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Background Blinatumomab is a bispecific T cell antibody construct, that binds and allows CD-3 positive cytotoxic T cells to recognize and eradicate CD19-positive acute lymphocytic leukemia (ALL) blasts. The drug is approved for patient (pts) with relapsed/ refractory (RR) B-cell ALL and those with minimal residual disease (MRD) based on efficacy in clinical trials. We sought to evaluate the safety and efficacy of blinatumomab in the "real world" setting. Methods We conducted a retrospective multicenter study in collaboration with 11 U.S. academic institutions, and evaluated the outcome of RR B-cell ALL pts, who received blinatumomab outside of clinical trials. These pts were evaluated for response, duration of response (DOR), overall survival (OS) from the time of blinatumomab initiation and toxicity. DOR was estimated among pts who had achieved complete remission (CR)/CR with incomplete count recovery (CRi). Survival curves were estimated using the Kaplan-Meier method and compared via log-rank test. Results From December 2014 to May 2019, 239 pts with B-cell ALL were identified. Baseline characteristics are summarized in Table 1. The median age of pts at blinatumomab initiation was 48 years (yrs) (range, 18-85). Sixty-one (26%) pts had Philadelphia chromosome [t(9;22)] positive (Ph+ve) disease. Sixty-one (26%) pts had ≥ 3 prior therapies and 46 (19%) pts had allogeneic stem cell transplantation (allo-HCT) prior to blinatumomab. Twenty-two (9%) pts received inotuzumab ozagamicin prior to blinatumomab. Twenty-nine (12%) pts received blinatumomab in combination with tyrosine kinase inhibitor (TKI). Twelve (5%) pts received blinatumomab for MRD. Response rate (CR/CRi) in pts with RR disease was 61%; 44% had CR with MRD negativity by flow cytometry. Rate of CR/CRi in Ph+ve B-cell ALL was 74.5%. Among 12 pts who received Blinatumomab for MRD, 9 (75%) pts achieved MRD negativity. Overall 113 (48%) pts were successfully bridged to allo-HCT. Median DOR in pts with RR disease was 32.1 months (95% CI; 9.5-not reached [NR]) (Fig. 1a) and when censored at allo-HCT was 14.8 months (95% CI; 5.2-NR) (Fig. 1b). Median OS in pts with RR disease after blinatumomab was 12.7 months (95% CI; 9.2 -17.9) (Fig. 1c) and when censored at allo-HCT was 8.6 months (95% CI; 6.4-11.6) (Fig.1d). Median OS after blinatumomab in RR B-cell ALL Ph+ve pts was NR (59% alive at 2 yr). Among pts who received blinatumomab for MRD, median DOR was NR and 54% sustained MRD negativity at 2 yrs. Median OS was 34.7 months (95% CI; 8.8-34.7) in group of pts who received blinatumomab for MRD. Seven (3%) pts discontinued blinatumomab due to adverse events and 40 (21%) pts had dose interruptions. Cytokine release syndrome (CRS) of any grade (G) was reported in higher number of pts (93 [39%]) compared to clinical trials, though G3-4 CRS appears to be similar (G1-2 [36%], G3-4 [3%]). Forty-four (44%) pts were treated with steroids and 8 (8%) pts required tocilizumab with steroids for CRS. Ninety-three percent of pts had complete resolution of CRS. CNS toxicities were observed in 31 (13%) pts, among them 60% (n= 19) had G3-4 toxicities. Hepatic toxicities were observed in 84 (35%) pts as outlined in Table 1. Six (2.5%) pts died due to blinatumomab induced toxicities. Conclusion: Our real-world data with multicenter collaboration suggest that overall blinatumomab was well tolerated and had led to significant response in pts with RR B-cell ALL. Disclosures Advani: Amgen: Research Funding; Abbvie: Research Funding; Pfizer: Honoraria, Research Funding; Macrogenics: Research Funding; Kite Pharmaceuticals: Consultancy; Glycomimetics: Consultancy, Research Funding. Aldoss:AUTO1: Consultancy; Helocyte: Consultancy, Honoraria, Other: travel/accommodation/expenses; Agios: Consultancy, Honoraria; Jazz Pharmaceuticals: Honoraria, Other: travel/accommodation/expenses, Speakers Bureau. Podoltsev:Agios Pharmaceuticals: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding; Astellas Pharma: Research Funding; Alexion: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo: Research Funding; Sunesis Pharmaceuticals: Research Funding; Jazz Pharmaceuticals: Research Funding; Pfizer: Research Funding; Astex Pharmaceuticals: Research Funding; CTI Biopharma: Research Funding; Celgene: Other: Grant funding, Research Funding; Genentech: Research Funding; AI Therapeutics: Research Funding; Samus Therapeutics: Research Funding; Arog Pharmaceuticals: Research Funding; Kartos Therapeutics: Research Funding. Curran:Incyte: Research Funding; Merck: Research Funding; Gilead: Research Funding. Yang:Agios: Consultancy; AstraZeneca: Research Funding. Mattison:Pfizer: Membership on an entity's Board of Directors or advisory committees. Liedtke:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; IQVIA/Jazz: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech/Roche: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celator: Research Funding; Caelum: Membership on an entity's Board of Directors or advisory committees; BlueBirdBio: Research Funding; Amgen/Onyx: Consultancy, Honoraria, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees; Agios: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Atallah:Helsinn: Consultancy; Takeda: Consultancy, Research Funding; Jazz: Consultancy; Pfizer: Consultancy; Helsinn: Consultancy; Novartis: Consultancy; Jazz: Consultancy.

Background: CMML is a heterogeneous disease with overlapping features of MDS and MPN. Several risk scores have been proposed in CMML, including CPSS (Such Blood 2013) that identifies 4 risk groups (low, intermediate-1 [int-1], int-2 and high risk) with median overall survival (OS) ranging from 12 months to > 5 years. HSCT is the only curative treatment in CMML, with an expected 20-40% post-transplantation OS. Current guidelines, common to MDS and CMML recommend rapidly transplanting higher-risk CMML and delaying transplant in lower-risk disease (de Witte Blood 2017). Retrospective transplant studies have shown better outcome in lower-risk CMML (Liu et al BBMT 2017). Whether this translates into a survival benefit compared to a delayed transplant strategy requires prospective studies. Multistate models based on retrospective data from transplant and non-transplant patients (pts) have addressed similar issues in MDS (Koreth JCO 2013, Della Porta Leukemia 2017). Through a large collaborative study, we address the question of optimal timing for HSCT in CMML patients through a similar large international collaborative study. Method: We retrospectively selected pts from 2 registries: International MDS/MPN Working Group (IWG cohort, Padron Blood Cancer J 2015) and EBMT with the following criteria: WHO-defined CMML, age ≤ 70y, ECOG 0-2, diagnosis after 2000, available CPSS at the time of diagnosis. Different states were considered in higher- (CPSS int-2 and high) and lower- risk (CPSS low/int-1) pts: diagnosis, AML transformation, transplantation and death. IWG data was used to estimate transition probabilities from diagnosis to AML, transplantation and death and from AML to transplantation and death. EBMT data was used for transplantation to death transitions (Figure 1). Results: 719 and 403 pts were identified in the IWG and EMBT registry, respectively (resp). Median age was 64 (range 16-70) in IWG and 58 (19-70) years in EBMT cohort. Patients were male in 69% and 67% of IWG and EBMT cohorts, respectively (resp). CPSS was low in 22% and 13%, int-1 in 31% and 31%, int-2 in 40% and 45% and high in 8% and 11% of the IWG and EBMT pts, resp. In the IWG cohort, the 1 year cumulative incidence of transformation into AML were 7.3% and 18.2% in lower and higher risk patients, resp. Among the 719 pts from IWG, 102 received HSCT. At the time of diagnosis the expected life time of higher risk (int-2 and high) patients was 25.2 months while it was 44.1 months in lower risk (int-1 and low) patients. Table 1 reports gain or loss in expected life time (until 60 months after diagnosis) for transplantation at different intervals from diagnosis (within 6, 12, 18 and 24 months) for patients who have survived and not transformed to AML until the prediction time point, taking into account CPSS at diagnosis. Expected life time is also given separately for higher risk pts after transformation into AML. There was a modest gain of life expectancy with transplantation in higher risk patients (CPSS int-2 and high) while it was not the case in lower risk patients. The survival gain in higher risk pts with HSCT rose from 1.11 at 6 months to 3.4 months at 24 months. There was also a survival benefit of HSCT in higher risk pts who were transformed to AML during their follow-up which was even higher in terms of gain of months: from 9.89 month if HSCT performed within 6 months to 14.25 months if performed within 18 months. Of note, the loss of survival in lower risk patients who underwent HSCT decreased over time: 11.1 months if HSCT is performed within 6 months and 3.7 months if HSCT is performed within 24 months, probably owing to transition to higher-risk CMML at this stage in some pts, a transition that could not be captured in the present dataset. Conclusion: For the first time, using a multistate model, we could provide evidence that the transplant benefit in CMML is restricted to higher-risk pts, in line with findings in MDS and current guidelines. More analyses will be performed to analyze other subgroups of patients, especially regarding their risk (other classification than CPSS, the role of somatic mutation…). More studies are needed to analyze the role of pre HSCT treatment and its potential impact on post-transplant outcome. Disclosures Robin: Novartis Neovii: Research Funding. Beelen:Medac GmbH Wedel Germany: Consultancy, Honoraria. Fenaux:Celgene Corporation: Honoraria, Research Funding; Astex: Honoraria, Research Funding; Jazz: Honoraria, Research Funding; Aprea: Research Funding. Kroeger:Riemser: Research Funding; Novartis: Honoraria, Research Funding; Medac: Honoraria; DKMS: Research Funding; Neovii: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; JAZZ: Honoraria; Sanofi-Aventis: Honoraria. Nazha:Tolero, Karyopharma: Honoraria; MEI: Other: Data monitoring Committee; Novartis: Speakers Bureau; Jazz Pharmacutical: Research Funding; Incyte: Speakers Bureau; Daiichi Sankyo: Consultancy; Abbvie: Consultancy. Rampal:Agios, Apexx, Blueprint Medicines, Celgene, Constellation, and Jazz: Consultancy; Constellation, Incyte, and Stemline Therapeutics: Research Funding. Finke:Riemser: Honoraria, Other: research support, Speakers Bureau; Neovii: Honoraria, Other: research support, Speakers Bureau; Medac: Honoraria, Other: research support, Speakers Bureau. Komrokji:Agios: Consultancy; DSI: Consultancy; pfizer: Consultancy; celgene: Consultancy; JAZZ: Consultancy; Novartis: Speakers Bureau; JAZZ: Speakers Bureau; Incyte: Consultancy. Killick:JAZZ: Honoraria; Celgene: Honoraria; NOVARTIS: Honoraria, Membership on an entity's Board of Directors or advisory committees; ALEXION: Honoraria. Blaise:Molmed: Consultancy, Honoraria; Sanofi: Honoraria; Pierre Fabre medicaments: Honoraria; Jazz Pharmaceuticals: Honoraria. Garcia-Manero:Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding. Patnaik:Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees.

Background Left ventricular ( LV ) recovery in takotsubo syndrome ( TTS ) occurs over a wide‐ranging interval, varying from hours to weeks. We sought to investigate the clinical predictors and prognostic impact of recovery time for TTS patients. Methods and Results TTS patients from the International Takotsubo Registry were included in this study. Cut‐off for early LV recovery was determined to be 10 days after the acute event. Multivariable logistic regression was used to assess factors associated with the absence of early recovery. In‐hospital outcomes and 1‐year mortality were compared for patients with versus without early recovery. We analyzed 406 patients with comprehensive and serial imaging data regarding time to recovery. Of these, 191 (47.0%) had early LV recovery and 215 (53.0%) demonstrated late LV improvement. Patients without early recovery were more often male (12.6% versus 5.2%; P =0.011) and presented more frequently with typical TTS (76.3% versus 67.0%, P =0.040). Cardiac and inflammatory markers were higher in patients without early recovery than in those with early recovery. Patients without early recovery showed unfavorable 1‐year outcome compared with patients with early recovery ( P =0.003). On multiple logistic regression, male sex, LV ejection fraction <45%, and acute neurologic disorders were associated with the absence of early recovery. Conclusions TTS patients without early LV recovery have different clinical characteristics and less favorable 1‐year outcome compared with patients with early recovery. The factors associated with the absence of early recovery included male sex, reduced LV ejection fraction, and acute neurologic events. Clinical Trial Registration URL : http://www.clinicaltrials.gov . Unique identifier: NCT 01947621.

Abstract Introduction Right ventricular (RV) size informs about prognosis and need for pulmonary valve replacement in patients with repaired tetralogy of Fallot (rTOF). Cardiac magnetic resonance (CMR) is considered the reference standard for measurement of RV volumes. Despite known limitations for RV evaluation, 2D transthoracic echocardiography (TTE) remains the primary and most available imaging modality in the rTOF population. Purpose To determine which TTE RV size parameters best correlate with CMR-derived indexed RV end-diastolic (RVEDVi) and end-systolic (RVESVi) volumes in the rTOF population. We sought to determine the best TTE measurement thresholds to predict normal RV volume (RVEDVi ≤110 mL/m2) and significant RV dilatation by CMR (RVEDVi ≥150ml/m2). Method We retrospectively enrolled all rTOF patients followed at a single-center between 2010 and 2018 who had both TTE and CMR exams performed within a 12-month interval. All TTE exams were reviewed by an observer measuring RV areas, RV inlet and RV outlet at end-diastole and end-systole. Analyses of CMR studies were performed by 3 observers who measured RV area, RV inlet, RV outlet and RV volumes at end-diastole and end-systole. Correlations between TTE and CMR parameters were performed using Pearson correlation coefficients. Using the TTE RV parameters with the strongest correlation with CMR, we subsequently determined thresholds to predict a CMR RVEDVi ≤110ml/m2 and ≥150ml/m2 using ROC analysis. Results We enrolled 130 patients (59 women [45%], mean age 43±12.8 years). Median age at TOF repair was 4 [3–6] years; 18 patients (14%) had subsequent pulmonary valve replacement. Median interval between TTE and CMR exams was 114 [59–239] days. There were significant correlations between all TTE parameters and CMR RVEDVi. TTE indexed RV end-diastolic area (RVEDAi) most strongly correlated with CMR RVEDVi (r=0.73, p<0.0001). All TTE RV parameters significantly correlated with CMR RVESVi but indexed RV end-systolic area had the strongest correlation (r=0.77, p<0.0001). ROC analysis performed to predict RVEDVi of ≤110ml/m2 and ≥150ml/m2 using TTE RVEDAi revealed areas under the curve of 0.86±0.04 and 0.90±0.03, respectively. A TTE RVEDAi ≤17cm2/m2 predicted a normal CMR RV volume (≤110ml/m2) with a sensitivity of 90% and a specificity of 74%. A TTE RVEDAi ≥19cm2/m2 predicted a CMR RVEDVi ≥150 mL/m2 with a sensitivity of 93% and a specificity of 76%. Conclusion In rTOF patients, both diastolic and systolic TTE RV area best correlate with CMR-derived RV end-diastolic and end-systolic volumes. A cut-off value of TTE RVEDAi of 19cm2/m2 is 93% sensitive and 76% specific to predict a CMR RVEDVi ≥150ml/m2. Simple RV size measurement using TTE may help inform the need and frequency of CMR evaluations in rTOF patients.

Abstract The prognosis of elderly patients (pts) with acute lymphoblastic leukemia (ALL) remains poor, and novel therapeutic approaches are clearly needed. CD19 is expressed on the majority of precursor-B ALLs and represents an attractive therapeutic target. The anti-CD19 bi-specific engager antibody blinatumomab has demonstrated significant activity in both relapsed/refractory ALL and minimal residual disease (MRD) positive ALL. Therefore, we evaluated blinatumomab as a single agent in the upfront treatment of newly diagnosed elderly pts with Philadelphia chromosome (Ph) negative B-lineage ALL to determine response rates and overall survival (OS). Methods: Pts were treated at National Clinical Trial Network sites from June 2015 to September 2017. The primary objective of the study was to estimate 3-year OS. An IND was approved by the FDA and the protocol was approved by a central institutional review board. Eligibility: age > 65 years, newly diagnosed Ph negative B-lineage ALL with adequate organ function and no evidence of central nervous system (CNS) disease. Pts received blinatumomab for induction at standard dosing for 1-2 cycles until attainment of complete response (CR) or CR with incomplete count recovery (CRi) (defined below). Pts then received 3 cycles of blinatumomab post-remission therapy followed by 18 months of maintenance POMP (prednisone, vincristine, 6-mercaptopurine, methotrexate). A total of 8 doses of intrathecal methotrexate were administered as CNS prophylaxis. Cytogenetic risk was ascribed by NCCN 2018 criteria and bone marrow samples were analyzed for the presence of the Ph-like signature. MRD was assessed centrally by 8 color flow cytometry pre-treatment, on Day 35 of induction cycle 1, and on Day 35 of re-induction (if applicable). Response was assessed at the completion of 1-2 cycles of blinatumomab. CR was defined as < 5% marrow blasts with no evidence of extramedullary disease and recovery of counts [absolute neutrophil count (ANC) > 1000/uL, platelets >100,000/uL]. CRi was defined the same as CR but ANC < 1000/ uL and/ or platelets ≤ 100,000/ uL. OS was measured from day of registration on trial until the date of death. Disease-free survival (DFS) was measured from the date the pt achieved CR/ CRi until relapse or death. Toxicities were graded according to NCI CTCAE version 4.0. Results: Of 31 pts enrolled, 29 were eligible. The median age was 75 years (range 66 - 84), 22 (76%) were male, median baseline white blood count was 3.7 x 103/uL (range 0.3 - 7,100), and median bone marrow blast count percentage was 86.5% (range 30-100). Three pts received hydroxyurea or steroids prior to treatment initiation. Cytogenetic risk at diagnosis was: poor (34% of pts; n=10), standard (55% of pts; n=16), good (3% of pts; n=1) and unknown (7% of pts, n=2). Testing for the Ph-like signature is being completed. The most common Grade 3-5 non-hematologic toxicities related to treatment during induction were hyperglycemia (14%), dyspnea (10%), febrile neutropenia (10%), hypertension (10%), and lung infection (7%). One pt developed Grade 3 cytokine release syndrome and 1 developed Grade 3 neurotoxicity. No pts died during the first 28 days of treatment. The overall response rate (CR + CRi) was 66% (all CRs). Thirteen of the 19 responders have available MRD data post-treatment. Of these, 12 pts (92%) achieved MRD negativity, all at Cycle 1 Day 35. One pt required 2 cycles of blinatumomab to achieve CR. One pt proceeded to allogeneic hematopoietic stem cell transplant. The median follow-up time is 1 year and median duration on trial is 170 days (6 pts are still on maintenance therapy). OS estimated by Kaplan Meier at 6 months is 79% (95% CI 58%-90%) and at 1 year is 65% (95% CI 43%-80%). DFS estimated at 6 months is 68% (95% CI 43%-84%) and at 1 year is 56% (95% CI 31%-75%). No baseline features including CD19 expression (by percentage or mean-fluorescent intensity) or presence of a CD19 negative subpopulation were associated with response. Conclusions: Blinatumomab was well tolerated and effective in the treatment of newly diagnosed elderly patients with Ph negative B-lineage ALL. Further follow up will determine the durability of these responses. Disclosures Advani: Pfizer: Honoraria, Research Funding; Amgen: Research Funding; Novartis: Consultancy; Glycomimetics: Consultancy. Wieduwilt:Leadiant: Research Funding; Merck: Research Funding; Shire: Research Funding; Reata Pharmaceuticals: Equity Ownership; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding. Park:Adaptive Biotechnologies: Consultancy; Pfizer: Consultancy; AstraZeneca: Consultancy; Novartis: Consultancy; Kite Pharma: Consultancy; Juno Therapeutics: Consultancy, Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Shire: Consultancy. Stock:Jazz Pharmaceuticals: Consultancy. Erba:Immunogen: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Agios: Consultancy, Speakers Bureau; Takeda/Millenium: Research Funding; Amgen: Research Funding; Novartis: Consultancy, Speakers Bureau; Juno: Research Funding; Juno: Research Funding; Celgene: Consultancy, Speakers Bureau; Daiichi Sankyo: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Takeda/Millenium: Research Funding; Incyte: Consultancy, Speakers Bureau; MacroGenics: Consultancy; Jazz: Consultancy, Speakers Bureau; MacroGenics: Consultancy; Agios: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Amgen: Research Funding; Agios: Consultancy, Speakers Bureau; Astellas: Research Funding; MacroGenics: Consultancy; Takeda/Millenium: Research Funding; Seattle Genetics: Consultancy, Research Funding; MacroGenics: Consultancy; Novartis: Consultancy, Speakers Bureau; Amgen: Research Funding; Novartis: Consultancy, Speakers Bureau; Janssen: Research Funding; Celgene: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Janssen: Research Funding; Jazz: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Amgen: Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Pfizer: Consultancy, Other: grant; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Astellas: Research Funding; Pfizer: Consultancy, Other: grant; Celgene: Consultancy, Speakers Bureau; Seattle Genetics: Consultancy, Research Funding; Incyte: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Pfizer: Consultancy, Other: grant; Incyte: Consultancy, Speakers Bureau; Juno: Research Funding; Jazz: Consultancy, Speakers Bureau; Pfizer: Consultancy, Other: grant; Astellas: Research Funding; Seattle Genetics: Consultancy, Research Funding; Takeda/Millenium: Research Funding; Immunogen: Consultancy, Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Juno: Research Funding; Jazz: Consultancy, Speakers Bureau.

Abstract Abstract 845 Background: Waldenstrom's macroglobulinemia (WM) is a relatively uncommon plasma cell disorder and most of previous literature is limited to small patient series. We have noted ethnic disparities in multiple myeloma, another plasma cell disorder. We undertook a large Surveillance Epidemiology and End Results (SEER) based analysis to describe outcome disparities in different subgroups of WM patients, with a focus on various ethnicities, so that therapeutic resources can be targeted more effectively. Methods: The SEER 17 Registry data (1973–2008) was utilized for patients with confirmed diagnosis of WM. To avoid bias of under representation of different ethnicities, analysis was restricted to patients with a diagnosis date of 1992 or later. Cases that received a diagnosis at death certificate or autopsy, no follow-up records, as well as lacking documentation on age at diagnosis, sex, or race/ethnicity were excluded. Cox proportional hazards models, adjusted for gender, age, race, year of diagnosis, marital status and stratified by SEER registries were used to evaluate associatio n between patient characteristics and survival. All statistical tests were two-sided and utilized the SAS software (v9.2) with a significance level of 0.05. Results: The final analysis included 2,840 WM patients (1,759 males; 62%, 1,081 females; 38%). The studied age-group cohorts included: 18–64 yrs (845; 30%), 65–74 yrs (795; 28%) and >75 yrs (1,200; 42%). Patients were stratified by race/ethnicity: White (2,471; 87%), African-American (AA) (102; 4%), Hispanic (133; 5%), Asian (129; 5%), and Native American (5; 0.1%). Patients were also stratified based on year of diagnosis (before or after 2002) to study the impact of certain novel agents (proteasome inhibitors, IMiDs) on WM treatment. There was a significant difference in the age at diagnosis of WM patients across different ethnicities, with AA the youngest (median 61.5 years) and Whites the oldest (median 73 years) subgroup (p<0.001). (Figure 1) Cause-specific mortality could not be evaluated due to variable documentation of reported causes of death for WM patients in the database. Survival analysis revealed that for all patients, females had better median overall survival (OS) than males (7.3 years vs. 6.2 years, HR 0.834; 95% CI 0.740, 0.939; p=0.003). Among the different age cohorts, patients with age ≥75 years had a significantly worse median OS (4.1 years) than those 65–74 year-old (7.3 years) or 18–64 year-old (10+ years) (p<0.001). Patients diagnosed after 2002 had a significantly better median OS (7.3 years) as compared to patients diagnosed previously (6.1 years) (p=0.002). Hispanics had the worst median OS (5 years) and Whites had the best median OS (6.8 years) across various ethnicities. In a multivariate model using gender, age, marital status, year of diagnosis and race, a significant interaction was noted between race, age and survival, with Hispanics having a significantly worse OS than Whites (HR 1.86; 95% CI 1.269, 2.726; p=0.003) (Figure 2). Conclusions: Studies of outcome disparities are important for evaluating disease characteristics and management needs of specific patient populations as well as optimal triaging of healthcare resources. We have performed the largest population-based analysis for WM including various ethnicities in the novel therapeutic agent era. We observed that AA patients had a significantly younger age at WM diagnosis. Older patients had worse OS across all ethnic subgroups and patients diagnosed after 2002 had a better OS suggesting an impact of novel therapeutic agents (e.g., proteasome inhibitors, IMiDs). Hispanic WM patients had the worst OS among all ethnicities. This survival difference was more significant and pronounced in patients >75 years. This suggests that the impact of race on survival is influenced by patient's age. These results will help in better understanding of various influences on disease biology and clinical behavior. Disclosures: No relevant conflicts of interest to declare.

Abstract Total body irradiation (TBI)-based conditioning regimens are considered the standard of care for patients with acute lymphoblastic leukemia (ALL) undergoing allogeneic hematopoietic cell transplantation (HCT). However, due to concerns regarding acute and long-term toxicities, non-TBI regimens, commonly including busulfan (BU), have been increasingly explored. We performed a retrospective cohort analysis with the hypothesis that there would be equivalence of these two myeloablative approaches by reviewing outcomes for adult patients (pts), aged 18-60 years, undergoing a first, well-matched sibling, related or unrelated donor HCT in CR1 or CR2 reported to the Center for International Blood and Marrow Transplant Research (CIBMTR) from 2005-2014. Eight hundred nineteen pts received TBI (63% 9-12 Gy, 37% ≥13 Gy) combined with etoposide (25%) or cyclophosphamide (Cy) (75%) and 299 pts received intravenous BU combined with a second alkylator Cy (15%) or melphalan (Mel) (13%), or a nucleoside analogue fludarabine (Flu) (41%) or clofarabine (Clo)(30%). The majority of the BU-based pts were treated at the Moffitt or MD Anderson Cancer Center. The BU-based regimens were grouped together for analyses since no significant differences in basic outcomes among the different chemotherapy-only regimens were noted. Patients in the BU-containing group were older but had better performance status, took longer to achieve CR1 and longer to receive HCT; more received peripheral blood than marrow grafts, peri-HCT ATG, pre- and post HCT tyrosine kinase inhibitors ( TKI), and were treated more recently than pts in the TBI-based group (Table 1). With median follow-up of 3.6 years for the BU-based group and 5.3 years for the TBI-based group, adjusted 3 year outcomes showed treatment-related mortality (TRM) BU 19% vs. TBI 25% (p=.04); relapse BU 37% vs. TBI 28% (p=.007); disease-free survival (DFS) Bu 45% vs. TBI 48% (p=.35); and overall survival (OS) BU 57% vs. TBI 53% (p=.35) (Figures A-B). Patients in the BU group had significantly more grade II-IV acute GVHD (47% vs. 40%, p=.025), but marginally less chronic GVHD (49% vs. 55% at 3 years, p=.073). In multivariate analysis, the BU group had a significantly higher rate of acute GVHD after day 50 (RR 1.75, 95% CI 1.19-2.58, p=.004), but marginally less chronic GVHD (RR 0.83, 95% CI 0.68-1.01 p=.059) and higher risk of relapse (RR 1.46, 95% CI 1.15-1.85 p=.002) compared with TBI-based regimens. Despite the observed higher risks of acute GVHD and relapse, BU-based conditioning led to similar TRM, OS, and DFS following HCT for ALL. Table 1 Table 1. Figure Figure. Disclosures Ciurea: Spectrum Pharmaceuticals: Other: Advisory Board; Cyto-Sen Therapeutics: Equity Ownership. Seftel:Otsuka: Research Funding. Pulsipher:Medac: Other: Housing support for conference; Chimerix: Consultancy; Jazz Pharmaceutical: Consultancy; Novartis: Consultancy, Other: Study Steering Committee. Champlin:Ziopharm Oncology: Equity Ownership, Patents & Royalties; Intrexon: Equity Ownership, Patents & Royalties.

Abstract Abstract 414 Background: SGI-110 is a dinucleotide of decitabine (DAC) and deoxyguanosine formulated as a low volume and pharmaceutically stable SQ injection allowing more extended decitabine exposure than DAC IV infusion. The anticipated differentiated PK profile offers the potential of improved biological and clinical activity and safety over currently available HMAs. Methods: A randomized Phase 1–2 FIH Pharmacokinetics/Pharmacodynamics (PK/PD)-guided, dose-escalation study has been conducted in patients with relapsed/refractory intermediate or high-risk MDS or AML. The objective of the first stage (dose escalation) is to determine safety and tolerability and to establish the Maximum Tolerated Dose (MTD) and Biologically Effective Dose (BED). Patients were randomized to one of two SQ regimens (dailyx5 or once weeklyx3, 28-day courses). PD is evaluated by LINE-1 global DNA hypomethylation. The second stage (dose expansion) is to determine the clinical activity and safety in AML and MDS using the established BED and MTD. We report here the results of the dose escalation phase which has completed enrolment. Results: 78 patients (64 AML, 14 MDS) were enrolled in the dose escalation phase: 44 patients in the dailyx5 regimen and 34 in the weeklyx3 regimen. Median age was 69 years (range 29–86), 65% were male, and 82% had ECOG PS of 0–1. Median number of prior regimens was 3 (range 1–9), 59% of patients had prior HMA treatment (50% of AML patients, and 100% of MDS patients). Six patients are still ongoing treatment. The PK profile demonstrated efficient conversion of SGI-110 to decitabine as predicted from the SGI-110 rational design, resulting in longer decitabine exposure window (beyond 8 hrs) compared to DAC IV (3–4 hrs). At SGI-110 dose range of 60–125 mg/m2, observed mean decitabine AUCs (88–231 ng*hr/mL) reach or exceed the therapeutic range seen with 20 mg/m2 DAC IV (115 ng*hr/mL) while achieving only a small fraction of the Cmax (26–64 ng/mL vs 146 ng/mL for DAC IV). The effective half-life for decitabine after SQ SGI-110 injection appeared to be prolonged (up to 4-fold or ∼2.4 hrs) compared to DAC IV (0.58 hrs). Decitabine exposures (AUC) increased in a dose-proportional manner regardless of the regimen and no accumulation was observed. Dose-related LINE-1 hypomethylation was observed in patients treated with the daily regimen between 18 and 60 mg/m2; a plateau in maximum average hypomethylation (∼25%) was evident at higher daily doses (90-125 mg/m2) and therefore the BED for the dailyx5 schedule is established at 60 mg/m2. The 25% average hypomethylation of LINE-1 compares favorably with that observed historically after DAC IV at the dose of 20 mg/m2 dailyx5. The extent of LINE-1 hypomethylation after weeklyx3 SGI-110 was inferior as the maximum average hypomethylation plateaued at ∼8% from baseline. Starting at 36 mg/m2 daily and 60 mg/m2 weekly (44 AML, and 7 MDS patients), clinical responses were observed: 2CRs, 1CRp, and 1CRi in heavily pretreated AML patients; 1 mCR and 1 HI in MDS patients previously treated with azacitidine. All responses were in patients who achieved >10% LINE-1 hypomethylation. The most common Adverse Events (AEs), regardless of relationship to SGI-110, were diarrhea (21%), febrile neutropenia (17%), fatigue/injection site pain/nausea at 15% each. The most common drug-related AEs were injection site pain (15%), fatigue (8%), nausea (6%), and thrombocytopenia (5%). MTD was not reached with the weekly regimen up to 125 mg/m2 weeklyx3. With the daily regimen, 125 mg/m2dailyx5 resulted in 2 Dose-Limiting Toxicities (DLTs) of febrile neutropenia in 3 MDS patients (1 associated with bacteremia, and the other with sepsis and thrombocytopenia Grade 4) while none of the 9 patients with AML had DLT at that dose. Conclusions: SGI-110 is well tolerated at doses higher than BED which is established at 60 mg/m2 dailyx5 where average hypomethylation of ∼25% was achieved. MTD estimated to be 90 mg/m2 dailyx5 for MDS and 125 mg/m2dailyx5 for AML patients. SQ administration of SGI-110 achieved efficient conversion to decitabine resulting in an improved PK profile over DAC IV. Clinical responses were observed in this heavily pretreated population and they seem to correlate with the extent of LINE-1 hypomethylation. Study is currently enrolling patients in the dose-expansion Phase 2 stage. Disclosures: Kantarjian: Astex Pharmaceuticals: Research Funding. Roboz:Astex Pharmaceuticals: Research Funding. Rizzieri:Astex Pharmaceuticals: Research Funding. Stock:Astex Pharmaceuticals: Research Funding. O'Connell:Astex Pharmaceuticals: Research Funding. Griffiths:Astex Pharmaceuticals: Research Funding. Yee:Astex Pharmaceuticals: Research Funding. Tibes:Astex Pharmaceuticals: Research Funding. Garcia-Manero:Astex Pharmaceuticals: Research Funding. Ravandi:Astex Pharmaceuticals: Research Funding. Walsh:Astex Pharmaceuticals: Research Funding. Feldman:Astex Pharmaceuticals: Research Funding. Ritchie:Astex Pharmaceuticals: Research Funding. Rao:Astex Pharmaceuticals: Research Funding. Decastro:Astex Pharmaceuticals: Research Funding. Schimmer:Astex Pharmaceuticals: Research Funding. Mesa:Astex Pharmaceuticals: Research Funding. Syed:Astex Pharmaceuticals: Research Funding. Choy:Astex Pharmaceuticals: Employment. Oganesian:Astex Pharmaceuticals: Employment. Taverna:Astex Pharmaceuticals: Employment. Azab:Astex Pharmaceuticals: Employment. Chung:Astex Pharmaceuticals: Research Funding. Issa:Astex Pharmaceuticals: Honoraria, Research Funding.

Abstract Objectives Translational research in laboratory medicine and pathology is transforming health care based on recent quantum advances in omics technologies, computational science, and precision medicine. However, high-volume clinical settings where this research may be most effective often have significant constraints on faculty time that challenge productivity. The objective of this study was to assess our experience with a new resource designed to address this challenge. Methods In September 2016, we established the Research and Innovation Office (RIO) in the Department of Laboratory Medicine and Pathology, Mayo Clinic–Rochester. The goal was to provide infrastructure to unburden faculty from performing administrative, organizational, and operational tasks related to research. Over 30 months, we solicited faculty input into desired services, conducted surveys on utility and ease of use, and tracked metrics, including faculty participation, numbers of projects, and publications. Results Faculty members were highly satisfied with the range of services, ease of use, and service-oriented approach of RIO. Initial services included project organization, institutional process support (eg, IRB protocol management), biospecimen requests and handling, and data management. Based on early feedback, patient consenting, budget support, and manuscript assistance were added as additional services. Total RIO staff increased from 6 to 10 during in the first 30 months. Over this time, 97 of 160 faculty members (60%) utilized RIO services in over 1,000 discrete project requests. Annual departmental publications increased by 50% during this time. Conclusion Faculty time is a critical element for translational research productivity in laboratory medicine and pathology departments. Numerous tasks previously performed by faculty could be managed effectively by a team of research facilitators that unburdened constraints on research time and led to high levels of faculty engagement, satisfaction, and productivity. This model may promote advances in transformative laboratory medicine and pathology research in high-volume clinical settings.