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Abstract INTRODUCTION Immunotherapy with engineered CAR T cells is a promising new therapy for glioblastoma, for which predictive and prognostic biomarkers are needed to inform effective intervention. Recently, our group analyzed standard-of-care (SOC) MRI images of long-term and short-term glioblastoma survivors and identified six intratumoral “habitats” of which “Habitat 6” was correlated with survival at diagnosis in high-grade glioma. Based on the MRI characteristics of “Habitat 6”, viz. high enhancement and high edema, we hypothesized that it could be a marker of tumor immune infiltrates. We are studying longitudinal changes in tumor “habitat” composition on MRIs of subjects with recurrent high-grade glioma treated with CAR T cells engineered to target IL13Ra2. METHODS MRI scans of the brain were acquired in 6 subjects at 3.0 T at baseline and various times before and after initiation of CAR T cell therapy. FLAIR, T1W and T1W-CE MRI images were registered to T2W images and six intratumoral “habitats” were computed as per our recently published methodology. The six habitats generated at the end of the tumor segmentation process were: “Habitat 1” (low FLAIR, low enhancement), “Habitat 2” (high FLAIR, low enhancement), “Habitat 3” (low FLAIR, medium enhancement), “Habitat 4” (high FLAIR, medium enhancement), “Habitat 5” (low FLAIR, high enhancement), and “Habitat 6” (high FLAIR, high enhancement). RESULTS Analysis of temporal changes in the six “habitats” shows an initial increase in both “Habitat 4” and “Habitat 6” following CAR T cell therapy initiation. Subjects with higher absolute volumes of “Habitat 6” at the baseline (pre-treatment) showed longer overall survival. Overall survival is a function of absolute “Habitat 6” volume at baseline, its direction of change immediately post-therapy, the duration of any increase in “Habitat 6” post-treatment, and the “Habitat 6” to “Habitat 4” ratio. Additional subjects are being evaluated to further understand these preliminary observations.

Abstract Background Hot flashes (HFs) negatively affect quality of life among perimenopausal and postmenopausal women. This study investigated the efficacy of oxybutynin vs placebo in decreasing HFs. Methods In this randomized, multicenter, double-blind study, women with and without breast cancer with 28 or more HFs per week, lasting longer than 30 days, who were not candidates for estrogen-based therapy, were assigned to oral oxybutynin (2.5 mg twice a day or 5 mg twice a day) or placebo for 6 weeks. The primary endpoint was the intrapatient change from baseline in weekly HF score between each oxybutynin dose and placebo using a repeated-measures mixed model. Secondary endpoints included changes in weekly HF frequency, HF-related daily interference scale questionnaires, and self-reported symptoms. Results We enrolled 150 women. Baseline characteristics were well balanced. Mean (SD) age was 57 (8.2) years. Two-thirds (65%) were taking tamoxifen or an aromatase inhibitor. Patients on both oxybutynin doses reported greater reductions in the weekly HF score (5 mg twice a day: −16.9 [SD 15.6], 2.5 mg twice a day: −10.6 [SD 7.7]), placebo −5.7 (SD 10.2); P < .005 for both oxybutynin doses vs placebo), HF frequency (5 mg twice a day: −7.5 [SD 6.6], 2.5 mg twice a day: −4.8 [SD 3.2], placebo: −2.6 [SD 4.3]; P < .003 for both oxybutynin doses vs placebo), and improvement in most HF-related daily interference scale measures and in overall quality of life. Patients on both oxybutynin arms reported more side effects than patients on placebo, particularly dry mouth, difficulty urinating, and abdominal pain. Most side effects were grade 1 or 2. There were no differences in study discontinuation because of adverse effects. Conclusion Oxybutynin is an effective and relatively well-tolerated treatment option for women with HFs.

Abstract Background: Currently, low molecular weight heparin is the guideline endorsed treatment of patients with cancer associated venous thromboembolism (VTE). While apixaban is approved for the treatment of acute VTE, there are limited data supporting its use in cancer patients. Methods: Patients with cancer associated acute VTE were randomly assigned to receive either apixaban 10 mg twice daily for 7 days followed by 5 mg twice daily or subcutaneous dalteparin (200 IU/kg for 1 month followed by 150 IU/kg once daily) for 6 months. The primary outcome was major bleeding. Secondary outcomes included VTE recurrence and a composite of major plus clinically relevant non-major bleeding. Results: Of the 300 patients who underwent randomization, 287 were included in the primary analysis. Of these, metastatic disease was present in 65.5% of subjects and 74% were receiving concurrent systemic cancer therapy. Colorectal, lung, pancreas, and breast cancers were the four most prevalent cancer types. Major bleeding occurred in 0 of the 142 patients (0%) in the apixaban group as compared with 3 of the 145 patients (2.1%) in the dalteparin group (p=0.9956). Recurrent VTE occurred in 5 patients (3.4%) in the apixaban group and 20 patients (14.1%) in the dalteparin group (difference in risk -10.7 percentage points) with a Hazard Ratio (HR) 0.26, (95% CI, 0.09 - 0.80, p = 0.0182). Major plus clinically relevant non-major bleeding were similar at 9% for both groups. There were no mortality differences comparing apixaban (15.9%) and dalteparin (10.6%) groups at 6 months (HR 1.36, 95% CI 0.79 - 2.35). Monthly quality of life surveys favored apixaban therapy for many measures including: concern for excess bruising, stress, irritation, burden of delivery, and overall satisfaction with anticoagulant therapy (p<0.05). Monthly bruising questionnaire favored apixaban at each interval (p<0.002). Conclusions: Oral apixaban therapy was associated with very low rates of bleeding and significantly lower VTE recurrence with superior quality of life outcome measures compared to parenteral dalteparin in the treatment of cancer associated VTE. These data support the clinical utility of apixaban for the acute treatment of VTE in this patient population. Table. Table. Disclosures No relevant conflicts of interest to declare.

Abstract Background: To address the current and long-term unmet health needs of the growing population of patients diagnosed with non-Hodgkin lymphoma (NHL) and NHL survivors, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/) with recruitment at eight centers (Cornell University, Emory University, Mayo Clinic, MD Anderson, University of Iowa, University of Miami, University of Rochester, and Washington University). Here we report on the first two years of enrollment. Methods: All patients ≥18 years with NHL (exclusive of chronic lymphocytic leukemia) newly diagnosed within 183 days of enrollment are eligible. LEO reviews all pathology diagnoses; annotates and harmonizes all cases with clinical, epidemiologic, pathology and treatment data; builds a NHL tumor bank that includes an H&E slide, a formalin-fixed, paraffin-embedded tissue sample and extracted tumor DNA and RNA; collects peripheral blood and banks DNA, serum, plasma and buffy coat in a central biorepository; and prospectively follows patients regularly to ascertain disease progression/relapse, retreatment, transformation, second cancers, survival, updated exposures, and patient-reported outcomes. We examined the demographics, clinical characteristics, and NHL subtypes for patients enrolled in the first two years (2015-2017) in LEO Cohort and compared these characteristics to population-based registry data from the United States Surveillance, Epidemiology, and End Results (SEER) Program for 2011-2015. We also examined baseline body mass index (BMI), comorbidities and quality of life (QOL) measured with the Functional Assessment of Cancer Therapy - General (FACT-G) scores (0-100 scale) overall and by NHL subtype that were collected in LEO but not available in SEER or any other large, prospective US NHL cohort. Results: From 2015-2017, LEO enrolled 3244 NHL patients across 47 states (Figure) with a median age at diagnosis of 62 years (range, 18-94 years) and 55.9% male. Based on self-identified race/ethnicity, 85% of the participants were White, 7.4% were Black/African American, 2.6% were Asian, and 3.5% other or more than one race; 9.9% were Hispanic (regardless of race). The most common subtypes were diffuse large B-cell (DLBCL, 33.9%), follicular (FL, 22.2%), mantle cell (MCL, 9.3%), marginal zone (MZL, 8.3%), T-cell (TCL, 10.9%), and all other NHL subtypes (other NHL, 15.3%). These distributions were all within 5% of SEER data, except that 6.8% of participant in LEO were in the age 80+ years group compared to 18.5% in SEER (Table). The overall prevalence of self-reported comorbidities at enrollment was 13.5% for heart disease (range, 12.1% for FL to 16.6% for MCL), 8.8% for diabetes (range, 7.1% for FL to 9.8% for DLBCL), 4.6% for osteoporosis (range, 3.0% for MCL to 6.3% for MZL), and 5.9% for autoimmune disease (range, 2.0% for MCL to 12.6% for MZL). The median BMI was 27.9 kg/m2 (range, 26.7 kg/m2 for TCL to 28.3 kg/m2 for MZL). A total of 2151 participants completed the FACT-G with a median score of 78.7 (range, 75.9 for TCL to 83.3 for MZL). Complete IPI data were available on 2296 participants: 40.4% IPI 0-1, 32.7% IPI 2, 18.3% IPI 3, 8.7% IPI 4-5. Overall, 73.7% of participants were initially treated with systemic therapy (range, 40.0% for MZL and 91.8% for DLBCL); 14.5% were initially managed with observation (range, 1.4% DLBCL and 31.8% for FL); and 2.0% were initially manage with radiotherapy (range, 0.2% for MCL and 3.8% for DLBCL). Outcomes are being prospectively collected. Conclusions: LEO is a large and diverse cohort of newly diagnosed NHL patients and the first two years of enrollment reflects the broader United States NHL population. Enrollment is ongoing. This unique resource will enable examination of the interactions among a broad array of clinical and molecular factors and their impact on multiple outcomes, to improve prognostication, identify new approaches to improve outcomes and survivorship, and facilitate clinical trials using this infrastructure. Disclosures Flowers: Acerta: Research Funding; Pharmacyclics/ Janssen: Consultancy; OptumRx: Consultancy; Janssen Pharmaceutical: Research Funding; V Foundation: Research Funding; Burroughs Wellcome Fund: Research Funding; Spectrum: Consultancy; Eastern Cooperative Oncology Group: Research Funding; Abbvie: Consultancy, Research Funding; Bayer: Consultancy; Millennium/Takeda: Research Funding; Abbvie: Research Funding; Celgene: Research Funding; Gilead: Consultancy; BeiGene: Research Funding; Karyopharm: Consultancy; Denovo Biopharma: Consultancy; Genentech/Roche: Consultancy; Gilead: Research Funding; Genentech/Roche: Research Funding; National Cancer Institute: Research Funding; TG Therapeutics: Research Funding; Pharmacyclics: Research Funding. Nastoupil:TG Therappeutics: Research Funding; Merck: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Janssen: Research Funding; Spectrum: Honoraria; Gilead: Honoraria; Genentech: Honoraria, Research Funding; Karus: Research Funding; Novartis: Honoraria; Juno: Honoraria. Kahl:Acerta: Consultancy; Genentech: Consultancy; Seattle Genetics: Consultancy; Juno: Consultancy; CTI: Consultancy; ADC Therapeutics: Consultancy; Gilead: Consultancy; Celgene: Consultancy; AstraZeneca: Consultancy; Abbvie: Consultancy. Casulo:Celgene: Research Funding; Gilead: Honoraria. Friedberg:Bayer: Honoraria. Lossos:Affimed: Research Funding. Martin:Seattle Genetics: Consultancy; Kite: Consultancy; Janssen: Consultancy; Gilead: Consultancy; Bayer: Consultancy; AstraZeneca: Consultancy. Leonard:Bayer: Consultancy; Celgene: Consultancy; Biotest: Consultancy; United Therapeutics: Consultancy; BMS: Consultancy; MEI Pharma: Consultancy; Juno: Consultancy; Sutro: Consultancy; Karyopharm: Consultancy; ADC Therapeutics: Consultancy; Pfizer: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy; Genentech/Roche: Consultancy; Novartis: Consultancy. Bernal-Mizrachi:Kodikaz Therapeutic Solutions: Consultancy, Equity Ownership; Takeda Pharmaceutical Company: Research Funding. Maurer:Morphosys: Research Funding; Nanostring: Research Funding; Celgene: Research Funding. Cerhan:Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding.

Abstract Background: Erythropoiesis-stimulating agents (ESAs) reduce anemia in cancer patients; however, there are concerns that ESAs increase mortality in some patients. Within the framework of an international collaboration we thus conducted a patient-level meta-analysis to assess the effects of ESAs on mortality in cancer patients. Methods: We performed a meta-analysis, based on the intention-to-treat principle, of cancer patients enrolled in randomized controlled trials comparing epoetin alfa, epoetin beta or darbepoetin alfa plus red blood cell transfusions as needed versus transfusion alone, for prophylaxis or treatment of anemia while or after receiving anticancer therapy. Patient-level data were obtained and analyzed by independent statisticians at two academic departments. Primary endpoints were on-study mortality and overall survival in patients receiving chemotherapy, defined as all patients from studies in which =/> 70% of study population received chemotherapy, and in all cancer patients regardless of anticancer therapy. On-study mortality was defined as death from any cause between date of randomization and 28 days after end of active study phase. Overall survival was defined as death from any cause between date of randomization and longest follow up available. Hazard ratios (HR) and 95% confidence intervals (CIs) were calculated per study and meta-analyzed with fixed-effects and random-effects models. Stratified multivariable Cox-regression analyses were conducted to assess the impact of baseline imbalances. Tests for interactions were used to identify differences in effect across pre-specified subgroups. All analyses were pre-specified in a peer-reviewed protocol (Bohlius et al. 2008). An independent steering committee consisting of clinicians and methodologists agreed on all analyses and interpretations. Independent investigators and representatives from manufacturers contributing data offered advice, but had no decision-making authority. Results: Data from 13,933 cancer patients enrolled in 53 studies were included in the analysis; 38 trials including 10,441 patients used mainly chemotherapy. Including all cancer patients ESAs increased on-study mortality by 17% (HR 1.17; 95% CI 1.06–1.30), with little evidence for a difference between chemotherapy and other trials (p for interaction=0.42), and worsened overall survival by 6% (HR 1.06; 95% CI 1.00–1.12). In the chemotherapy population on-study mortality was increased by 10% (HR 1.10, 95% CI 0.98–1.24) and overall survival was worsened by 4% (HR 1.04; 95% CI 0.97–1.11). Adjusting for known prognostic factors had little effect on the overall estimates. There was no conclusive evidence for effect modification by patient level characteristics such as age, sex, Hb and Hct at baseline, Hb ceiling, type and stage of tumor or study level characteristics (anticancer treatment, ESA treatment schedules, study design and quality) for the outcomes tested. Conclusion: ESA treatment in cancer patients increased on-study mortality by 17% and worsened overall survival by 6%. For patients undergoing chemotherapy the increase was less pronounced, but could not be excluded. In clinical practice, risks of ESAs must be balanced against benefits of ESAs depending on the clinical circumstances of the individual patient.

Abstract We have recently reported that event-free survival at 24 months from diagnosis (EFS24) is a robust endpoint for assessment of disease related outcome for newly diagnosed patients with diffuse large B-cell lymphoma (DLBCL) treated with anthracycline-based immunochemotherapy (IC). Patients who achieve EFS24 following IC have a subsequent overall survival that is equivalent to the age and sex matched general population. The IPI was developed in the pre-rituximab era using OS/EFS endpoints. While the IPI is associated with outcome in the IC era, the original survival estimates for the IPI risk groups are outdated. The IPI is also a discrete risk classifier, with only 6 possible groups. Here we remodel the IPI using EFS24 as the endpoint in a large international cohort of patients treated with IC. This model provides an individual level 0-100% risk of failing to achieve EFS24 for each patient and can be used for patient prognosis, treatment stratification, and risk assessment. Methods Newly diagnosed DLBCL patients treated with immunochemotherapy from the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource, NCCTG N0489 clinical trial, GELA LNH2003B program, and a Lyon, France based hospital registry were included in the original EFS24 study. Patients with a relapse, progression, unplanned re-treatment, or death due to any cause within 730 days of diagnosis were considered a failure for the EFS24 endpoint. Patients alive and progression/relapse free at 730 days from diagnosis with no subsequent treatment following initial IC were considered a success for the EFS24 endpoint. Variables selected for potential model inclusion were the IPI components (age, stage, ECOG PS, number of extranodal sites, and LDH), as well as standard clinical variables typically reported in studies of DLBCL: presence of B-symptoms, bone marrow involvement, bulky disease (>10 cm), and sex. The IPI24, a prognostic model for EFS24, was developed using logistic regression models. Model building began by fitting the classic IPI score (0-5), then allowing individual IPI variables to carry different model weights and number of categories, followed by dropping insignificant variables, finally adding any additional significant variables. Model performance was assessed using bias corrected c-statistics, AIC, and R2 values. Model selection was done using the complete case set with multiple imputation on the full dataset used to refine parameter estimates for the final model. Results 1596 total patients were available for modeling. The median age was 62 (range 18-93) and 53% were male; 33% were IPI 0-1, 25% were IPI 2, 25% were IPI 3, and 17% were IPI of 4-5. The failure rate for achieving EFS24 was 29%. All variables but sex (p=0.33) were univariately associated with EFS24 (p<6.4x10-5). The original IPI had good prognostic ability for EFS24 (c=0.696, p=2.2x10-32). Allowing multiple categories for ECOG PS, stage, and age (continuous) improved model fit and prognostic ability (c=0.727). The number of extranodal sites was not significant when IPI variables were modeled separately and was removed from the model. Sex and bulky disease were additional significant variables when added to the model. Thus, the final IPI24 model contained the following risk predictors: male sex, ECOG PS (0 vs. 1 vs 2 vs 3-4), stage (I vs. II, vs. III vs. IV), LDH (elevated vs. normal range), bulky disease > 10cm, and age (continuous). This model resulted in improved fit and prognostic ability (c=0.749) over the standard IPI (c=0.696, bootstrap p<0.001). Model validation was performed on an additional 158 patients from the SPORE MER and showed good concordance (c=0.697). Additional validation is planned in a larger set of independent patients. Conclusion The IPI24, generated using standard clinical variables, yields an individual risk prediction for failing to achieve EFS24 following IC for treatment of DLBCL. The IPI24 has superior prognostic ability to the standard IPI and can be implemented in the clinic using a nomogram or as a simple electronic application. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 2686 Background: DLBCL is the most commonly occurring form of non-Hodgkin lymphoma and is a highly curable disease, but one that is universally fatal if untreated or improperly treated. In a series of studies, we have reported racial disparities in the clinical presentation and the treatment outcomes for patients (pts) with DLBCL in the United States (Shenoy Cancer 2010; Flowers CEBP 2012). These studies showed that black pts with DLBCL are diagnosed at an age a decade younger than whites, are more likely to have advanced stage disease, and are less likely to survive 5 years. One explanation is that black patients in the US less often receive standard of care therapy (Flowers CEBP 2012). However, in a cohort study of 533 white and 144 black patients with DLBCL managed at Emory and University of Alabama-Birmingham (UAB) black race predicted worse overall survival (OS) even when black and white pts received the same therapy (CHOP; Hazard ratio [HR] 1.8, p<0.001) suggesting a biological basis for some disparities(Flowers Leuk Lymph 2012). To address these findings, we examined whether known prognostic biological variants within DLBCL [germinal center B-cell-like (GCB) and activated B-cell like (ABC)] occurred differentially between black and white pts. Methods: DLBCL pts within our Emory-UAB cohort study provided formalin fixed material available for construction of tissue microarrays (TMAs). All pts were diagnosed with DLBCL from 1990–2010 and met the following criteria: age ≥18 years at diagnosis and available information on demographics, race, gender, initial clinical features at presentation, treatment, and treatment outcomes. H&E slides from each block for each case were reviewed to identify the appropriate zone(s) for cores. Sections placed in TMAs underwent immunohistochemistry (IHC) staining with BCL6, GCET1, CD10, FOXP1, and LMO2 antibodies. The percentages of positive cells were scored in 10% increments for each antibody, and recorded for each case by 3 hematopathologists blinded to the clinical and demographic data. The Choi algorithm was used to classify all patients into ABC and GCB subsets; other IHC algorithms were used as a backup. Descriptive statistics for the baseline characteristics of black and white pts were compared using Chi-square tests. Kaplan–Meier estimation was used to evaluate OS for the two groups and compared with the log-rank test. To evaluate prognostic factors and the effects of treatment on OS, Cox proportional hazards models were used controlling for age, sex, stage, LDH, performance status, presence of B-symptoms, race, treatment (R-CHOP vs. other), and ABC subtype. Results: Tissues for 26 black pts and 63 white pts meeting all eligibility criteria were evaluated in the TMA. There were significant differences in baseline characteristics between the two groups; 23% of black pts vs. 46% of whites were > 60 years of age (p=0.04), 73% had stage III/IV disease vs. 56% (p=0.03), and 77% had an LDH>ULN vs. 51% (p=0.04). There were no significant differences between the two racial groups in terms of sex, ECOG PS, presence of B-symptoms (38% vs. 29%p=0.46), extranodal sites (50% vs. 78% ≤ 1, p=0.27), IPI risk, or treatment received (RCHOP 46% vs. 40% p=0.93). By the Hans, Natkunam, Tally, and Choi algorithms black patients more commonly presented with the poor-risk ABC/non-GCB subtype (by Choi black 64% ABC vs. white 37%; p= 0.01, Table). After controlling for clinical confounders including age, sex, stage, LDH, performance status, presence of B-symptoms, race, treatment (RCHOP vs. other), and ABC subtype, being >60 years of age [HR 3.1 95% CI 1.3–7.2], being black (HR 3.5 95% CI 1.5–8.2), and receiving treatment other than RCHOP (HR 12.8, 95% CI 3.2–50.6) were associated with inferior OS. Conclusions: The rate of ABC DLBCL is significantly higher in black pts compared to white pts in this university-based cohort from the Southern United States. Additional studies confirming these findings in larger populations and examining the mutations associated with these differences are underway to address biological differences intrinsic to DLBCL that may in part explain comparatively adverse features and outcomes for black pts with DLBCL. Disclosures: Flowers: Celgene, Spectrum, Millennium, Gilead, Janssen: Research Funding; Genentech/Roche (unpaid), Millennium (unpaid), Celgene: Consultancy. Bernal-Mizrachi:Empire Genomics (not related to current work): Patents & Royalties. Sinha:Celgene: Research Funding. Jaye:Millenium Pharmaceuticals (For single lecture on immunohistochemical subtyping of large B cell lymphomas): Honoraria.

Abstract Abstract 1540 Background: Diffuse Large B-cell Lymphoma (DLBCL) is the most common lymphoma in the western world. Outcomes have improved with the standard initial therapy of rituximab and anthracyline based chemotherapy (immunochemotherapy). However, 20–40% of patients will either fail to achieve remission or relapse following initial immunochemotherapy. Most relapses occur early, and long-term outcome of relapsed/refractory patients is generally poor despite salvage regimens and stem cell transplant. Traditionally, studies for DLBCL have been evaluated using progression-free and/or overall survival. However, the event rate in DLBCL slows significantly approximately 12–18 months after diagnosis, and late events are often due to competing (non-DLBCL related) risks, especially in older patients. Here we examine outcome of DLBCL patients based on their event status at 12 months. Methods: Newly diagnosed DLBCL patients were prospectively enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE Molecular Epidemiology Resource (MER). Clinical data were abstracted from medical records using a standard protocol. Patients were actively followed for events (progression, re-treatment, or death due to any cause) and overall survival (OS). Event-free status at 12 months after diagnosis (EFS12) was assessed as a dichotomous variable. Cause of death was determined by medical record and death certificate review using prospectively determined definitions. Expected survival was based on age and sex matched survival using the Minnesota population death rates. Confirmation cohorts were from a Lyon, France hospital based registry and NCCTG clinical trial N0489. Results: 680 patients with newly diagnosed DLBCL and treated with rituximab + anthracycline based chemotherapy were enrolled in the MER from 2002 to 2009. The median age was 62 years (range 18–92). 53% were male. At a median follow-up of 59 months (range 8–116), 266 patients (39%) had an event and 188 patients (28%) died. 162 patients (24%) had an event in the first 12 months after diagnosis, comprising 60% of all events. Patients with an event in the first 12 months had poor survival with death almost exclusively due to disease (Figures 1a, 2a). In contrast, patients who were event-free at 12 months had comparable survival to the age and sex matched general population (Figure 2b) and were more likely to die of other causes than DLBCL (Figure 1b). Overall survival rates by EFS12 status were validated in patients from a French hospital-based registry (N=265) and the NCCTG N0489 clinical trial (N=87) with additional replication studies underway. Conclusions: DLBCL patients who are event-free at 12 months after diagnosis have an excellent prognosis with an overall survival similar to that of an age- and sex- matched general population and are more likely to die of other causes than DLBCL. This finding has implications for clinical management, new clinical trials, and follow-up testing in this patient population. In contrast, patients with an event within the first 12 months after diagnosis have a poor prognosis with almost all deaths secondary to DLBCL. EFS status at 12 months identifies patients with poor outcomes due to disease. This can be utilized as an endpoint in biologic studies and clinical trials to address early treatment failures. EFS status at 12 months should be incorporated into prognostic models to identify high risk patients in newly diagnosed DLBCL. Disclosures: No relevant conflicts of interest to declare.

Abstract Background: One of the main complications in CLL is Richter syndrome (RS). RS derives from the rare transformation of chronic lymphocytic leukemia (CLL) into an aggressive lymphoma, most commonly of the diffuse large B-cell lymphoma (DLBCL) type. RS occurs in 2.2% to 8% of patients with CLL and the prognostic is poor with a median survival from 5 to 8 months. Detection of RS by imaging has resulted in conflicting and non-significant results. Aim: The objective of this study was to validate recent findings correlating FDG/PET imaging and histological features in CLL and to demonstrate that a tumoral maximum standardized uptake value > 10 measured on 18F-FDG-PET is a new valid marker to discriminate RS. Results: From June 2006 through December 2012, 240 patients from the Division of hematology of Centre Hospitalier Lyon Sud and Créteil and from the Mayo Clinic Rochester have been analyzed with a mean age of 62 years (21-91). Clinical, histological (confirm by biopsy) and biological parameters have been identified with 10% of the patients as having RS, 34% stable CLL disease; 42% of rapid CLL progression (histological features of progression defined as increased large cell number, large confluent proliferation centers or high proliferation rate assessed by Ki-67 but not meeting criteria for diffuse large B-cell lymphoma/RS) and 14% with others diseases (e.g. infection and or cancers). For patients with stable CLL disease, the median tumoral SUV max was 2 (range: 0-2.4). Among patients with a rapid progression of CLL, 90% had a tumoral SUV max <10 but greater than the liver median SUV max (4.5 range: 1-11). In contrast, 90% of patients with RS had a median tumoral SUV max >10 (12.9; range: 5-27). A statistically significant difference between SUV max of CLL patients with stable disease and RS was observed (2.2 vs. 12.9; p< 0.0001) and similarly for SUV max of CLL patients with rapid disease progression and RS (4.5 vs 12.9; p< 0.0001). Regardless of the RS prevalence (2.2% to 8%), statistical tests identified a threshold of tumor SUV max > 10 as the more discriminating cut off. Using this threshold, the sensitivity and specificity of PET to identify RS in our cohort are 91% and 95% respectively. Assuming an RS prevalence of 2.2%, positive predictive value (PPV) and negative predictive value (NPV) using the >10 threshold were 28.7% and 99.8%; for an 8% prevalence of RS, the PPV and NPV are 60.8 and 99.2% respectively.The proportion of correctly classified patients with RS is more accurate using a threshold of tumoral SUV max > 10 than 5 (2.2% RS prevalence: 94.8% versus 71.8%; 8% RS prevalence: 94.6% versus 73.5%). Finally analysis of the area under the curve (AUC) reveals a value of 0.95 (95% confidence interval: 0.89- 0.99). Recently, Falchi et al, reported on 332 patients with CLL classified as 95 RS, 117 rapid progression and 120 stable disease and demonstrated a strong correlation between histological features and PET imaging. A SUV max ≥10 strongly correlated with a shorter overall survival. Similarly, in our study we have shown excellent sensitivity and negative predictive value estimated at 100%, revealing the ability of 18F-FDG-PET-CT to rule out the diagnosis of RS if the tumor SUV max is less than 10. Conclusion: 18F-FDG-PET-CT is a valuable tool in the diagnostic evaluation of RS for patients with CLL. It is not only useful to identify RS syndrome and guide the site of biopsy but also to identify CLL patients who will experience more rapid disease progression. An SUV max > 10 is the optimal threshold to distinguish RS in CLL. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Persons of African ancestry (AA) have a 2-3-fold higher risk of multiple myeloma (MM) than persons of European ancestry (EA). Like other B-cell malignancies, genome-wide association scans (GWAS) have identified MM risk variants in the HLA region in persons of EA. We conducted a case-control analysis with data from the National Marrow Donor Program (NMDP)1comprising MM patients typed for bone marrow transplant to donor controls matched by race-ethnicity, and found associations between specific HLA alleles/haplotypes and MM risk that varied by race and ethnicity. To confirm our results and identify additional novel signals, we have now investigated associations between HLA alleles and haplotypes and MM risk in the African American Multiple Myeloma Study (AAMMS) Cohort. Methods: The source of subjects was the AAMMS, in which AA MM patients were identified from 10 cancer centers and 4 Surveillance, Epidemiology and End-Results (SEER) Program cancer registries in order to identify genetic risk factors for MM among AAs. A GWAS was conducted using the Illumina Human Core BeadChip array on DNA samples from 1,305 AA MM patients in the AAMMS comparing results to those from 7,078 AA controls with GWAS data generated from the Illumina 1MDuo2. The major histocompatibility complex (MHC) region single nucleotide polymorphisms (SNPs) were imputed to classical HLA variants using HIBAG. Unconditional logistic regression was used to estimate HLA associations, adjusting for sex, age and the first 2 principal components. P-values were adjusted for false discovery rate (FDR) for each locus group. Results: We did not identify any single HLA alleles associated with MM risk among AAs. However, several B*07:02-containing haplotypes were associated with MM risk (odds ratios [OR] ranging from 2.38 to 2.64 and FDR P-values ranging from 1.43 x 10-6 to 3.57 x 10-8). We found associations between MM risk and genotypes containing DRB3*02:02, including DRB3*02:02~DRB1*11:01+ DRB3*02:02~DRB1*11:01 (OR=1.93, PFDR= 9.36 x 10-5) similar to those observed in the NMDP study1. Novel findings included associations between MM risk and HLA Class I haplotypes B*53:01+ B*57:01 (OR=1.94, PFDR= 0.003) and C04:01~B*53:01+C*06:02~B*57:01 (OR=1.96, PFDR= 0.0050). Results from an ongoing meta-analysis between the two data sets (one based on an imputed GWAS and one based on NMDP HLA typing) will be presented. Conclusions: This study is the second to examine HLA alleles and risk of MM among AA's and is by far the largest. We confirmed a previously observed association between an HLA Class II DRB3 variant and MM risk and confirmed an association with B*07 haplotypes previously observed among EAs1. We also identified novel associations between other HLA Class I haplotypes and MM risk in AA's. Because HLA is highly polymorphic, many HLA alleles are rare variants for which genetic associations are difficult to detect without very large sample sizes. Further investigation with large sample sizes will be necessary to refine these associations in order to better identify the underlying causal alleles and determine the functional significance of these HLA associations. 1Beksac M, Gragert L, Fingerson S, et al.: HLA polymorphism and risk of multiple myeloma.Leukemia. 2016 Jul 27. doi: 10.1038/leu.2016.199. 2Rand KA, Song C, Hwang AE, et al. Genetic susceptibility markers of multiple myeloma in African-Americans. Abstract # 2030, 56th Annual American Society of Hematology Meeting, San Francisco, California, 2014. Disclosures Ailawadhi: Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy. Nooka:Spectrum, Novartis, Onyx pharmaceuticals: Consultancy. Zonder:Pharmacyclics: Other: DSMC membership; Prothena: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Lonial:BMS: Consultancy; Novartis: Consultancy; Millenium: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Merck: Consultancy; Celgene: Consultancy; BMS: Consultancy; Novartis: Consultancy; Onyx: Consultancy; Janssen: Consultancy; Onyx: Consultancy.