Kahl, Brad S.

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: Relapsed/refractory (R/R) Hodgkin lymphoma (HL) remains a significant clinical challenge. We hypothesized that using immune checkpoint blockade to activate the immune cells in the tumor microenvironment, and concurrently targeting tumor cells with the CD30 targeting antibody-drug conjugate brentuximab vedotin (BV) could overcome tumor resistance. E4412 is a Phase 1/2 ECOG-ACRIN sponsored study of the combinations of BV, nivolumab (Nivo), and ipilimumab (Ipi) in patients with R/R HL. Here we present the preliminary safety and response data on the full cohort of patients treated in Phase 1 with BV + Ipi + Nivo (Arms G-I). Methods: Patients with confirmed R/R HL were treated with Nivo 3mg/kg, Ipi 1mg/kg and BV 1.2mg/kg (Arm G) or 1.8mg/kg (Arm H) with a 3+3 design, and an expansion cohort (Arm I) of 9 patients with BV at 1.8mg/kg. BV and Nivo are given every 21 days for 16 cycles; Nivo may be continued for an additional 12 months. Ipi is given every 12 weeks except for the first 2 patients in Arm G who received Ipi every 6 weeks for the first 3 cycles. Dose limiting toxicity (DLT) was defined within the first cycle of therapy. Results: As of 6/30/18 22 patients with a median of 2 prior therapies (range 1-5) have been treated; 7 in Arm G, 6 in Arm H, and 9 in Arm I. Median age was 35, range (19-60); 11 patients were male. Nine patients had prior SCT (1 alloSCT, 8 autoSCT); 1 patient had prior BV. Safety: All 22 enrolled patients are evaluable for safety. There were 3 DLTs, one in each arm. In Arm G one patient experienced grade 4 diabetic ketoacidosis and hyperglycemia, and went off treatment after cycle 1. In Arm H, one patient had transient grade 3 AST elevation; this was of no clinical significance and did not require a delay in therapy. In Arm I a post AlloSCT patient had grade 4 Steven-Johnson syndrome with grade 3 pruritis, rash, and GVHD, and came off therapy. Common toxicities considered at least possibly related to drug, are shown in Table 1, and grade 3 or greater toxicity in Table 2. There were no grade 5 AEs or additional grade 4 AEs. Significant grade 3 AEs were: rash, colitis, gastritis, pancreatitis, and arthritis each in one patient, resulting in dose delays but not discontinuation of therapy. One patient experienced grade 2 angioedema in cycle 1 and came off therapy. No significant infusion reactions were noted. Response: Nineteen of 22 patients are evaluable for response. Three patients discontinued treatment after cycle 1 and are not evaluable for response. For the full population the overall response rate (ORR) was 82% (18/22), with a complete response (CR) rate of 68% (15/22). For patients treated with at least 3 cycles of therapy who were evaluable for response, the ORR is 95% (18/19) with a CR rate of 79% (15/19). Six patients went from treatment to SCT. With a median follow-up of 0.52 years median progression free survival (PFS) has not been reached (Figure 1), and with a median follow-up of 0.82 years overall survival (OS) has not been reached (Figure 2). Conclusion: In this study of the triplet combination of BV, Ipi and Nivo for R/R HL, therapy was generally well tolerated, although more grade 3 AEs were seen than in the doublets. In a heavily pretreated patient population, with 9 patients post SCT, the ORR of 95% and CR rate of 79% in evaluable patients is extremely promising. Data will be updated to include longer term PFS and OS by the time of the meeting. Optimization of this strategy is ongoing in E4412, now a randomized phase 2 study comparing the doublet of BV-Nivo to the triplet of BV-Ipi-Nivo. Disclosures Diefenbach: Trillium: Research Funding; Incyte: Research Funding; Genentech: Consultancy; Seattle Genetics: Consultancy, Research Funding; Denovo: Research Funding; Acerta: Research Funding; Millenium/Takeda: Research Funding; Merck: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding. Hong:Merck: Consultancy. Cohen:Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; Takeda: Research Funding; BioInvent: Consultancy; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Advani:Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Merck: Research Funding; Autolus: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Kura: Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Cell Medica: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Janssen: Research Funding; Millenium: Research Funding; Infinity: Research Funding; Regeneron: Research Funding; Agensys: Research Funding; Bayer: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Gilead/Kite: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Kyowa: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Forty Seven: Research Funding. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Merck, Takeda, Celgene, Seattle Genetics, Bayer: Research Funding. Svoboda:Regeneron: Research Funding; Seattle Genetics: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Merck: Research Funding; Kyowa: Consultancy; TG Therapeutics: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; KITE: Consultancy. Karmali:AstraZeneca: Speakers Bureau; Gilead: Speakers Bureau. Kahl:Genentech: Consultancy; Abbvie: Consultancy; Acerta: Consultancy; Celgene: Consultancy; AstraZeneca: Consultancy; ADC Therapeutics: Consultancy; Seattle Genetics: Consultancy; Juno: Consultancy; CTI: Consultancy; Gilead: Consultancy. Ansell:LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Pfizer: Research Funding; Celldex: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Merck & Co: Research Funding; Takeda: Research Funding.

Abstract Background We have previously reported and validated that the E-IPI, provided better discrimination of overall survival (OS) than the IPI for DLBCL patients > 60 years of age treated with R-CHOP (Advani et al., BJH 2010 and 12-ICML 2013 Abstract 222). Recent reports suggest that males > 60 years treated with R-CHOP have worse outcomes likely related to differences in rituximab clearance (Muller et al., Blood 2012). In this study, we explored if the addition of male sex to the E-IPI further improved risk stratification. Methods DLBCL patients > 60 years treated with R-CHOP on the E4494, RICOVER-60 and GELA 98-5 trials were included. A multivariate analysis was performed to assess whether male sex is an independent prognostic factor for OS in addition to the five E-IPI risk factors, E-IPI score, and E-IPI risk group. Male sex (S) was added as an additional risk factor to the E-IPI (S-EIPI, 0-6) and patients regrouped according to the number of risk factors: low (L)=0-1, low intermediate (LI)=2, high intermediate (HI)=3 and high (H)=4-6 based on the observed OS using Kaplan-Meier curves. C-statistic was used to compare the discrimination ability. The 5 year OS was estimated using the Kaplan-Meier method. Results 1079 patients (E4494, n=267; RICOVER-60, n=610; GELA 98-5, n=202) with a median follow-up of 8.9 years were included. In multivariate analyses, male sex was a significant independent predictor for OS adjusting for all five E-IPI factors, (HR 1.5, p < 0.0001), E-IPI score (HR 1.42, p < 0.001), and E-IPI risk group (HR 1.42, p < 0.001) (Table 1). C-statistic was 0.66 for S-EIPI and 0.64 for EIPI. Incorporation of sex into the E-IPI shifted 35% patients to higher risk groups, including 110 patients into the highest risk group (Table 2). The estimated 5 year OS for the S-EIPI L, LI, HI, and H risk groups was 87%, 70%, 58%, and 40%, respectively (Table 3). Compared to E-IPI, the 95% C.I. did not overlap among S-EIPI risk groups. Conclusion For DLBCL patients >60 years treated with R-CHOP, our results suggest the addition of male sex to the E-IPI may improve categorization of patients into well-defined clinically relevant risk groups. Patients with low risk S-EIPI have an excellent outcome (5 year OS 87%). Patients with high risk S-EIPI have a 5 year OS of only 40% and therapies beyond standard R-CHOP need to be explored. Disclosures: Horning: Genentech: Employment; Roche: Equity Ownership.

Abstract Background:The role of radiation therapy (XRT) for advanced stage Hodgkin lymphoma (HL) is controversial. In the HD15 trial, the German Hodgkin Study Group (GHSG) administered XRT for PET-positive residual disease ≥2.5 cm at least 2 weeks after completion of chemotherapy and showed 91.5 % in-field control rate with a median follow-up of 102 months (Engert, A; personal communication). However, there is no comparison arm where patients with PET-positive residual disease ≥2.5 cm did not receive XRT. SWOG S0816 was a US intergroup trial utilizing ABVD-based therapy with response adaptation based on interim PET imaging; XRT was not allowed per protocol, and counted as an event. In this analysis, we identified patients in S0816 who would have met HD15 criteria for XRT, but did not receive XRT per design. We then modeled the potential impact of XRT on disease control. Patients and Methods:Of 336 eligible and evaluable HIV-negative patients enrolled in S0816, 49 had an end-of-treatment PET (termed "PET3," to be done 6-8 weeks after completion of chemotherapy) that was positive (i.e. Deauville 4-5) upon central review. We simulated the progression free survival (PFS) if XRT had been delivered per HD15 criteria (PET positive disease and ≥2.5 cm), evaluating by assumptions of 50, 80 and 90% control of the disease within the XRT fields. Receiver operating characteristics (ROC) analyses were performed with additional size cut-off points of 2.0 and 1.5 cm. Results:The median follow-up for the 49 PET3 positive patients was 71 months (range 9.7-92.6). For these 49 patients, the observed landmark PFS at 2 years after the date of PET3 was 30.6%. Twenty-four (49%), 33(67%), and 40 (82%) of the 49 patients had at least one site of disease that met the HD15 criteria for XRT with ≥2.5 cm, ≥2.0 cm, and ≥1.5 cm size cut-offs respectively. Sixteen, 19, and 25 patients had disease progression respectively from each group at median of 1.4-1.5 months. Twelve, 12, and 15 patients had relapses limited to the sites that would have been radiated following HD15 criteria with ≥2.5 cm, ≥2.0 cm, and ≥1.5 cm respectively. Estimated landmark PFS at 2 years for the 49 PET3 positive patients assuming 50, 80, and 90 % control of the disease within the radiated sites following HD15 guideline with ≥2.5 cm, ≥2.0 cm, and ≥1.5 cm cut-off are summarized in columns A, B, and C of the table respectively. For the entire group of 336 patients, the observed PFS at 2 years was 79%. Estimated 2-year PFS for the entire group of 336 patients assuming 50, 80, and 90 % control of the disease within the radiated sites following HD15 guideline with ≥2.5 cm, ≥2.0 cm, and ≥1.5 cm cut-off are in columns D, E, and F of the table respectively. Conclusion: Among the PET3 positive patients, consolidation XRT per HD15 criteria with cut-off points of 2.5, 2.0, and 1.5 cm could have raised the 2-year PFS by 12-28 % assuming 50-90% local control within radiated sites. However, the improvement in PFS is more moderate at 1.6-3.9 % if we consider the entire cohort of 336 patients. Although there may be some gain in PFS as the cut-off point is lowered by our ROC analysis, one needs to consider the trade-off against potentially increasing normal tissue toxicity as more sites are irradiated. Table. Table. Disclosures Brem: Pharamcyclics: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Genetech: Membership on an entity's Board of Directors or advisory committees; Celgene: Speakers Bureau; Bayer: Membership on an entity's Board of Directors or advisory committees. Bartlett:Merck & Co: Research Funding; Forty Seven: Research Funding; Celgene: Research Funding; Immune Design: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; ImaginAB: Research Funding; Janssen: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Millennium: Research Funding; Genentech: Research Funding; Astra Zeneca: Research Funding; Pharmacyclics: Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Meyers Squibb: Research Funding; Affimed: Research Funding; Novartis: Research Funding; Pharmacyclics: Research Funding. Evens:Seattle Genetics, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Affimed: Consultancy; Janssen: Consultancy; Tesaro: Research Funding; Bayer: Consultancy; Acerta: Consultancy; Pharmacyclics International DMC: Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy. Rimsza:NanoString: Other: Inventor on the patent for the Lymph2Cx assay. Leonard:Novartis: Consultancy; Celgene: Consultancy; MEI Pharma: Consultancy; AstraZeneca: Consultancy; ADC Therapeutics: Consultancy; United Therapeutics: Consultancy; BMS: Consultancy; Biotest: Consultancy; Sutro: Consultancy; Karyopharm: Consultancy; Juno: Consultancy; Gilead: Consultancy; Genentech/Roche: Consultancy; Pfizer: Consultancy; Bayer: Consultancy. Kahl:Seattle Genetics: Consultancy; Genentech: Consultancy; Acerta: Consultancy; AstraZeneca: Consultancy; Abbvie: Consultancy; ADC Therapeutics: Consultancy; CTI: Consultancy; Gilead: Consultancy; Juno: Consultancy; Celgene: Consultancy. Smith:BMS: Consultancy; Portola: Honoraria. Friedberg:Bayer: Honoraria.

Abstract PURPOSE Urgency to initiate therapy has to be weighed against the time required for screening and consenting to enroll a patient onto a clinical trial. Exclusion of patients with rapidly progressive or symptomatic disease may lead to selection of patients with less aggressive disease. We recently identified that a short diagnosis to treatment interval (DTI) is associated with adverse clinical factors and inferior outcome in patients with diffuse large B-cell lymphoma (DLBCL) (Maurer et al, JCO 2018); shorter time to treatment was also found to be associated with outcome in other aggressive lymphomas, including mantle cell lymphoma (MCL), in the National Cancer Database (Olszewski et al, BJH 2018). Here we assess the association of DTI with clinical variables and outcome in MCL from an observational cohort with validation in patients enrolled on an NCTN clinical trial. PATIENTS AND METHODS Newly diagnosed patients with MCL were prospectively enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE Molecular Epidemiology Resource (MER), now a subcohort of the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study. Patients initially managed with observation were excluded. DTI was defined as the time in days from date of first lymphoma-containing biopsy to the initiation of therapy. Associations of DTI with clinical factors and outcome were examined using a 14 day split based on the previous MER study of DTI in DLBCL. Odds ratios (OR) and Cox model hazard ratios (HR) are reported. Outcome was assessed using event-free survival (EFS) where events were defined as progression/relapse, initiation of new anti-lymphoma therapy, or death due to any cause. A validation cohort was assembled from patients enrolled in CALGB (Alliance) clinical trial 50403. Protocol therapy was high dose chemotherapy with autologous hematopoietic stem cell transplantation (ASCT) consolidation and post-ASCT rituximab followed by bortezomib as either consolidation or maintenance. DTI was defined as time from diagnosis to study registration and outcome was assessed using progression-free survival (PFS) as defined on the clinical trial. RESULTS 271 patients with MCL enrolled in the MER from 2002-2015 and initiated treatment within 100 days of diagnosis. Median age at diagnosis was 64 years (range 36-76), 211 (78%) were male, and 92% were stage III-IV; MIPI was Low (41%), Intermediate (36%) and High (23%). Induction therapy was R-CHOP based (50%), B-R based (16%), HyperCVAD based (8%), 2-CDA based (11%), and other (15%). Median EFS of the cohort was 41 months (95% CI: 34-46). Median DTI was 26 days (IQR: 14-38) and 28% enrolled within 14 days of diagnosis, exhibiting a longer DTI than DLBCL patients enrolled in the MER during the same time period. Short DTI (0-14 days) was associated with adverse clinical factors including ECOG PS 2-4 (OR=5.74, 95% CI: 2.51-13.1, p<0.0001), elevated LDH (OR=2.30 95% CI: 1.25-4.22, p=0.0072), and higher MIPI score (OR=1.48, 95% CI: 1.04-2.07, p=0.025) but was not significantly associated with age, sex, B-symptoms, or stage (all p>0.30). Short DTI was also associated with inferior EFS (HR=1.78, 95% CI: 1.27-2.49, p=0.0008) which remained significant after adjusting for MIPI score (HR=1.72, 95% CI: 1.23-2.41, p=0.0016). In the validation cohort, 144 patients enrolled on 50403 within 100 days of diagnosis from 2006-2010. Median age at diagnosis was 59 years (range 29-69), 77% were male, and 97% were stage III-IV; MIPI was Low (51%), Intermediate (31%) and High (17%). Median PFS of the cohort was 84 months (95% CI: 50-109). Median DTI was 35 days (IQR: 22-46) and 11% enrolled within 14 days of diagnosis. Short DTI (0-14 days) was associated with PS (OR=9.00, 95% CI: 1.18-69.0, p=0.034) and) higher MIPI score (OR=2.09, 95% CI: 1.08-4.04, p=0.029) but not elevated LDH (OR=1.27, 95% CI: 0.43-3.74, p=0.66). Short DTI was associated with inferior PFS (HR=2.21, 95% CI:1.19-4.09, p=0.011) which remained clinically significant after adjusting for MIPI score (HR=1.85, 95% CI: 0.98-3.47, p=0.056). CONCLUSION A short diagnosis-to-treatment interval is strongly associated with adverse clinical factors and poor outcome in newly diagnosed MCL in the MER. Clinical trials are encouraged to facilitate enrollment of patients with short DTI to avoid potential selection bias. Support: U01 CA195568, P50 CA097274, U10CA180821, U10CA180882; ClinicalTrials.gov Identifier: NCT00310037 (CALGB 50403) Figure. Figure. Disclosures Maurer: Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Research Funding. Kaplan:Bayer Pharmaceuticals: Consultancy. Cohen:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioInvent: Consultancy; Takeda: Research Funding. Martin:Gilead: Consultancy; Kite: Consultancy; Seattle Genetics: Consultancy; AstraZeneca: Consultancy; Janssen: Consultancy; Bayer: Consultancy. Kahl:Abbvie: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy; Acerta: Consultancy; Juno: Consultancy; Celgene: Consultancy; Genentech: Consultancy; Seattle Genetics: Consultancy; CTI: Consultancy; ADC Therapeutics: Consultancy. Bartlett:ImaginAB: Research Funding; Bristol-Meyers Squibb: Research Funding; Novartis: Research Funding; Immune Design: Research Funding; Janssen: Research Funding; Merck & Co: Research Funding; Forty Seven: Research Funding; Novartis: Research Funding; Pharmacyclics: Research Funding; Affimed: Research Funding; Astra Zeneca: Research Funding; Pharmacyclics: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Millennium: Research Funding; Genentech: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cerhan:Celgene: Research Funding; Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding. Leonard:Karyopharm: Consultancy; Biotest: Consultancy; Bayer: Consultancy; Pfizer: Consultancy; ADC Therapeutics: Consultancy; Novartis: Consultancy; AstraZeneca: Consultancy; Juno: Consultancy; BMS: Consultancy; Sutro: Consultancy; MEI Pharma: Consultancy; Genentech/Roche: Consultancy; Celgene: Consultancy; Gilead: Consultancy; United Therapeutics: Consultancy.

Abstract Introduction The role of body mass index (BMI) impacting clinical outcome among lymphoma patients is controversial. Two recent studies suggest that increased BMI is associated with significantly improved survival. In this study the association between BMI at study entry and failure-free survival (FFS) and overall survival (OS) was evaluated in three phase III Eastern Cooperative Oncology Group-led trials, among patients with DLBCL (E4494), follicular lymphoma (FL) (E1496) and Hodgkin's lymphoma (HL) (E2496). Patients and Methods 537 patients with DLBCL, 730 patients with HD and 282 patients with FL were included in the analysis. BMI was calculated as weight (kilograms) divided by the square of height (meters), using data at study entry. BMI was analyzed both as continuous and categorical variables (underweight <18.5 kg/m2, normal weight: 18.5 to < 25 kg/ m2, overweight: 25 to < 30 kg/ m2, and obese :≥ 30 kg/ m2).The underweight group was excluded due to low (< 2%) prevalence. Baseline patient and clinical characteristics, treatment received and clinical outcomes were compared across BMI categories. PFS was defined as the time from study entry to relapse, progression, or death. OS was measured from study entry to death of any cause. The log-rank test and Cox regression models was used to check the association. The association between BMI and FFS/OS was also independently assessed among patients treated with rituximab. A sensitivity analysis was performed excluding patients with significant weight loss at baseline. Results Among patients with DLBCL, HL and FL, the median age was 70, 33 and 56; 29%, 29% and 37% were obese and 38%, 27% and 37% were overweight, respectively. Age was significantly different among BMI groups in all three studies. Higher BMI groups tended to have better prognosis at study entry among DLBCL and HL patients. BMI was not associated with clinical outcome, with p-values of 0.89, 0.30 and 0.40 for FFS, and p-values of 0.64, 0.67 and 0.09 for OS, for patients with DLBCL, HL and FL, respectively (Figure 1). In multivariate analysis adjusting for other clinical factors, BMI remains an insignificant predictor for all three histologies (Table 1). When limiting to patients treated with rituximab, the association remains non-significant for both FL patients (p=0.92 for PFS, p=0.36 for OS) and DLBCL patients (Figure 2). A subset analysis of males with DLBCL treated on R-CHOP, which matched the study cohort used in a recent report (Carson et al, 2012), revealed no differences in FFS (p=0.48) or OS (p=0.58) (Figure 2). Sensitivity analysis excluding patients with weight loss at study entry resulted in similar findings. Conclusion BMI was not significantly associated with clinical outcomes among patients with DLBCL, HL or FL, in three prospective phase III clinical trials. The findings contradict some previous reports of similar investigations. Further work is required to understand the observed discrepancies. Disclosures: Horning: Genentech: Employment.

Abstract Abstract 87 Background: The International Prognostic Index (IPI) remains the most powerful predictor of clinical outcome in DLBCL in the R-CHOP era, serving as a useful surrogate for the biology we are just beginning to understand. With a follow-up of more than 9 years, its uniformly staged and treated patients and its prospectively collected unstained slides for correlative studies, the clinical data set from E4494, the US Intergroup trial comparing CHOP and RCHOP in patients >60 years with DLBCL, stands as a valuable resource for investigating prognosis in DLBCL. Based on immunohistochemistry, we previously showed that rituximab modulates the prognostic significance of some biomarkers in DLBCL. With these same specimens, the quantitative nuclease protection assay (qNPA), a methodology for measuring mRNA levels in FFPET, was used to develop separate prognostic signatures for the CHOP and RCHOP arms that can be simply applied using stored unstained slides. Methods: Five micron unstained FFPET sections from 183 eligible and evaluable cases enrolled on E4494 and submitted for prospective immunohistochemical correlative studies more than ten years ago were used for this analysis. Tissue was scraped from slides and a multiplexed qNPA was performed in triplicate using a customized Array Plate assay (HTG, Inc) for 43 genes of interest. TBP served as a housekeeping gene. Association between standardized log gene expression and patient failure-free survival (FFS) and overall survival (OS) was obtained using the Cox proportional hazards model. A weighted analysis was used to eliminate the confounding effect of maintenance rituximab. Genes that showed at least marginal significance in the univariate analysis were used to perform LASSO (penalized method to select best subset) to select a final list of genes in the multivariate analysis. Using the predictive model for either CHOP or R-CHOP induction, individual risk scores were calculated based on the multivariable model, and cases were dichotomized into low and high risk groups based on the median risk score. The model was then validated using the Lenz dataset (NEJM, 2008). Results: In six cases, tissue from slides prepared >10 years ago was compared to freshly cut sections from corresponding blocks, and showed excellent concordance (corr=0.86). On-study characteristics for the 176 cases with analyzable data were representative of the greater E4494 patient population. Six gene predictors were developed for each arm of the trial: RCHOP: FN1, LMO2, AKT1, HIF1a, AKT3, BCL2; and CHOP: PDCD4, HLADRB1, COL3A1, LMO2, ROBO4, TP53. Both signatures proved powerful predictors of FFS and OS among CHOP (FFS: p=0.0031; OS: p=0.0013) and RCHOP (FFS: p=0.001; OS=p=0.0015) treated patients. When adjusted for the clinically-based IPI, the gene-risk score retained its significance (CHOP: FFS p=0.0007; OS p=0.0011; RCHOP: FFS p=0.003; OS, p=0.001) while the IPI became only marginally significant (CHOP: FFS: p=0.06, OS p=0.06; R-CHOP: FFS p=0.09, OS p=0.02), suggesting that the gene predictor accounted for much of the predictive power of the IPI. The predictive model was then validated using the Lenz dataset for OS. The predictor models for CHOP and R-CHOP-treated patients effectively dichotomized patients into prognostic subgroups (CHOP: p<0.0001; RCHOP: p=0.0014; see figure below) and this difference was maintained when the subset over age 60 was analyzed (CHOP: p=0.0008; RCHOP: p=0.017). When adjusted for the IPI, the molecular predictor developed for CHOP treated patients remained robust (OS: P=.0001; HR 2.39), while the molecular predictor for RCHOP predicted OS marginally (p=.06; HR 1.82), with shorter followup than the CHOP cohort. Conclusions: Unstained slides from FFPET stored for many years may be used to investigate gene expression in lymphoma biopsy specimens for which there is mature followup. Gene risk scores based on the expression of a limited number of genes are powerful predictors of clinical outcome. Disclosures: Pollock: HTG, Inc.: Employment, Equity Ownership. Botros:HTG, Inc.: Employment, Equity Ownership. Horning:Genentech: Employment, Equity Ownership.

Abstract Background Despite improvements in outcome following the addition of rituximab (R) to CHOP (cyclophosphamide, doxorubicin, vincristine, prednisone) (R-CHOP), patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL) and International Prognostic Index (IPI) scores of 3-5 at diagnosis have a poor outcome. Enzastaurin is a potent inhibitor of PKCβ, a component of the B-cell receptor signaling complex, with preclinical activity and clinical activity in a phase II trial in patients with relapsed DLBCL, providing the rationale for this study in the primary therapy setting. Methods PRELUDE was a multi-national, randomized, double-blinded, placebo-controlled study. Patients were required to have a histologic diagnosis of DLBCL, pre-treatment IPI score ≥3, and a complete response (CR) or CRu by International Working Group Criteria, or a negative FDG-PET scan after 6–8 cycles of R-CHOP. Patients were randomly assigned in a 2:1 ratio to receive either enzastaurin 500 mg daily or an identical placebo as maintenance therapy, for a planned treatment duration of 3 years. The primary endpoint was DFS, defined as lack of disease progression or death. Assuming a 2-year DFS rate in the control group of 70%, the primary analysis had 80% power to detect a HR of 0.67, eg, a 2-year DFS rate of 79% in the enzastaurin group. Secondary endpoints included overall survival (OS) and event-free survival (EFS). Data were analyzed 3 years after the last enrolled patient initiated treatment. Results From May 2006–April 2010, 758 patients were enrolled (enzastaurin, n=504; placebo, n=254). Median age at enrollment was 64 years (range 21-89); at diagnosis, 65% of patients had stage IV disease, 48% had B symptoms, and 25% had a mass >10 cm; baseline disease and patient characteristics were well balanced between treatment arms. Fifty-seven percent had a negative PET scan following completion of R-CHOP. Median follow-up time for all patients was 48 months (range 0.03–80). At the time of analysis, 209 events had occurred. The DFS HR for enzastaurin vs. placebo was 0.92 (95% CI: 0.69, 1.22; 2-sided log-rank p=0.54). DFS at 24 and 48 months were 79% and 70% for the enzastaurin arm, and 75% and 71% for placebo, respectively. OS at 24 and 48 months was 87% and 81% for enzastaurin, and 89% and 82% for placebo; HR for enzastaurin vs. placebo was 1.04 (95% CI: 0.74, 1.47; 2-sided log-rank p=0.81). Percent of ITT population patients on therapy at 12, 24, and 36 months was 70.6%, 60.6%, and 20.1% for enzastaurin; 72.3%, 60.6%, and 22.1% for placebo. Biomarker subgroup analysis was performed and will be available at time of presentation. Treatment emergent AEs (all grades) that were possibly study drug-related and significantly different between enzastaurin and placebo included chromaturia (18.5% vs. 0.4%), QTc prolongation (10.8% vs. 3.6%), and diarrhea (10.3% vs. 2.8%). There were no significant differences in number of patients with at least 1 grade 3 or higher AE between treatment arms. No significant differences were observed in the frequency of deaths while on therapy. Conclusion Enzastaurin did not improve DFS, EFS, or OS in patients with high-risk DLBCL and CR following R-CHOP treatment. Disclosures: Crump: Roche: Honoraria; Jansen-Ortho: Honoraria; Celgene: Honoraria; Lundbeck: Honoraria; Novartis: Research Funding; Seattle Genetics: Honoraria. Off Label Use: rituximab for maintenance therapy post autolgous transplant for lymphoma. Leppä:Eli Lilly: Research Funding. Ogura:Eli Lilly: Research Funding. Rifkin:Millenium, Celgene, ONYX: Membership on an entity’s Board of Directors or advisory committees. Mackensen:Eli Lilly: Consultancy. Offner:Eli Lilly: Membership on an entity’s Board of Directors or advisory committees. Smith:Genentech, Celgene, Spectrum, Seattle Genetics, Gilead, Amgen/Micronet: Consultancy. Tobinai:Eli Lilly: Research Funding. Hahka-Kemppinen:Eli Lilly: Employment. Thornton:Eli Lilly: Employment. Shi:Eli Lilly: Employment. Lin:Eli Lilly: Employment. Kahl:Genentech: Consultancy. Savage:Eli Lilly: Consultancy.

Abstract Abstract 1603 Background: We have previously reported similar outcomes for patients with bulky stage I or II mediastinal HL treated with combined modality therapy either with ABVD + radiotherapy or the Stanford V regimen in the North American Intergroup trial E2496 (Advani et al, ASH 2010 abstract 416). In the current analysis, we compare the patterns of failure between the two groups. Methods: Patients with stage I/II bulky mediastinal HL (maximum mediastinal mass width > 1/3 of intrathoracic diameter) were randomized to receive chemotherapy (CT) on either Arm A (ABVD x 6–8 cycles administered q 28 days) or Arm B (12 weeks of Stanford V administered weekly). Two-3 weeks after completion of chemotherapy all patients received modified involved field radiotherapy (RT) (36 Gy) delivered to the mediastinum, hila, and supraclavicular regions. Patients on Stanford V arm also received involved field RT to any other sites ≥ 5 cm at diagnosis. Patients were assessed 3, 6 and 12 months after completing RT with computed tomography scanning and then every 6 months for 5 years. The primary end points were failure free survival (FFS) and overall survival (OS). Disease progression was defined as 'in-field', 'distant' or both relative to the radiation fields prescribed in the E2496 protocol. Distant sites of failure were further characterized as intra-thoracic, intra-abdominal or other (bone, bone marrow and axillae, if not previously irradiated). Results: Two hundred and sixty-seven patients were randomized: 136 on the ABVD arm and 131 on the Stanford V arm. Patient characteristics were well matched with no differences between two arms in overall response rates (ORR), FFS and OS. (Advani et al ASH 2010 abstract 416). At a median follow up of 5.5 years 40 patients have relapsed with no difference in ABVD (n=18, 13%) versus Stanford V (n=22, 17%) (p=0.49). Central review of RT fields available in 37/40 patients found major violations with under treatment of tumor noted in 7/37 (19%). Patterns of failure are shown in Table 1. There were no differences in patterns of relapse for the two study arms. In-field relapses occurred in <10% in both study arms. Conclusion: For patients with stage I/II bulky mediastinal HL, combined modality therapy with either ABVD +RT or the Stanford V regimen results in excellent disease control. In-field relapse was uncommon. These results set a benchmark for assessing ongoing trials omitting RT in patients with stage I/II bulky mediastinal HL. Future research efforts should focus on risk stratification to identify the small subset of patients who are likely to fail standard upfront therapy. US cooperative group efforts in this subset of patients are ongoing that use interim PET-CT imaging based risk-adapted strategies. Disclosures: Horning: Genentech: Employment, Equity Ownership.

Abstract Abstract 2687 Background: Patients with early stage (Stages I, II) diffuse large B cell (DLBCL) have been traditionally treated with either CHOP x6 alone or with CHOP followed by involved field external beam radiotherapy (IFRT). With the demonstration of the superiority of rituximab CHOP (RCHOP) in advanced stage DLBCL, RCHOP has been adopted as the chemoimmunotherapy standard of care in early stage disease with or without IFRT. Radioimmunotherapy (RIT) has the advantage of delivering high-energy, short path length radiation in a targeted approach using an anti-CD20 antibody as the carrier. Thus, radiation is potentially targeted to microscopic sites outside of known disease. Goals: To evaluate the complete response (CR) rate and functional CR rate (CR or CRu/PR and PET negative) to a treatment regimen of RCHOP followed by 90Y-ibritumomab tiuxetan (Zevalin, Spectrum Pharmaceuticals) radioimmunotherapy (RIT); only patients not achieving PET negative status after RIT were to be given IFRT. The study goal was to achieve a functional CR rate of ≥75%. Patients and Methods: Eligible patients were those with new, untreated Stages I or II DLBCL as determined by standard CT scanning, adequate blood counts, creatinine and bilirubin <2.0 mg/dl, cardiac ejection fraction >45%, and a performance status 0–2. Stage I patients were required to have ≥1 adverse risk factor (≥60 years, bulky disease, elevated LDH or PS2). Patients received standard RCHOP21 × 2 cycles and then were restaged. Patients in CR received 2 additional cycles; those in PR or CRu received 4 additional cycles. At end of RCHOP a PET scan was repeated and centrally reviewed; those with a PR or functional CR proceeded to Zevalin RIT 0.4 mCi/kg (maximum 32 mCi) within 12 weeks of the last RCHOP. Patients were restaged 12 weeks post-RIT; PET negative patients were observed without maintenance; PET positive patients received 30Gy involved field radiation and then were restaged. Descriptive statistics were used to summarize the patient characteristics, treatment and response. The Kaplan-Meier method was used to estimate failure rates. Results: Between Dec 2004 and Nov 2008, 62 patients were enrolled; after pathology review 53 were considered eligible. 42% (22/53) patients were stage I/IE; 58% (31/53) were stage II/IIE. 57% (30/53) received 6 cycles of RCHOP; 40% (21/53) received 4 cycles; and 2 patients received 1 and 2 cycles, respectively. After immunochemotherapy, 79% (42/53) were in functional CR and 19% (10/53) PR; 1 was unevaluable. Of the 53 eligible patients who completed RCHOP therapy 91% (48/53) proceeded to RIT. After RIT, 87% (46/53; 95% CI: 75–95) were in CR/CRu and 89% (47/53; 95% CI:77–96%) were in functional CR. One patient proceeded to IFRT. The median follow-up is now 4.3 years. Seven (13%) of patients have had tumor progression but only 2 have died (1 of disease). At 4 years, 88% of patients remain progression free and 98% remain alive (Fig 1,2). The median has not been reached for either PFS or OS. There has been one case of myelodysplastic syndrome. Conclusions: Combination immunochemotherapy and RIT is an active regimen for patients with early stage DLBCL. Nearly all patients will achieve functional CR without the requirement of IFRT. The regimen of RCHOP and RIT for early stage DLBCL is worthy of further study. Disclosures: Witzig: Spectrum: Membership on an entity's Board of Directors or advisory committees, Research Funding, uncompensated Other. Off Label Use: Use of Zevalin in treating patients with Stage I-II DLBCL. Kahl:Roche: Consultancy; Genentech: Consultancy, Research Funding. Horning:Genentech: Employment; Roche: Equity Ownership.