84; 95% CI, 1.21-2.80; P = .004) and HLA-mismatched unrelated donor (aHR, 1.74; 95% CI, 1.00-3.02; P = .049). MAGIC biomarkers also stratified the risk of NRM both at CR/VGPR and at the time of flare. We conclude that GVHD flares are common and carry a significant mortality risk. The occurrence of future flares can be predicted by serum biomarkers that may serve to guide adjustment and discontinuation of immunosuppression.
•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.
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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.
•Biomarker scores predicted risk of NRM better than clinical severity at the onset of GVHD treatment in children.•A combined biomarker/clinical model was highly sensitive and specific for NRM in ...children with GVHD.
Acute graft versus host disease (GVHD) is a common and serious complication of allogeneic hematopoietic cell transplantation (HCT) in children but overall clinical grade at onset only modestly predicts response to treatment and survival outcomes. Two tools to assess risk at initiation of treatment were recently developed. The Minnesota risk system stratifies children for risk of nonrelapse mortality (NRM) according to the pattern of GVHD target organ severity. The Mount Sinai Acute GVHD International Consortium (MAGIC) algorithm of 2 serum biomarkers (ST2 and REG3α) predicts NRM in adult patients but has not been validated in a pediatric population. We aimed to develop and validate a system that stratifies children at the onset of GVHD for risk of 6-month NRM. We determined the MAGIC algorithm probabilities (MAPs) and Minnesota risk for a multicenter cohort of 315 pediatric patients who developed GVHD requiring treatment with systemic corticosteroids. MAPs created 3 risk groups with distinct outcomes at the start of treatment and were more accurate than Minnesota risk stratification for prediction of NRM (area under the receiver operating curve (AUC), .79 versus .62, P = .001). A novel model that combined Minnesota risk and biomarker scores created from a training cohort was more accurate than either biomarkers or clinical systems in a validation cohort (AUC .87) and stratified patients into 2 groups with highly different 6-month NRM (5% versus 38%, P < .001). In summary, we validated the MAP as a prognostic biomarker in pediatric patients with GVHD, and a novel risk stratification that combines Minnesota risk and biomarker risk performed best. Biomarker-based risk stratification can be used in clinical trials to develop more tailored approaches for children who require treatment for GVHD.
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Graft-vs-host disease (GVHD) is a major cause of non-relapse mortality (NRM) following allogeneic hematopoietic cell transplant (HCT). Algorithms containing either the GI GVHD biomarker amphiregulin ...(AREG) or a combination of two GI GVHD biomarkers, (ST2+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 serum concentrations of ST2, REG3, and AREG by ELISA at the time of GVHD diagnosis in 715 patients divided by date of transplant into training (2004-2015) and validation (2015-2017) cohorts. The training cohort (n=341) was used to develop algorithms for predicting probability of 12 month NRM that contained all possible combinations of 1-3 biomarkers and a threshold corresponding to the concordance probability was used to stratify patients for risk of NRM. Algorithms were compared to each other based on several metrics including the area under the receiver operating characteristics curve (AUC), 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 AUC (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 post-transplant 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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