6-month Non-relapse Mortality Research Articles

A Validated Risk Stratification That Incorporates MAGIC Biomarkers Predicts Long-Term Outcomes in Pediatric Patients with Acute 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.

Assessment of systemic and gastrointestinal tissue damage biomarkers for GVHD risk stratification

AbstractWe 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.

Prognostic Value of Elafin in Acute Graft-Versus-Host Disease

Prognostic Value of Elafin in Acute Graft-Versus-Host Disease

Evaluation of Elafin as a Prognostic Biomarker in Acute Graft-versus-Host Disease

Acute graft-versus-host disease (GVHD) is a major cause of mortality in patients undergoing hematopoietic cell transplantation (HCT) for hematologic malignancies. The skin is the most commonly involved organ in GVHD. Elafin, a protease inhibitor overexpressed in inflamed epidermis, was previously identified as a diagnostic biomarker of skin GVHD; however, this finding was restricted to a subset of patients with isolated skin GVHD. The main driver of nonrelapse mortality (NRM) in HCT recipients is gastrointestinal (GI) GVHD. Two biomarkers, Regenerating islet-derived 3a (REG3α) and Suppressor of tumorigenesis 2 (ST2), have been validated as biomarkers of GI GVHD that predict long-term outcomes in patients treated for GVHD. We undertook this study to determine the utility of elafin as a prognostic biomarker in the general population of acute GVHD patients in whom GVHD may develop in multiple organs. We analyzed serum elafin concentrations as a predictive biomarker of acute GVHD outcomes and compared it with ST2 and REG3α in a large group of patients treated at multiple centers. A total of 526 patients from the Mount Sinai Acute GVHD International Consortium (MAGIC) who had received corticosteroid treatment for skin GVHD and who had not been previously studied were analyzed. Serum concentrations of elafin, ST2, and REG3α were measured by ELISA in all patients. The patients were divided at random into equal training and validation sets, and a competing-risk regression model was developed to model 6-month NRM using elafin concentration in the training set. Additional models were developed using concentrations of ST2 and REG3α or the combination of all 3 biomarkers as predictors. Receiver operating characteristic (ROC) curves were constructed using the validation set to evaluate the predictive accuracy of each model and to stratify patients into high- and low-risk biomarker groups. The cumulative incidence of 6-month NRM, overall survival (OS), and 4-week treatment response were compared between the risk groups. Unexpectedly, patients in the low-risk elafin group demonstrated a higher incidence of 6-month NRM, although the difference was not statistically significant (17% versus 11%; P=.19). OS at 6 months (68% versus 68%; P > .99) and 4-week response (78% versus 78%; P=.98) were similar in the low-risk and high-risk elafin groups. The area under the ROC curve (AUC) was 0.55 for elafin and 0.75 for the combination of ST2 and REG3α. The addition of elafin to the other 2 biomarkers did not improve the AUC. Our data indicate that serum elafin concentrations measured at the initiation of systemic treatment for acute GVHD did not predict 6-month NRM, OS, or treatment response in a multicenter population of patients treated systemically for acute GVHD. As seen in previous studies, serum concentrations of the GI GVHD biomarkers ST2 and REG3α were significant predictors of NRM, and the addition of elafin levels did not improve their accuracy. These results underscore the importance of GI disease in driving NRM in patients who develop acute GVHD.

Elevation of Early Plasma Biomarkers in Patients with Clinical Risk Factors Predicts Increased Nonrelapse Mortality after Allogeneic Hematopoietic Stem Cell Transplantation

Early prediction of nonrelapse mortality (NRM) in patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT) based on the results of laboratory tests is challenging. Thus, there is a need to evaluate biomarkers for prediction of NRM, a major problem that offsets the advantages of allo-HSCT. We tested the validity and efficacy of 2 plasma biomarkers, ST2 and Reg3α, based on the Mount Sinai Acute GVHD International Consortium (MAGIC) algorithm, for early prediction of NRM in Japanese patients who underwent allo-HSCT. We conducted a multicenter retrospective study to analyze the clinical data of 112 patients with hematopoietic malignancies who underwent allo-HSCT. Patient blood samples on day 7 after allo-HSCT were obtained from 6 hospitals. The plasma concentrations of ST2 and Reg3α were used to calculate a 6-month NRM risk score. Based on the scores determined in this study, we identified 64 low-risk patients and 48 high-risk patients for the 6-month NRM. The cumulative incidence of 6-month NRM was 29.2% in the high-risk group and 10.9% in the low-risk group (P < .05). The cumulative incidence of relapse mortality was similar in the high-risk and low-risk patients. The biomarker score was predictive in patients with an unrelated donor, an HLA-mismatched donor, high/very high Disease Risk Index, and Hematopoietic Cell Transplantation Comorbidity Index ≥1. Multivariate analysis identified high biomarker probability as a significant predictor of NRM. The MAGIC algorithm based on blood samples obtained at 7 days after allo-HSCT can identify individuals at high risk for NRM among patients with clinical risk factors for NRM in a Japanese cohort.

303 - Effect of Remestemcel-L Treatment in Pediatric Steroid Refractory Acute Graft-Versus-Host Disease: A Biomarker Substudy

Introduction: Steroid-refractory acute graft-versus-host dose disease (SR-aGVHD) is a common, potentially fatal complication of hematopoietic stem cell transplantation (HSCT) with no approved therapies for use in children Methods: Whole blood samples for biomarker analyses were collected at baseline, and days 28, 100, 160 and 180. Circulating levels of NK cells, T and B lymphocytes and of activated T cells (CD25+, HLA-DR+), key effectors of aGVHD development and progression, were measured by multicolor flow cytometry. Plasma levels of regenerating islet-derived protein 3α (REG3α) were measured using a multiplexed immunoassay; soluble suppression of tumorigenicity 2 (ST2) levels were measured by ELISA. REG3α and ST2 were used to derive the MAGIC algorithm probability (MAP) score at each time point as an index of gastrointestinal disease burden and risk of 6-month non-relapse mortality (NRM), with a threshold probability of 0.291 cut-off for GVHD low and high risk of NRM. Least-Squares Means (LSM) were calculated for longitudinal biomarker analyses using the restricted maximum likelihood (REML) approach followed by post-hoc pairwise comparisons between days using the Tukey-Kramer HSD significance test. These analyses were exploratory, so no adjustment was made for multiplicity. Results: Biomarker data were collected in 40 subjects. At baseline, the mean age was 8.5 years, aGVHD severity by IBMTR grade C or D, median MAP was 0.369, with a MAP ≥ 0.291 in 60% of subjects, reflecting active gastrointestinal inflammation and high risk for 6-month NRM. In this biomarker cohort day 28 (N=40) overall response was 70% and survival was 78% and 70% through day 100 and 180, respectively. Baseline biomarker profile was consistent with an inflammatory state characteristic of SR-aGVHD, with elevated plasma levels of Reg3α, ST2 and frequencies of activated CD4+ and CD8+ T cells. MAP decreased from ≥0.291 to Conclusions: Clinically meaningful overall response and survival with remestemcel-L-treatment in pediatric SR-aGVHD are associated with changes in soluble and cellular biomarkers consistent with reduced inflammation and risk of mortality. These observed changes in biomarkers provide mechanistic evidence of immunomodulation. Download : Download high-res image (411KB) Download : Download full-size image Disclosures See: Mesoblast, Inc,: Current Employment. Segal: Mesoblast, Inc,: Current Employment. Simmons: Mesoblast, LTD: Current Employment. Kurtzberg: Mesoblast, Inc,: Consultancy, Honoraria.

Effect of Remestemcel-L Treatment in Pediatric Steroid Refractory Acute Graft-Versus-Host Disease: A Biomarker Substudy

Introduction: Steroid-refractory acute graft-versus-host dose disease (SR-aGVHD) is a common, potentially fatal complication of hematopoietic stem cell transplantation (HSCT) with no approved therapies for use in children &amp;lt; 12 years old with SR-aGVHD. We recently reported the results from a phase 3 pivotal single arm study of remestemcel-L, human, culture-expanded, allogeneic mesenchymal stromal cells as first line therapy after failure to respond to steroids (NCT02336230). Subjects (n=54) received 8 intravenous infusions of remestemcel-L (2 x 106 cells/kg) twice weekly for 4 weeks. The primary endpoint, overall response at day 28 was achieved in 38/54 (70%) of patients and 40/54 (74%) survived through day 100. To explore further the biologic, mechanistic basis for effects of remestemcel-L in SR-aGVHD, we assessed a panel of soluble and cellular biomarkers in a subset of subjects (N=40) who participated in an elective biomarker substudy. The aim of the biomarker substudy was to explore the effect of remestemcel-L treatment on biomarkers involved in disease processes in aGVHD and which have established prognostic and/or predictive value in aGVHD Methods: Whole blood samples for biomarker analyses were collected at baseline, and days 28, 100, 160 and 180. Circulating levels of NK cells, T and B lymphocytes and of activated T cells (CD25+, HLA-DR+), key effectors of aGVHD development and progression, were measured by multicolor flow cytometry. Plasma levels of regenerating islet-derived protein 3α (REG3α) were measured using a multiplexed immunoassay; soluble suppression of tumorigenicity 2 (ST2) levels were measured by ELISA. REG3α and ST2 were used to derive the MAGIC algorithm probability (MAP) score at each time point as an index of gastrointestinal disease burden and risk of 6-month non-relapse mortality (NRM), with a threshold probability of 0.291 cut-off for GVHD low and high risk of NRM. Least-Squares Means (LSM) were calculated for longitudinal biomarker analyses using the restricted maximum likelihood (REML) approach followed by post-hoc pairwise comparisons between days using the Tukey-Kramer HSD significance test. These analyses were exploratory, so no adjustment was made for multiplicity. Results: Biomarker data were collected in 40 subjects. At baseline, the mean age was 8.5 years, aGVHD severity by IBMTR grade C or D, median MAP was 0.369, with a MAP ≥ 0.291 in 60% of subjects, reflecting active gastrointestinal inflammation and high risk for 6-month NRM. In this biomarker cohort day 28 (N=40) overall response was 70% and survival was 78% and 70% through day 100 and 180, respectively. Baseline biomarker profile was consistent with an inflammatory state characteristic of SR-aGVHD, with elevated plasma levels of Reg3α, ST2 and frequencies of activated CD4+ and CD8+ T cells. MAP decreased from ≥0.291 to &amp;lt;0.291 by day 100 with further reductions through day 180, P&amp;lt;0.0001; baseline MAP = 0.36, 95% CI [0.30, 0.41] vs day 100 = 0.26, 95% CI [0.20-0.32], P=0.0037; baseline MAP vs day 180 = 0.20, 95% CI [0.14, 0.26], P&amp;lt;0.0001). These changes in MAP were attributable to significant reductions in ST2 levels. Levels of activated T cells declined over the course of the study (CD3+CD4+CD25+HLA-DR+ (%), F(4, 83.8) = 6.84, P&amp;lt;0.0001; CD3+CD8+ HLA-DR+ (%), F(4, 72.65) = 8.00, P&amp;lt;0.0001) The frequency of CD3+CD4+CD25+HLA-DR+ T cells significantly decreased from baseline (26.57%, 95% CI [22.02, 31.06]) to day 28 (17.70%, 95% CI [13.40-22.00], P=0.0084), plateaued through day 100 and remained significantly below baseline at day 180 (12.74%, 95% CI [7.29-18.19], P=0.0004 vs baseline). The percentage of CD3+CD8+HLA-DR+ T cells significantly decreased from baseline (67.81%, 95% CI [60.21, 75.42]) to day 100 (54.14%, 95% CI [45.99, 62.29], P=0.0075) and decreased further by day 180 (47.10%, 95% CI [38.49, 55.72], P=0.0001 vs baseline). In contrast, levels of T, B and NK cells generally increased over time suggesting no long-term impairment of hematopoietic reconstitution following remestemcel-L treatment. Conclusions: Clinically meaningful overall response and survival with remestemcel-L-treatment in pediatric SR-aGVHD are associated with changes in soluble and cellular biomarkers consistent with reduced inflammation and risk of mortality. These observed changes in biomarkers provide mechanistic evidence of immunomodulation. Disclosures See: Mesoblast, Inc,: Current Employment. Segal:Mesoblast, Inc,: Current Employment. Simmons:Mesoblast, LTD: Current Employment. Kurtzberg:Mesoblast, Inc,: Consultancy, Honoraria.

ATIR101 administered after T-cell-depleted haploidentical HSCT reduces NRM and improves overall survival in acute leukemia

Overcoming graft-versus-host disease (GvHD) without increasing relapse and severe infections is a major challenge after allogeneic hematopoietic stem-cell transplantation (HSCT). ATIR101 is a haploidentical, naïve cell-enriched T-cell product, depleted of recipient-alloreactive T cells to minimize the risk of GvHD and provide graft-versus-infection and -leukemia activity. Safety and efficacy of ATIR101 administered after T-cell-depleted haploidentical HSCT (TCD-haplo + ATIR101) without posttransplant immunosuppressors were evaluated in a Phase 2, multicenter study of 23 patients with acute leukemia and compared with an observational cohort undergoing TCD-haplo alone (n = 35), matched unrelated donor (MUD; n = 64), mismatched unrelated donor (MMUD; n = 37), and umbilical cord blood (UCB; n = 22) HSCT. The primary endpoint, 6-month non-relapse mortality (NRM), was 13% with TCD-haplo + ATIR101. One year post HSCT, TCD-haplo + ATIR101 resulted in lower NRM versus TCD-haplo alone (P = 0.008). GvHD-free, relapse-free survival (GRFS) was higher with TCD-haplo + ATIR101 versus MMUD and UCB (both P < 0.03; 1-year rates: 56.5%, 27.0%, and 22.7%, respectively) and was not statistically different from MUD (1 year: 40.6%). ATIR101 grafts with high third-party reactivity were associated with fewer clinically relevant viral infections. Results suggest that haploidentical, selective donor-cell depletion may eliminate requirements for posttransplant immunosuppressors without increasing GvHD risk, with similar GRFS to MUD. Following these results, a randomized Phase 3 trial versus posttransplant cyclophosphamide had been initiated.

The MAGIC algorithm probability is a validated response biomarker of treatment of acute graft-versus-host disease

AbstractThe 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.

Plasma Biomarker Predicts Lethal Acute Graft Versus Host Disease and Non-Relapse Mortality in Japanese Patients

Introduction Allogeneic hematopoietic stem cell transplantation (aHSCT) is a curative treatment option for hematopoietic malignancies. In addition to relapse mortality, non-relapse mortality (NRM) such as severe graft-versus-host disease(GVHD) is a major cause of aHSCT. Pre-transplant clinical risk factors for acute GVHD include the degree of human leukocyte antigen (HLA) match between donor and recipient, recipient age, donor type, and conditioning regimen intensity. Although GVHD prophylaxis is usually decided by these risk factors, excessive immunosuppression induces opportunistic infection. Laboratory test cannot predict the risk of NRM or severe GVHD after aHSCT prior to the onset of GVHD symptoms; however, 2-biomarker (ST2 and REG3α) algorithm, namely MAGIC algorithm, may predict severe GVHD as has been shown recently (Hartwell et al. JCI Insight 2017). We retrospectively analyzed these 2 biomarkers in our patients to try whether the 2-biomarker algorithm is available to identify high risk of lethal GVHD and non-relapse mortality in Japanese patients. Patients and Methods We retrospectively analyzed consecutive 47 patients who received aHSCT for hematologic malignancies at Kansai Medical University Hospital from January 1, 2010 until April 30, 2016.Overall survival (OS), non-relapse mortality, cause of death, and GVHD clinical staging were investigated. Non-relapse deaths were considered related to GVHD if the patient died from either GVHD itself or from an infection that developed while receiving systemic steroids (at least 10 mg prednisone daily or equivalent) for the treatment of GVHD. Bloodsamples were obtained 7 days after transplantation. ST2 and REG3α concentrations were analyzed by ELISA, and were used for the 2-biomarker algorithm (Hartwell et al. JCI Insight 2017). Results Of the 47 patients (male 24, female 23), median age was 52 years (range, 22-69 years). Eleven patients received PBSCT, 27 patients received bone marrow transplantation, and 9 patients received cord blood transplantation. Of 27 patients who received bone marrow transplantation, 3 patients were transplanted allografts from HLA mismatched donor. Twenty-seven patients underwent reduced intensity conditioning regimen. The median survival time and 1-year OS rate were 375 days (range, 7-3236 days) and 53.2 %, respectively.The overall cumulative incidences of 6-month NRM was 23.4%. The incidence of grade II-IV and III-IV acute GVHD were 17.0%, and 13.2%, respectively. Twelve patients were identified as high risk (HR), and 35 patients were identified as low risk (LR) by the MAGIC algorithm. OS was 33.3% in HR and 71.4% in LR (p&lt;0.05). Six-month cumulative incidence of NRM in HR patients was significantly higher than that of LR (58.3% vs. 11.4%, p&lt;0.001) (Figure), whereas the relapse rate did not differ between risk groups. Four and three patients died from GVHD in HR and LR patients, respectively (33.3% vs. 8.6%, p&lt;0.05). Severe gastrointestinal GVHD was greater in HR patients (18.7 % vs. 8.6%). Conclusion The biomarker algorithm based on blood sample taken 7 day after aHSCT can identify HR patients of lethal GVHD and NRM in Japanese patients as well. Figure Disclosures Ito: Celgene: Honoraria; Bristol-Myers Squibb: Honoraria, Research Funding.

Haploidentical transplantation using posttransplant cyclophosphamide as GVHD prophylaxis in patients over age 70.

Hematologic malignancies in older people are unlikely to be cured with chemotherapy alone. Advances in allogeneic blood or marrow transplantation (alloBMT), especially nonmyeloablative (NMA) conditioning and the use of haploidentical donors, now make this therapy available to older people; however, long-term outcomes and predictors of success are unclear. We reviewed the outcomes of 93 consecutive patients aged 70 and older (median, 72; range, 70-78), who underwent haploidentical BMT at Johns Hopkins Hospital between 1 September 2009 and 1 April 2018. All patients received NMA conditioning and posttransplantation cyclophosphamide (PTCy) as graft-versus-host disease (GVHD) prophylaxis. The 2-year overall survival was 53%, and 2-year event-free survival was 43%. The 180-day cumulative incidence (CuI) of nonrelapse mortality (NRM) was 14%, and the 2-year CuI was 27%. The 2-year CuI of relapse was 30%. Of 78 patients who were alive and had their weight recorded on day 180, weight loss predicted subsequent NRM (subdistribution hazard ratio, 1.0; 95% CI, 1-1.13; P = .048). In conclusion, haploidentical BMT with PTCy is feasible and relatively safe in septuagenarians. Although early, 6-month NRM was relatively low at 14%, but overall NRM continued to climb to 27% at 2 years, at least in part because of late deaths that appeared to be somewhat age related. Further studies to elucidate predictors of NRM are warranted.

An early-biomarker algorithm predicts lethal graft-versus-host disease and survival.

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.

Amphiregulin Improves Stratification of the Refined Minnesota Acute Graft-Versus-Host Disease Risk Score: Results from BMT CTN 0302/0802

Introduction: Amphiregulin (AREG) is an epidermal growth factor receptor (EGFR) ligand that can restore integrity to damaged intestinal mucosa in murine models of acute graft-versus-host disease (aGVHD). We previously described AREG as a circulating biomarker of late-onset aGVHD, but its relevance combined with clinical risk factors has not yet been tested in a large cohort of patients with aGVHD occurring prior to day 100 post-transplant. We therefore tested samples from two aGVHD first-line treatment trials, Blood and Marrow Transplant Clinical Trials Network (BMT CTN) 0302 and 0802, and identified a clinically relevant threshold level of circulating AREG at aGVHD onset. We then investigated whether incorporating AREG into the refined Minnesota Risk Score could further risk-stratify patients.Patients and Methods: Blood samples were obtained at the onset of systemic aGVHD treatment within BMT CTN 0302 (serum) and BMT CTN 0802 (plasma). All patients with response data and samples for analysis from both trials were included (N=251). We determined the association of AREG with clinical outcomes, including risk stratification by the refined Minnesota criteria, day 28 complete/partial response (CR/PR) to first-line therapy, 2-year overall survival (OS) and 6-month and 2-year non-relapse mortality (NRM). We investigated the effect of AREG on clinical endpoints per a doubling in the value of AREG, defined a clinically relevant threshold level in the AREG values using two-fold cross-validation, and confirmed the clinical relevance of this cut-point in independent samples (N=92) from pooled from drawn from the Chronic GVHD Consortium and the Mount Sinai Acute GVHD International Consortium (MAGIC).Results: In patients enrolled in BMT CTN 0302/0802, AREG levels were 1.7-fold higher in patients with Minnesota high-risk (HR) compared to standard-risk (SR) aGVHD (HR median 53.4 vs SR 31 pg/ml, p<0.01). Every 2-fold increase in AREG was associated with a 33% decrease in the likelihood of day 28 CR/PR (odds ratio [OR] 0.67, p<0.01, table). Clinical factors alone, as determined by the refined Minnesota Risk Score, were associated with day 28 CR/PR (p=0.02, table). Adding AREG to the Minnesota Risk Score could further risk-stratify patients. Minnesota SR patients with elevated AREG ≥ 33 pg/mL showed a 59% lower odds of day 28 CR/PR than SR patients with low AREG (OR 0.41, p=0.02). Patients with Minnesota HR aGVHD with AREG ≥ 33 pg/mL had the worst outcomes, with an 82% lower odds of day 28 CR/PR in comparison to HR with low AREG (OR 0.18, p<0.01). High AREG was associated with worse OS and NRM in both Minnesota SR (hazard ratios 2-year OS 2.3, p<0.01 and 6 month NRM 2.95, p=0.01, respectively) and HR patients (hazard ratios 2-year OS 3.35, p<0.01 and 6-month NRM 9.38, p<0.01 respectively, figure). Finally, in independent samples from the Chronic GVHD Consortium/MAGIC we confirmed that high AREG was associated with worse day 28 CR/PR (55.2% vs. 79.4%, p=0.02) and significantly worse 6-month survival after the onset of aGVHD (57.1% vs. 82.5%, p=0.01).Conclusion: AREG is elevated in patients with poor aGVHD outcomes and adds to the accuracy of risk stratification when combined with the refined Minnesota Risk Score. AREG ≥33 pg/mL at aGVHD onset is associated with lower day 28 CR/PR and higher mortality in samples from 4 multicenter cohorts. The mechanism of elevated circulating AREG in severe aGVHD is not yet known, although we hypothesize the degree of AREG elevation reflects the intensity of immune-mediated tissue injury resulting in AREG release. With accumulating evidence of altered EGFR ligands in aGVHD, further investigation into epithelial repair pathways involving AREG may lead to new adjunctive therapies to overcome poor steroid response in high-risk aGVHD. [Display omitted] DisclosuresHoltan:Incyte: Other: One-time advisory board member. Khera:Novartis: Consultancy. Lee:Mallinckrodt: Honoraria; Amgen: Other: One-time advisory board member; Bristol-Myers-Squibb: Other: One-time advisory board member; Kadmon: Other: One-time advisory board member. Chen:Immudex: Research Funding. Arora:Takeda Oncology: Consultancy. Flowers:Pharmacyclics: Consultancy. Cutler:Pfizer: Consultancy; Kite: Consultancy; Incyte: Consultancy; Bristol-Myers Squibb: Consultancy; Pharmacyclics: Consultancy; Astellas: Consultancy. Jagasia:Janssen: Consultancy, Research Funding; Therakos: Consultancy, Research Funding; Mallinckrodt: Consultancy. Hexner:Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding. Levine:Novartis Pharmaceuticals Corporation: Membership on an entity's Board of Directors or advisory committees. MacMillan:Magenta Therapeutics: Research Funding.

Acute Graft-Versus-Host Disease Prognosis: Are Biomarkers Ready for Preemptive Clinical Trials?

Although many factors are known to influence hematopoietic cell transplant (HCT)2 outcomes, including the age of the recipient, comorbidity, conditioning intensity, donor source, donor–recipient human leukocyte antigen (HLA) compatibility, conditioning regimen, and posttransplant graft-versus-host disease (GVHD) prophylaxis, they incompletely predict results. Biomarkers promise to further refine our ability to risk-stratify individual patients for the likelihood of a certain event's occurrence. It is important to define the clinical context of the use of biomarker(s) of interest and the outcome data that will be captured to assess a clinical endpoint, for example, grade II acute GVHD (aGVHD) or 6-month nonrelapse mortality (6m-NRM). Once the biomarkers are validated, risk stratification may allow prevention of complications via a biomarker-based personalized treatment approach. To develop the best biomarkers, the 2014 NIH Chronic GVHD Consensus Biomarker Working Group, which included world experts in the field and U.S. Food and Drug Administration advisors, defined the different types of biomarkers and summarized an ideal framework for biomarker development (1). The group defined 4 types of GVHD markers: (a) diagnostic biomarkers that are used to identify patients at the onset of clinical disease, (b) prognostic biomarkers that are used to categorize patients by degree of risk for disease occurrence, (c) predictive biomarkers that are used to categorize patients by their likelihood of response or outcome to a particular treatment when measured before the treatment, and (d) response biomarkers to treatment that are measured after initiation of therapy and serve as a substitute for a clinical efficacy endpoint. One important recommendation the group made was the verification of a potential GVHD marker in at least 2 independent cohorts (each having sufficient power for statistical significance), which would support its use in GVHD clinical trials and patient management. One promising marker is STimulation-2 (ST2), the interleukin (IL)-33 receptor. Of note, …

95 - Biomarkers Predict Graft-Vs-Host Disease Outcomes Better Than Clinical Response after One Week of Treatment

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 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 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 entity9s 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.

An early-biomarker algorithm predicts lethal graft-versus-host disease and survival

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.

Biomarkers Predict Graft-Vs-Host Disease Outcomes Better Than Clinical Response after One Week of Treatment

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. [Display omitted] [Display omitted] [Display omitted] DisclosuresMielke: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.

An Early Biomarker Algorithm Predicts Lethal Graft-Versus-Host Disease and Survival after Allogeneic Hematopoietic Cell Transplantation

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. [Display omitted] [Display omitted] [Display omitted] DisclosuresChen: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.

Predictors for Steroid Tapering in Patients with Acute Graft-Versus-Host Disease and Their Impact on Graft-Versus-Host Disease Response and Non-Relapse Mortality: Older Age and Co-Morbidities Are Associated with Quicker Tapering and Worse Outcomes

IntroductionThe hematopoietic cell transplantation comorbidity index (HCT-CMI) at the time of transplant has previously been shown to predict the development of grade 3/4 acute GVHD (aGHVD) and higher non-relapse mortality (NRM) for patients with a high CMI (≥3). It has been postulated that inflammatory cytokines associated with many of the conditions accounted for in the CMI may contribute to GVHD development, severity, and ultimately mortality. Because of concerns for corticosteroid toxicities in frail or elderly patients, some clinicians will attempt to rapidly taper steroid doses. We hypothesized that patients with a high CMI and/or advanced age (>60 yo) are treated differently with respect to systemic steroids, and this results in a higher likelihood of progression to more severe aGVHD, increases the need for second-line GVHD therapy, and increases NRM. In order to test this hypothesis, we examined steroid tapering patterns in patients who received systemic steroids for aGVHD in order to determine the influence of age and/or CMI on the rate of taper, and whether this impacted treatment outcome.MethodsPatients who underwent a first allogeneic HCT at MD Anderson Cancer Center between January 2010 and 2015 were retrospectively identified in our HCT database. All patients ≥18 years old that developed aGVHD in the first 100 days and required systemic therapy were evaluated. Detailed information on GVHD therapy, steroid tapering, indication for taper, response, and outcomes were collected retrospectively from the medical records using standard criteria. Competing risks analyses were used to estimate the incidence of second line therapy and NRM, and to evaluate predictors of early (≤5 days) taper, need for second line therapy, and non-relapse mortality. Incidence of second line therapy and NRM were estimated in landmark analysis starting on the date of initial taper.ResultsA total of 417 patients met the eligibility criteria for this analysis (Table 1). Median age of patients was 53 (range 18-75; 28% >60 yo), median CMI was 1 (0-10). Grade of aGVHD at the initiation of therapy was ≤ 2 in 87% of patients and grade 3/4 in 13% of patients with a median time to initiation of therapy of 2 days (0-58). The time from aGVHD diagnosis to initiation of therapy, initial aGVHD grade, and median starting steroid dose, (mg/kg/day) in methylpred equivalents, were comparable in patients ≤60 yo vs >60 yo (Table 1). However CMI>3 was higher in patients >60 yo as would be expected. The median time to initial taper was 5 days (1-26). Predictors for early taper (≤ 5 days) on multivariate analysis included CMI>3 in patients older than 60 yo (HR=1.6, p=0.02) and starting steroid dose >1.5 mg/kg/day (HR=1.5, p=0.001). In the subset of patients with grade 2-4 aGVHD (N=276) who were initially tapered for response, the median steroid dose on day 14 was significantly lower in patients >60 yo with a CMI>3 (0.4 [range 0.05-1.5] vs 0.7 [range 0-9]; p= 0.02) in all other patients. In responding patients, early taper was significantly predictive for cumulative incidence of second line therapy within the first month from the time of first taper (14% vs 6%, HR=2.5, p=0.04). The highest incidence of second line therapy (29%) was in patients >60 yo with CMI>3 who were tapered within the first 5 days (HR 2.8, CI 1.03-7.5, p=0.04). Importantly, none of the patients >60 yo with CMI>3 (n=8) who were tapered after 5 days required second line therapy (n=8). In patients >60 yo with CMI>3, those who were tapered early had a 6-month NRM of 47% vs 25% in those tapered after 5 days (p= 0.1).ConclusionsThese results confirm earlier reports implicating the impact of a high CMI at the time of transplant on aGVHD-related mortality. Our data offers evidence that tapering practices differ according to age and CMI and that this directly impacts GVHD outcomes. Investigating alternative (steroid sparing) strategies to prevent under-treatment of aGVHD is thus essential to improving survival outcomes in these patients. [Display omitted] [Display omitted] DisclosuresCiurea:Spectrum Pharmaceuticals: Other: Advisory Board; Cyto-Sen Therapeutics: Equity Ownership.

Outcomes of Nonmyeloablative HLA-Haploidentical Blood or Marrow Transplantation With High-Dose Post-Transplantation Cyclophosphamide in Older Adults.

Recent advances in nonmyeloablative (NMA), related HLA-haploidentical blood or marrow transplantation (haplo-BMT) have expanded the donor pool. This study evaluated the effect of age on NMA haplo-BMT outcomes in patients age 50 to 75 years. A retrospective analysis was performed of 271 consecutive patients with hematologic malignancies, age 50 to 75 years, who received NMA, T-cell-replete haplo-BMT with high-dose post-transplantation cyclophosphamide. The median age was 61 years, with 115 patients (42%) age 50 to 59, 129 (48%) age 60 to 69, and 27 (10%) age 70 to 75 years. Overall, 84% of patients had intermediate- or high-/very high-risk disease. The 6-month probabilities of grade 3 or 4 acute graft-versus-host disease (GVHD) and nonrelapse mortality (NRM) were 3% and 8%, respectively. Patients in their 50s, 60s, and 70s had 6-month NRM probabilities of 8%, 9%, and 7%, respectively (P=.20). With a median follow-up of 4 years, corresponding 3-year progression-free survival probabilities were 39%, 35%, and 33% (P=.65), and corresponding 3-year overall survival probabilities were 48%, 45%, and 44% (P=.66). Three-year progression-free survival probabilities were 40% in acute myeloid leukemia (n=65), 39% in aggressive non-Hodgkin lymphoma (n=83), and 37% in indolent or mantle-cell lymphoma (n=65). Older patient age was associated with a significantly higher risk of grade 2 to 4 acute GVHD but not grade 3 to 4 acute or chronic GVHD. No statistically significant associations were found between older age (relative to age 50 to 59 years or as a continuous variable) and NRM, relapse, or survival. NMA haplo-BMT with post-transplantation cyclophosphamide has encouraging safety and survival outcomes in patients age 50 to 75 years. In patients otherwise fit for BMT, the results support consideration of this approach despite advanced age.