Hong, Fangxin

e19132 Background: The Functional Assessment of Cancer Therapy–General has an item about patient tolerability of treatment: “I am bothered by side effects of treatment” (GP5). We examined the predictive value of this single item for early treatment discontinuation in clinical trials. Methods: GP5 level prior to protocol therapy (rated using a 5-point Likert scale) and treatment start/end dates and off treatment reason data at each treatment phase were drawn from five phase III clinical trials conducted by ECOG-ACRIN. In the present analysis, GP5 was dichotomized as 0 = “Not at all”/“A little bit” and 1 = “Somewhat”/“Quite a bit”/“Very Much”. Early treatment discontinuation was defined either as receiving less than protocol specified cycles of treatment when maximum cycles specified in the protocol (E1A06 induction, E1912 induction, E1609 induction, E1105 induction, E5103 adjuvant), analyzed using logistic regression via odds ratio [OR]), or treatment cessation for reasons other than progressive disease or death when treatment continued until progression or intolerability (E1A06 maintenance, E1912 maintenance, E1609 maintenance, E1105 maintenance), analyzed using Cox proportional hazard model via hazard ratio [HR]. Results: GP5 prior to treatment was significantly associated with early discontinuation of E1A06 maintenance, E1609 maintenance, E1912 maintenance, and E1912 induction. No significant association was found for other therapies examined in the study. Conclusions: High GP5 level prior to treatment is associated with higher likelihood of early treatment discontinuation in patients who have received previous treatment. The limited predictive value of GP5 for treatment naïve patients is more limited, serial on-treatment assessment should be considered in this setting. Clinical trial information: NCT00602641 . [Table: see text]

Abstract Background: Despite advances in chemotherapy, relapsed/refractory (R/R) Hodgkin lymphoma (HL) remains a significant clinical challenge and an unmet medical need. HL has a unique biology in which a small number of malignant Hodgkin Reed-Sternberg (HRS) cells propagate an immunosuppressive microenvironment. We hypothesized that using immune checkpoint inhibitor therapy to activate the immune cells in the tumor microenvironment, and concurrently targeting HRS cells with the CD30 antibody-drug conjugate brentuximab vedotin (BV), could overcome tumor cell resistance. E4412 is a Phase 1 ECOG-ACRIN sponsored study of the combination of BV and ipilimumab (IPI) and nivolumab (Nivo) in patients with R/R HL. Here we present the preliminary safety and response data on the patients treated with BV + Nivo (Arms D and E). Methods: Patients with confirmed R/R HL were treated with Nivo 3mg/kg and BV 1.2mg/kg (Arm D: Dose Level 1) or 1.8mg/kg (Arm E: Dose Level 2) in dose escalation with a 3+3 design and an expansion cohort (Arm F) of 9 patients. BV and Nivo are given every 21 days for 16 cycles; Nivo may be continued for an additional year (total 2 years of Nivo therapy). Dose limiting toxicity (DLT) was defined for purposes of dose escalation within the first cycle of therapy. Patients are followed for toxicity up to 30 days beyond their last treatment. Results: As of 7/20/2016 10 patients (1 ineligible) have been treated with BV + Nivo. We report the data on the dose escalation population: 3 patients: Arm D, 7 patients: Arm E. Data will be updated to include the full BV + Nivo dose escalation and dose expansion cohorts (Arms D, E & F) (N = 19) by the time of the Annual Meeting. Median age was 46; (range: 25-53). Six patients were male. Patients were heavily pretreated with a median of 3 prior therapies. Six patients had prior SCT (5 autologous, 1 allogeneic); 2patients had prior treatment with BV. Safety: Ten of 10 patients are evaluable for safety. Overall safety profiles show that the regimen of BV + Nivo was extremely well tolerated. One patient out of 7 in dose level 2 experienced a DLT (pneumonitis grade 3 with grade 3 dyspnea and hypoxia, and typhilits grade 3), this patient had received a prior SCT, and made a full recovery from his toxicities. Per protocol he discontinued further therapy. No other DLTs were noted for the remaining 9 patients. Common and relevant toxicities considered at least possibly related to drug during any cycle of treatment are shown in Table 1. There were no Grade 4 treatment related adverse events (AEs). The only additional grade 3 AEs noted were one each grade 3 rash and puritis. The most common grade 1-2 treatment related adverse events were: transaminitis (9), peripheral sensory neuropathy (6), and rash (3). Other AEs of interest included: diarrhea (3), blurry vision (2), and myalgias (2). One grade 1-2 infusion reaction was noted, this patient was able to receive subsequent therapy with pre-medication. Response: Eight of 10 patients are evaluable for response. One patient is not yet evaluable. For the 8 evaluable patients the overall response rate (ORR) for the combination of BV + Nivo was 100%, with a CR rate of 62.5% (5/8), with 95% CI of 0.25-0.91. One patient was ineligible for laboratory studies that were out of range at screening, however this patient continues on therapy, and also had a response. One of 5 CRs occurred at in dose level 1 (BV 1.2 mg/kg). Both patients who had been treated with prior BV achieved CRs. The progression free survival (PFS) to date is 100% with a median follow-up of 0.3 years. Conclusion: In this first reported study of the combination of the checkpoint inhibitor Nivo and the ADC BV therapy was well tolerated with one DLT, and primarily grade 1 and 2 toxicities. In a heavily pretreated patient population, 20% of whom had had prior BV and 60% of whom were s/p ASCT, the ORR of 100% and CR rate of 62.5% suggests a deepening of response compared to either therapy alone. Optimization of this combination strategy is planned with ongoing accrual to cohorts receiving BV + Nivo, and BV + Ipi + Nivo. Data will be updated to include the full BV + Nivo cohort (N = 19) by the time of the Annual Meeting. Disclosures Diefenbach: Seattle Genetics: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Research Funding; Merck: Research Funding; Genentech: Research Funding; Incyte: Research Funding; LAM Therapeutics: Research Funding; Molecular Templates: Research Funding; Oncomed: Research Funding; This study was coordinated by the ECOG-ACRIN Cancer Research Group (Robert L. Comis, MD and Mitchell D. Schnall, MD, PhD, Group Co-Chairs) and supported by the National Cancer Institute of the National Institutes of Health under the following award number: Research Funding. Hong:This study was coordinated by the ECOG-ACRIN Cancer Research Group (Robert L. Comis, MD and Mitchell D. Schnall, MD, PhD, Group Co-Chairs) and supported by the National Cancer Institute of the National Institutes of Health under the following award number: Research Funding. Cohen:Seattle Genetics: Consultancy, Honoraria, Research Funding; BMS: Research Funding. Advani:Stanford University: Employment; Juno: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Spectrum: Consultancy, Honoraria; Sutro: Consultancy, Honoraria; Genentech: Consultancy, Honoraria, Research Funding; Kura: Research Funding; Merck: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Agensys: Research Funding; Pharmacyclics: Research Funding; Infinity: Research Funding; Millennium: Research Funding; FortySeven: Consultancy, Honoraria; Kyowa Hakko Kirin: Consultancy, Honoraria. Kahl:This study was coordinated by the ECOG-ACRIN Cancer Research Group (Robert L. Comis, MD and Mitchell D. Schnall, MD, PhD, Group Co-Chairs) and supported by the National Cancer Institute of the National Institutes of Health under the following award number: Research Funding. Ansell:BMS, Seattle Genetics, Merck, Celldex and Affimed: Research Funding.

Background: Standard first-line treatment for patients diagnosed with diffuse large B-cell lymphoma (DLBCL) is the R-CHOP regimen. Despite numerous efforts to improve on this regimen, in all comers and specifically in those with activated B-cell (ABC)-type DLBCL, results from large randomized studies have failed to show a significant clinical advantage above this standard. Recently, 2 large clinical trials in previously untreated DLBCL evaluated the combination of lenalidomide/R-CHOP (R2-CHOP) vs standard R-CHOP and demonstrated discordant results. We analyzed data from these trials to identify differences that may have impacted the disparate trial outcomes while identifying patient characteristics associated with benefit from the addition of lenalidomide across the trials. Methods: The 2 trials included in this evaluation are ROBUST, an international, randomized, double-blinded, placebo-controlled, phase III study of R2-CHOP vs placebo/R-CHOP, and the Intergroup ECOG-ACRIN 1412 (E1412) trial, a US-only, randomized, open-label, phase II study of R2-CHOP vs R-CHOP. Additional key study design differences included dosing, and subtype timing and inclusion (both studies used gene expression profiling [GEP] by NanoString). R-CHOP dosing differed only for prednisone, which was a flat 100 mg dose, d1-5 in ROBUST and 100 mg/m2, d1-5 in E1412. The lenalidomide dose and schedule varied between studies: 15 mg/d, d1-14/21 for ROBUST (210 mg/cycle) and 25 mg/d, d1-10/21 (250 mg/cycle) for E1412. ROBUST enrolled only patients prospectively identified with the ABC subtype, whereas E1412 enrolled all otherwise eligible patients and retrospectively evaluated for ABC-type with prespecified ABC-type accrual and power parameters. Both studies enrolled patients with IPI status ≥ 2, ECOG PS 0-2, and Ann Arbor stage II-IV (E1412 stage II with mass > 10 cm). The primary endpoint in both was progression-free survival (PFS; central review for ROBUST and investigator-assessed for E1412). Secondary endpoints included event-free survival (EFS; key for ROBUST), overall and complete response rates, overall survival (OS), and safety. Results: ROBUST enrolled 570 ABC patients and E1412 enrolled 280 GCB, ABC, and unclassified DLBCL patients. Patient profiles in both studies (ROBUST [ABC]/E1412 [all COO]) were similar in terms of median ages (65 y/66 y), male sex (58%/61%), and ECOG PS 1-2 (55%/63%). Patients in E1412 were more high risk: IPI 2 (42% ROBUST/34% E1412), IPI ≥ 3 (58%/66%), and Ann Arbor stage III/IV disease (87%/97%). Importantly, there was a notable difference in the time from patient diagnosis to treatment: median 31 days for ROBUST and 21 days (22% > 31 d) for E1412. Only 6% of patients in ROBUST were treated within 2 weeks of diagnosis vs 30% in E1412. At a median follow-up of ~2.5 y for both studies, E1412 met its primary endpoint of improvement in PFS with 34% reduction in the risk of PD/death (2-y PFS: 76% vs 70%) for all patients, but did not reach statistical significance in ABC-DLBCL patients for 2-y PFS (71% vs 61%) or 2-y OS (88% vs 76%). ROBUST showed no significant improvement in the primary PFS endpoint (2-y PFS: 67% vs 64%) or 2-y OS (79% vs 80%) in ABC patients. Subgroup analyses of PFS comparing R2-CHOP vs R-CHOP control within each study suggested that certain baseline factors favor the R2-CHOP arm, including: female sex, high IPI score (≥ 3), non-bulky disease (< 7 cm), and high Ann Arbor stage IV disease. Conclusion: While the ROBUST study design integrated state-of-the-art, real-time GEP to prospectively identify ABC-DLBCL patients with rapid lab turnaround time, cases of logistical delays in tissue submission for central analysis and staging procedures may have resulted in accrual of patients with lower-risk DLBCL and prolonged time from diagnosis to treatment. In contrast, E1412 retrospectively stratified patients by COO through GEP and was able to accrue higher-risk patients irrespective of COO within a shorter time from diagnosis to treatment, which among other differences (eg, smaller population size, study phase), could contribute to the improvement over R-CHOP control. Our comparative findings have significant implications for the design of future biomarker-driven trials and provide momentum for studies of novel combinations with R-CHOP in DLBCL. Further investigation into other factors, including dose intensity and their correlation with outcomes, will be presented. Disclosures Nowakowski: Celgene: Consultancy, Research Funding; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding; Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; Curis: Research Funding; Bayer: Consultancy, Research Funding. Chiappella:Servier: Other: advisory board, Speakers Bureau; Roche: Speakers Bureau; Teva: Speakers Bureau; Celgene: Other: advisory board, Speakers Bureau; Janssen: Other: advisory board, Speakers Bureau. Hong:Dana Farber Cancer Institute: Employment; Merck: Consultancy. Scott:Roche/Genentech: Research Funding; Celgene: Consultancy; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding. Amengual:Appia Pharmaceuticals: Research Funding; Epizyme: Speakers Bureau. Leonard:BeiGene: Consultancy; Miltenyi: Consultancy; Sandoz: Consultancy; Gilead: Consultancy; Celgene: Consultancy; ADC Therapeutics: Consultancy; MorphoSys: Consultancy; ADC Therapeutics: Consultancy; Epizyme, Inc: Consultancy; Miltenyi: Consultancy; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy; Karyopharm Therapeutics: Consultancy; Akcea Therapeutics: Consultancy; Merck: Consultancy; Nordic Nanovector: Consultancy; Akcea Therapeutics: Consultancy; Bayer Corporation: Consultancy; Sandoz: Consultancy; MorphoSys: Consultancy; Gilead: Consultancy; BeiGene: Consultancy; AstraZeneca: Consultancy; Nordic Nanovector: Consultancy; Sutro Biopharma: Consultancy; Merck: Consultancy. Friedberg:Bayer: Honoraria, Other: Data & Safety Monitoring Committee; Acerta: Other: Data & Safety Monitoring Committee. Kostakoglu:F. Hoffman-La Roche: Consultancy; Genentech: Consultancy. Jurczak:Morphosys: Research Funding; Bayer: Research Funding; Roche: Research Funding; Incyte: Research Funding; Gilead: Research Funding; Celgene Corporation: Research Funding; Sandoz: Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novo Nordisk: Research Funding; Servier: Research Funding; Takeda: Research Funding; TG Therapeutics: Research Funding; Celtrion: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Loxo: Membership on an entity's Board of Directors or advisory committees, Research Funding. Yamamoto:Bristol-Myers Squibb: Consultancy, Honoraria; Bayer: Research Funding; Celgene Corporation: Consultancy, Honoraria, Research Funding; Mundipharma: Consultancy, Honoraria, Research Funding; Astra-Zeneca: Consultancy, Research Funding; Eisai: Consultancy, Honoraria, Research Funding; Meiji Seika Pharma: Consultancy, Honoraria; ARIAD: Research Funding; MSD: Consultancy, Honoraria; Gilead Sciences: Research Funding; Ono: Consultancy, Honoraria, Research Funding; SymBio: Research Funding; HUYA/IQVIA Services Japan: Consultancy, Honoraria; AbbVie: Consultancy, Research Funding; Chugai: Consultancy, Honoraria, Research Funding; Pfizer: Honoraria; Sumitomo Dainippon: Honoraria; Incyte: Research Funding; Janssen: Honoraria; Kyowa Kirin: Honoraria; Novartis: Honoraria, Research Funding; Otsuka: Honoraria; Sanofi: Honoraria; Solasia Pharma: Research Funding; Takeda: Consultancy, Honoraria, Research Funding. Czuczman:Celgene Corporation: Employment, Equity Ownership. Russo:Celgene Corporation: Employment, Equity Ownership. Hudak:Celgene Corporation: Employment, Equity Ownership; Novartis: Employment, Equity Ownership. Zhang:Celgene Corporation: Employment, Equity Ownership. Wade:Celgene: Employment, Equity Ownership. Kahl:ADC Therapeutics: Consultancy, Research Funding; BeiGene: Consultancy; TG Therapeutics: Consultancy; Seattle Genetics: Consultancy. Vitolo:Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; F. Hoffmann-La Roche: Speakers Bureau; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. OffLabel Disclosure: Yes, these trials discuss off-label clinical trial investigation of lenalidomide plus R-CHOP in patients with newly diagnosed diffuse large B-cell lymphoma.

Abstract Background: Checkpoint blockade therapies (CBT) have substantially improved outcomes for patients in a variety of cancers. However, they are associated with a unique spectrum of immune-related adverse events (AEs). Additionally, unlike standard chemotherapy, many patients (pts) remain on CBT for prolonged periods of time, thus immune-related symptomatic AEs may be chronic or low grade therefore important to capture long term tolerability when used as a single agent or in combination with chemotherapy. In this study, we applied the Toxicity over Time (ToxT) analytic approach (Thanarajasingam et al, Lancet Oncol 2016), which incorporates the dimension of time and includes chronic lower grade events, to the first 6 cohorts (A-F) of a Phase 1/2 ECOG-ACRIN sponsored study of the combinations of Brentuximab Vedotin (BV) and the CBT therapies ipilimumab (Ipi) and nivolumab (Nivo) in pts with relapsed or refractory Hodgkin lymphoma (R/R HL). Methods: Pts with confirmed R/R HL were treated with BV 1.8mg/kg + Ipi 1or 3 mg/kg (n=23); or Nivo 3mg/kg + BV: 1.2 or 1.8 mg/kg (n=19). BV was administered every 21 days for 16 cycles; Ipi every 21 days x 4 and then every 3 months for one year and Nivo every 21 days for up to 2 years. Seven symptomatic (subjective) AEs were selected: fatigue, peripheral sensory neuropathy (PSN), nausea/vomiting (NV), rash/skin (RS), diarrhea, ocular-all types, and hair loss. Treatment-related AEs of any grade were investigated by conventional maximum grade toxicity analysis (ToxC) and ToxT methods up to 12 cycles. Using ToxT, mean AE grades over cycles were analyzed for time trend with repeated measures models, time to grade 2 or higher AE (gr2+) was analyzed with time-to-event analysis; AE profile over the entire course of the study was summarized by area under the curve (AUC) analyses. Comparisons were performed between treatment groups: BV/Ipi(A-C arms) and BV/Nivo (D-F arms). Results: 9/23 (BV/Ipi) and 6/19 (BV/Nivo) pts completed 10 cycles. For BV/Ipi vs. BV/nivo, ToxC provides overall incidence rates (any grade): fatigue 52% vs 26% (p=0.09); PSN 61% vs 53%; NV 70% vs 53% ; RS 65% vs. 37% (p=0.07); diarrhea 57% vs. 21% (p=0.02); ocular 17% vs. 21% ; and hair loss 17% vs. 0% (p=0.06), respectively. Gr3 AE occurred in 1 pt (2.4%) each for PSN, NV, diarrhea, and 6 pts (14.3%) for RS, and were similar between BV/ipi and BV/nivo. AUC from ToxT which captures chronic lower grade AEs suggested for BV/Ipi: diarrhea (p=0.02) and NV (p=0.03) are significantly more substantial over time with a trend seen for fatigue (p=0.07), RS (p=0.07) and hair loss (p=0.07) . Additionally, ToxT captures the trajectory of AEs, demonstrated a rising incidence and worsening grade of PSN (BV-related) on BV/Ipi (c1: 9% gr1, c2: 21% gr1 5% gr2, c5: 11% gr1 and c10: 22% gr2 [p=0.005], Fig 1a). In contrast there was a slow but significant decreasing incidence of NV on both combinations; for BV/Nivo (c1:52% gr1, c5: 26% gr1 and c10: 22% gr1) and BV/Ipi (c1: 47% gr1 ,c5: 0% and c10 1% gr1) with p=0.006 (Fig 1b). RS and diarrhea appear early on treatment and are not cumulative (Fig1c and 1d). There is no significant difference in the time to gr 2+ toxicities in any of the 7 AE. Combining all 7 AEs and using the maximum grade as a pilot measure of overall AE burden , ToxC indicates no difference in any grade (100% vs 100%) but a significantly higher gr 3+ incidence (35% vs. 11%) for BV/Ipi. Additionally, ToxT further elucidates that BV/Ipi is associated with significantly higher overall AE over time (Fig 2a, p=0.02) and compared to BV/Nivo a significantly higher risk of developing gr 2+ toxicity ( 57% vs 16% gr2 + event by day 50) (HR=0.41, p=0.02, Fig 2b). Conclusions: The CBT therapies Ipi and Nivo, in combination with BV, are overall both well tolerated over time, although BV/Ipi has a higher overall AE burden. Neither regimen has significant cumulative immune toxicity. Results of this analysis should be interpreted in the context of limited number of pts in both cohorts. A larger scale examination of this analysis is planned to incorporate both phase 1 and the ongoing phase 2 components of E4412. Compared with conventional tox analysis, ToxT delineated important additional and clinically relevant depictions of AEs over time and adds a more comprehensive assessment of the tolerability of chronically administered immune therapies for lymphoma. Disclosures Hong: Merck: Consultancy. Ansell:Regeneron: Research Funding; Merck & Co: Research Funding; Takeda: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Pfizer: Research Funding; Celldex: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding. Cohen:Bristol-Myers Squibb: Research Funding; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Janssen: Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: 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; Infinity Pharmaceuticals: 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; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioInvent: Consultancy; AbbVie: 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; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Research Funding; BioInvent: Consultancy; Pharmacyclics: 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; Takeda: Research Funding. Advani:Kura: Research Funding; Janssen: Research Funding; Bayer: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Autolus: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Cell Medica: Consultancy, 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; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Millenium: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Celgene: Research Funding; Agensys: Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Infinity: Research Funding; Forty Seven Inc.: Research Funding; Celgene: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Regeneron: Research Funding; Gilead/Kite: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Merck, Takeda, Celgene, Seattle Genetics, Bayer: Research Funding. Svoboda:Pharmacyclics: Consultancy, Research Funding; Merck: Research Funding; KITE: Consultancy; TG Therapeutics: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Regeneron: Research Funding; Seattle Genetics: Consultancy, Research Funding; Kyowa: Consultancy. Karmali:AstraZeneca: Speakers Bureau; Gilead: Speakers Bureau. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Dueck:Bayer: Employment; Phytogine: Employment; Pfizer: Honoraria. Kahl:Genentech: Consultancy; Acerta: Consultancy; AstraZeneca: Consultancy; Abbvie: Consultancy; Juno: Consultancy; Celgene: Consultancy; Seattle Genetics: Consultancy; ADC Therapeutics: Consultancy; CTI: Consultancy; Gilead: Consultancy. Diefenbach:Merck: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Acerta: Research Funding; Millenium/Takeda: Research Funding; Genentech: Consultancy; Denovo: Research Funding; Incyte: Research Funding; Seattle Genetics: Consultancy, Research Funding; Trillium: Research Funding.

Abstract Background: Bortezomib has efficacy in follicular lymphoma (FL). Though generally well tolerated, it is associated with a few known toxicities, including neurotoxicity. As a chronically administered agent, it is important to investigate the tolerability of bortezomib over time as a single agent and in combination with chemotherapy. The current method of summarizing adverse events (AEs) -focusing on the maximum grade and reporting only grade 3 or higher incidences- fails to capture toxicity that evolves over time or chronic low grade AEs that may occur at significant expense to patients' quality of life. In this study, we applied the Toxicity over Time (ToxT) analytic approach (Thanarajasingam et al, Lancet Oncol 2016), which graphically and analytically depicts AEs longitudinally, to a randomized Phase 2 ECOG-ACRIN sponsored study, E2408, to characterize chronic toxicity of bortezomib (V) when added to standard bendamustine-rituximab (BR) induction in previously untreated high risk FL. Methods: In E2408, patients (pts) were randomized to one of 3 arms at a 1:2:2 ratio: A) BR x 6 followed by maintenance rituximab (MR) x 2 years (yrs) vs B) BVR x 6 (bortezomib 1.3 mg/m2 IV/SQ days 1, 4, 8, 11) then MR x 2 yrs vs C) BR x 6 then MR x 2 yrs + lenalidomide 20mg/day x 1 yr. Pts enrolled 1/2011-5/2015. This analysis focuses on the 6 cycles of induction only, with arms A and C combined. Six AEs of interests were selected, 4 symptomatic (subjective) AEs (peripheral sensory neuropathy (PSN), diarrhea, febrile neutropenia, fatigue); and 2 non-symptomatic (objective) AEs (neutropenia and thrombocytopenia). Treatment-related post baseline AEs of any grade were investigated by conventional maximum grade toxicity analysis (ToxC) and ToxT methods. The mean AE grades over cycles were analyzed by repeated measures models, time to grade 2 or higher (gr2+)AE were analyzed with time-to-event analysis; and AE profile over the entire course of the study was summarized by area under the curve (AUC) analyses. Comparisons were performed between treatment arms (BVR vs. BR). Results: All 280 randomized treated pts (187 on BR, 93 on BVR) were included in the analysis regardless of eligibility status; 87% (163/187 BR, 81/93 BVR) completed all 6 cycles. Analyzing the symptomatic AEs,ToxC indicates that the overall incidence of grade 3+ PSN was significantly higher in BVR (12%) than BR (1%) (p<.0001). Additional, ToxT captures the trajectory, demonstrating a rapid, rising incidence and worsening grade of PSN on BVR vs BR over 6 cycles in a steam plot of mean gr. by cycle (Fig 1a) and bar chart of incidence and grade per cycle (c1: 13% gr1 3% gr2, c6: 36% gr1 12% gr2 6% gr3 on BVR; c1: 3% gr1, c6: 10% gr1 1% gr2 on BR, Fig. 1b). Risk of developing gr2+ PSN was significantly higher in BVR than BR with 28% vs 0.5% by day 100 (HR=0.01, p<.0001, Fig. 1c). ToxC captures a higher incidence of grade 3+ diarrhea on BVR (7% vs. 1% , p=.01) while AUC from ToxT includes chronic lower grade diarrhea, that is substantial over time on BVR vs. BR (p<.0001), but is not cumulative. Furthermore, the risk of developing gr2+ diarrhea affecting drug tolerability is significantly higher on BVR than BR(13% vs 5% by day 100) (HR=0.3, p=.05). Febrile neutropenia appeared to be similar, and fatigue was marginally more severe under BVR (p=.06 by AUC). For objective AEs, ToxC reveals no significant difference in neutropenia or thrombocytopenia BVR vs BR (neutropenia gr 3+: 36% vs 31%, p=.4; thrombocytopenia gr3+: 10% vs. 5%, p=.12). However, ToxT illustrates that neutropenia is cumulative, worsening over repeated exposure to drug (c1: 2% gr1 5% gr2 5% gr 3+ , c6: 7% gr1 10% gr2 12% gr3+ both arms combined; p<.0001) on mean grade over time (Fig. 2a). In contrast, thrombocytopenia does not worsen with continued treatment (Fig 2b, p=.73). Conclusions: Compared with conventional toxicity analysis (ToxC), ToxT delineated important additional and clinically relevant depictions of both symptomatic and laboratory AEs over time for bortezomib added to BR in FL pts. In patients receiving BVR, close monitoring is suggested for PSN, diarrhea and neutropenia for reassessment of risks and benefits, symptom interventions and dose modification. Longitudinal toxicity analyses such as ToxT can guide AE interventions as well as patient and clinician education, and provide a more patient-centered toxicity assessment of chronically administered therapies for lymphoma. Disclosures Hong: Merck: Consultancy. Evens:Seattle Genetics, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta: Consultancy; Abbvie: Consultancy; Bayer: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Tesaro: Research Funding; Affimed: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics International DMC: Membership on an entity's Board of Directors or advisory committees. Advani:Kura: Research Funding; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Celgene: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kyowa: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Bayer: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Cell Medica: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Infinity: Research Funding; Gilead/Kite: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Janssen: Research Funding; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Regeneron: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Forty Seven Inc.: Research Funding; Merck: Research Funding; Millenium: Research Funding; Agensys: Research Funding; Celgene: Research Funding; Autolus: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board. Gascoyne:NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Dueck:Bayer: Employment; Pfizer: Honoraria; Phytogine: Employment. Kahl:Genentech: Consultancy; Acerta: Consultancy; ADC Therapeutics: Consultancy; Seattle Genetics: Consultancy; Abbvie: Consultancy; Juno: Consultancy; Gilead: Consultancy; Celgene: Consultancy; CTI: Consultancy; AstraZeneca: Consultancy.

Abstract Background: There remains a critical need to identify untreated HR FL patients (pts) who are at increased risk of early progression and death with conventional treatment. Data examining baseline PET has been reported to be prognostic in FL, however, there remains a paucity of data analyzing this in the context of bendamustine/rituximab (BR) induction followed by maintenance rituximab (MR). We examined the prognostic impact of baseline PET metabolic imaging from the randomized BIONIC study for pts with untreated HR FL. Methods: The BIONIC study conducted by the ECOG-ACRIN Cancer Research Group enrolled untreated grade I/II or IIIa FL pts with HR disease defined as GELF high tumor burden and/or FLIPI score of 3-5. Pts were randomized to: a) standard BR induction x 6 followed by maintenance rituximab (MR) q 2 months x 2 years vs b) bortezomib + BR x 6 followed by MR q 2 months x 2 years vs c) BR x 6 followed by q 2 months MR x 2 years + lenalidomide given concurrently with the first year of MR. Survival analyses showed no significant differences in 4-year progression-free survival (PFS) or overall survival (OS) for any study arm (Evens AM et al, ASH 2017). All pts were thus pooled for the purpose of analyzing baseline PET imaging and other characteristics and for correlation with clinical outcomes. Kruskal-Wallis & Wilcoxon Rank Sum test were used to assess differences in distribution of: metabolic measurements (SUVmax and SUVmean of the dominant mass (i.e., the mass/lesion with the highest SUV uptake); metabolic tumor volume (MTV); and total lesion glycolysis (TLG) by categorical variables); induction treatment response; and end-of-induction (EOI) PET response vis-à-vis Deauville scoring (1-3 = negative). Cox proportional hazards regression was used to correlate these metabolic measurements with PFS & OS and multivariable analyses were conducted. An optimal cutoff threshold (grouping into 'High' or 'Low' categories) was used for the metabolic measurements that were significantly associated with PFS & OS. Results: Metabolic data were received and measurements were analyzed centrally on 182 (71%) of 257 eligible pts. The EOI overall response rate (ORR) for all pts on study was 92% with a complete remission (CR) rate of 73%. Additionally, 12% of pts experienced early progression of disease (POD) within 2 years. SUVmax was borderline for association with PFS (P=0.06) and MTV and TLG were not associated with PFS or OS. We demonstrated a statistically significant linear relationship between continuous SUVmean score with PFS and OS, and thereafter, used the minimum p-vlaue approach to determine the optimal cutoff threshold of 7.03 to group pts into 'High' and 'Low' risk groups; with this threshold, baseline SUVmean of the dominant mass was categorized as high risk in 27% pts. The 4-year PFS rates for SUVmean low vs high groups were 80% (95% CI 72, 90%) vs 55% (40, 74%), respectively, P<0.001; and the corresponding 4-year OS rates were 93% (89, 98)% vs 80% (95% CI 69, 93%), respectively, P=0.01 (see Fig. 1). Sensitivity analyses showed no differences in baseline SUVmean by study arm, GELF or FLIPI. The only clinical characteristic that varied among patients with low vs high baseline SUVmean was Black race (0.8 vs 8.0%, respectively, Chi-square P=0.08); there were no other differences based on age, sex, stage, FLIPI, GELF status, ECOG PS, LDH, or # of extranodal sites. In addition, baseline SUVmean correlated with EOI PET (negative EOI PET with baseline SUVmean Low vs High: 81% vs 62%, respectively, P=0.03). In multivariable analyses, both baseline SUVmean and EOI PET remained significant (SUVmean: PFS HR 2.62 (95% CI 1.40-4.92), P=0.001, OS HR 2.37 (95% CI 1.01-5.56), P=0.02; EOI PET PFS HR 4.70 (95% CI 2.74-9.54), P<0.001, OS HR 2.78 (95% CI 1.18-6.56), P=0.01). Finally, baseline SUVmean was also strongly predictive of FL pts who experienced early 2-year POD (Chi-square P<0.001). Conclusions: High baseline SUVmean of the dominant mass was a strong independent prognostic factor for survival for untreated HR FL pts treated with BR-based induction with rituximab maintenance and significance was independent of FLIP or GELF criteria. Collectively, this represents a novel and simple method to identify FL pts at increased risk of early POD and poor survival with standard therapy. Continued investigation of combined PET imaging analyses and other correlative studies to enrich prognostication are warranted. Disclosures Hong: Merck: Consultancy. Advani:Bristol Myers Squibb: Other: Consultancy/Advisory role and Institutional Research Support; Kyowa: Other: Consulting/Advisory Role; Infinity: Other: Institutional Research Support; Pharmacyclics: Other: Institutional Research Support; Seattle Genetics: Other: Consultancy/Advisory role, Institutional Research Support; Regeneron Pharmaceuticals, Inc.: Other: Institutional Research Support; Millenium: Other: Institutional Research Support; Bayer Healthcare Pharmaceuticals: Other: Consultancy/Advisory Role; Autolus: Other: Consultancy/Advisory Role; Takeda: Other: Consultancy/Advisory Role; Celgene: Other: Institutional Research Support; Roche/Genentech: Other: Consultancy/Advisory Role, Institutional Research Support; AstraZeneca: Other: Consultancy/Advisory Role; Cell Medica: Other: Consultancy/Advisory Role; Gilead/Kite: Other: Consultancy/Advisory Role; Agensys: Other: Institutional Research Support; Kura: Other: Institutional Research Support; Forty Seven, Inc: Other: Institutional Research Support; Merck: Other: Institutional Research Support; Janssen Pharmaceutical: Other: Institutional Research Support. Gascoyne:NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Kahl:Acerta: Consultancy; Celgene: Consultancy; Abbvie: Consultancy; Juno: Consultancy; CTI: Consultancy; Gilead: Consultancy; Seattle Genetics: Consultancy; Genentech: Consultancy; AstraZeneca: Consultancy; ADC Therapeutics: Consultancy. Evens:Affimed: Consultancy; Novartis: Consultancy; Acerta: Consultancy; Bayer: Consultancy; Tesaro: Research Funding; Pharmacyclics International DMC: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy.

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 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.