Farber, Charles Michael

Abstract Introduction RCHOP is the standard frontline treatment for patients with DLBCL. However, for patients with high-intermediate or high-risk disease (IPI 3-5), outcomes are suboptimal, with an estimated 3-year PFS of about 55%. In addition to IPI, an additional factor associated with an increased risk include non-GCB cell of origin. Brentuximab vedotin, an ADC targeting CD30, has demonstrated single-agent activity in relapsed/refractory DLBCL patients. Of note, higher ORR and CR, as well as longer duration of PFS, were observed in those patients with CD30 detected on tumor cells by routine IHC. Methods This phase 2 study was designed to evaluate combination therapy using brentuximab vedotin (BV) and standard RCHOP chemotherapy as frontline treatment in patients with high-intermediate/high risk (standard IPI score 3-5 or age-adjusted IPI [aaIPI] score 2-3) DLBCL, regardless of CD30 expression (ClinicalTrials.gov NCT01925612). Patients were randomized to receive either 1.2 mg/kg BV+RCHOP or 1.8 mg/kg BV+RCHOP for up to 6 cycles of treatment. BV was given on Day 1 of every 21-day cycle. Response was assessed per investigator using Cheson 2007. AEs, physical examination findings, and laboratory testing were utilized to characterize safety. Tumor cell CD30 expression was measured by IHC and gene expression analysis; soluble CD30 was measured in plasma. Tumor microenvironment was also evaluated for frequency of immune-infiltrating cells. The primary endpoints for this study were the tolerability of each regimen and the CR rate at the end of treatment (EOT). Key secondary endpoints included progression-free survival (PFS). Additional exploratory endpoints included CD30 expression on tumor specimens (CD30- defined as <1% per IHC) and correlation of CD30 expression and response. Results Twenty-nine patients were treated with 1.2 mg/kg BV+RCHOP and 22 patients were treated with 1.8 mg/kg BV+RCHOP. Over half (63%) were high-intermediate risk (IPI 3, aaIPI 2) and 37% were high risk (IPI 4-5, aaIPI 3). Most had Stage IV disease (71%) and 27% had an ECOG score of 2. AEs in ≥50% of patients included peripheral sensory neuropathy (63%), fatigue (61%), nausea (55%), and diarrhea (53%). Grade 3 or higher events occurred in 76% of patients; the most frequent were neutropenia (33%) and febrile neutropenia (31%). The PET-negative CR rate was 69% overall; CD30+ patients had a CR rate of 76% (19/25) compared with 63% (12/19) in CD30- patients by IHC. Although PFS data are still immature (median follow up of 8 months), the estimated PFS rate at 12 months was 82% (95% CI: 58, 93) in CD30+ patients and 56% (95% CI: 32, 75) in CD30- patients. 60% (3/5) of patients with CD30- ABC-DLBCL progressed versus 27% (3/11) of CD30+ ABC-DLBCL patients. Four patients with EBV+ DLBCL were treated and all achieved CR; 3 EBV+ patients remain in remission after a median follow-up of 12 months. Within the microenvironment, a higher percentage of CD3+ T-cells was observed in patients with CR (23%; range, 4-80%) than in those with PR (14%; range, 10-15%) or PD (11%; range, 5-15%). Of the 32 patients who have not yet progressed, 50% had ≥20% CD3+ cells compared to 18% of patients with PD (2/11). Other factors, including soluble CD30 levels and infiltrating CD68+ cells, were not associated with clinical outcomes. Conclusions Interim results demonstrate that adding BV to RCHOP results in a high rate of CR in this population of IPI 3-5 DLBCL. Patients with CD30-expression in the tumor appear to have a higher CR rate and fewer early progression events than patients with CD30- DLBCL. Furthermore, subsets of patients who have a particularly poor prognosis (CD30+ ABC subtype and EBV+ DLBCL) appeared to have a favorable outcome with BV+RCHOP. Evaluation of the tumor microenvironment showed that higher frequencies of infiltrating CD3+ cells were observed in the CR group, suggesting possible immunologic correlates of response. However, CD30 expression appears to have greater prognostic significance in this study despite the relatively small sample size. These results are intriguing and merit further testing in a randomized trial. Disclosures Yasenchak: Seattle Genetics, Inc.: Research Funding. Off Label Use: Brentuximab vedotin is indicated in the US for treatment of patients with Hodgkin lymphoma after failure of autologous stem cell transplant or after failure of at least two prior multi-agent chemotherapy regimens in patients who are not ASCT candidates and for the treatment of patients with systemic anaplastic large cell lymphoma after failure of at least one prior multi-agent chemotherapy regimen. The drug is being evaluated in this study for use as frontline treatment in patients with high-intermediate/high risk DLBCL in combination with multiagent chemotherapy. . Halwani:Abbvie: Research Funding; Pharmacyclics: Other: Travel expenses, Research Funding; Takeda/Millenium: Research Funding; BMS: Research Funding; Seattle Genetics, Inc.: Other: Travel expenses, Research Funding; Roche/Genentech: Research Funding; Kyowa Hakko Kirin: Research Funding; Amgen: Research Funding. Advani:Seattle Genetics, Inc.: Research Funding; Genetech: Consultancy. Ansell:Bristol-Myers Squibb: Research Funding; Celldex: Research Funding. Budde:Merck: Research Funding; Ikara Inc: Patents & Royalties; Atara Biotherapeutics: Consultancy; Seattle Genetics, Inc.: Research Funding. Burke:Millenium/Takeda: Consultancy; Incyte: Consultancy; TG Therapeutics: Other: Travel expenses; Gilead: Consultancy; Janssen: Consultancy; Seattle Genetics, Inc.: Research Funding. Farber:Seattle Genetics, Inc.: Research Funding. Holkova:Seattle Genetics, Inc.: Research Funding. Kolibaba:GSK: Research Funding; Seattle Genetics, Inc.: Research Funding; Acerta: Research Funding; Celgene: Research Funding; Gilead: Consultancy, Research Funding; Takeda Pharmaceuticals International Co.: Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Janssen: Research Funding; TG Therapeutics: Research Funding. Knapp:Celgene: Research Funding; Heron Pharmaceuticals: Other: Travel expenses, Research Funding; Merck: Research Funding; Seattle Genetics, Inc.: Research Funding; Takeda Pharmaceuticals International Co.: Research Funding; Brystol-Myers Squibb: Research Funding; Genentech: Honoraria, Other: Travel expenses, Research Funding; Pharmacyclics LLC, an AbbVie Company: Research Funding; EMD Serono: Research Funding. Li:Seattle Genetics, Inc.: Employment, Equity Ownership. Manley:Seattle Genetics, Inc.: Employment, Equity Ownership. Patel-Donnelly:Seattle Genetics, Inc.: Research Funding. Seetharam:Seattle Genetics, Inc.: Research Funding. Yimer:Seattle Genetics, Inc.: Research Funding. Bartlett:Gilead: Consultancy, Research Funding; Janssen: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding; Pfizer: Research Funding; Novartis: Research Funding; Millennium: Research Funding; Colgene: Research Funding; Medimmune: Research Funding; Kite: Research Funding; Insight: Research Funding; Seattle Genetics: Consultancy, Research Funding; MERC: Research Funding; Dynavax: Research Funding; Idera: Research Funding; Portola: Research Funding; Bristol Meyers Squibb: Research Funding; Infinity: Research Funding; LAM Theapeutics: Research Funding.

Abstract Abstract 4591 Introduction: Clinicians and investigators appreciate the value of measuring HRQOL for monitoring CLL and the impact of treatments, and commonly use ECOG performance status (PS) and clinician-reported patient fatigue as surrogates for HRQOL in clinical practice. However, limited data exist on the relationships between PS, fatigue, and HRQOL in CLL patients (pts) undergoing treatment in clinical practices. We examined the associations between these measures and 3 psychometrically validated, patient-reported, HRQOL instruments: the Brief Fatigue Inventory (BFI), EQ-5D, and Functional Assessment of Cancer Therapy-Leukemia (FACT-Leu). Methods: Data were collected as part of Connect CLL®, a prospective observational registry initiated in March 2010 involving US practices. Data on pt demographics and clinical characteristics were provided by clinicians. HRQOL was self-reported by pts at enrollment using the BFI, EQ-5D, and FACT-Leu. Mean BFI, EQ-5D and FACT-Leu scores were analyzed by ECOG PS and clinician-reported fatigue. Differences in HRQOL scores between sub-cohorts were assessed by ANOVA. Results: HRQOL data were reported by 604 pts enrolled from 10 academic, 148 community, and 3 government centers. Pts were predominantly male (62%) and white (90%); mean age was 70 (standard deviation 11) years. BFI data (scale: 0 [no fatigue] - 10 [worst fatigue]) indicated that on average pts report that global fatigue, fatigue severity and fatigue-related interference worsen by ECOG severity (Table 1) and are statistically associated with clinician-reported fatigue (Table 2). Mean EQ-5D overall HRQOL as measured by a Visual Analogue Scale (VAS) from 0 (worst) to 100 (best) worsens by ECOG severity and is significantly worse in pts with fatigue. Mean EQ-5D domain scores (scale: 1 [no problem], 2 [some problems], 3 [incapacity]) indicated that pain/discomfort, mobility and usual activities increase in severity as ECOG worsens and in pts with fatigue. FACT-Leu domains except social/family were statistically worse with worse ECOG PS and in pts with fatigue. Conclusions: Initial results from Connect CLL® indicate that HRQOL worsens with worsening ECOG PS, especially in physical / functioning domains, pain/discomfort, and mobility, and worsens across multiple domains among pts whose physicians reported fatigue. Future analyses should be conducted on how HRQOL, PS and fatigue may change over time with changes in CLL, and how they are influenced by therapies. These results may serve as baseline reference. Disclosures: Pashos: Celgene: Membership on an entity's Board of Directors or advisory committees. Flowers:Genentech/Roche (unpaid): Consultancy; Celgene: Consultancy; Millennium/Takeda: Research Funding; Wyeth: Research Funding; Novartis: Research Funding. Weiss:Celgene: Membership on an entity's Board of Directors or advisory committees. Lamanna:Celgene: Membership on an entity's Board of Directors or advisory committees. Farber:Celgene: Membership on an entity's Board of Directors or advisory committees. Kipps:Igenica: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Research Funding; Abbot Industries: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; GSK: Research Funding; Gilead Sciences: Consultancy, Research Funding; Amgen: Research Funding. Lerner:Celgene: Membership on an entity's Board of Directors or advisory committees. Kay:Celgene: Membership on an entity's Board of Directors or advisory committees. Sharman:Celgene: Membership on an entity's Board of Directors or advisory committees. Grinblatt:Celgene: Membership on an entity's Board of Directors or advisory committees. Flinn:Celgene: Membership on an entity's Board of Directors or advisory committees. Kozloff:Celgene: Membership on an entity's Board of Directors or advisory committees. Swern:Celgene Corporation: Employment, Equity Ownership. Kahn:Celgene Corporation: Employment, Equity Ownership. Street:Celgene: Employment, Equity Ownership. Sullivan:Celgene: Employment, Equity Ownership. Keating:Celgene: Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction The natural history of patients (pts) with CLL varies considerably. Some pts may have asymptomatic, indolent disease, while others may require therapy soon after diagnosis. Clinical staging systems cannot identify early-stage pts at risk for inferior survival. Genetic and molecular markers can provide additional information regarding prognosis and response prediction, however their utilization is limited in routine practice (Mato, ASCO 2015) and results can be conflicting. There is a need to identify characteristics of early-stage CLL pts at highest risk of early progression and/or death. Such characteristics, if readily available and reproducible, may identify such pts as candidates for early-intervention studies; particularly in the era of kinase inhibitor therapy. The Connect CLL registry is the largest prospective study describing real-world management of a diverse cohort of 1494 CLL pts. In this analysis, we evaluate key factors that are associated with early CLL-associated mortality in clinical practice. Methods Connect CLL is a multicenter, observational cohort study aimed at understanding patterns of CLL management without a study-specific intervention. Eligible pts were adults with a clinical diagnosis of CLL, enrolled between 2010-2014 at 179 community (n=1311), 17 academic (n=155), and 3 government (n=28) sites within ≤ 2 months of initiating either a first line of therapy (LOT1), or a second-line or subsequent LOT (LOT≥2). The goal of this analysis was to assess potential predictors of death occurring within 18 months following initiation of frontline therapy (LOT1). Because CLL usually presents as an indolent disease associated with a prolonged clinical course, we chose to define early mortality as any death occurring ≤ 18 months following enrollment. Univariate logistic regression was performed against potential predictor variables including several clinical characteristics and comorbid conditions, race, treatment (Tx) site, insurance type, geographic region, presence of prior malignancies, genetic prognostic factors (FISH and cytogenetics) at enrollment, cell surface markers (Zap70, CD38), reasons for Tx initiation and Tx choice for LOT1 (BR or FCR). IgVH mutation status and genetic mutations (P53, Notch1, etc.) were not included as these tests were not readily performed in community practice. Predictors that were found to be significant at the 0.15 significance level were included in the multivariable logistic regression using a stepwise variable selection process, to identify factors associated with early mortality. Results 1344 pts completed 18 months of follow-up (n=1111) or died (n=233) within the first 18 months of study enrollment. Of these, 801 pts were enrolled in LOT1 (median time from diagnosis to LOT1 was 1.3 yrs; IQR, 0.1-3.7 yrs). 82 of 801 pts (10.2%) died within 18 months of LOT1 initiation; 41% of pts with available clinical information who died, were defined as early-stage (Rai stage 0-1). Of 26 potential predictors evaluated, 12 were associated with early mortality among LOT1 pts at the 0.15 significance level in univariate analyses including site, race, age>75, CD-38, del(17p), ECOG PS, CCI group, RAI stage, creatinine clearance, insurance status, reasons for Tx initiation, anemia and lymphocytosis. In multivariable logistic regression analyses we identified 4 independent predictors of mortality within 18 months of LOT1 initiation (Table): pt age, CD38 expression, baseline decreased hemoglobin (as a reason for Tx initiation), and race. Conclusions In CLL pts with Rai stage 0-1, we have identified 4 factors which are associated with increased risk of death within 18 months of initiation of frontline therapy. Interestingly, neither choice of FCR vs BR chemoimmunotherapy nor the presence of del(17p)/del(11q) were predictors of early mortality. Using these results, we are currently designing a model to predict early mortality in early-stage pts. Once validated, these results may provide a framework for trials targeting the "early stage, symptomatic" CLL pts for novel interventions. Table. Multivariable Analysis: Predictors of Early Mortality Odds ratio estimate 95% CI P -value LOT1, n=781 Age ≥75 years, yes vs no 2.2 1.4-3.5 0.0012 CD38 expression, positive vs negative/not specified 1.8 1.1-2.9 0.0182 Anemia as reason for treatment, yes vs no 2.1 1.3-3.4 0.0040 Race, other vs Caucasian 1.9 1.0-3.8 0.0501 Disclosures Farber: Gilead: Speakers Bureau; Genentech: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Pharmacyclics: Honoraria, Speakers Bureau. Mato:TG Therapeutics: Research Funding; Genentech: Consultancy; AbbVie: Consultancy, Research Funding; Pronai Pharmaceuticals: Research Funding; Gilead: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Celgene Corporation: Consultancy, Research Funding; Janssen: Consultancy. Nabhan:Celgene Corporation: Honoraria, Research Funding. Kipps:Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor. Flowers:Spectrum: Research Funding; Pharmacyclics: Research Funding; Infinity Pharmaceuticals: Research Funding; OptumRx: Consultancy; Gilead Sciences: Research Funding; Spectrum: Research Funding; Genentech: Research Funding; Onyx Pharmaceuticals: Research Funding; Acerta: Research Funding; OptumRx: Consultancy; Gilead Sciences: Research Funding; AbbVie: Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Consultancy; Onyx Pharmaceuticals: Research Funding; Genentech: Research Funding; Millennium/Takeda: Research Funding; Celegene: Other: Unpaid consultant, Research Funding; Janssen: Research Funding; Infinity Pharmaceuticals: Research Funding; Acerta: Research Funding; AbbVie: Research Funding; Seattle Genetics: Consultancy; Celegene: Other: Unpaid consultant, Research Funding; Janssen: Research Funding; Millennium/Takeda: Research Funding. Kay:Pharmacyclics: Research Funding; Hospira: Research Funding; Genentech: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharma: Research Funding; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding. Lamanna:Genentech-Abbvie: 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; Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Grinblatt:Celgene Corporation: Consultancy, Honoraria, Speakers Bureau. Kozloff:Celgene: Consultancy, Speakers Bureau; Genentech: Consultancy, Speakers Bureau; Roche: Consultancy, Speakers Bureau; AbbVie: Consultancy. Sullivan:Celgene Corporation: Employment, Equity Ownership. Flick:Celgene Corporation: Employment, Equity Ownership. Kiselev:Celgene Corporation: Consultancy. Bhushan:Celgene Corporation: Employment, Equity Ownership. Swern:Celgene Corporation: Employment, Equity Ownership. Sharman:TG Therapeutics, Inc.: Research Funding; Celgene Corporation: Consultancy, Research Funding; Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Research Funding; Calistoga: Honoraria; Roche: Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding.

Abstract Background: The majority of pts with MF present with a mutation in exon 14 of the JAK2 gene (JAK2V617F). Studies have suggested that in pts with MF and this mutation, a lower AB is associated with a myelodepletive phenotype and shortened survival (Tefferi, Leukemia 2008; Guglielmelli Blood 2009; reviewed in Vannucchi, Ther Adv Hematol 2011). For example, in a Cox proportional hazard model for factors predictive of overall survival (OS) in pts with primary MF, a JAK2V617F AB of <25% was associated with a shortened OS (p=0.002; Guglielmelli, Blood 2009). In the phase III trials of ruxolitinib (RUX) therapy in JAK inhibitor-naïve MF, RUX-treated pts had a median decrease in AB of 16% (maximal) in COMFORT-I followed up to 216 weeks and 7% in COMFORT-II at 48 weeks. The median AB at the start of therapy was not reported for COMFORT-I and in COMFORT-II was 84.5% (Cervantes, Blood 2013; Deininger, Blood2015). Methods: In this communication, we report on clinical correlates of quantitative baseline JAK2 mutational status and the effect of treatment on JAK2V617Fmutational burden in the PERSIST-1 trial. This trial enrolled JAK inhibitor-naïve pts with primary or secondary MF without restrictions on baseline platelet counts, randomized 2:1 between PAC and BAT (excluding JAK2 inhibitors) arms. Stratifications included Dynamic International Prognostic Scoring System (DIPSS) risk category, and baseline platelet counts (<50,000/μL, 50,000-100,000/μL, >100,000/μL). Following the 24-week primary analysis, crossover was allowed by physician/pt choice and 90/107 BAT-treated pts (84%) crossed over to receive PAC. Baseline characteristics have been previously reported (Mesa, ASCO 2016) and included 203/327 (62%) pts with Primary MF, 42 (13%) with post-essential thrombocythemia MF and 81 (25%) with post-polycythemia vera MF. 320 of 327 pts had informative PCR testing for JAK2V617F. We report the baseline characteristics of pts with high (≥50%) AB of JAK2V617F, low (<50%) AB of JAK2V617Fand those without a detectable mutation at baseline (<0.1%), as well as the effect of PAC and BAT on AB and correlation with outcome measures. Results: 131 (40.9%) had AB >50% (high AB), 115 (35.9%) had an AB ≥0.1% and ≤50% (low AB), and 74 (23.1%) had AB <0.1% (wild-type JAK2). Median AB values were 80.3% for the high AB group and 30.3% for the low AB group. Baseline characteristics that were significantly different between high and low AB pts are shown in the Table. No differences were noted in the DIPSS risk category or baseline percentage of blasts between pts with low or high AB. There were a higher percentage of pts with a lower AB in the PAC arm (64% vs. 48%; p=0.01). PAC therapy resulted in a median decrement in AB at Week 24 of −15.8% vs −7.9% for pts in the BAT arm (Figure). The median greatest reduction from baseline in AB in PAC-treated pts was −31.6%. Decrease in AB was strongly correlated with spleen volume reduction (p=0.003) and trended towards correlation with improvement in total symptom score (p=0.07) in PAC-treated, but not in BAT-treated pts. Overall survival was shorter in PAC-treated pts with a minimal AB reduction vs pts with greater decreases in AB. Conclusions: In the PERSIST-1 trial, pts with a JAK2V617FAB of <50% had substantially different disease and demographic characteristics when compared with those pts with a >50% AB despite similar distribution of DIPSS scores. In this trial, reduction in AB associated with PAC, but not BAT correlated with clinical benefit. Disclosures Vannucchi: Novartis: Consultancy, Research Funding, Speakers Bureau; Baxalta: Speakers Bureau; Shire: Speakers Bureau. Mead:Baxalta: Consultancy, Honoraria. Perkins:Novartis Oncology: Consultancy, Honoraria; Bristol-Myers Squibb: Other: Travel, Accommodations, Expenses. Mayer:CTI BioPharma Corp.: Other: Travel, Accommodations, Expenses, Research Funding. Schouten:Sanofi: Consultancy; Novartis: Consultancy. Farber:Alexion: Equity Ownership; Celgene: Honoraria, Research Funding, Speakers Bureau; Genentech: Research Funding, Speakers Bureau; Acerta: Research Funding; Gilead: Research Funding, Speakers Bureau; TG Therapeutics: Research Funding; Seattle Genetics: Speakers Bureau; Pharmacyclics: Speakers Bureau. Kiladjian:Novartis: Honoraria, Research Funding; AOP Orphan: Consultancy, Research Funding. Nangalia:Novartis: Consultancy, Other: Travel, Accommodations, Expenses. Dean:CTI BioPharma Corp.: Employment, Equity Ownership. Zhou:CTI BioPharma Corp.: Employment, Equity Ownership. Singer:CTI BioPharma Corp.: Employment, Equity Ownership, Other: Leadership . Mesa:Novartis: Consultancy, Honoraria; Incyte: Research Funding; Gilead: Research Funding; CTI BioPharma: Research Funding; Celgene: Research Funding; Genetech: Research Funding; Promedior: Research Funding. Harrison:Novartis: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses, Research Funding, Speakers Bureau; CTI BioPharma: Consultancy, Honoraria, Speakers Bureau; Baxter: Consultancy, Honoraria; Shire: Speakers Bureau; Gilead: Speakers Bureau; Incyte: Speakers Bureau.

Key Points Early progression of disease within 2 years of initial therapy independently predicts inferior survival in CLL. Early progression of disease is a robust clinical end point and a useful posttreatment risk stratification tool.

Abstract Background Outcomes for patients with DLBCL have improved over the past decade, with the addition of rituximab to CHOP or CHOP-like multi-agent chemotherapy regimens improving the 3-year overall survival (OS) of patients by 10-16% compared to multi-agent chemotherapy alone (Coiffier 2002; Pfreundschuh 2010). However, patients with high-intermediate or high-risk disease have relatively poor outcomes with the standard RCHOP regimen (Ziepert 2010); in a recent prospective trial of intermediate- and high-risk DLBCL patients, complete response (CR) rate for RCHOP alone was 26% (Hainsworth 2011). Brentuximab vedotin (ADCETRIS®) is an antibody-drug conjugate comprising the antibody cAC10, specific for human CD30, covalently attached to the microtubule-disrupting agent monomethyl auristatin E (MMAE) via a protease-cleavable linker. Brentuximab vedotin has demonstrated compelling activity as a single agent in patients with relapsed or refractory DLBCL, even those with low CD30 expression (Bartlett 2013). This phase 2, randomized, open label study is designed to evaluate the antitumor activity and safety of brentuximab vedotin (1.2 or 1.8 mg/kg) when administered in combination with standard RCHOP chemotherapy (A+RCHOP) for the front-line treatment of patients with CD30-unselected high-intermediate/high-risk (standard IPI score 3–5 or age-adjusted IPI [aaIPI] score 2–3) DLBCL (ClinicalTrials.gov NCT01925612). Methods Patients were randomized to receive up to 6 cycles of either 1.2 or 1.8 mg/kg brentuximab vedotin administered IV on Day 1 of every 21-day cycle in combination with RCHOP; prednisone was administered orally on Days 1-5 of every 21-day cycle. Assessments included disease response per Cheson 2007, as evaluated by the investigator, surveillance of adverse events (AEs), physical examination findings, and laboratory testing. The primary endpoints for this study are the CR rate at the end of treatment (EOT) and the type, incidence, and severity of AEs. Key secondary endpoints include objective response rate (ORR), progression-free survival (PFS), and OS. Results At the time of the planned interim analysis, 33 patients were enrolled (17 patients, 1.2 mg/kg A+RCHOP; 16 patients, 1.8 mg/kg A+RCHOP). Median age for all patients was 66 years (range, 21 to 81). At baseline, 36% were high-risk (IPI 4-5, aaIPI 3) and 64% were high-intermediate risk (IPI 3, aaIPI 2). The majority of patients (73%) had Stage IV disease and 33% had an ECOG status of 2. At the time of interim analysis, a total of 12 patients (6 patients in each arm) had completed EOT. Across both dose levels, ORR was 92% (11/12), with 7 CRs (58%), 4 PRs (33%), and 1 PD. The patient with PD subsequently died. Patients with PR had a median reduction of baseline tumor size of 84% (range, 92% to 83%), as measured by SPD. The only patient with follow-up after EOT converted from PR to CR without subsequent therapy. Treatment-emergent AEs occurring in ≥30% of patients treated (26/33) were nausea, diarrhea, peripheral sensory neuropathy, fatigue, and decreased appetite. Grade 3 or higher events occurring in more than 2 patients were febrile neutropenia and neutropenia. Events of peripheral neuropathy occurred equally per arm (46%, 1.2 mg/kg A+RCHOP; 46% 1.8 mg/kg A+RCHOP) and were generally Grade 1 or 2 (15% and 23%, respectively); events were of similar grade across dose levels. The median time to onset of any grade of peripheral neuropathy was 6 weeks (range, 2 to 10 weeks). Five patients (19%) had dose reductions due to peripheral neuropathy and 3 patients (12%) had dose reductions due to febrile neutropenia. One patient who received 1.2 mg/kg A+RCHOP discontinued study drug due to an AE (thrombocytopenia). Conclusions At doses of 1.2 or 1.8 mg/kg, A+RCHOP exhibited manageable toxicity in the treatment of newly-diagnosed DLBCL; the incidence of peripheral neuropathy was similar to single-agent administration of brentuximab vedotin (Pro 2012, Younes 2012) and RCHOP alone (Rummel 2013, Flinn 2014). In 12 patients with response-assessable, high-intermediate and high-risk DLBCL, A+RCHOP showed encouraging antitumor activity, with an ORR of 92% and a CR rate of 58%. Disclosures Yasenchak: Seattle Genetics, Inc.: Research Funding. Off Label Use: Brentuximab vedotin is indicated in the US for treatment of patients with Hodgkin lymphoma after failure of autologous stem cell transplant or after failure of at least two prior multi-agent chemotherapy regimens in patients who are not ASCT candidates and for the treatment of patients with systemic anaplastic large cell lymphoma after failure of at least one prior multi-agent chemotherapy regimen. . Farber:Seattle Genetics, Inc.: Research Funding. Budde:Seattle Genetics, Inc.: Research Funding. Ansell:Seattle Genetics, Inc.: Research Funding. Advani:Takeda Pharmaceuticals International Co.: Research Funding; Celgene: Research Funding; Pharmacyclics: Research Funding; Jansseen Pharmaceuticals: Research Funding; Genentech: Research Funding; Seattle Genetics, Inc.: Research Funding, Travel expenses Other. Holkova:Seattle Genetics, Inc.: Research Funding. Halwani:Seattle Genetics, Inc.: Research Funding. Knapp:Takeda Pharmaceuticals International Co.: Research Funding; EMD Serono: Research Funding; Bristol Myers Squibb: Research Funding; Celgene: Research Funding; Merck: Research Funding; Heron Pharmaceuticals: Research Funding, Travel expenses, Travel expenses Other; Genentech: Research Funding, Travel expenses, Travel expenses Other; Seattle Genetics, Inc.: Research Funding; Pharmacyclics: Research Funding. Fayad:Seattle Genetics, Inc.: Consultancy, Research Funding. Kolibaba:Genentech: Research Funding; Takeda Pharmaceuticals International Co.: Research Funding; Seattle Genetics, Inc.: Research Funding. Patel-Donnelly:Seattle Genetics, Inc.: Research Funding. Seetharam:Seattle Genetics, Inc.: Research Funding. Manley:Seattle Genetics, Inc.: Employment, Equity Ownership. Bartlett:Genentech: Research Funding; ImaginAb: Research Funding; Celgene: Research Funding; MedImmune: Research Funding; Novartis: Research Funding; Pharmacyclics: Research Funding; Pfizer: Research Funding; Takeda Pharmaceuticals International Co.: Research Funding; Seattle Genetics, Inc.: Research Funding, Travel expenses Other; Janssen: Research Funding; Astra Zeneca: Research Funding.