Urvi Kapoor

PURPOSE Severe (grade 3-4) acute graft-versus-host disease (AGVHD) is a major cause of death after unrelated-donor (URD) hematopoietic cell transplant (HCT), resulting in particularly high mortality after HLA-mismatched transplantation. There are no approved agents for AGVHD prevention, underscoring the critical unmet need for novel therapeutics. ABA2 was a phase II trial to rigorously assess safety, efficacy, and immunologic effects of adding T-cell costimulation blockade with abatacept to calcineurin inhibitor (CNI)/methotrexate (MTX)-based GVHD prophylaxis, to test whether abatacept could decrease AGVHD. METHODS ABA2 enrolled adults and children with hematologic malignancies under two strata: a randomized, double-blind, placebo-controlled stratum (8/8-HLA-matched URD), comparing CNI/MTX plus abatacept with CNI/MTX plus placebo, and a single-arm stratum (7/8-HLA-mismatched URD) comparing CNI/MTX plus abatacept versus CNI/MTX CIBMTR controls. The primary end point was day +100 grade 3-4 AGVHD, with day +180 severe-AGVHD-free-survival (SGFS) a key secondary end point. Sample sizes were calculated using a higher type-1 error (0.2) as recommended for phase II trials, and were based on predicting that abatacept would reduce grade 3-4 AGVHD from 20% to 10% (8/8s) and 30% to 10% (7/8s). ABA2 enrolled 142 recipients (8/8s, median follow-up = 716 days) and 43 recipients (7/8s, median follow-up = 708 days). RESULTS In 8/8s, grade 3-4 AGVHD was 6.8% (abatacept) versus 14.8% (placebo) ( P = .13, hazard ratio = 0.45). SGFS was 93.2% (CNI/MTX plus abatacept) versus 82% (CNI/MTX plus placebo, P = .05). In the smaller 7/8 cohort, grade 3-4 AGVHD was 2.3% (CNI/MTX plus abatacept, intention-to-treat population), which compared favorably with a nonrandomized matched cohort of CNI/MTX (30.2%, P < .001), and the SGFS was better (97.7% v 58.7%, P < .001). Immunologic analysis revealed control of T-cell activation in abatacept-treated patients. CONCLUSION Adding abatacept to URD HCT was safe, reduced AGVHD, and improved SGFS. These results suggest that abatacept may substantially improve AGVHD-related transplant outcomes, with a particularly beneficial impact on HLA-mismatched HCT.

The Mount Sinai Acute GVHD International Consortium (MAGIC) algorithm probability (MAP), derived from 2 serum biomarkers, measures damage to crypts in the gastrointestinal tract during graft-versus-host disease (GVHD). We hypothesized that changes in MAP after treatment could validate it as a response biomarker. We prospectively collected serum samples and clinical stages of acute GVHD from 615 patients receiving hematopoietic cell transplantation in 20 centers at initiation of first-line systemic treatment and 4 weeks later. We computed MAPs and clinical responses and compared their abilities to predict 6-month nonrelapse mortality (NRM) in the validation cohort (n = 367). After 4 weeks of treatment, MAPs predicted NRM better than the change in clinical symptoms in all patients and identified 2 groups with significantly different NRM in both clinical responders (40% vs 12%, P < .0001) and nonresponders (65% vs 25%, P < .0001). MAPs successfully reclassified patients for NRM risk within every clinical grade of acute GVHD after 4 weeks of treatment. At the beginning of treatment, patients with a low MAP that rose above the threshold of 0.290 after 4 weeks of treatment had a significant increase in NRM, whereas patients with a high MAP at onset that fell below that threshold after treatment had a striking decrease in NRM that translated into clear differences in overall survival. We conclude that a MAP measured before and after treatment of acute GVHD is a response biomarker that predicts long-term outcomes more accurately than change in clinical symptoms. MAPs have the potential to guide therapy for acute GVHD and may function as a useful end point in clinical trials.

The standard primary treatment for acute graft-versus-host disease (GVHD) requires prolonged, high-dose systemic corticosteroids (SCSs) that delay reconstitution of the immune system. We used validated clinical and biomarker staging criteria to identify a group of patients with low-risk (LR) GVHD that is very likely to respond to SCS. We hypothesized that itacitinib, a selective JAK1 inhibitor, would effectively treat LR GVHD without SCS. We treated 70 patients with LR GVHD in a multicenter, phase 2 trial (NCT03846479) with 28 days of itacitinib 200 mg/d (responders could receive a second 28-day cycle), and we compared their outcomes to those of 140 contemporaneous, matched control patients treated with SCSs. More patients responded to itacitinib within 7 days (81% vs 66%, P = .02), and response rates at day 28 were very high for both groups (89% vs 86%, P = .67), with few symptomatic flares (11% vs 12%, P = .88). Fewer itacitinib-treated patients developed a serious infection within 90 days (27% vs 42%, P = .04) due to fewer viral and fungal infections. Grade ≥3 cytopenias were similar between groups except for less severe leukopenia with itacitinib (16% vs 31%, P = .02). No other grade ≥3 adverse events occurred in >10% of itacitinib-treated patients. There were no significant differences between groups at 1 year for nonrelapse mortality (4% vs 11%, P = .21), relapse (18% vs 21%, P = .64), chronic GVHD (28% vs 33%, P = .33), or survival (88% vs 80%, P = .11). Itacitinib monotherapy seems to be a safe and effective alternative to SCS treatment for LR GVHD and deserves further investigation.

A disease risk index (DRI) that was developed for adults with hematologic malignancy who were undergoing hematopoietic cell transplantation is also being used to stratify children and adolescents by disease risk. Therefore, to develop and validate a DRI that can be used to stratify those with AML and ALL by their disease risk, we analyzed 2569 patients aged <18 years with acute myeloid (AML; n = 1224) or lymphoblastic (ALL; n = 1345) leukemia who underwent hematopoietic cell transplantation. Training and validation subsets for each disease were generated randomly with 1:1 assignment to the subsets, and separate prognostic models were derived for each disease. For AML, 4 risk groups were identified based on age, cytogenetic risk, and disease status, including minimal residual disease status at transplantation. The 5-year leukemia-free survival for low (0 points), intermediate (2, 3, 5), high (7, 8), and very high (>8) risk groups was 78%, 53%, 40%, and 25%, respectively (P < .0001). For ALL, 3 risk groups were identified based on age and disease status, including minimal residual disease status at transplantation. The 5-year leukemia-free survival for low (0 points), intermediate (2-4), and high (≥5) risk groups was 68%, 51%, and 33%, respectively (P < .0001). We confirmed that the risk groups could be applied to overall survival, with 5-year survival ranging from 80% to 33% and 73% to 42% for AML and ALL, respectively (P < .0001). This validated pediatric DRI, which includes age and residual disease status, can be used to facilitate prognostication and stratification of children with AML and ALL for allogeneic transplantation.

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 REG3α via enzyme-linked immunosorbent assay. Performances of the 4 strongest algorithms from the training cohort (TNFR1 + TIM3, TNFR1 + ST2, TNFR1 + REG3α, and ST2 + REG3α) 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 + REG3α, 0.73; ST2 + REG3α, 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.