Ailawadhi, Sikander

Abstract The objective of the study was to assess racial disparities in the treatment and outcomes among white, African American, and Hispanic patients with multiple myeloma (MM). Patients with an MM diagnosis from the Surveillance Epidemiology and End Results (SEER)–Medicare (2007-2013) database were included. Continuous Medicare enrollment for 6 months before (baseline) and after MM diagnosis was required unless death occurred. Time from MM diagnosis to novel therapy initiation and autologous stem cell transplant (ASCT), overall survival (OS), and MM-specific survival (MSS) was evaluated. Unadjusted and multivariable regressions compared African Americans and Hispanics vs whites. Trends of novel therapy and ASCT use across MM diagnosis years were assessed using linear regression models. The study included 3504 whites, 858 African Americans, and 468 Hispanics. African Americans and Hispanics had a longer time from MM diagnosis to novel therapy initiation vs whites (median: 5.2 and 4.6 vs 2.7 months, respectively). All cohorts had an increasing trend of novel therapy initiation within 6 months of MM diagnosis, particularly whites (all P < .05). Median MSS was significantly longer for African Americans (5.4 years) than whites (4.5 years; P < .05), and was comparable for Hispanics and whites. Median OS was similar overall (2.6-2.8 years). ASCT rate within 1 year of MM diagnosis rose among whites and African Americans (P < .05), but not Hispanics, who were less likely to receive ASCT vs whites. Significant variations in novel therapy and ASCT use were observed among different racial/ethnic groups with MM. Although OS was similar, both African Americans and Hispanics may not be fully benefitting from the introduction of novel therapies, as they receive them later than whites.

Abstract Introduction Waldenstrom macroglobulinemia (WM) is a rare disease accounting for only 1-2% of all hematologic malignancies and with an overall annual, age-adjusted incidence of approximately 3.5 to 5.5 cases per million-person years. With approximately 13,000 active hematologist/oncologists in the US, most of who are in the community oncology setting, it's estimated that a hematologist/oncologist will only diagnose a WM case approximately every 8 years. Therefore, the clinical experience of a general hematologist/oncologist in the management of WM is likely very limited compared to more prevalent malignances. Previous studies in the setting of rare cancers suggest a correlation between higher volume of care and improved outcomes. Therefore, we explored the volume-outcome relationship in WM using the National Cancer Data Base (NCDB). Methods Patient-level data from the NCDB, a nationwide, facility-based, database covering approximately 70% of all newly diagnosed cancer cases in the US, was queried for all new WM cases diagnosed between 2004 and 2014. Only patients requiring treatment were included. Treatment facilities were divided into quartiles based on the average annual volume of newly diagnosed cases of WM seen. Cox regression was used to analyze the association between facility WM volume and survival, adjusted by demographics (sex, age, race), socioeconomic status (income, education, insurance type), geography (area of residence, treatment facility type, travel distance), comorbidity factors (Charlson-Deyo score), and year of diagnosis. Time-to-event analysis was calculated from frontline therapy initiation date using the Kaplan-Meier method and the log-rank test. Results A total of 3,732 patients with WM treated in 831 facilities were included. The median age at diagnosis was 70 years and 75% of the patients were treated within 20 miles from their residency zip code. Patient characteristics per treatment facility volume quartile are shown in table 1. The median annual facility volume was 1 new WM patient/year (range 0.1 to 21). The median follow-up from frontline treatment was 5 years. The unadjusted median OS by facility volume was: Q1: 6.5 years (95% CI: 5.7-7.4), Q2: 7 years (95% CI: 6.3-8.2), Q3: 8.2 years (95% CI: 7.1-8.9), and Q4: NR (95% CI: 8.5-NR), p<0.0001 (figure 1). The estimated 5-year OS by facility volume was: Q1: 56%, Q2: 61%, Q3: 64%, Q4: 71%, p<0.0001. Multivariate analysis including all variables showed in Table 1 demonstrated that facility volume was independently associated with all-cause mortality. Compared to patients treated at Q4 facilities, patients treated at lower-quartiles facilities had a higher incremental risk of death (Q3 hazard ratio [HR], 1.07 [95% CI: 0.88 to 1.29] p=0.46; Q2 HR, 1.34 [95% CI: 1.11 to 1.63] p=0.002; Q1 HR, 1.52 [95% CI: 1.23 to 1.88] p=<0.0001). Conclusion Our results suggest that a volume-outcome relationship exits in WM as patients treated initially at higher-volume facilities had a lower risk of mortality. Although differences in the underlying disease biology, referral patterns after initial therapy, or cumulative treating-physician experience could not be assessed, these potential biases would only underestimate the magnitude of the volume-outcome relationship reported. Disclosures Ansell: Celldex: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Pfizer: Research Funding; Affimed: Research Funding; Merck & Co: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding. Gertz:Medscape: Consultancy; janssen: Consultancy; Alnylam: Honoraria; Ionis: Honoraria; Physicians Education Resource: Consultancy; Prothena: Honoraria; Teva: Consultancy; Research to Practice: Consultancy; spectrum: Consultancy, Honoraria; celgene: Consultancy; Amgen: Consultancy; Abbvie: Consultancy; annexon: Consultancy; Apellis: Consultancy. Kapoor:Takeda: Research Funding; Celgene: Research Funding. Ailawadhi:Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Research Funding; Celgene: Consultancy; Takeda: Consultancy. Reeder:Affimed: Research Funding. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Lacy:Celgene: Research Funding. Kumar:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Background: Multiple myeloma (MM) is characterized by the invasion of malignant plasma cells into the bone marrow. While first line treatment options result in significant clinical benefit to patients, spatiotemporal clonal evolution results in disease relapse and mortality. Advances in genomics have armed clinicians with unprecedented insight into the molecular architecture of MM cells, however, the clinical benefit derived by genomics-guided intervention has been limited. We present a novel computational biology modelling (CBM) tool, which takes into account the combined effect of individual mutations, gene copy number abnormalities and large scale chromosomal changes in order to predict the salient molecular pathways utilized by the MM cell for survival. By reverse-engineering MM cell architecture in silico, the CBM tool is able to predict drug response and resistance mechanisms. Thus, our aim was to determine the accuracy of the CBM tool in predicting treatment response of relapsed/refractory MM patients for future management of their disease, in a more individualized manner. Methods: Cytogenetics and somatic mutations (by targeted NGS) for 15 MM patients were input into the CBM model to predict responses to different therapeutic combinations. All patients were relapsed to prior treatment. CBM uses PubMed and other online resources to generate patient-specific protein network maps of activated and inactivated disease pathways. We simulated the specific combinations of the drugs per patient and measured the quantitative drug effect on a composite MM disease inhibition score (i.e., cell proliferation, viability, apoptosis and paraproteins). The actual clinical outcome of the treatments was compared with predicted outcomes. Results: Fifteen patients were analysed using CBM for prediction of treatment response after NGS was performed. 13/15 were clinically evaluable, of which 1 was a responder and 12 were non-responder. 6/13 patients were treated on clinical trial and 7/13 were on drug combinations per physician decision. CBM correctly predicted 1 responder and 11 non-responder with a PPV of 50%, NPV 100%, specificity 91.67%, sensitivity 100%. The accuracy of CBM prediction was 92.30%. CBM also predicted the response of prior drug therapies for its non-response at relapse. For prior drug treatment options, 14 patients were evaluable. All the 14 patients were clinically non-responders and CBM correctly predicted for 13 patients with NPV 100%, Specificity 92.85% and overall accuracy of 92.85%. The majority of patients did not respond to therapies recommended at relapse. As an example, the operative molecular pathways from 2 patients who did not respond to combination treatment, either pre-NGS or post-NGS profiling, are shown in Fig. 1 and Table 1. CBM identified amplification (AMP) of chromosome (chr) 1 (WNT3A, IL6R, CKS1B, MCL1, PIK3C2B, USF1), chr 3 (HES1, PIK3CA, CTNNB1, WNT7A, FANCD2), chr 5 (IL6ST, IRF1, GLRX, SKP2), chr 7 (CDK5, EZH2, IL6, CAV1, ABCB1), chr 9 (NOTCH1, HSPA5, FANCC, FANCG), chr 15 (DLL4, FANCI, ALDH1A2), chr 19 (ERCC1, ERCC2, USF2); deletion(DEL) of chr 13 (CUL4A) , chr 16 (AXIN1, CDH1) and TP53 mutation in different combinations, which confer resistance to therapies at relapse. Conclusions: The CBM technology represents a potential means to identify therapeutic options for MM patients based on the patients individual tumor-genome profile and which can also be deployed for uncovering drug resistance mechanisms. This tool may aid clinicians in decision making for recommending the most appropriate therapy based on standard of care agents or clinical trials; thus improving patient outcomes and reducing unnecessary costs or drug-related toxicities. Disclosures Singh: Cellworks Research India Private Limited: Employment. Sauban:Cellworks Research India Private Limited: Employment. Husain:Cellworks Research India Private Limited: Employment. Kumar:Cellworks Research India Private Limited: Employment. Kumari:Cellworks Research India Private Limited: Employment. Tyagi:Cellworks Research India Private Limited: Employment. Abbasi:Cell Works Group Inc.: Employment. Vali:Cell Works Group Inc.: Employment. Ailawadhi:Pharmacyclics: Research Funding; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Janssen: Consultancy.

Abstract Background: Therapeutic advancements have led to significant improvement in outcomes for MM patients. Revised diagnostic criteria from International Myeloma Working Group focus on initiating treatment before the onset of end-organ damage. Thus, timeliness of initial therapy can significantly improve patient morbidity and outcomes. Such an analysis has not been reported for MM. Methods: We analyzed patients diagnosed with MM between 2004-2015 from the National Cancer Database (NCDB). Patients who received systemic treatment any time within the first year of diagnosis were included; those treated later than one year were considered possibly initially diagnosed with smoldering myeloma and hence, excluded. Time to initial treatment was divided into centiles with the 4 centiles analyzed being 0-7 days, 8-18 days, 19-37 days and >37 days. We performed univariate and multivariate analyses to compare sociodemographic and clinical factors influencing patient distribution across these timeliness categories and trends over time. Results: A total of 53,665 patients were included with 15,282 in 0-7 days, 12,462 in 8-18 days, 12,723 in 19-37 days and 13,198 in the >37 days treatment categories. Distribution across these centiles over time is shown in Figure. Univariate analyses showed a significant difference in distribution across the timeliness categories by year of diagnosis, patient age, gender, race/ethnicity, education level, insurance type, comorbidity score, treatment facility type, geographical location and distance to treating facility (all p<0.001) but no effect of income level. Multivariate analysis showed that there was a significantly higher likelihood of being in 4th centile (>37 days to treatment) for women (p<0.001), African Americans (p<0.001) or Hispanics (p=0.03; reference: Whites) or diagnosed in more recent years (p<0.001). Patients were less likely to be in the 4th centile if they were ≥80 years (HR 0.89, 95% CI 0.81-0.98, p=0.02), had >0 Charlson comorbidity score (p<0.001), were uninsured (p=0.02) or had Medicaid (p=0.03) as compared to having private insurance, were in non-community treatment facilities or geographical location other than Northeast (p<0.001). Patient education, income level or distance from treating facility was no longer significant. Conclusions: Several factors were found to affect timeliness of treatment in MM. We noted relatively faster time to initial treatment in elderly, uninsured or those who were treated in academic/comprehensive cancer programs but a delay in treatment for women and racial/ethnic minorities among other factors. These factors need to be addressed for equitable access and treatment practices and to realize improved outcomes for all. Figure. Figure. Disclosures Ailawadhi: Amgen: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Pharmacyclics: Research Funding.

Abstract INTRODUCTION: Significant burden of pain syndromes are reported in patients with hematological malignancies undergoing HSCT mostly due to underlying disease and associated treatments. Opioid analgesics and benzodiazepines are routinely used for symptomatic management in this patient population. The use of narcotic analgesics and benzodiazepines in non-transplant hospitalized patients has been shown to adversely affect health related outcomes such as length-of-stay (LOS), falls and other complications. However, there is a significant knowledge gap regarding the patterns of opioid and benzodiazepine use and their impact on health outcomes in HSCT patients. METHODS: We identified 275 patients from the year 2015-2018 who underwent HSCT (allogeneic and autologous transplants) at our center for a variety of hematological malignancies. Opioid exposure was defined in three groups of patients 1) Opioid naïve: those did not report prior use of opioid at admission and who were not prescribed opioid during hospitalization, 2) Previous Opioid users: those who reported active use of opioid at admission and continued during hospitalization 3) New Opioid users: Patients who did not report opioid use at admission but were prescribed opioid during hospitalization. Multivariable analysis was performed to identify differences in opioid status, opioid use, benzodiazepine use, disease diagnosis, Karnofsky score, gender, age, race, and marital status with associated complications (Poisson regression), emergency department visits (Logistic Regression) and length of stay (Ordinal Logistic Regression) Figure 1 and Figure 2. RESULTS: The median age of patients was 59 (range: 25-74 ) years with slight male predominance (57%). Patients undergoing autologous transplants for multiple myeloma (MM) comprised 48% of the population. The majority (72 %) were exposed to opioid during hospitalization. Ninety two percent of the opioid naïve population (28% of the total population) underwent autologous transplant. Conversely, 36% of patients undergoing autologous transplants never received opiates during hospitalization as compared to 7% of those who received an allogeneic transplant. Median morphine milligram equivalent daily dose was 3.1 mg. Median diazepam equivalent daily dosage in patients that were opiate exposed was 2.07 milligram. Of the total transplant population, 55% received benzodiazepine concurrently with opiates during hospitalization. 76 % of the population was exposed to both opioid and benzodiazepine. Twenty five percent of those who were exposed to opioid did not receive benzodiazepines. Sixty four percent of the MM patients were exposed to opioid of which majority (59%) were previous opioid users. Of the non-MM patients undergoing HSCT, 80% were exposed to opioid of which 36% were previous opioid users and 64% were new users. A wide range of complications from neutropenic fever to death, were seen in 89% of all patients (opioid users and non-users) but all the falls occurred in patients who were on opioid medications. Autologous transplant recipients had higher odds of having a greater number of complications compared to Allogeneic transplant patients (OR 1.25, 95% CI: 1.01 - 1.55, p=0.04), as well as a reduced odds of having a medium or high length of stay (OR 0.03, 95% CI: 0.02 - 0.07). Of the opioid naïve patients, 6% presented to the ED within 30 days of discharge versus 15% of those that were exposed to opiates during hospitalization. Benzodiazepine use at admission for HSCT was associated with greater odd of presenting to ED within 30 days of discharge (OR 3.94, 95% CI: 1.55-10.04) and this was more significant in patients with MM (OR 4.08, 95% CI: 1.01-16.44). Finally, we also saw a trend towards longer stay in patients who were exposed to opioids as compared to opioid naïve (40% vs. 17%). CONCLUSION: Our study, albeit limited due to its retrospective design, is among the first to report the patterns of use and the impact of opioids and benzodiazepines in patients undergoing HSCT. Our results indicate that the use of these medications is frequent in this population and as in the non-transplant hospitalized patients and is associated with more emergency room visits post discharge, along with other potentially adverse outcomes. Disclosures Kharfan-Dabaja: Incyte Corp: Speakers Bureau; Seattle Genetics: Speakers Bureau; Alexion Pharmaceuticals: Speakers Bureau. Ailawadhi:Amgen: Consultancy; Pharmacyclics: Research Funding; Celgene: Consultancy; Takeda: Consultancy; Janssen: Consultancy.

Abstract INTRODUCTION: Treatment of chronic lymphocytic leukemia (CLL) has expanded significantly with the approval of multiple small molecule inhibitors. This is of great significance for patients with adverse cytogenetic features who tend to respond poorly to standard chemo-immunotherapy (CIT). While single agent ibrutinib and venetoclax (V) have shown high rates of overall response, complete remission and minimal residual disease (MRD) eradication rates remain low. This argues for further testing and development of various combination strategies. The MURANO trial compared venetoclax and rituximab (VR) versus bendamustine and rituximab (BR) in patients with relapsed/refractory CLL reporting clear superiority of VR over BR. MRD rates in the bone marrow were reported to be 27.3% for VR versus 1.5% for BR. Given much higher rates of MRD eradication with combination of small molecule inhibitors and monoclonal antibodies (mAb) compared to standard CIT, we performed a comparative investigation into the direct and immune-mediated cytolytic effects of VR versus V + Obinutuzumab (O, type II anti-CD20 mAb) in primary CLL cells and B-lymphoid cell lines. METHODS: CD19+ B-cells were isolated from PBMCs of CLL patients (N=3). For all experiments using primary CLL cells, concentration of VR and VO was 3nM (V) and 10ug /ml (R, O), respectively. For cell lines, VR and VO was used at 5uM (V) and 10ug /ml (R, O), respectively. Apoptosis was determined by annexin-V/PI staining followed by flow cytometry. Antibody-dependent cell-mediated cytotoxicity (ADCC) induced by VR and VO was assessed in Calcein AM labeled CLL cells or cell lines co-cultured with healthy donor PBMCs (E:T ratio, 40:1); complement-dependent cytotoxicity (CDC) was measured using 10% serum from a healthy human donor. RESULTS: We assessed the ability of V+/-O or V+/-R to induce apoptotic cell death in the CD20+ BCWM.1 cell line (Waldenström's macroglobulinemia [WM] phenotype) and the MEC-1 cell line (B-PLL phenotype); with CD20- RPCI-WM1 (WM cells, negative control). Notably, Bcl-2 protein is expressed in all the aforementioned cell lines. We observed that single agent V, O and R induced ~30%, 61% and 13.64% annexin V/PI positivity in BCWM.1 cells, respectively. However, a significant degree of cell death was noted in VO-treated cells (~74%) compared to VR-treated cells (~40%) (p<0.01). Next, we examined for apoptosis in MEC1 cells and noted a similar trend; where the VO combination induced markedly more cell death (~71%) than VR (~57%). Contrastingly, in RPCI-WM1 cells neither single agent O or R could elicit >12% annexin V/PI positivity and where the addition of V increased apoptosis by only 3 - 4%. We also examined the apoptotic potential of VO or VR in tumor cells from low, intermediate and high-risk CLL patients. In low and intermediate-risk CLL cells from low and intermediate-risk patients, V alone induced ~30% cell death, which increased significantly with the addition of O (VO) to between 48 - 52%. Contrastingly, the combination of VR did not induce more than 29 - 32% apoptosis. In CLL cells from high-risk patient, we noted that exposure to single agent V induced ~ 28% cell death and in VO-treated cells, this number increased to 47%. We also examined for ADCC and CDC in the same cell lines and primary CLL cells. Despite considerable variability, single agent O and VO treatment of tumor cells resulted in greater ADCC than VR treatment. By contrast, in single agent R or VR-treated cells, more CDC was observed. CONCLUSION: Our preliminary investigation in VR- and VO-treated cell lines and primary CLL cells suggests the VO combination may be superior to VR in induction of direct tumor cell death. Mechanistic experiments underway will provide further insight and can aid in design of future VO-based clinical studies in CLL. Disclosures Ailawadhi: Pharmacyclics: Research Funding; Takeda: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Amgen: Consultancy.

Abstract Background : Treatment for relapsed multiple myeloma (MM) has evolved with the availability of many novel agents; outcomes in patients with newly diagnosed MM have improved with IMiD® agents (lenalidomide [R] or pomalidomide) and proteasome inhibitor (PI) use. Regardless of autologous stem cell transplant, many patients receive R maintenance therapy (Jagannath, Blood Adv 2018; Palumbo, N Engl J Med 2012). However, there is a lack of data describing the nature of relapse and treatment choices for patients progressing on R maintenance therapy. Recent phase III data do not evaluate these patients who are relapsed or refractory to R; current treatment guidelines do not specifically recommend second-line (2L) treatment options for these patients (Laubach, Leukemia 2016). However, phase III data show that pomalidomide in combination with bortezomib and dexamethasone improves progression-free survival (PFS) (HR 0.54; P = 0.0027) in R-exposed and refractory patients, including those with 1 prior line (Richardson, J Clin Oncol 2018). The Connect MM Registry is a US, multicenter, prospective observational cohort study designed to examine diagnostic and treatment patterns, clinical outcomes and quality of life in patients with MM. For patients who received R maintenance therapy, we describe patterns of relapse, 2L treatment choice, and outcomes. Methods : From 250 sites, transplant eligible and ineligible adult patients ≤ 60 days from MM diagnosis were enrolled (N = 3011). Patients were treated at physicians' discretion and followed up for treatment and outcomes until early discontinuation or study end. Patients who relapsed during R maintenance therapy (≤ 15 mg; assessed by treating physician), were analyzed for baseline (BL) characteristics, nature of relapse, and 2L treatment. Patients with symptoms at time of relapse were defined as the presence of ≥ 1 CRAB (hyperCalcemia, Renal failure, Anemia, and Bone disease) criterion ± 60 d from PD; absence of CRAB criteria at PD in this window was considered nonsymptomatic relapse. Primary endpoint was PFS from start of 2L; safety (serious adverse events; SAE) from start of 2L was also assessed. Logistic regression analyses on all BL factors and factors before start of 2L treatment were performed to determine covariates differentiating comparator groups. Survival outcomes were analyzed using a Cox regression after adjusting for covariates. Results : Data cutoff: 1/15/18. Of 2938 treated patients, 1102 entered 2L, 236 having received R maintenance therapy in 1L. Of those patients, 52% (n = 123) and 47% (n = 112) experienced symptoms at time of relapse and nonsymptomatic relapse, respectively (data not available for 1 patient). The top ten 2L regimens are presented in the Table. Median duration of prior maintenance therapy (367 d [IQR: 577] vs 489 d [IQR: 599]) and time from first progression to start of 2L treatment (0.3 vs 0.3 mo) did not notably differ between nature of relapse groups. Prolonged median PFS from start of 2L was observed for patients receiving triplet+ (≥ 3 agents) vs doublet (≤ 2 agents) regimens (HR: 0.72; Figure 1). PFS was better for IMiD agent + PI group compared with PI (without IMiD agents) group (HR, 0.68; Figure 2). Results of sensitivity analyses and overall survival will be presented. SAEs occurred similarly among treatment groups: 42.6% with IMiD agent + PI, 34.5% with IMiD agent (without PI), and 35.8% with PI. Conclusions: This is the first description of relapse patterns, 2L treatment choice and survival outcomes after PD on R maintenance therapy in community-based patients. Nearly equal numbers of patients had symptoms at time of relapse and nonsymptomatic relapse on R maintenance therapy. After PD on R maintenance, approximately 50% of patients switched to PI regimens without IMiD agents, 25% continued with IMiD agent + PI regimens, and 25% continued in the IMiD agents group. Our data show PFS benefit for triplet+ over doublet treatment in 2L. Patients in the IMiD agent + PI group gained survival benefits over patients in the PI group. Further characterization of the patients continuing with IMiD treatment in 2L after R maintenance therapy relapse (~ 25% of patients) are ongoing. Follow-up with recently approved agents (elotuzumab, daratumumab) and their use in 2L is limited in this analysis. These data may be used to better inform treatment choices after relapse on R maintenance therapy. Disclosures Jagannath: Celgene: Consultancy; Merck: Consultancy; Multiple Myeloma Research Foundation: Speakers Bureau; Medicom: Speakers Bureau; Bristol-Myers Squibb: Consultancy; Novartis: Consultancy. Narang:Janssen: Speakers Bureau; Celgene: Consultancy, Speakers Bureau. Ailawadhi:Takeda: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Research Funding; Celgene: Consultancy. Rifkin:Celgene: Consultancy; Boehringer Ingelheim: Consultancy; McKesson: Equity Ownership; EMD Serono: Consultancy; Amgen: Consultancy; Takeda: Consultancy; Sandoz: Consultancy. Terebelo:Celgene: Consultancy; Janssen: Speakers Bureau; Takeda: Speakers Bureau; Pharmacyclics: Speakers Bureau. Toomey:Celgene: Consultancy; Myriad Genetics: Speakers Bureau; Dava Oncology: Other: Travel. Durie:Takeda: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Amgen: Consultancy. Hardin:Celgene: Consultancy. Gasparetto:Janssen: Consultancy, Honoraria, Other: Travel; Bristol-Myers Squibb: Consultancy, Honoraria, Other: Travel; Takeda: Honoraria; Celgene: Consultancy, Honoraria, Other: Travel, Research Funding. Wagner:EveryFit: Consultancy; Gilead: Consultancy; Janssen: Consultancy. Omel:Takeda Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Srinivasan:Celgene: Employment. Kitali:Celgene: Employment. Agarwal:Celgene Corporation: Employment, Equity Ownership. Abonour:Prothena: Research Funding; Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.

Abstract Background: DLBCL is the most common adult NHL and despite significant advancements, outcomes in ethnic minorities remain suboptimal. Factors responsible for these disparities in ethnic minorities, especially variability in clinical and pathological features with evaluation of patient-level data have not been studied. Methods: A multi-institutional database of DLBCL patients seen at Mayo Clinic in Florida, University of Miami and University of Southern California between 1996-2016 was developed. Patient demographics, clinical disease characteristics and details of DLBCL immunophenotype [CD10, MUM1, BCL6 (Han's classification), Ki 67, MYC, BCL2) were reviewed. Comparisons between Hispanic and Non-Hispanic patients were made by Chi-square, Fischer's exact and Signed rank tests, where applicable. Patients with missing data on a certain feature were not included in the statistical analysis of that specific characteristic. Results: A total of 966 DLBCL patients with 69 Hispanics and 752 non-Hispanics were identified. These included 52% males (N=36) and 48% females (N=33) in Hispanics versus 58% males (N=436) and 42% females (N=316) in Non-Hispanics (p=0.35). Median age at diagnosis was significantly lower at 61 years (range 27-89) in Hispanics versus 66 in non-Hispanics (p=0.014). Extranodal disease was seen significantly more commonly in Hispanics (74%) than in non-Hispanics (60%) (p=0.037). There was no significant difference in disease stage at presentation between the two cohorts (p=0.189) although the proportion of patients with stage III and IV disease was higher among Hispanics (80.4%) as compared to non-Hispanics (68.5%). Similarly there was no significant difference in presence of primary CNS DLBCL at diagnosis between the two groups (p=0.74). GCB phenotype per the Hans' classification was seen in 59% (N=29) in both, Hispanics and Non-Hispanics (N=241) (p=0.99). Similarly, the median ki67 index of 80% was seen in both cohorts (p=0.48). MYC was positive in 59% in Hispanics versus only 37.5% in non-Hispanics (p=0.024). BCL2 expression by itself and also combined BCL2 and MYC double expression were not significantly different between the two groups (p=0.58 and p=0.11, respectively). Median overall survival (OS) was 22.5 months in Hispanics compared 54.9 months in Non-Hispanics (p<0.0001) (Figure 1). Conclusion: Survival outcome disparities in racial and ethnic minorities have been previously reported from population-based analyses. Lack of patient-level clinical data makes these analyses hypothesis generating, but not conclusive. We confirmed some prior findings including younger age at diagnosis for Hispanics with DLBCL. We also reported greater incidence of extranodal as well as stage III or IV disease at the time of presentation among Hispanics which may contribute to poor outcomes in this population. From DLBCL pathology standpoint, we found increased expression of MYC among Hispanics but no other significant immunohistochemical differences including double expression or non-GCB phenotype. The inferior OS despite uniform treatment practices at large Cancer Centers suggest multifactorial influences on patient outcomes which may at least in part include some of the differences we report here. Disclosures Ailawadhi: Pharmacyclics: Research Funding; Janssen: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy.

Abstract Introduction The 2-3 fold excess risk of multiple myeloma (MM) among family members of cases suggests a heritable contribution to risk. Recently, a genome-wide association study (GWAS) identified two genome-wide significant and one promising novel loci associated with multiple myeloma risk. To confirm these associations and identify additional novel risk loci, we performed a four-center, genome-wide association meta-analysis. Methods A fixed effects model was used for the meta-analysis which included a total of 1248 cases and 1485 controls, all of European descent, genotyped and analyzed at four separate centers with samples contributed by 10 studies. After quality control and imputation using the 1000 Genomes Project, the analysis included ∼9.5 million variants (λ=1.024). Associations between (single nucleotide polymorphisms) SNP genotypes and MM risk were evaluated under a log-additive model of inheritance, with each study adjusting for age, sex, and up to 10 principal components to control for population stratification. Promising results were replicated in an independent set of 1587 cases and 1770 controls using TaqMan, for a total of 2835 and 3255 cases and controls, respectively, in a combined meta-analysis. Results The discovery meta-analysis did not reveal any genome-wide significant associations (defined as p<5 x 10-8). We used a novel pruning algorithm to identify the top 35 most promising single nucleotide polymorphisms (SNPs) to advance to replication. We successfully genotyped 22 SNPs in the replication set. In the combined discovery and replication meta-analysis, rs1345359 at 12q23.1 was the most strongly associated SNP (P=9 x 10-8, Table 1). The variant allele C was associated with reduced risk (odds ratio discovery set [OR]= 0.69, OR replication set = 0.78, OR combined = 0.74). A second locus at 20q13.2 (rs150220835), was associated with a two-fold increased risk (P=1.22 x 10-6), a borderline increased risk (P=0.0900) and 45% increased risk (P=2.44 X 10-5) in the discovery, replication, and combined analysis sets respectively (Table 1). We also confirmed the association between MM risk and two previously published SNPs (rs4487645, p=0.0007and rs105251, p=0.0044) (Broderick et al., Nat. Genet., 2011). The third previously suggested SNP (rs6746082) was of nominal significance (p=0.0517) in the meta-analysis. Discussion We confirmed the association between MM risk and two previously published SNPs and identified a possible association with a novel SNP in chromosome 12q23.1 (rs1345359). This SNP is not located in a gene nor associated with biofeatures in ENCODE, thus further examination of correlated SNPs is necessary to identify a functional SNP linked to this locus. We also found suggestive evidence for a second locus at 20q13.2 requiring additional replication. Larger studies would improve risk variant discovery for this rare hematologic malignancy. Disclosures: Wolf: Celgene: Honoraria, Research Funding; Millenium: Honoraria; Onyx: Honoraria. Anderson:Celgene, Millennium, BMS, Onyx: Membership on an entity’s Board of Directors or advisory committees; Acetylon, Oncopep: Scientific Founder , Scientific Founder Other.