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Abstract Graft-versus-host disease (GVHD), the primary cause of non-relapse mortality (NRM) following allogeneic hematopoietic stem cell transplantation, does not always respond to treatment with high dose systemic corticosteroids. We have recently shown that a combination of three biomarkers (TNFR1, ST2, and REG3α) measured at onset of GVHD can predict day 28 response to treatment and 6-month NRM (Levine, Lancet Haem, 2015). Our goal in the current study was to determine if the same biomarker-based Ann Arbor GVHD algorithm can alsopredict treatment response andmortality whenapplied after one week of systemic corticosteroid treatment. The study population consisted of 378 patients (pts) with acute GVHD from 11 centers in the Mount Sinai Acute GVHD International Consortium. All pts were treated with systemic steroids and provided a plasma or serum sample obtained after one week of treatment (±3 days). The median starting dose of systemic steroids for Grade II-IV GVHD was 2.0 mg/kg/day and for Grade I was 1.0 mg/kg/day, after which treatment varied. Patients were divided into test (n=236) and validation (n=142) cohorts. We applied the Ann Arbor GVHD algorithm to concentrations of TNFR1, ST2, and REG3α measured after one week of treatment to generate a predicted probability of 6-month NRM, which we term the treatment score (TS). We employed unsupervised k-medoidclustering to partition TS values from the test cohort into two groups (high and low). This unbiased approach identified a high score group made up of 25% of pts (n=58) in the test cohort. We observed that the day 28 response rate (complete, CR + partial, PR) was significantly lower in pts with high scores compared to low scores in the test cohort (24% vs 65%, p<0.0001) (Fig 1A). Analysis of the validation cohort using the same TS definitions showed similar differences in response rates (22% vs 61%, p<0.0001) (Fig 1B). Further, nearly four times as many pts with high scores in both cohorts died within 6 months from non-relapse causes compared to pts with low scores (test: 57% vs 17%, p<0.0001; validation: 57% vs 14%, p<0.0001) (Fig 1C/D). As expected, the majority of non-relapse deaths in pts treated for GVHD were directly attributable to GVHD (test: 95%; validation: 89%). Relapse rates for high and low score pts were similar (data not shown), and thus pts with a high TS experienced significantly worse overall survival in both cohorts (test: 37% vs 72%, p<0.0001; validation: 38% vs 79%, p<0.0001) (Fig 1E/F). Approximately half of the pts in each cohort (test: 48%; validation: 44%) responded (CR+PR) to the first week of steroids and these ptshad significantly lower 6-month NRM than non-responders (NR) (test: 17% vs 36%, p=0.0002; validation: 13% vs 36%, p=0.0014). Yet the TS continued to stratify mortality risk independently of clinical response. In the test cohort, pts with a high score comprised 16% of all early responders and experienced more than twice the NRM of early responders with a low score (33% vs 13%, p=0.022) (Fig 2A). Conversely, test cohort pts who did not respond by day 7, but had a low score, fared much better than non-responders with a high score (NRM 21% vs 68%, p<0.0001) (Fig 2B). Two thirds of early non-responders comprised this more favorable group. These highly significant results reproduced in the independent validation cohort in similar proportions (CR+PR: 45% vs 6%, p=0.0003; NR: 61% vs 22%, p=0.0001) (Fig 2C/D). Finally, a subset analysis revealed that pts classified as NR after one week of steroids due to isolated, yet persistent, grade I skin GVHD (24/378, 6%) overwhelmingly had low treatment scores (22/24, 92%) and experienced rates of NRM (9%) comparable to responders with low scores, thus forming a distinct, albeit small, subset of pts with non-responsive GVHD that fares particularly well (Fig 3). In conclusion, a treatment score based on three GVHD biomarkers measured after one week of steroids stratifies pts into two groups with distinct risks for treatment failure and 6-month NRM. It is particularly noteworthy that the TS identifies two subsets of pts with steroid refractory (SR) GVHD who have highly different outcomes (Fig 2B/D). The much larger group, approximately two thirds of all SR pts, may not need the same degree of treatment escalation as is traditional for clinical non-response, and thus overtreatment might be avoided. Because the TSis measured at a common decision making time point, it may prove useful to guide risk-adapted therapy. Disclosures Mielke: Novartis: Consultancy; MSD: Consultancy, Other: Travel grants; Celgene: Other: Travel grants, Speakers Bureau; Gilead: Other: Travel grants; JAZZ Pharma: Speakers Bureau. Kroeger:Novartis: Honoraria, Research Funding. Chen:Incyte Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding. Jagasia:Therakos: Consultancy. Kitko:Therakos: Honoraria, Speakers Bureau. Ferrara:Viracor: Patents & Royalties: GVHD biomarker patent. Levine:Viracor: Patents & Royalties: GVHD biomarker patent.

Abstract Background: Chronic GVHD contributes to morbidity and mortality after allogeneic transplantation. Several phase 2 and 3 open label studies suggested that ATLG (formerly referred to as ATG-F) reduces cGVHD without impacting relapse or survival. This report describes the first prospective randomized double blind phase 3 trial to assess the effect of ATLG (Neovii) when added to tacrolimus / methotrexate prophylaxis on cGVHD free survival. Patients and Methods: This study was conducted at 27 sites in the United States and Australia. 260 patients were randomized (132 placebo, 128 ATLG). 6 patients who were randomized never received ATLG/placebo (4 placebo and 2 ATLG). Data presented include the 128 placebo and 126 ATLG patients who underwent treatment and transplant. Patients were ages 18-65 years with a diagnosis of acute myeloid (AML, 64%) or lymphoblastic (ALL, 21%) leukemia in first or subsequent complete remission or myelodysplastic syndrome (MDS, 15%) with less than 10% marrow blasts. Median age was 48 years (18-65) with 55% males. All patients received 8/8 HLA (A, B, C, DR) allele matched unrelated products (80% mobilized peripheral blood, 20% bone marrow). Myeloablative conditioning was with cyclophosphamide and total body irradiation (Cy/TBI, 27%), busulfan and cyclophosphamide (Bu/Cy, 33%), or busulfan and fludarabine (Bu/Flu, 40%). All patients received tacrolimus starting on Day -1 and standard mtx on days 1, 3, 6, and 11 for GVHD prophylaxis. Patients received ATLG or placebo on Days -3, -2, -1 at an ATLG dose of 20 mg/kg per day (60 mg/kg total). The primary endpoint of the study was moderate/severe chronic GVHD free survival. cGVHD was scored by the investigator and then confirmed or overturned by an independent adjudication committee. Secondary endpoints included engraftment, acute GVHD , moderate/severe cGVHD, non-relapse mortality, GVHD and relapse free survival (GRFS), progression free (PFS) and overall survival (OS). The impact of ATLG on immune reconstitution was assessed in 91 patients. Results: Treatment arms were balanced with respect to age, diagnosis, remission status, cytogenetics, graft source (PB or BM), CMV serostatus and conditioning regimen. Median follow up of survivors was 745 days (61, 1425). Regarding the primary endpoint, there was no difference in 2 year moderate/severe cGVHD free survival between ATLG and placebo (48 vs 44%, p = 0.57), nor was there a difference in GRFS (Table 1). Neutrophil engraftment at Day 30 was less in the ATLG arm (85% vs 95%, p=0.00001). Grade 2 or higher infusion reactions were higher in the ATLG arm (16% vs 2.3%, p=0.0001). Reactivation of CMV was similar (27% vs 31%, p=0.58). The Day 180 cumulative incidence of grades 2-4 acute GVHD was lower in the ATLG arm (23 vs 40%, p = 0.003) as was the 2-year cumulative incidence of moderate/severe cGVHD (12 vs 33%, p = 0.000006). However, both 2-year OS and PFS were lower in ATLG treated patients (58 v 76% and 47 vs 67%, respectively) due in part to a higher incidence of relapse (32 vs 19%, p=0.068). Multivariable models confirmed that ATLG was associated with inferior OS, HR 1.85 (1.1-2.9, p=.0075) and PFS, HR 1.63 (1.1-2.41, p=0.015). We then conducted an unplanned post-hoc analysis and discovered a striking influence of conditioning regimen on outcomes. There were no differences in OS or PFS between ATLG and placebo arms in patients receiving Bu/Cy or Bu/Flu but a dramatic difference in patients receiving Cy/TBI conditioning (OS, 88% vs 48% p =0.006 and PFS, 75 vs 29%, p=0.007 in placebo and ATLG arms, respectively). 91 patients (44 ATLG, 47 placebo) participated in the immune reconstitution study. ATLG treatment was associated with lower CD3, CD4, and CD8 counts at Days 30, 100, and 360, respectively. In turn lower CD3, CD4, and CD8 counts assessed as time dependent variables were all associated with inferior OS and PFS as well as higher NRM (data not shown). Conclusion: In this first ever prospective, randomized, double blind trial of ATLG added to tacrolimus /methotrexate in recipients of matched unrelated donor grafts after myeloablative conditioning, there was no significant difference in 2 year moderate/severe cGVHD free survival or GRFS. ATLG did significantly reduce grades 2-4 acute and moderate/severe chronic GVHD. However, overall survival was higher in the placebo arm, driven mainly by patients who received Cy/TBI conditioning. Further analyses are needed to understand the proper role for ATLG in HCT. Disclosures Soiffer: Juno: Membership on an entity's Board of Directors or advisory committees; Kiadis: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Porter:Genentech: Employment; Novartis: Patents & Royalties, Research Funding. Jagasia:Therakos: Consultancy. Szer:Alnylam: Honoraria, Membership on an entity's Board of Directors or advisory committees; Ra Pharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Alexion Pharmaceuticals, Inc.: Honoraria, Membership on an entity's Board of Directors or advisory committees. Ritz:Kiadis: Membership on an entity's Board of Directors or advisory committees. Glavin:Neovii Biotech: Employment. Chen:Incyte Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding.

Abstract No laboratory test can predict non-relapse mortality (NRM) after hematopoietic cellular transplantation (HCT) prior to the onset graft-versus-host disease (GVHD). Recently, we have shown that a signature of three GVHD plasma biomarkers (TNFR1, ST2, and REG3α) can predict response to GVHD therapy and NRM at the onset of clinical GVHD (Levine, Lancet Haem, 2015). Our goal in the current study was to identify a blood biomarker signature that could predict lethal GVHD and six-month NRM well in advance of the onset of GVHD symptoms. Patient samples on day +7 after HCT were obtained from 1,287 patients from 11 HCT centers in the Mount Sinai Acute GVHD International Consortium (MAGIC). Samples from two large centers (n = 929) were combined and randomly assigned to a training set (n = 620) and test set (n = 309). 358 patients from nine others centers constituted an independent validation set. The overall cumulative incidences of 6-month NRM were 11%, 12%, and 13% for the training, test, and validation sets respectively. The incidence of lethal GVHD, defined as death without preceding relapse while under steroid treatment for acute GVHD, were 18%, 24%, and 14% in the same groups, respectively. The median day of GVHD onset was 28 days in the training set and 29 days in the test and validation sets. We measured four GVHD related biomarkers [ST2, REG3α, TNFR1, and IL2Rα] in all samples and used the training set alone to develop competing risks regression models that used all 13 possible combinations of one to four biomarkers to predict 6-month NRM. The best algorithm, which we rigorously confirmed through Monte Carlo cross-validation of 75 different combinations of training sets, included ST2 and REG3α. No combination of one, three, or four biomarkers was superior to the combination of these two biomarkers. The day 7 algorithm identified high risk (HR) and low risk (LR) groups with 6-month NRMs of 28% and 7%, respectively (p<0.001) (Fig 1A). The relapse rates did not differ between risk groups so that overall survival (OS) was 60% for HR and 84% for LR (p<0.001) (Fig 1B). When applied to the test set (Fig 1C/D), the algorithm identified 54/309 (17%) of the patients as HR with an NRM of 33% vs 7% for LR patients (p<0.001) and 6-month OS of 57% and 81% for HR and LR patients, respectively (p<0.001). In the independent validation set (Fig 1 E/F), the algorithm identified 72/358 (20%) of the patients as HR with an NRM of 26% vs 10% for LR patients (p<0.001) and OS of 68% and 85% for HR and LR patients, respectively (p<0.001). High risk patients were three times more likely to die from GVHD than LR patients in each cohort (p<0.001) (Fig 2). The GI tract is the GVHD target organ that is most resistant to treatment and represents a major cause of NRM, and we observed twice as much severe GI GVHD (stage 3 or 4) in HR patients as in LR patients (p<0.001, data not shown). The algorithm successfully separated HR and LR strata for 6 month NRM in several groups with differing risks for GVHD and NRM, including donor type, degree. of HLA-match, age group, and conditioning regimen intensity (Fig 3). In conclusion, we have developed a blood biomarker algorithm that predicts the development of lethal GVHD seven days after HCT, which performed successfully in large multicenter validation sets. The GVH reaction is already in progress by day +7, even though clinical symptoms may not occur until days or weeks later. We speculate that the blood biomarker concentrations at this early time point reflect subclinical GI pathology, a notion that is reinforced by the fact that ST2 and REG3α, the two biomarkers in the algorithm, are closely associated with GI GVHD. The algorithm identified HR and LR strata in several patient groups with different overall risk for lethal GVHD (donor, HLA match, conditioning regimen intensity, age). This day +7 algorithm should prove useful in clinical BMT research by identifying patients at high risk for lethal GVHD who might benefit from aggressive preemptive treatment strategies. Disclosures Chen: Novartis: Research Funding; Incyte Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Jagasia:Therakos: Consultancy. Kitko:Therakos: Honoraria, Speakers Bureau. Kroeger:Novartis: Honoraria, Research Funding. Levine:Viracor: Patents & Royalties: GVHD biomarkers patent. Ferrara:Viracor: Patents & Royalties: GVHD biomarkers patent.

Abstract Clinical GVHD staging varies between centers and is not agreed upon by independent reviewers (Weisdorf, BBMT 2003). These inconsistencies help explain why promising GVHD treatments from single center studies have not reproduced in multicenter trials. To address this issue, our international GVHD research consortium has developed guidance that has been refined through consensus following case discussions, resulting in uniform and reproducible GVHD clinical symptom reporting. We record all raw target organ symptom data and apply staging based upon this data (Table 1). Only areas of erythema, bullae and desquamation are quantified because other skin changes are not typical of active GVHD rash. Upper GI symptoms must meet thresholds to diagnose GVHD: anorexia with associated weight loss, nausea and/or 2+ vomiting episodes/day lasting 3+ days. For lower GI GVHD we collect stool volumes excluding formed/mostly-formed stools. Unquantified episodes are counted at 200 ml per episode (3 ml/kg for children <50kg) based upon a chart review of 300 patients with post-BMT diarrhea from any cause. Non-GVHD rectal bleeding that results in flecks or streaks of blood in the stool are ignored for staging. We use the highest daily stool output in the 3 days prior to the diagnosis of lower GI GVHD to determine onset stage and, when available, a 3-day average stool volume for subsequent staging to smooth daily variability. We classify biopsy report interpretation into four standardized categories: Positive (unequivocal presence of GVHD), Equivocal (findings suggestive of GVHD, but the pathologist cannot confirm the diagnosis), Non-diagnostic (no abnormalities or subtle findings insufficient to determine etiology), and Non-GVHD etiology (definitive evidence of another diagnosis without concomitant features suggestive of GVHD). We then combine the biopsy interpretation with clinical decision making to assign an overall confidence level to the diagnosis of GVHD in each target organ (Table 2): Confirmed (positive biopsy, regardless of clinician treatment decision), Probable (GVHD diagnosis is sufficiently favored that treatment is given without a positive biopsy), Possible (symptoms present without a positive biopsy; not treated as GVHD), Negative (no symptoms or symptoms are present but a GVHD diagnosis is not entertained and a non-GVHD etiology is identified). Uniform clinical data collection is essential for future GVHD trials and requires application of clear guidance. While still subject to refinement, these guidelines, in use for 2 years by an international research consortium, are designed to be clear, easy to apply, and for clinical trial use. Table 1. GVHD Target Organ Staging Stage Skin (active erythema only) Liver (bilirubin) Upper GI Lower GI (stool output/day) 0 No active (erythematous) GVHD rash < 2 mg/dl No or intermittent nausea, vomiting or anorexia Adult: < 500 ml/day or <3 episodes/day Child: < 10 ml/kg/day or <4 episodes/day 1 Rash < 25% BSA 2-3 mg/dl Persistent nausea, vomiting or anorexia Adult: 500-999 ml/day or 3-4 episodes/day Child: 10 -19.9 ml/kg/day or 4-6 episodes/day 2 Rash 25 - 50% BSA 3.1-6 mg/dl - Adult: 1000-1500 ml/day or 5-7 episodes/day Child: 20 - 30 ml/kg/day or 7-10 episodes/day 3 Rash > 50% BSA 6.1-15 mg/dl - Adult: >1500 ml/day or >7 episodes/day Child: > 30 ml/kg/day or >10 episodes/day 4 Generalized rash (>50% BSA) and bullous formation or desquamation > 5% BSA >15 mg/dl - Severe abdominal pain with or without ileus, or grossly bloody stool (volume independent) Table 2. Confidence Levels Pathologic evidence Clinician assessment Treatment for acute GVHD Comments Confirmed Unequivocal evidence of GVHD GVHD is the etiology for symptoms Not required GVHD is clearly present even if other etiologies co-exist simultaneously Probable Not required (includes equivocal and non-diagnostic biopsies) GVHD most likely etiology for symptoms Yes GVHD is most likely present but other etiologies may also explain the symptoms and there insufficient evidence to make a confirmed diagnosis Possible GVHD in differential diagnosis (but no treatment is being provided) No GVHD may be present, but other etiologies are favored Negative Unequivocal evidence of a diagnosis other than GVHD (e.g., drug rash) GVHD is not considered as an explanation for the symptoms No and the symptoms resolve without GVHD treatment A "negative" biopsy (e.g., normal skin) is not unequivocal evidence of a diagnosis other than GVHD Disclosures Devine: Genzyme: Research Funding. Chen:Bayer: Consultancy, Research Funding. Porter:Novartis: Patents & Royalties, Research Funding. Levine:Novartis: Consultancy.

Abstract Purpose: To develop a prognostic model and cytogenetic risk classification for previously treated patients with chronic lymphocytic leukemia (CLL) undergoing reduced intensity conditioning (RIC) allogeneic hematopoietic cell transplantation (HCT). Experimental Design: We performed a retrospective analysis of outcomes of 606 patients with CLL who underwent RIC allogeneic HCT between 2008 and 2014 reported to the Center for International Blood and Marrow Transplant Research. Results: On the basis of multivariable models, disease status, comorbidity index, lymphocyte count, and white blood cell count at HCT were selected for the development of prognostic model. Using the prognostic score, we stratified patients into low-, intermediate-, high-, and very-high-risk [4-year progression-free survival (PFS) 58%, 42%, 33%, and 25%, respectively, P &lt; 0.0001; 4-year overall survival (OS) 70%, 57%, 54%, and 38%, respectively, P &lt; 0.0001]. We also evaluated karyotypic abnormalities together with del(17p) and found that del(17p) or ≥5 abnormalities showed inferior PFS. Using a multivariable model, we classified cytogenetic risk into low, intermediate, and high (P &lt; 0.0001). When the prognostic score and cytogenetic risk were combined, patients with low prognostic score and low cytogenetic risk had prolonged PFS (61% at 4 years) and OS (75% at 4 years). Conclusions: In this large cohort of patients with previously treated CLL who underwent RIC HCT, we developed a robust prognostic scoring system of HCT outcomes and a novel cytogenetic-based risk stratification system. These prognostic models can be used for counseling patients, comparing data across studies, and providing a benchmark for future interventions. For future study, we will further validate these models for patients receiving targeted therapies prior to HCT.

Key Points Biomarker scores generated after 1 week of steroid treatment of GVHD are prognostic. Biomarkers reflect prognosis better than early clinical response to GVHD treatment.

BACKGROUND. No laboratory test can predict the risk of nonrelapse mortality (NRM) or severe graft-versus-host disease (GVHD) after hematopoietic cellular transplantation (HCT) prior to the onset of GVHD symptoms. METHODS. Patient blood samples on day 7 after HCT were obtained from a multicenter set of 1,287 patients, and 620 samples were assigned to a training set. We measured the concentrations of 4 GVHD biomarkers (ST2, REG3α, TNFR1, and IL-2Rα) and used them to model 6-month NRM using rigorous cross-validation strategies to identify the best algorithm that defined 2 distinct risk groups. We then applied the final algorithm in an independent test set ( n = 309) and validation set ( n = 358). RESULTS. A 2-biomarker model using ST2 and REG3α concentrations identified patients with a cumulative incidence of 6-month NRM of 28% in the high-risk group and 7% in the low-risk group ( P < 0.001). The algorithm performed equally well in the test set (33% vs. 7%, P < 0.001) and the multicenter validation set (26% vs. 10%, P < 0.001). Sixteen percent, 17%, and 20% of patients were at high risk in the training, test, and validation sets, respectively. GVHD-related mortality was greater in high-risk patients (18% vs. 4%, P < 0.001), as was severe gastrointestinal GVHD (17% vs. 8%, P < 0.001). The same algorithm can be successfully adapted to define 3 distinct risk groups at GVHD onset. CONCLUSION. A biomarker algorithm based on a blood sample taken 7 days after HCT can consistently identify a group of patients at high risk for lethal GVHD and NRM. FUNDING. The National Cancer Institute, American Cancer Society, and the Doris Duke Charitable Foundation.

BACKGROUNDPatients with FMS like tyrosine kinase 3 (FLT3)‐mutated acute myeloid leukemia (AML) have a poor prognosis and are referred for early allogeneic hematopoietic stem cell transplantation (HCT).METHODSData from the Center for International Blood and Marrow Transplant Research (CIBMTR) were used to evaluate 511 adult patients with de novo AML who underwent HCT during 2008 through 2011 to determine whether FLT3 mutations had an impact on HCT outcomes.RESULTSIn total, 158 patients (31%) had FLT3 mutations. Univariate and multivariate analyses revealed an increased risk of relapse at 3 years in the FLT3 mutated group compared with the wild‐type (WT) group (38% [95% confidence interval (CI), 30%‐45%] vs 28% [95% CI, 24%‐33%]; P = .04; relative risk, 1.60 [95% CI, 1.15‐2.22]; P = .0048). However, FLT3 mutation status was not significantly associated with nonrelapse mortality, leukemia‐free survival, or overall survival. Although more patients in the FLT3 mutated group died from relapsed primary disease compared with those in the WT group (60% vs 46%), the 3‐year overall survival rate was comparable for the 2 groups (mutated group: 49%; 95% CI, 40%‐57%; WT group: 55%, 95% CI, 50%‐60%; P = .20).CONCLUSIONSThe current data indicate that FLT3 mutation status did not adversely impact overall survival after HCT, and about 50% of patients with this mutation who underwent HCT were long‐term survivors. Cancer 2016;122:3005‐3014. © 2016 American Cancer Society.

Purpose To develop a system prognostic of outcome in those undergoing allogeneic hematopoietic cell transplantation (allo HCT) for myelodysplastic syndrome (MDS). Patients and Methods We examined 2,133 patients with MDS undergoing HLA-matched (n = 1,728) or -mismatched (n = 405) allo HCT from 2000 to 2012. We used a Cox multivariable model to identify factors prognostic of mortality in a training subset (n = 1,151) of the HLA-matched cohort. A weighted score using these factors was assigned to the remaining patients undergoing HLA-matched allo HCT (validation cohort; n = 577) as well as to patients undergoing HLA-mismatched allo HCT. Results Blood blasts greater than 3% (hazard ratio [HR], 1.41; 95% CI, 1.08 to 1.85), platelets 50 × 109/L or less at transplantation (HR, 1.37; 95% CI, 1.18 to 1.61), Karnofsky performance status less than 90% (HR, 1.25; 95% CI, 1.06 to 1.28), comprehensive cytogenetic risk score of poor or very poor (HR, 1.43; 95% CI, 1.14 to 1.80), and age 30 to 49 years (HR, 1.60; 95% CI, 1.09 to 2.35) were associated with increased hazard of death and assigned 1 point in the scoring system. Monosomal karyotype (HR, 2.01; 95% CI, 1.65 to 2.45) and age 50 years or older (HR, 1.93; 95% CI, 1.36 to 2.83) were assigned 2 points. The 3-year overall survival after transplantation in patients with low (0 to 1 points), intermediate (2 to 3), high (4 to 5) and very high (≥ 6) scores was 71% (95% CI, 58% to 85%), 49% (95% CI, 42% to 56%), 41% (95% CI, 31% to 51%), and 25% (95% CI, 4% to 46%), respectively (P < .001). Increasing score was predictive of increased relapse (P < .001) and treatment-related mortality (P < .001) in the HLA-matched set and relapse (P < .001) in the HLA-mismatched cohort. Conclusion The proposed system is prognostic of outcome in patients undergoing HLA-matched and -mismatched allo HCT for MDS.