Novel MAGIC composite scores using both clinical symptoms and biomarkers best predict treatment outcomes of acute GVHD.

Acute graft-vs-host disease (GVHD) grading systems that use only clinical symptoms at treatment initiation such as Minnesota risk identify standard and high risk categories but lack a low risk category suitable to minimize immunosuppressive strategies. We developed a new grading system that includes a low risk stratum based on clinical symptoms alone and determined whether the incorporation of biomarkers would improve the model's prognostic accuracy. We randomly divided 1863 patients in the Mount Sinai Acute GVHD International Consortium (MAGIC) who were treated for GVHD into training and validation cohorts. Patients in the training cohort were divided into 14 groups based on similarity of clinical symptoms and similar NRM; we used a classification and regression tree (CART) algorithm to create three Manhattan risk groups that produced a significantly higher area under the receiver operating characteristic curve (AUC) for 6-month NRM than the Minnesota risk classification (0.69 vs. 0.64, P=0.009) in the validation cohort. We integrated serum GVHD biomarker scores with Manhattan risk using patients with available serum samples and again used a CART algorithm to establish three MAGIC composite scores that significantly improved prediction of NRM compared to Manhattan risk (AUC, 0.76 vs. 0.70, P=0.010). Each increase in MAGIC composite score also corresponded to a significant decrease in day 28 treatment response (80% vs. 63% vs. 30%, P<0.001). We conclude that the MAGIC composite score more accurately predicts response to therapy and long term outcomes than systems based on clinical symptoms alone and may help guide clinical decisions and trial design.

The MAGIC algorithm probability predicts treatment response and long-term outcomes to second-line therapy for acute GVHD.

ABSTRACT: The significance of biomarkers in second-line treatment for acute graft-versus-host disease (GVHD) has not been well characterized. We analyzed clinical data and serum samples at the initiation of second-line systemic treatment of acute GVHD from 167 patients from 17 centers of the Mount Sinai Acute GVHD International Consortium (MAGIC) between 2016 and 2021. Sixty-two patients received ruxolitinib-based therapy, whereas 102 received other systemic agents. In agreement with prospective trials, ruxolitinib resulted in a higher day 28 (D28) overall response Frate than nonruxolitinib therapies (55% vs 31%, P = .003) and patients who received ruxolitinib had significantly lower nonrelapse mortality (NRM) than those who received nonruxolitinib therapies (point estimates at 2-year: 35% vs 61%, P = .002). Biomarker analyses demonstrated that the benefit from ruxolitinib was observed only in patients with low MAGIC algorithm probabilities (MAPs) at the start of second-line treatment. Among patients with a low MAP, those who received ruxolitinib experienced significantly lower NRM than those who received nonruxolitinib therapies (point estimates at 2-year: 12% vs 41%, P = .016). However, patients with high MAP experienced high NRM regardless of treatment with ruxolitinib or nonruxolitinib therapies (point estimates at 2-year: 67% vs 80%, P = .65). A landmark analysis demonstrated that the relationship between the D28 response and NRM largely depends on the MAP level at the initiation of second-line therapy. In conclusion, MAP measured at second-line systemic treatment for acute GVHD predicts treatment response and NRM. The outcomes of patients with high MAP are poor regardless of treatment choice, and ruxolitinib appears to primarily benefit patients with low MAP.

Amphiregulin, ST2, and REG3α biomarker risk algorithms as predictors of nonrelapse mortality in patients with acute GVHD.

ABSTRACT: 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.

A Day 14 Endpoint for Acute GVHD Clinical Trials.

The overall response rate (ORR) 28 days after treatment has been adopted as the primary endpoint for clinical trials of acute graft versus host disease (GVHD). However, physicians often need to modify immunosuppression earlier than day (D) 28, and non-relapse mortality (NRM) does not always correlate with ORR at D28. We studied 1144 patients that received systemic treatment for GVHD in the Mount Sinai Acute GVHD International Consortium (MAGIC) and divided them into a training set (n=764) and a validation set (n=380). We used a recursive partitioning algorithm to create a Mount Sinai model that classifies patients into favorable or unfavorable groups that predicted 12 month NRM according to overall GVHD grade at both onset and D14. In the Mount Sinai model grade II GVHD at D14 was unfavorable for grade III/IV GVHD at onset and predicted NRM as well as the D28 standard response model. The MAGIC algorithm probability (MAP) is a validated score that combines the serum concentrations of suppression of tumorigenicity 2 (ST2) and regenerating islet-derived 3-alpha (REG3α) to predict NRM. Inclusion of the D14 MAP biomarker score with the D14 Mount Sinai model created three distinct groups (good, intermediate, poor) with strikingly different NRM (8%, 35%, 76% respectively). This D14 MAGIC model displayed better AUC, sensitivity, positive and negative predictive value, and net benefit in decision curve analysis compared to the D28 standard response model. We conclude that this D14 MAGIC model could be useful in therapeutic decisions and may offer an improved endpoint for clinical trials of acute GVHD treatment.

Flares of acute graft-versus-host disease: a Mount Sinai Acute GVHD International Consortium analysis.

ABSTRACT: 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.