Abstract: 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 & lt;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 & lt;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 & lt;0.01). High AREG was associated with worse OS and NRM in both Minnesota SR (hazard ratios 2-year OS 2.3, p & lt;0.01 and 6 month NRM 2.95, p=0.01, respectively) and HR patients (hazard ratios 2-year OS 3.35, p & lt;0.01 and 6-month NRM 9.38, p & lt;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. Disclosures Holtan: 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.

Abstract: Background: Len maintenance after autoHCT has improved progression-free (PFS) and overall survival (OS). However, the role of additional interventions after autoHCT such as tandem autoHCT or triple therapy consolidation remains to be determined. Methods: This is a phase III clinical trial (NCT#01109004) of transplant-eligible patients (pts) with symptomatic MM 〈 71 years of age within 12 months of initiating therapy and without prior progression who were randomly assigned 1:1:1 to receive melphalan 200mg/m2 autoHCT and 4 cycles of RVD consolidation (lenalidomide 15mg daily days 1-14, dexamethasone 40mg day 1,8 and 15, and bortezomib 1.3mg/m2 days 1,4,8 and 11 every 21 days) (ACM), versus tandem melphalan 200mg/m2 autoHCT (TAM) or versus a single autoHCT (AM). Randomization was stratified by disease risk (cytogenetic abnormalities - del13q by karyotype, del17q, t(4;14), t(14;16), t(14;20) and hypodyploid; or high beta-2 microglobulin) and center. All arms included Len maintenance (at maximum tolerated dose of 5 to 15 mg orally daily until progression) with dose modifications for toxicities. All patients were reviewed centrally for eligibility, response and progression. The primary objective was to compare 38-month PFS of the three arms. The events for PFS included progression, non-protocol anti-myeloma therapy, or death. Comparisons between treatment groups were based on pairwise log-rank tests stratified on disease risk, with significance levels adjusted for the 3 pairwise comparisons and for interim analyses. In calculating the cumulative incidence of progression, the events were progression or non-protocol anti-myeloma therapy, and death was a competing risk. Results: From June 2010 to November 2013, 758 pts (ACM, N=254; TAM, N=247; AM, N=257) aged 20-70 years (median 57y) were enrolled. Of those enrolled, 24% were classified as high risk. Non-compliance rates following the first autoHCT were 12%, 32% and 5% for ACM, TAM and AM, respectively. Median available follow up from randomization was 38 months. Follow-up is continuing through January 2017. 38-month estimated probabilities for PFS were 57% (95% CI: 50-63%), 56% (95% CI: 49-63%) and 52% (95% CI: 45-59%) for ACM, TAM and AM, respectively (ACM vs TAM p=0.75, ACM vs AM p=0.21, TAM vs AM p=0.37). Corresponding probabilities of OS were 86% (95% CI: 80-90%), 82% (95%CI: 76-87%) and 83% (95% CI: 78-88%). Median OS has not been reached. Cumulative incidences of disease progression at 38 months were 42% (95% CI: 36-48%), 42% (95% CI: 35-48%) and 47% (95% CI: 40-54%) for the ACM, TAM and AM arms, respectively. There were 39 cases of second primary malignancy (SPM) reported in 36 participants and the cumulative incidences for first SPM were 6.0% (95% CI: 3.4-9.6%), 5.9% (95% CI: 3.3-9.6%) and 4.0% (95% CI: 1.9-7.2%) for the ACM, TAM, and AM, respectively. Conclusions: The primary results of the largest randomized US transplant trial in MM demonstrated comparable PFS and OS. The addition of RVD consolidation or a second auto-HCT was not superior to a single auto HCT followed by Len maintenance in the upfront treatment of MM. A long term follow-up trial to track outcomes in these patients is ongoing. Disclosures Stadtmauer: Amgen: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Janssen: Consultancy. Pasquini:Atara: Other: travel reimbursement for a meeting; Baxalta: Honoraria, Membership on an entity's Board of Directors or advisory committees. Efebera:Millennium/Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Honoraria. Ganguly:Onyx: Speakers Bureau; Seattle Genetics: Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees. Giralt:Celgene: Consultancy; Millenium/Takeda: Consultancy. Hari:Celgene: Consultancy; Millennium/Takeda: Consultancy. McCarthy:Celgene: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Millennium/Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; The Binding Site: Consultancy, Honoraria. Qazilbash:Celgene: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Shah:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium/Takeda: Membership on an entity's Board of Directors or advisory committees. Vesole:Takeda: Speakers Bureau; Celgene: Speakers Bureau. Vij:Millennium/Takeda: Consultancy; Celgene: Consultancy. Vogl:Celgene: Consultancy; Millennium/Takeda: Consultancy, Research Funding. Somlo:PUMA: Consultancy; Abbvie: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium/Takeda: Speakers Bureau; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees. Krishnan:Celgene: Consultancy, Speakers Bureau; Millennium/Takeda: Consultancy, Speakers Bureau; Onyx: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau.

Abstract: Background: Geriatric deficits in patients with malignancy are predictive of morbidity and mortality. Measuring geriatric deficits provides additional prognostic information not otherwise captured in routine oncology care. Currently, the gap in geriatric-care delivery is the paucity of data demonstrating effective interventions once geriatric deficits are identified. Older adults with hematologic malignancy are understudied and evaluating both the impact of geriatric factors and interventions to improve upon geriatric deficits are warranted. Here we demonstrate the impact of identifying functional impairment and an exercise program among older adults with hematologic malignancy. Methods: This was a single center prospective study of older patients (≥60 years) with hematologic malignancy. Patients actively receiving any therapeutic treatment (chemotherapy, immunotherapy, targeted agents) were enrolled in a six-month exercise program to attenuate functional decline. The Otago Exercise Program (OEP) has been found to be an effective exercise regimen to improve functional balance, muscle strength, and prevent fall-related injury and mortality.1 The OEP is a structured combination of physical therapist prescribed individualized exercise plans with home-based exercise targeted to improve balance and functional decline. Patients enrolled had mild or moderate impairments in physical function, as defined by a score ≤9 on the Short Physical Performance Battery (SPPB). Patients were evaluated at baseline for geriatric deficits (Visit 1), after four months of OEP training (Visit 2), and following two months of self-directed exercise (Visit 3 - end of study) using a standardized Geriatric Assessmpent (GA) tool (CARG GA). The relationship between geriatric deficits and mortality and hospital utilization were analyzed. The change in GA factors over 3 visits were evaluated through a linear mixed model. The proportional hazards model was built to assess the association between Visit 1 GA and overall survival (OS), where OS was defined as time from date of V1 to death, censoring patients who were still alive at time of last follow-up. The generalized linear models were used to link Visit 1 GA with other clinical outcomes such as hospital length of stay (LOS) and the probability of emergency room (ER) visit. Results: Older adults (median age: 75.5; range 62-83) actively receiving chemotherapy for hematologic malignancy were enrolled (n=30). Physical health scores as measured by the MOS-PFS increased significantly at the second visit. [Median MOS-PFS: V1=55 (0-100); V2=70 (30-100), p 〈 .01; V3=57.5 (0-90), p=0.43], where patient reported KPS increased significantly and the improvement was sustainable [Median KPS: V1=80 (40-100); V2=90 (60-100), p=0.02; V3=90 (50-100), p=0.04] . Objective measures of physical function improved to normal scores by visit 2 and were sustained [Median SPPB: V1=7 (0-11); V2=11 (2-12), p 〈 .01; V3=9 (2-12), p 〈 0.01]. With a median follow-up of 21.4 months, 9 patients had died. Half of patients were hospitalized either once or multiple times with a median of 3 admissions (range 1-7).The total LOS ranged from 2 to 41 days with a median of 13 days. During the study period and 1-year follow up, 67% (20/30) patients had ER visits with a median count of 1.5 visits (range 1-6). The SPPB was the only tool that was associated with all three clinical outcomes; OS with a hazard ratio (HR) of 0.80 (95% confidence interval (CI) 0.65-0.97, p=0.03), LOS [Incidence Rate Ratio=0.86 (95% CI 0.75-0.98), p=0.02] , and the odds of ER visit [odds ratio = 0.77 (95% CI 0.62-0.94), p=0.01]. Chronologic age had no relationship with OS, LOS, or ER utilization. Conclusions: Functional deficits of older patients with hematologic malignancy on active chemotherapy, both subjective and objective metrics, improved with the OEP exercise program. Objective markers of physical function (SPPB) correlated with mortality and hospital utilizations among this population. There was no significant relationship between age and clinical outcomes. Mitigating functional impairment among older adults with hematologic malignancy is important to improve clinical outcomes in this high-risk population. Disclosures Rosko: Vyxeos: Other: Travel support. Baiocchi:Prelude: Consultancy. Brammer:Celgene: Research Funding; Seatlle Genetics: Honoraria, Speakers Bureau. Byrd:Novartis: Other: Travel Expenses, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; Ohio State University: Patents & Royalties: OSU-2S; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau. Efebera:Takeda: Honoraria; Akcea: Other: Advisory board, Speakers Bureau; Janssen: Speakers Bureau. Maddocks:Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Merck: Research Funding; Teva: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding. Rogers:Acerta Pharma: Consultancy; AbbVie: Research Funding; Genentech: Research Funding; Janssen: Research Funding.

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.