Citations

Background The epidemiological transition of non-communicable diseases replacing infectious diseases as the main contributors to disease burden has been well documented in global health literature. Less focus, however, has been given to the relationship between sociodemographic changes and injury. The aim of this study was to examine the association between disability-adjusted life years (DALYs) from injury for 195 countries and territories at different levels along the development spectrum between 1990 and 2017 based on the Global Burden of Disease (GBD) 2017 estimates. Methods Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm—the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate. Results For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced. Conclusions The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.

Abstract Aims As health systems around the world increasingly look to measure and improve the value of care that they provide to patients, being able to measure the outcomes that matter most to patients is vital. To support the shift towards value-based health care in atrial fibrillation (AF), the International Consortium for Health Outcomes Measurement (ICHOM) assembled an international Working Group (WG) of 30 volunteers, including health professionals and patient representatives to develop a standardized minimum set of outcomes for benchmarking care delivery in clinical settings. Methods and results Using an online-modified Delphi process, outcomes important to patients and health professionals were selected and categorized into (i) long-term consequences of disease outcomes, (ii) complications of treatment outcomes, and (iii) patient-reported outcomes. The WG identified demographic and clinical variables for use as case-mix risk adjusters. These included baseline demographics, comorbidities, cognitive function, date of diagnosis, disease duration, medications prescribed and AF procedures, as well as smoking, body mass index (BMI), alcohol intake, and physical activity. Where appropriate, and for ease of implementation, standardization of outcomes and case-mix variables was achieved using ICD codes. The standard set underwent an open review process in which over 80% of patients surveyed agreed with the outcomes captured by the standard set. Conclusion Implementation of these consensus recommendations could help institutions to monitor, compare and improve the quality and delivery of chronic AF care. Their consistent definition and collection, using ICD codes where applicable, could also broaden the implementation of more patient-centric clinical outcomes research in AF.

Background: Molecular genetic testing is increasingly utilized in clinical care, typically with peripheral blood as the preferred specimen. Despite the prevalence of therapeutic blood transfusions, whether donor DNA is present in a sufficient quantity to interfere with recipient genetic testing has not been systematically studied. Microchimerism secondary to transfusion of blood products with donor leukocytes has been well-documented in trauma patients receiving whole blood; however, most medical centers currently transfuse leukoreduced (LR) red blood cell products for non-trauma patients. The degree of leukoreduction varies among centers, but to meet AABB standards must be <5x106 white blood cells (WBC) in 95% of units tested. We sought to determine what quantity, if any, of infused LR or non-LR (NLR) products leads to detectable microchimerism that may impact genetic test results. Methods: We performed an in vitro spiking study utilizing four whole blood units collected from different anonymous donors. Three were leukoreduced at varying levels in order to establish a LR (per our institutional guidelines and standards), a partially leukoreduced (PLR) and a NLR unit, which were then considered "donors". The 4th unit was divided to generate two separate "recipients". The first half was left untreated simulating an immunocompetent recipient while the other was leukoreduced to mimic a leukopenic recipient. Based on a 70 kg patient, we calculated the volume of blood from each "donor" to mix with aliquots of each "recipient" to represent a transfusion of 2, 5, or 16 units, with 2 units corresponding to a double apheresis red blood cell (RBC) transfusion and 16 units corresponding to a near total volume transfusion. DNA was extracted from each individual unit as well as all "transfused" combinations within 24 hours of mixing. Chimerism analysis was then performed by STR analysis using the GlobalFiler PCR amplification kit followed by ChimerMarker analysis software. Results: None of the LR units, despite volume transfused, revealed any level of microchimerism in either the immunocompetent or leukopenic "recipients". The PLR transfused combinations displayed levels ranging from 0.14% to 1.52% of donor chimerism for the immunocompetent "recipient", which is below the limit of detection for most clinical assays evaluating germline genetic variation, and 6.3% to 27.78% of donor chimerism for the leukopenic "recipient", which would be expected to impact a subset of clinical genetic assays. The NLR transfused combinations displayed levels ranging from 13.28% to 95.66% of donor chimerism. Discussion:In vitro "transfusion" of LR RBCs into simulated immunocompetent or leukopenic samples does not lead to detectable donor DNA. However, "transfusion" of PLR and NLR units in an in vitro model reveals significant levels of microchimerism dependent on volume transfused and immune status of the "recipient" which implies possible risk for impact on clinical genetic tests. The minimum time required for clearance of donor leukocytes in the recipient is unknown; we were unable to fully evaluate this and other variables in our in vitro system, but follow-up in vivo studies addressing this question are planned. Disclosures No relevant conflicts of interest to declare.

Introduction Approximately 20% of patients (pts) with classical Hodgkin lymphoma (cHL) are age ≥ 60 years (yrs) at diagnosis (dx). Standard anthracycline-based therapies (ABTx) have historically shown lower efficacy and greater toxicity in this older population compared with younger pts, especially for unfit or frail pts. However, prior analyses have pre-dated the use of brentuximab vedotin (BV) and other novel targeted agents in the front-line setting and there remains no clearly defined or unified standard of care for this pt population. Studies in older lymphoma pts have also defined specific categories of pt fitness that may potentially guide therapy, although continued validation of these definitions in cHL are needed. We performed a large, multicenter retrospective study to identify current practice patterns in the US in older untreated cHL pts with specific attention to pt fitness using established definitions and to outcomes with ABTx versus non-ABTx. Methods Following IRB approval at each site, detailed pathologic and clinical data, including geriatric assessments (GAs) for the latter, were collected across 10 US academic medical centers. Eligible pts included: cHL dx on or after 1/1/2010, age ≥ 60 yrs at dx, and no preceding hematologic malignancy. Subjects with inadequate clinicopathologic and outcomes data or with dx other than cHL were excluded. A multivariable Cox proportional hazards model was developed to study the association of PFS and OS with various factors of interest, and survival rates were estimated by Kaplan-Meier using SPSS. Associations were considered significant for two-sided P values ≤ 0.05. Results Among 254 eligible older cHL pts with newly diagnosed disease, clinical features included: median age 67 yrs (range 60-90+), 54% male, 64% stage III/IV, 46% B symptoms, and 86.1% ECOG PS 0-1. 68.9% had nodular sclerosis, 18.9% mixed cellularity, and 12.2% other subtypes; EBV was detectable by IHC or peripheral blood in 39.3% of evaluable cases (n=98). In terms of geriatric measures, 31 pts (12.2%) had loss of at least one ADL; 40 (15.8%) had a geriatric syndrome; and 16 (6.3%) had both. Of note, only one pt underwent a comprehensive GA prior to treatment. Using established fitness definitions in lymphoma (Tucci et al, 2015), pts were classified as "Fit" (n=129; 50.8%), "Unfit" (n=8; 3.2%), or "Frail" (n=112 (44.1%); 5 (2%) were unclassifiable due to incomplete data (Table 1). Front-line regimens included ABVD (n=145; 57.1%), AVD (n=33; 13.0%), and CHOP (n=18; 7.1%). 6 pts (2.4%) received BV monotherapy; 21 (8.3%) received BV with AVD, the latter either concurrently (N=11) or sequentially (n=10). 11 pts did not receive systemic tx, of whom 9 received radiation alone; 58 pts received radiation with systemic tx. ABVD recipients received an average of 7.4 doses of bleomycin (range 1-14) and 18.4% (n=26) had pulmonary toxicity. In addition, 56.7% (n=130) of pts experienced at least one tx-related toxicity, which was similar across all fitness groups (Table 1). 15.1% (n=38) of pts stopped tx due to toxicity, which was noted more often in "frail" pts though it was relatively uncommon. 11 pts (4.3%) experienced treatment-related mortality (TRM). Compared with pts receiving non-ABTx, ABTx was associated with significantly improved PFS (HR 0.391, P=0.008) and OS (HR 0.195, P=0.0004). ECOG PS >1 was associated with inferior PFS (HR=1.96, P=0.017) and OS (HR=3.09, P=0.002). Pts defined as "frail" had no apparent difference in PFS compared with fit pts (Figure 1A;P=0.169), although decreased OS was seen (Figure 1B; P=0.01). Discussion To the best of our knowledge, these data represent one of the largest analyses of older cHL pts in the modern era. Our real-world analysis shows that in those who are able to receive them, anthracyclines provide meaningful survival benefit in this older cHL patient population and can be well-tolerated for many pts. The impact of dose intensity and backbone regimen are not yet known. In addition, current definitions of "fitness" incompletely identified pts at risk for poor outcomes or greater toxicity. Further studies are planned to better delineate fitness in this population. Disclosures Bartlett: Celgene: Research Funding; ADC Therapeutics: Consultancy, Research Funding; Affimed: Research Funding; Merck: Research Funding; Janssen: Research Funding; Immune Design: Research Funding; Gilead: Research Funding; Millenium: Research Funding; Pfizer: Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Research Funding; Forty Seven: Research Funding; Genenetech: Research Funding; Bristol-Myers Squibb: Research Funding. Grover:Seattle Genetics: Consultancy. Bennani:Adicet Bio: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Adicet Bio: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Purdue Pharma: Other: Advisory board; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Kite Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board. Hill:Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria; Celegene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Amgen: Research Funding; TG therapeutics: Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Research Funding. Advani:Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gilead Sciences, Inc./Kite Pharma, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium: Research Funding; Kura: Research Funding; Janssen: Research Funding; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bayer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Merck: Research Funding; Regeneron: Research Funding; Infinity Pharma: Research Funding; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Celmed: Consultancy, Membership on an entity's Board of Directors or advisory committees; Forty-Seven: Research Funding; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Kyowa Kirin Pharmaceutical Developments, Inc.: Consultancy; Agensys: Research Funding; Stanford University: Employment, Equity Ownership; Seattle Genetics: Consultancy, Research Funding; Cell Medica, Ltd: Consultancy; AstraZeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Svoboda:AstraZeneca: Consultancy; Celgene: Research Funding; Incyte: Research Funding; Pharmacyclics: Consultancy, Research Funding; Kyowa: Consultancy; Merck: Research Funding; BMS: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding. Magarelli:Tevan Oncology: Speakers Bureau. Feldman:Takeda: Honoraria, Speakers Bureau; Celgene: Honoraria, Research Funding, Speakers Bureau; Seattle Genetics: Consultancy, Honoraria, Other: Travel expenses, Speakers Bureau; AbbVie: Honoraria, Other: Travel expenses, Speakers Bureau; Pharmacyclics: Honoraria, Other: Travel expenses, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Kite Pharma: Honoraria, Other: Travel expenses, Speakers Bureau; Bayer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Cell Medica: Research Funding; Roche: Research Funding; Corvus: Research Funding; Eisai: Research Funding; Kyowa Hakko Kirin: Research Funding; Pfizer: Research Funding; Portola Pharma: Research Funding; Roche: Research Funding; Trillium: Research Funding; Viracta: Research Funding. Cohen:Astra Zeneca: Research Funding; ASH: Research Funding; UNUM: Research Funding; Hutchison: Research Funding; Takeda Pharmaceuticals North America, Inc.: Research Funding; Gilead/Kite: Consultancy; Lymphoma Research Foundation: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics, Inc.: Consultancy, Research Funding; Bristol-Meyers Squibb Company: Research Funding; Janssen Pharmaceuticals: Consultancy; Genentech, Inc.: Consultancy, Research Funding. Evens:Seattle Genetics: Consultancy, Honoraria, Research Funding; Tesaro: Research Funding; Epizyme: Consultancy, Honoraria; Verastem: Consultancy, Honoraria; Pharmacyclics: Consultancy, Honoraria. Portell:AbbVie: Research Funding; Pharmacyclics: Consultancy; Janssen: Consultancy; Genentech: Consultancy, Research Funding; Amgen: Consultancy; Bayer: Consultancy; BeiGene: Consultancy, Research Funding; Kite: Consultancy, Research Funding; Acerta/AstraZeneca: Research Funding; TG Therapeutics: Research Funding; Xencor: Research Funding; Roche/Genentech: Research Funding; Infinity: Research Funding.

Abstract With increasing epidemiological and biological studies on meningiomas, standardized clinical data capture will be necessary to interpret results across studies and to translate them to clinical practice. To meet this need for consistent clinical data capture, the International Consortium on Meningioma, has developed a set of common data elements (CDEs), to be used across clinical and biological research. Building from terminology used in clinical practice and ongoing studies, we used a consensus-of-experts approach to arrive at a set of standardized and vetted data elements. Areas of focus include patient characteristics, patient history, radiological and intra-operative description, histological diagnosis and molecular testing, non-surgical interventions, and surveillance. These data elements are implemented in Research Electronic Data Capture (REDCap) forms. With REDCap implementation, components of the CDE set can be selected and instituted in a local REDCap instance for efficient study start-up. The scope of the current CDE set focuses on surgically treated meningioma. However, modular forms provide flexibility and to allow the scope to be expanded to include non-surgically treated meningioma. Dissemination plans are underway to introduce the CDEs to neuro-oncology researchers and clinicians through publication and presentations, where feedback will be solicited. Adoption of CDEs for research will improve consistency and interpretability across studies, expediting research in this frequently occurring tumor.

Abstract Premalignant states are known to precede malignancy in many different cancers, including multiple myeloma (MM). Each year, 1% of Monoclonal Gammopathy of Undetermined Significance (MGUS) patients and 10% of Smoldering Multiple Myeloma (SMM) patients transition to symptomatic MM, which remains an incurable disease. By identifying patients at imminent risk (within 2 years) of progression to MM, treatment could begin early and potentially prevent full blown MM and associated morbidity and mortality. Multiple risk-factor models are currently utilized to identify patients at high-risk of developing MM. Commonly cited risk factors include percentage of bone marrow plasma cells, free light chain ratio, serum levels of M-protein, IgG subtype and levels of circulating plasma cells. These tests have individual and combined merit but there remains no consensus for measuring imminent risk of MM progression. To determine whether serum proteomics could help predict progression or provide information on relevant pathways involved in progression to MM, we evaluated 200 MGUS and SMM (187 non-IgM) patient samples on the Myriad DiscoveryMAP(r) platform (250+ serum proteins), supplemented by demographic and clinical information. Of the 187 non-IgM patients, 100 progressed to MM within 2 years (high-risk), and 87 did not progress to MM within 5 years (low-risk). We performed different subset analyses to screen for proteins that were informative and predictive of disease progression from MGUS/SMM to MM. First, a univariate Wilcoxon rank sum test was performed. The top 10 proteins that were found to be differential between high-risk/low-risk for all MGUS and SMM patients were IgM, Progesterone, MCP-2, Kallikrein-5, FGF4, EPO, MCP-4, MIP-1β, MCP-1, and TF. Interestingly, when analyzing MGUS and SMM patients separately, additional proteins that were important in distinguishing high-risk/low-risk patients included IgM, EN-RAGE, BAFF, and several others previously shown to be relevant in MM, as well as a handful of novel proteins with unidentified roles in MM. Second, to determine whether specific combinations of proteins could be utilized together to define high/low-risk, a classification tree was assembled. The combination of 8 features (IgM, Progesterone, Aldose Reductase, E-Selectin, Fas Ligand, Hemoglobin, Age and Creatine kinase-MB) appropriately classified 86% of the 187 patients into high/low-risk. Future analyses will include examining this high/low risk classifier in contrast to current risk factor models, and application to two additional sets of similar patient samples that serve as an independent validation set. Disclosures: No relevant conflicts of interest to declare.

Abstract Autologous stem cell transplantation (ASCT) remains an important consolidation treatment for multiple myeloma (MM) patients, even in the era of novel agents. The prolongation of plateau-phase induced by ASCT is generally attributed to intensive cytoreduction. However, ASCT generates inflammation and profound lymphodepletion, which may result in hitherto unexpected immunological effects. To investigate potential immunological contributions to myeloma control after ASCT, we developed preclinical models of transplantation for MM using Vk*MYC myeloma that generates bony lytic lesions, a serum M band and marrow plasmacytosis that are hallmarks of clinical disease. Myeloma-bearing B6 recipients underwent myeloablative conditioning and were transplanted with naïve B6 bone marrow (BM) grafts with or without T cells from donors that were myeloma-naïve (SCT) or had low M bands at the time of harvest to mimic ASCT. Surprisingly, we demonstrate the broad induction of T cell-dependent myeloma control with enhanced median survival in recipients of grafts containing T cells compared to T cell depleted (TCD) BM alone (SCT= 91 days and ASCT > 100 days post-transplant vs TCD BM alone= 44 days; p<0.0001). Myeloma was most efficiently controlled when recipients were transplanted with memory T cells (CD44+) from autologous grafts (median survival: ASCT-CD44+ T cells >90 days post-transplant vs. CD44─ T cells = 50 days; p = 0.0006). Importantly, T cells adoptively transferred from recipients surviving > 120 days (MM-primed) protected secondary recipients compared to T cells from naïve donors (median survival: MM-primed > 120 days post-transplant vs 65 days naïve T cells; p = 0.0003). Furthermore, MM-primed CD8 T cells were restricted in TCR repertoire and provided protection in a myeloma clone-specific fashion, indicative of a tumor-specific T cell response. Despite this immune-mediated control of myeloma after SCT, progression still occurred in the majority of recipients. We phenotyped CD8+ T cells from the BM of MM-relapsed, MM-controlled and MM-free (that had never seen myeloma) mice 8 weeks after SCT. Expression of the inhibitory receptors, programmed cell death protein 1 (PD-1) and T cell immunoreceptor with Ig and ITIM domains (TIGIT) on BM CD8+ T-cells strongly correlated with myeloma cell number (r = 0.729, p<0.0001 and r = 0.796, p<0.0001 respectively). Additionally, the co-stimulatory/adhesion receptor CD226 (DNAM-1) was markedly downregulated as myeloma progressed (r = - 0.865, p<0.0001), as was interferon-γ secretion (r = - 0.76, p = 0.0022). t-SNE analysis confirmed an irreversible exhaustion signature at myeloma progression, characterized by the absence of DNAM-1 and co-expression of PD-1, TIM-3, TIGIT together with CD101 and CD38. Immune-checkpoint inhibition (CPI) early post-SCT, using antibodies against PD-1 or TIGIT facilitated long-term myeloma control (median survival in both treatment arms > 120 days post-SCT vs. 60 and 68 days respectively; p <0.05). Furthermore, TIGIT blockade limited CD8+ T cell exhaustion, increased CD107a and IFNγ secretion and expanded a memory CD8+ T cell population in the BM. Genetic deletion of either IFNγ or the IFNγ receptor from the donor graft resulted in dramatic myeloma progression after SCT. Consequently, treatment with a CD137 (4-IBB) agonist early after SCT profoundly augmented CD8+IFNγ+GranzymeB+ T-cell expansion in the BM, such that majority of treated animals eliminated myeloma and survived long-term. These data provide insights into an unappreciated mechanism of action of ASCT whereby myeloma immune-equilibrium is established and suggest that combination with immunotherapeutic strategies is a rational approach to generate long term disease control. Disclosures Smyth: Bristol Myers Squibb: Other: Research agreement; Tizona Therapeutics: Research Funding.

Abstract Background BMS-911543 is an oral, selective small-molecule inhibitor of JAK2 (IC50=1.1nM) with potent anti-proliferative and pharmacodynamic effects in cell lines and in vivo models dependent upon JAK2 signaling. In vitro, BMS-911543 demonstrates high selectivity within the JAK family (JAK1 [IC50=356nM], JAK3 [IC50=73nM] or TYK2 [IC50=66nM]) and across a large kinase panel (at 1 µM concentration of BMS-911543, only 8 of 451 kinases were markedly inhibited [≥67%]) It also has little activity in cells dependent on other JAK family pathways. Anti-proliferative responses were observed with BMS-911543 in colony growth assays using primary progenitor cells isolated from patients with JAK2V617F-positive polycythemia vera (PV) (Leukemia 2012;26:280). Methods In a multicenter phase 1/2a study, BMS-911543 was administered orally using a BID dosing schedule, in patients with high-, intermediate-2 or intermediate-1 risk symptomatic primary or secondary MF (JAK2 WT or mutant) with platelet counts ≥50,000/mm3. Patients were not required to have palpable splenomegaly. The aim of the study is to determine safety, maximum tolerated dose (MTD), pharmacokinetics, pharmacodynamics, and preliminary efficacy of BMS-911543. Safety was assessed using NCI-CTCAE version 4.0. Treatment effect was assessed using the International Working Group (IWG) response criteria, MF-SAF, BFI, physical examination, spleen and liver volume assessment by MRI, bone marrow morphology, karyotype, V617F mutant allele burden, plasma cytokine analysis, circulating CD34+ cells and other molecular parameters. Current status To date, 84 patients have been treated (dose escalation [n=42]; dose expansion [n=42]) and the maximum tolerated dose (MTD) was defined as 200mg BID. The summary below represents an interim data analysis of 36 patients from the dose escalation phase dosed at 5, 10, 20, 40, 80, 120, 160, and 200mg BID. Fifteen of 36 (42%) patients had received prior Jak inhibitors (Jaki) including 3 who had received ≥2 Jak inhibitors. PK, PD, Safety, Tolerability and Efficacy After repeat dosing, greater than dose-proportional increase in the Cmax and AUC, and drug accumulation was observed at doses ≥40mg BID. PD analysis indicated inhibition of JAK/STAT pathway signaling activity in peripheral blood mononuclear cells, and modulation of several soluble peripheral blood proteins including IL-6, EPO and Leptin. Eleven patients (31%) had drug-related AEs. The nine hematological AEs included 3 anemia (1 grade 3 and 2 grade 2); 3 neutropenia (grade 4); and single leukopenia (grade 4), thrombocytopenia (grade 4), and reduction in platelet count (grade 2). Nine non-hematological AEs included 3 nausea (grade1/2); amylase increased (grade 3) and lipase increased (grade 3) one each; and grade 1 fatigue, muscle spasms, insomnia, erectile dysfunction one each. Ten patients (28%) discontinued treatment: 4 were attributed to disease progression, 2 to lack of efficacy, 2 at patient’s request, 1 to poor compliance, and 1 to unrelated AE. Spleen volume reductions (SVR) by MRI were observed in Jaki failure and in Jaki naive patients. Of 11 patients treated at 160 and 200mg, 8 patients (73%) had SVR greater than 35% at 3 months. In contrast, 1 of 4 patients treated at 120mg and none treated below 120mg had SVR greater than 35%. Of the patients treated at 160mg and 200mg, more than 50% had MF-SAF reductions > 50%. Overall, 3 patients (8.3%; 2 treated at 10mg BID and 1 at 200mg BID) had an increase in hemoglobin of ≥2g/dL;. Other signs of clinical activity included reductions in V617F mutant allele burden, leukocytosis, leukoerythroblastosis, circulating CD34+ cells, and LDH. Conclusion BMS-911543 was generally well tolerated and has an acceptable safety and efficacy profile. BMS-911543 induced rapid control of constitutional symptoms, and splenomegaly in patients with symptomatic MF, including those previously treated with one or more Jak inhibitors. Updated data from all 84 patients who have been treated in the dose escalation and ongoing expansion phases, including MRI assessments of spleen and liver volume, V617F mutant allele burden and levels of select plasma cytokines, will be presented.</abstract> Disclosures: Pardanani: JW Pharmaceutical Corp.: Clinical trial support, Clinical trial support Other; PharmaMar: Clinical trial support, Clinical trial support Other; Sanofi: Clinical trial support, Publication support services, Clinical trial support, Publication support services Other; Bristol Myers Squibb: Clinical trial support Other. Off Label Use: Use of BMS-911543, Ruxolitinib, Momelotinib, Fedratinib and Pomalidomide for treatment of Myelofibrosis in Clinical Trial setting. Roberts:AbbVie, Inc.: Research Funding; Genentech: Research Funding; Walter and Eliza Hall Institute of Medical Research: Employee, recieves commercial income related to ABT-199, Employee, recieves commercial income related to ABT-199 Other, Employment. Seymour:Genentech: Consultancy, Membership on an entity’s Board of Directors or advisory committees. Verstovsek:Incyte Corporation: Research Funding. Yoshitsugu:Bristol-Myers Squibb: Employment, Equity Ownership. Gestone:Bristol-Myers Squibb: Employment, Equity Ownership. Phillips:Bristol-Myers Squibb: Employment, Equity Ownership. Xing:Bristol-Myers Squibb: Employment, Equity Ownership. Peltz:Bristol-Myers Squibb: Employment, Equity Ownership. Lorenzi:Bristol-Myers Squibb: Equity Ownership, Former employment Other. Alland:Bristol-Myers Squibb: Employment, Equity Ownership. Woolfson:Bristol-Myers Squibb: Equity Ownership, Former employment Other.

Abstract Introduction: Daratumumab is a human CD38 IgGκ monoclonal antibody that demonstrated significant activity and a manageable safety profile in combination with bortezomib and dexamethasone. In a randomized phase 3 study, daratumumab in combination with bortezomib and dexamethasone (DVd) significantly prolonged progression-free survival (PFS) versus bortezomib and dexamethasone alone (Vd) in a pre-specified interim analysis of patients (pts) with relapsed or refractory multiple myeloma (RRMM; Palumbo A. N Engl J Med 2016; in press). Herein, we examine subgroups from this study to compare the efficacy of DVd vs Vd in bortezomib-naive and bortezomib-experienced pt populations. In addition, the efficacy of DVd vs Vd in pts who were refractory to lenalidomide at last prior line of therapy was also evaluated. Methods: Pts who received ≥1 prior line of therapy were randomized (1:1) to 8 cycles (q3w) of Vd (bortezomib: 1.3 mg/m2 SC on Days 1, 4, 8, 11; dexamethasone: 20 mg PO on Days 1, 2, 4, 5, 8, 9, 11, 12) with or without daratumumab (16 mg/kg IV qw in Cycles 1-3, Day 1 of Cycles 4-8, then q4w until progression). Pts who were refractory to bortezomib were not eligible. The primary endpoint was PFS. Bone marrow aspirate samples that had been prepared with Ficoll were evaluated for minimal residual disease (MRD) using three different thresholds (10-4, 10-5, and 10-6) based on the ClonoSEQ assay (Adaptive Biotechnologies, Seattle, WA, USA). Results: Median follow-up was 7.4 months. Among bortezomib-naive pts (DVd, n=89; Vd, n=83), PFS was significantly improved with DVd vs Vd (median: not reached [NR] vs 7.5 months; HR, 0.25; 95% CI, 0.13-0.47; P&lt;0.0001); estimated 12-month PFS rates were 72% vs 28%, respectively. ORR was 88% with DVd vs 70% with Vd (P=0.0040), with ≥very good partial response (VGPR) rates of 72% vs 42% (P&lt;0.0001), and ≥complete response (CR) rates of 30% vs 20% (P=0.1199), respectively. For pts who previously received a bortezomib-containing regimen (DVd, n=162; Vd, n=164), PFS was also significantly longer with DVd vs Vd (median: 12.3 vs 6.7 months; HR, 0.46; 95% CI, 0.32-0.66; P&lt;0.0001). Estimated 12-month PFS rates were 55% vs 27%, respectively. ORR was significantly higher with DVd vs Vd (80% vs 60%; P=0.0001), along with significantly higher rates of ≥VGPR (52% vs 22%; P&lt;0.0001) and ≥CR (13% vs 3%; P=0.0019). Among pts who were refractory to lenalidomide at the last prior line of therapy (DVd, n=45; Vd, n=60), PFS was significantly longer in DVd vs Vd (median: 10.3 vs 4.4 mo; HR, 0.37; 95% CI, 0.21-0.65; P=0.0004; Figure). Within this subgroup, ORR was significantly higher for DVd vs Vd (81% vs 50%; P=0.0021), and the same trends were observed for rates of ≥VGPR (54% vs 12%; P&lt;0.0001) and ≥CR (20% vs 5%; P=0.0261). Updated efficacy and safety data, including MRD analyses across different sensitivity thresholds (10-4, 10-5, and 10-6), will be presented at the meeting. Conclusions: These analyses confirm that addition of daratumumab to Vd significantly improves outcomes for RRMM pts regardless of prior treatment with bortezomib. Importantly, this treatment benefit of DVd vs Vd was maintained in pts who were refractory to lenalidomide at the last prior line of therapy. These data lend further support to adding daratumumab to a standard-of-care regimen in RRMM. Figure Progression-free Survival in Patients Refractory to Lenalidomide at the Last Prior Line of Therapy Figure. Progression-free Survival in Patients Refractory to Lenalidomide at the Last Prior Line of Therapy Disclosures Lentzsch: BMS: Consultancy; Foundation One: Consultancy; Celgene: Consultancy, Honoraria. Quach:Celgene: Membership on an entity's Board of Directors or advisory committees; Janssen Cilag: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Ovilla:Janssen: Consultancy. Qi:Janssen: Employment. Deraedt:Janssen: Employment, Equity Ownership. Schecter:Janssen: Employment, Equity Ownership. Amin:Janssen: Employment. Qin:Janssen: Employment. Casneuf:Johnson & Johnson: Equity Ownership; Janssen R&D, Beerse, Belgium: Employment. Chiu:Janssen: Employment. Sasser:Johnson & Johnson: Equity Ownership; Janssen Pharmaceuticals R&D: Employment. Sonneveld:Karyopharm: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding.