Byrd, John C

Abstract Background: Patients (pts) with CLL/SLL that have del11q tend to have relatively short remission durations and shorter overall survival (OS) with standard chemotherapy regimens. Ibrutinib (ibr), a first-in-class, oral, once-daily inhibitor of Bruton's tyrosine kinase (BTK) is indicated by the US FDA for the treatment of pts with CLL/SLL and allows for treatment without chemotherapy. In phase 3 studies, treatment with single-agent ibr was superior to treatment with ofatumumab (ofa) in relapsed/refractory (R/R) CLL/SLL (RESONATE; Byrd, N Engl J Med 2013) or chlorambucil (clb) in treatment-naïve (TN) CLL/SLL (RESONATE-2; Burger, N Engl J Med 2015); treatment with ibr + bendamustine/rituximab (BR) was also superior to treatment with BR in R/R CLL/SLL (HELIOS; Chanan-Khan, Lancet Oncol 2016). We examined the outcome of pts in these 3 studies who did or did not have del11q to determine the impact of del11q on clinical outcomes. Methods: In RESONATE, pts with R/R CLL/SLL received ibr 420 mg/day until progressive disease (PD) or unacceptable toxicity (tox) vs ofa for up to 24 weeks (300 mg week 1, 2000 mg weekly for 7 weeks, 2000 mg every 4 weeks for 16 weeks). In RESONATE-2, pts ≥65 years of age with TN CLL/SLL (excluding del17p) received ibr 420 mg/day until PD or tox vs clb 0.5 mg/kg (up to max of 0.8 mg/kg) on days 1 and 15 of each 28-day cycle (≤12 cycles). In HELIOS, pts with R/R CLL/SLL (excluding del17p) received BR (≤6 cycles) with or without ibr 420 mg/day (starting on day 2 of cycle 1) followed by single-agent ibr or placebo continued until PD or tox. Data from pts in the 3 studies were pooled (ibr pool, comparator pool) and analyzed based on whether or not their CLL/SLL had del11q. We performed a multivariate analysis to examine for risk factors prognostic for survival (del11q del17p, age, sex, race, current Rai stage, baseline ECOG PS, number of prior therapies, cytopenias; no multiplicity adjustment). Results: A total of 1210 pts with del11q data were included in the analysis: 609 in the ibr pool (179 with del11q, 430 without del11q) vs 601 in the comparator pool (149 with del11q, 452 without del11q). Demographics and baseline characteristics were generally similar in pts regardless of del11q status; differences of more than 10% included proportions with bulky disease ≥5 cm (63% vs 49%) and unmutated IGHV (88% vs 72%) in pts with or without del11q, respectively. Median lymphadenopathy and absolute lymphocyte counts were also higher in pts with del11q. At the time of the primary analysis, median treatment durations in the ibr pool were 20.0 mo with del11q and 18.7 mo without del11q; in the comparator pool 5.3 mo with del11q and 8.5 mo without del11q. Overall, ibr-treated pts had higher overall response rate (ORR) and complete response (CR) rates and longer progression-free survival (PFS, Figure) and OS than comparator-treated pts regardless of del11q status. In the ibr pool, the presence of del11q was associated with a trend of longer PFS and OS while in the comparator pool, pts with del11q had shorter PFS (Figure, Table), as compared to pts without del11q. Results were similar when excluding pts with del17p (10% of ibr pool [6%/11% with/without del11q] and 9% of comparator pool [8%/10% with/without del11q]; Table). By multivariate analysis, in the comparator pool, del11q, male sex, >1 prior therapy, presence of cytopenias, and unmutated IGHV (in R/R only) were associated with shorter PFS. However, these differences were not found in the ibr pool. The presence of del11q did not unfavorably impact the tempo of reductions in lymphadenopathy for ibr-treated pts, but did for comparator-treated pts. Adverse events leading to discontinuation were similar in ibr- and comparator-treated pts (12% [9% vs 13% with/without del11q] vs 13% [12% vs 13% with/without del11q]). Deaths within 30 days of last dose occurred in 31 pts (5% [3% vs 6% with/without del11q]) in the ibr pool and 28 pts (5% [6% vs 4% with/without del11q]) in the comparator pool. Conclusions: Treatment with ibr was superior to comparator regardless of del11q status; the benefit of ibr was most marked for pts with CLL/SLL with del11q. Presence of del11q was associated with a trend of longer PFS and OS in ibr-treated pts and shorter PFS and lower ORR in comparator-treated pts. By multivariate analysis, presence of del11q was a prognostic factor for shorter PFS for comparator-treated pts, but not for ibr-treated pts. Disclosures Kipps: Celgene: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Pharmacyclics, LLC, an AbbVie Company: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Speakers Bureau. Hillmen:Pharmacyclics: Research Funding; Janssen: Honoraria, Research Funding; Roche: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; Abbvie: Research Funding. Demirkan:Amgen: Consultancy. Coutre:Pharmacyclics, LLC, an AbbVie Company: Consultancy, Research Funding; AbbVie: Research Funding; Janssen: Consultancy, Research Funding. Barrientos:Gilead: Consultancy, Research Funding; Janssen: Consultancy; AbbVie: Consultancy, Research Funding. Barr:Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; AbbVie: Consultancy. O'Brien:Pharmacyclics, LLC, an AbbVie Company: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria. Fraser:Celgene: Research Funding; Janssen: Honoraria, Research Funding, Speakers Bureau. Jaeger:Janssen: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses. Cramer:Janssen-Cilag: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses, Research Funding; Novartis: Consultancy, Research Funding; GlaxoSmithKline: Research Funding; Mundipharma: Other: Travel, Accommodations, Expenses; Astellas: Other: Travel, Accommodations, Expenses; Roche: Honoraria, Other: Travel, Accommodations, Expenses, Research Funding; Gilead: Other: Travel, Accommodations, Expenses, Research Funding. Stilgenbauer:Novartis: Consultancy, Honoraria, Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Research Funding; Genzyme: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses, Research Funding, Speakers Bureau; Mundipharma: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria, Research Funding; Gilead: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Hoffman La-Roche: Consultancy, Honoraria, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses, Research Funding, Speakers Bureau; Genentech: Consultancy, Honoraria, Research Funding. Salman:Janssen Research & Development: Employment, Equity Ownership, Other: Travel, Accommodations, Expenses. Solman:Pharmacyclics LLC, an AbbVie Company: Employment, Other: Travel, Accommodations, Expenses; AbbVie: Equity Ownership. Cheng:Johnson & Johnson: Equity Ownership; AbbVie: Equity Ownership; Pharmacyclics LLC, an AbbVie Company: Employment. Phelps:Johnson & Johnson: Employment, Equity Ownership. Ninomoto:Pharmacyclics LLC, an AbbVie Company: Employment; Amgen, Inc.: Equity Ownership; AbbVie: Equity Ownership. Howes:Janssen: Employment, Other: Leadership; Johnson & Johnson: Equity Ownership. James:Pharmacyclics LLC, an AbbVie Company: Employment; AbbVie: Equity Ownership. Hallek:Gilead: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Mundipharma: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; F. Hoffmann-LaRoche: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau.

Abstract Background: Contemporary approaches to non-Hodgkin lymphoma (NHL) and chronic lymphocytic leukemia (CLL) incorporate chemo-immunotherapy, biologic combinations, and immune modulating agents; toxicities in elderly pts (³65 years) receiving these therapies are not well studied. Further, clinical and biologic factors predicting these toxicities in pts receiving biologic therapy remain undefined. Methods: We reviewed data on NHL and/or CLL pts treated prospectively on 14 studies by the Alliance for Clinical Trials in Oncology from 2004-2014 (Table 1). Toxicity was assessed per the NCI CTCAE at the time of trial enrollment, and the probabilities of experiencing grade 3 and grade 4 hematologic (hem) and non-hematologic (non-hem) toxicities were modeled as a function of age (³65 years vs. < 65), time on study, treatment (biologics only vs. biologic + chemotherapy), gender, race, LDH, performance status (PS), stage, and an age-by-treatment interaction using logistic regression. Results: A total of 1199 pts (409 age ³ 65; 790 age < 65; 736=CLL and 463=NHL) were included. Among these patients, 493 received only biologic therapy (166 age ³ 65; 327 age < 65; 104 CLL; 389 NHL), and 706 received biologic + chemotherapy (243 age ³ 65; 463 age < 65; 632 CLL; 74 NHL). Among CLL pts (259 pts ³ 65), the effect of age on the probability of experiencing a grade 3 heme toxicity differed by treatment type (age-by-treatment interaction p = 0.047). Specifically, the adjusted odds ratio (OR) (age ³ 65 vs. < 65) for pts receiving only biologic therapy was 3.075 (95% CI: 1,15-8.25), and that for pts receiving biologic + chemotherapy was 1.044 (95% CI: 0.69 - 1.57). Similar results were seen in CLL pts for grade 4 heme toxicities (age-by-treatment interaction p = 0.033; biologic OR 6.937, 95% CI: 1.76-27.35; biologic + chemo OR 1.484, 95% CI: 1.04-2.13). No such interactions were found in CLL pts for grade 3 and 4 non-hem toxicities; however, older pts had significantly higher odds of experiencing a grade 3 non-hem toxicity than younger pts (adjusted OR 1.40; p = 0.047; 95% CI: 1.004-1.96). No age group differences were found in CLL pts for grade 4 non-hem toxicity. Similar analyses were performed for NHL pts (150 pts ³ 65), but no significant age group differences were found. Among CLL pts, women had significantly higher odds of experiencing a grade 3 heme toxicity than men (OR 2.01; p = 0.0007); no difference in grade 3 non-hem or any grade 4 toxicity was noted. Non-Caucasian CLL pts had higher odds of experiencing a grade 4 non-hem toxicity than Caucasians (OR 2.892; p = 0.0029), but no other toxicity differences were found. Worse PS was associated with increased toxicities (OR 1.871; p = 0.0009: grade 3 heme; OR 1.647; p = 0.0025: grade 3 non-hem; OR 1.410; p = 0.0448: grade 4 heme, and OR 1.931; p = 0.0252: grade 4 non-hem). CLL pts with advanced stage disease had higher odds of experiencing a heme toxicity (grade 3: OR 1.95; p = 0.0007, grade 4: OR 1.451; p = 0.0329), but no stage associations were found for non-hem toxicities. Among NHL pts, men had significantly higher odds of experiencing a grade 4 hematologic toxicity than women (OR 4.351; p = 0.0169), but no other toxicity differences were found. An increase in LDH was associated with significantly higher odds of experiencing grade 3 non-hem and grade 4 heme toxicities (grade 3 non-heme: OR 1.633; p = 0.021, grade 4 heme: OR 2.039, p = 0.0182), but no such effect was found for grade 3 heme or grade 4 non-hem. Worse PS was associated with higher odds of experiencing grade 3 toxicities (heme: OR 2.025; p = 0.0344, non-hem: OR 2.458; p = 0.0013), but no such differences were found for grade 4 toxicities. No significant stage or race effects were found in NHL patients. Conclusion: In pts ³65 years who have CLL or NHL, we identified several clinical and disease-related factors as potential predictors of developing grade 3 and/or 4 heme and non-hem toxicities (Table 2). A prognostic model is being constructed to predict toxicities in these under-studied pts to guide management and monitoring. Further, the impact of these toxicities on outcomes is being analyzed and will be presented at the meeting. Disclosures Hurria: Celgene: Other: Research; Optum Health Care SOlutions: Consultancy, Other: Conference panel, research; Boehringer Ingelheim Pharmaceuticals: Consultancy; Sanofi: Consultancy; Carevive: Consultancy; Novartis: Other: Research; GTx, Inc: Consultancy. Bartlett:Gilead: Consultancy. Cheson:Gilead: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding. Nabhan:Infinity: Consultancy; Abbvie: Consultancy; Cardinal Health: Consultancy; Seattle Genetics: Research Funding; Genentech: Consultancy, Research Funding; Astellas: Research Funding; Celgene Corporation: Consultancy, Research Funding.

Abstract In chronic lymphocytic leukemia (CLL), it is recognized that germinal center experience by the cell-of-origin has an influence on the malignant phenotype and impacts clinical behavior. Measurement of the mutational status of the IGHV locus is a commonly used approach that subgroups patients according to this natural history. Other biomarkers correlating with these subgroups, such as ZAP70 expression and ZAP70 DNA methylation, are also used. Recently, we and others have found vast differences in global DNA methylation profiles among CLL cases that classifies distinct subgroups related to their natural history. Here we systematically evaluate various markers of natural history of the cell-of-origin for their ability to discriminate clinical outcomes. IGHV mutational status and ZAP70 expression are currently the most widely used prognostic markers of germinal center experience. These markers are generally concordant, with IGHV-unmutated associating with ZAP70 positivity. To compare their relative prognostic impact, we selected CLL cases from a large sample cohort collected as a prospective study maintained by the CLL Research Consortium that were discordant (IGHV-mutated and ZAP70(+) or IGHV-unmutated and ZAP70(-); n=192). We found a significant difference in time-to-first-treatment (TTFT; P=0.002) and overall survival (OS; P=0.032) between discordant groups, with curves separating according to IGHV as opposed to ZAP70 (Fig.1A). DNA methylation-based classification of CLL according to their natural history has not been compared to IGHV status. This classification strategy subgroups the majority of cases into low-programmed CLL (LP-CLL) or high-programmed (HP-CLL) subgroups that generally correlate with IGHV-unmutated/ZAP70(+) and IGHV-mutated/ZAP70(-), respectively, along with a minority of cases in an intermediate (IP-CLL) subgroup. We used our previously-described DNA methylation assay, based on MassARRAY interrogating 7 genomic loci including ZAP70, to group the 192 samples with discordant IGHV/ZAP70 results with 327 samples analyzed previously from the same cohort. DNA methylation (LP-CLL vs. HP-CLL) outperformed IGHV classification (unmutated vs. mutated) in terms of separating TTFT curves (n=432; LP-CLL vs. HP-CLL median difference=4.8 years, unmutated vs. mutated IGHV median difference=2.9 years) and OS curves (n=491; LP-CLL vs. HP-CLL median difference=12.9 years, unmutated vs. mutated IGHV median difference=6.8 years). To evaluate whether DNA methylation subgroups provide additional prognostic information to IGHV, we compared TTFT and OS within IGHV subtypes. We found that the ability of DNA methylation subgrouping to separate OS curves was maintained in the IGHV-unmutated subtype (P<0.001; Fig.1B) and TTFT in both IGHV-unmutated and mutated subtypes (P<0.001 and P=0.016, respectively). Conversely, IGHV subtypes did not significantly separate outcomes within DNA methylation subgroups (P>0.5 for all). Further investigation of the features of DNA methylation subgroups as defined revealed a strong bias in the frequency of several recurrent adverse prognostic somatic mutations. In particular 17p deletions and EGR2, SF3B1 and XPO1 mutations occurred frequently within the LP-CLL subgroup. We next explored whether the presence of each mutation correlated with clinical outcome within its corresponding DNA methylation subgroup, and found heterogenous results. EGR2 mutations separated TTFT in the LP-CLL subgroup (P=0.0009), but 17p, XPO1 and SF3B1 did not (P>0.3). This suggests that the cell-of-origin should be taken into account to accurately assess the clinical impact of somatic mutations. In summary, we demonstrate that among discordant cases for IGHV/ZAP70, IGHV appears to be a stronger prognostic factor for both TTFT and OS. When then evaluating the relative importance of DNA methylation subgrouping and IGHV status on TTFT and OS, we find that DNA methylation subgrouping is the more powerful prognostic factor. Among the markers of the cell-of-origin, DNA methylation is a strong tool for risk-stratifying patients and should be considered in development of risk prediction models. Figure 1. A) Kaplan-Meier analysis of TTFT of IGHV-mutated and ZAP70(+) versus IGHV-unmutated and ZAP70(-) (P=0.002, median difference=4.4 years). B) Kaplan-Meier analysis of OS in patients with unmutated IGHV separated by DNA methylation subgroup (P<0.001). Figure 1. A) Kaplan-Meier analysis of TTFT of IGHV-mutated and ZAP70(+) versus IGHV-unmutated and ZAP70(-) (P=0.002, median difference=4.4 years). B) Kaplan-Meier analysis of OS in patients with unmutated IGHV separated by DNA methylation subgroup (P<0.001). Disclosures Wierda: Acerta: Research Funding; Novartis: Research Funding; Gilead: Research Funding; Genentech: Research Funding; Abbvie: Research Funding. Brown:Infinity: Consultancy; Janssen: Consultancy; Gilead Sciences: Consultancy; Roche/Genentech: Consultancy; Celgene: Consultancy; Sun BioPharma: Consultancy; Pfizer: Consultancy; Abbvie: Consultancy. Kipps:Roche: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Gilead: Consultancy, Honoraria, Speakers Bureau; Pharmacyclics, LLC, an AbbVie Company: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding.

AbstractAlterations in global DNA methylation patterns are a major hallmark of cancer and represent attractive biomarkers for personalized risk stratification. Chronic lymphocytic leukemia (CLL) risk stratification studies typically focus on time to first treatment (TTFT), time to progression (TTP) after treatment, and overall survival (OS). Whereas TTFT risk stratification remains similar over time, TTP and OS have changed dramatically with the introduction of targeted therapies, such as the Bruton tyrosine kinase inhibitor ibrutinib. We have shown that genome-wide DNA methylation patterns in CLL are strongly associated with phenotypic differentiation and patient outcomes. Here, we developed a novel assay, termed methylation-iPLEX (Me-iPLEX), for high-throughput quantification of targeted panels of single cytosine guanine dinucleotides from multiple independent loci. Me-iPLEX was used to classify CLL samples into 1 of 3 known epigenetic subtypes (epitypes). We examined the impact of epitype in 1286 CLL patients from 4 independent cohorts representing a comprehensive view of CLL disease course and therapies. We found that epitype significantly predicted TTFT and OS among newly diagnosed CLL patients. Additionally, epitype predicted TTP and OS with 2 common CLL therapies: chemoimmunotherapy and ibrutinib. Epitype retained significance after stratifying by biologically related biomarkers, immunoglobulin heavy chain mutational status, and ZAP70 expression, as well as other common prognostic markers. Furthermore, among several biological traits enriched between epitypes, we found highly biased immunogenetic features, including IGLV3-21 usage in the poorly characterized intermediate-programmed CLL epitype. In summary, Me-iPLEX is an elegant method to assess epigenetic signatures, including robust classification of CLL epitypes that independently stratify patient risk at diagnosis and time of treatment.

Abstract Background Leventhal’s Self-regulatory Model proposes that somatic characteristics of a health threat (e.g., symptom severity), and prior experience with the threat (e.g., unsuccessful treatment), are determinants of illness perceptions. Chronic lymphocytic leukemia (CLL) is appropriate for test of these postulates, having three phases differing in symptom severity and prior treatment experiences: indolent disease requiring no treatment (active surveillance; AS), symptomatic disease requiring a first treatment (FT), and highly symptomatic disease in those who have relapsed and/or failed to respond to prior treatments (relapsed/refractory; RR). Purpose To test symptom severity and prior treatment experiences as determinants of illness perceptions, illness perceptions were characterized and contrasted between CLL groups. Methods Three hundred and thirty CLL patients (AS, n = 100; FT, n = 78; RR, n = 152) provided illness perception data on one occasion during a surveillance visit (AS) or prior to beginning treatment (FT, RR). Results Analysis of variance with planned comparisons revealed that consequences, identity, and concern were least favorable among RR patients, followed by FT, then AS (ps < .01). AS patients endorsed the lowest levels of coherence (ps < .01), and the most chronic illness timeline (ps < .01). FT patients endorsed the highest levels of personal and treatment control (ps < .01). Conclusions Data provide preliminary empirical support for Self-regulatory Model postulates that symptom severity and prior disease experiences influence illness perceptions. Unique knowledge needs for AS patients and elevated psychological/physical symptoms for later-stage CLL patients may warrant clinical attention.

SummaryIbrutinib, a Bruton tyrosine kinase inhibitor, is approved for treatment of various B‐cell malignancies. In ibrutinib clinical studies, low‐grade haemorrhage was common, whereas major haemorrhage (MH) was infrequent. We analysed the incidence of and risk factors for MH from 15 ibrutinib clinical studies (N = 1768), including 4 randomised controlled trials (RCTs). Rates of any‐grade bleeding were similar for single‐agent ibrutinib and ibrutinib combinations (39% and 40%). Low‐grade bleeding was more common in ibrutinib‐treated than comparator‐treated patients (35% and 15%), and early low‐grade bleeding was not associated with MH. The proportion of MH in RCTs was higher with ibrutinib than comparators (4.4% vs. 2.8%), but after adjusting for longer exposure with ibrutinib (median 13 months vs. 6 months), the incidence of MH was similar (3.2 vs. 3.1 per 1000 person‐months). MH led to treatment discontinuation in 1% of all ibrutinib‐treated patients. Use of anticoagulants and/or antiplatelets (AC/AP) during the study was common (~50% of patients) and had an increased exposure‐adjusted relative risk for MH in both the total ibrutinib‐treated population (1.9; 95% confidence interval, 1.2–3.0) and RCT comparator‐treated patients (2.4; 95% confidence interval, 1.0–5.6), indicating that ibrutinib may not alter the effect of AC/AP on the risk of MH in B‐cell malignancies.

7503 Background: Prior to use of novel targeted agents for CLL, debate existed regarding the best chemoimmunotherapy regimen to build upon in patients (pts) with non-del(11q) disease. The role of lenalidomide (L) was also not defined. CALGB 10404 was a randomized phase 2 study addressing these questions. Methods: Pts with untreated CLL requiring therapy were randomized to treatment with fludarabine + rituximab (FR), FR + 6 monthly consolidative treatments of L (5 mg days 1-21/28 x 1 then 10 mg days 1-21/28 x 5) (FR+L), or FR + cyclophosphamide (FCR). Based on pretreatment central interphase cytogenetic screening, pts with del(11q22.3) in at least 20% of cells were excluded from the primary analysis, testing whether 2-year progression-free survival (PFS) rate was improved in non-del(11q) pts within each arm. A target accrual of 103 non-del(11q) pts per arm provided at least 84% power to detect an increase in 2-year PFS rate from 60% to 73%; the critical value was 69% using a single stage design and type I error rate of 4%. Results: A total of 342 non-del(11q) CLL pts were randomized to treatment with FR (n = 123), FR+L (n = 109), or FCR (n = 110). Baseline characteristics were similar across arms. Two-year PFS rates with exact 90% CIs were 64% (57-71%) (FR), 71% (63-78%) (FR+L), and 74% (66-80%) (FCR). Median PFS was significantly shorter with FR compared to FR+L (p = 0.03) and FCR (p < 0.01): 43 (95% CI: 33-50), 66 (95% CI: 45-not reached), and 78 (95% CI: 58-not reached) months respectively. Median overall survival (OS) has not been reached for any arm. OS at 1, 2, and 3 years was similar across arms, although there was a plateau in OS with no events beyond 41 months in the FR+L arm, different from FR/FCR where events continued to occur. The most common adverse events were cytopenias and infections. Conclusions: FR+L and FCR met the protocol defined primary endpoint. FR+L extended PFS relative to FR and a plateau in survival differentiated this arm from the FR/FCR arms. Future studies comparing FR+L to FCR or incorporating L into other novel treatment regimens are justified. Support: U10CA180821, U10CA180882, Celgene. Clinical trial information: NCT00602459.