Vitolo, Umberto

Introduction: Most patients with newly diagnosed FL treated with rituximab (R) alone or R + chemotherapy will experience prolonged progression-free survival and overall survival (OS), but it remains unclear what factors have the greatest influence on FL-associated and other causes of death in this patient population. We utilized individual patient data from 13 first-line randomized clinical trials from the FLASH database to perform a comprehensive multistate survival analysis to examine and quantify the relationships between clinical characteristics, treatment response, and early, intermediate, and late FL outcomes. Methods: The multistate survival analysis model defined states for "Alive after beginning Induction Treatment (TX)", "Alive after beginning Maintenance TX", "Death due to FL", and "Death from Other Causes" (Figure 1). We used the Aalen-Johansen estimator, a generalization of the Kaplan-Meier estimator, to calculate the likelihood of being in each model state and estimate the course of FL over time. Making no assumptions on the probability distributions and capable of coping with censored observations, the Aalen-Johansen estimator is a convenient and reliable nonparametric estimator for clinical data. Results: Among 7,465 FL patients with median age 56 (range 18-90) years, 49.2% were female; 28.7% Stage I-III, 71.3% Stage IV, and FLIPI was 0-1 (20.0%), 2 (36.8%), ≥ 3 (43.2%). Following initiation of induction treatment, 2-, 5- and 10-year death rates were 1.7%, 3.8%, and 5.8% due to FL, and 0.7%, 2.1%, and 4.8% from other causes (Figure 2). Death rates at 2, 5, and 10 years due to FL and other causes for subgroups based on clinical characteristics and treatment response are shown in Table 1. Notably, patients > 70 years and patients with FLIPI ≥ 3 had worse outcomes and patients achieving CR at 18, 24, and 30 months experienced improved outcomes. Conclusion: This is the largest study using data from randomized trials to quantify the impact of clinical factors on early, intermediate and late mortality by cause of death. We demonstrated that age > 70 years and FLIPI ≥ 3 were linked to increased FL-associated death and response to TX distinguished patients with favorable and poor outcomes. Future analyses should quantify the impact of predictors on the rate/time of FL outcomes in multivariable models. Disclosures Salles: Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Amgen: Honoraria, Other: Educational events; BMS: Honoraria; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Epizyme: Consultancy, Honoraria; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events. Hoster:Janssen: Research Funding; Roche Pharma AG: Other: Travel Support. Hiddemann:Bayer: Research Funding; Gilead: Consultancy, Honoraria; Vector Therapeutics: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria. Herold:Roche: Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Gilead: Honoraria; Celgene: Honoraria. Morschhauser:Servier: Consultancy; Gilead: Consultancy; Janssen: Honoraria; Roche/Genentech: Consultancy; BMS: Honoraria; Celgene: Honoraria. Rummel:Roche Pharma AG: Honoraria, Research Funding; Celgene: Honoraria; Janssen: Honoraria; Sandoz: Honoraria. Kimby:AbbVie,: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Gilead: Other: educational lectures. Vitolo:Abbvie: 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; Celgene: 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; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; F. Hoffmann-La Roche: Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Gyan:Pfizer: Honoraria. Ladetto:Celgene: Honoraria; Roche: Honoraria; Janssen: Honoraria; Abbvie: Honoraria; Acerta: Honoraria; Sandoz: Honoraria. Nielsen:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Flowers:AstraZeneca: Consultancy; BeiGene: Consultancy, Research Funding; Eastern Cooperative Oncology Group: Research Funding; Burroughs Wellcome Fund: Research Funding; AbbVie: Consultancy, Research Funding; Optimum Rx: Consultancy; V Foundation: Research Funding; Pharmacyclics/Janssen: Consultancy, Research Funding; Bayer: Consultancy; Gilead: Consultancy, Research Funding; TG Therapeutics: Research Funding; Denovo Biopharma: Consultancy; Acerta: Research Funding; National Cancer Institute: Research Funding; Millenium/Takeda: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Spectrum: Consultancy;

Introduction: The use of PET-CR as a surrogate endpoint would expedite the development of novel therapies and enable better estimates of sample size based on early outcomes of a trial. Previous studies have reported an association between end-of-therapy (EOT) PET results and long-term progression-free (PFS) and overall survival (OS) in diffuse large B-cell lymphoma (DLBCL) patients receiving standard first-line chemoimmunotherapy. We have also previously shown that the overall predictability of PET-CR for PFS and OS in these trials is similar to that in 18 literature-based studies. (15-ICML 2019, P195). To assess the potential for PET-CR as a surrogate endpoint in registration trials, we conducted a prospectively designed individual patient-level-data meta-analysis of available clinical trials. Methods: We synthesized patient-level data from three prospective phase II and III trials (GOYA [NCT01287741], GATHER [NCT01414855], MAYO [NCT00670358]) conducted in previously untreated DLBCL patients, using a Bayesian hierarchical model. We considered the two treatment arms in GOYA (GOYA-R-CHOP [rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone] and GOYA-G-CHOP [obinutuzumab, cyclophosphamide, doxorubicin, vincristine, and prednisone]) separate; hence a total of four arms, excluding patients without baseline PET scans. We investigated the relationship between PET-CR and long-term survival outcomes overall and within patient subgroups. We used Kaplan-Meier plots to compare survival endpoints by PET-CR status. We considered hypothetical RCTs that have PET-CR and PFS as endpoints to show how our model of the relationship between PET-CR and PFS can be used to predict the trial outcome. Results: We included 1496 patients (GOYA-R, GOYA-G, GATHER, MAYO, respectively: 665, 669, 100, 62). EOT PET-CR status was determined by the Lugano criteria in GOYA and by IHP in the other two studies. The overall rate of PET-CR was 72%; respectively 72%, 73%, 62% and 74% per arm. Panel A of the Figure shows Kaplan-Meier plots of PFS by PET-CR status. The Bayesian modeled hazard ratio (HR) comparing PET-CR versus nonCR was 0.13 (95% CI: 0.10, 0.15). The model can be used in planning a clinical trial as follows. Suppose a new therapy improves the PET-CR rate from 70% to 85%. Based on our model the expected HR for PFS treatment effect would be 0.71 (95% CI: 0.58, 0.84). The trial sample size required to demonstrate such an improvement with 90% power is about 650 patients, assuming an accrual rate of 50 patients per month and a minimum follow-up time of 12 months. Panel B of the Figure shows the model-based PFS HR and its CI (shaded) as it depends on the PET-CR rate of the new therapy. This plot also shows the estimated total trial sample size (in red), again assuming the relationship between PET-CR and PFS in our model. However, our model may not apply for the new therapy; and the trial could have an adaptive design with final sample size tailored to the accruing information about PET-CR and PFS and their relationship for the therapies in the trial. Conclusions: Achieving an EOT PET-CR in newly diagnosed DLBCL is highly predictive of favorable outcome in the populations we considered. The estimated HR is 0.13 for PFS, PET-CR versus nonCR, and it is 0.10 for OS. Based on our model, a treatment that improves PET-CR rate could be reasonably expected to have a benefit on PFS and OS, for the populations we considered. Whether a new therapy, with a different mechanism of action, that improves PET-CR rate will extend PFS in a clinical trial is less clear. An adaptive trial could be initiated based on our model as a hypothesis. This hypothesis can be verified or updated using accruing information in the trial itself. Our model can also help in planning clinical trials for re-estimating sample size during the trial and considering early stopping for futility. Further work should investigate the applicability of PET-CR in predicting PFS and/or OS for treatments that have different mechanisms of action and for other populations of patients. Acknowledgements: This work was funded by Genentech/Roche. Disclosures Berry: Berry Consultants, LLC: Consultancy, Employment, Equity Ownership, Other: Berry Consultants, LLC is a company that provides statistical design and analysis services to pharmaceutical companies (including Genentech/Roche), medical device companies, U.S. NIH cooperative groups, patient advocacy groups, and international consortia. Broglio:Berry Consultants LLC: Employment. Ward:Hoffmann La Roche: Employment, Equity Ownership. Mattiello:F. Hoffmann-La Roche Ltd: Employment. Sahin:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Nielsen:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. McGlothlin:Berry Consultants, LLC: Consultancy, Employment. Elliott:Berry Consultants, LLC: Employment. Sehn:Lundbeck: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Kite Pharma: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Apobiologix: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; TEVA Pharmaceuticals Industries: Consultancy, Honoraria; Janssen-Ortho: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Merck: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Astra Zeneca: Consultancy, Honoraria; TEVA Pharmaceuticals Industries: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; F. Hoffmann-La Roche/Genentech: Consultancy, Honoraria, Research Funding; Astra Zeneca: Consultancy, Honoraria; Kite Pharma: Consultancy, Honoraria; F. Hoffmann-La Roche/Genentech: Consultancy, Honoraria, Research Funding; Verastem: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Janssen-Ortho: Honoraria; Takeda: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria. Trněný:Abbvie: Consultancy, Honoraria; Gilead Sciences: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Celgene: Consultancy; Janssen: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; F. Hoffmann-La Roche: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; MorphoSys: Consultancy, Honoraria. Vitolo: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; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; 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; F. Hoffmann-La Roche: Speakers Bureau. Martelli:Servier: Honoraria; F. Hoffman-La Roche, Celgene, Janssen, Sandoz, Novartis, Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Honoraria; F. Hoffman-La Roche, Celgene, Janssen, Sandoz, Novartis, Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees. Kostakoglu:F. Hoffman-La Roche: Consultancy; Genentech: Consultancy. Nowakowski:F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding.

Abstract Introduction: Lenalidomide (Len) in association with standard Rituximab-CHOP (R2CHOP21) has been shown to be safe and effective in newly diagnosed Diffuse Large B-cell Lymphomas (DLBCL) [Nowakowski et al. JCO 2014, Vitolo et al. Lancet Oncol 2014]. The addition of lenalidomide appears to benefit primarily patients with non-Germinal Center B-cell (non-GCB) phenotype as determined by immunohistochemistry (IHC). These early results led to currently ongoing randomized trial in ABC subtype of DLBCL, however efficacy of R2CHOP in ABC DLBCL as defined by Gene Expression Prophyling (GEP) has not been reported. In the present combined analysis of two independent phase 2 studies, we report the long-term follow-up (FU) outcome in DLBCL patients treated with R2CHOP, comparing GCB and ABC according to Nanostring Platform. Methods: We included all newly diagnosed histologically-confirmed de-novo DLBCL patients enrolled in two R2CHOP21 phase 2 trials, conducted by Mayo Clinic (MC) and Italian Lymphoma Foundation (FIL). Inclusion criteria in the two trials were similar, main differences included: all age and all International Prognostic Index (IPI) vs age between 60 and 80 years old and IPI >1, in MC vs FIL study, respectively. All pts received R-CHOP21 plus Len at 25 mg/day for 10 days/cycle and 15 mg/day for 14 days/cycle in MC and FIL trial, respectively. Cell of origin (COO) was determined by IHC, according to Hans algorithm, and retrospectively, in patients with available pathological material, by Nanostring, performed according to Scott algorithm and Masque-Soler signature in MC and FIL study, respectively. We analyzed the long-term FU outcome in terms of progression-free survival (PFS), time to progression (TTP), overall survival (OS), comparing between GCB and ABC phenotypes according to GEP. Results: A total of 112 DLBCL pts (63 MC, 49 FIL) were included. Main characteristics were: median age 69 years (y) (range 22-87), male 65 (58%) pts, advanced stage III-IV in 94 (84%), B symptoms in 38 (34%), International Prognostic Index (IPI) intermediate-high/high in 71 (63%). At a median follow-up of 5.1 years (y), 5y-PFS was 63.5%, 5y-TTP 70.1% and 5y-OS 75.4%. A total of 32 relapses were observed, with only 2 cases of Central Nervous System (CNS) relapse. Late relapse occurring beyond 3 years was observed in 4 cases (3 cases with GCB phenotype and one case with missing COO data). In a subgroup analysis by IPI 0-2 vs 3-5 were: 5y-PFS, 5y-TTP and 5y-OS were: 69.0% vs 59.0% (p=0.100), 73.2% vs 67.4% (p=0.285) and 82.3% vs 70.2% (p=0.059), respectively. Regarding for COO defined by IHC, GCB phenotype vs non-GCB were 45 (40%) vs 41 (37%) patients respectively; 26 (23%) patients were not evaluable. 5y-PFS, 5y-TTP and 5y-OS were: 52.8% vs 64.5% (p=0.198), 61.6% vs 69.6% (p=0.444) and 68.6% vs 74.1% (p=0.238) in GCB vs non-GCB, defined by IHC, respectively. Regarding Nanostring analysis, GCB vs ABC vs Unclassified (Uncl) were 31 (46%) vs 22 (32%) vs 15 (22%) respectively; 44 pts were not evaluable. 5y-PFS, 5y-TTP and 5y-OS were: 62.3% vs 70.8% vs 64.2% (p=0.645), 68.1% vs 79.8% vs 64.2% (p=0.662) and 76.0% vs 74.8% vs 79.0% (p=0.658) in GCB vs ABC vs Uncl, defined by Nanostring, respectively (Table1, Fig1). Conclusions: The association of Len with R-CHOP21 appears to overcome the negative prognostic impact of ABC phenotype determined by GEP, with high PFS, TTP and OS rate, maintained at a long-term FU analysis. Figure 1. Figure 1. Disclosures Chiappella: Teva: Other: lecture fees; Janssen: Membership on an entity's Board of Directors or advisory committees, Other: lecture fees; Nanostring: Other: lecture fees; Roche: Other: lecture fees; Amgen: Other: lecture fees; Celgene: Membership on an entity's Board of Directors or advisory committees, Other: lecture fees. Gaidano:Roche: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Morphosys: Honoraria. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Vitolo: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, Research Funding, Speakers Bureau; Takeda: Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sandoz: Speakers Bureau; Gilead: Speakers Bureau.

Abstract Background Central nervous system (CNS) relapse of diffuse large B-cell lymphoma (DLBCL) is a devastating event occurring in approximately 5% of patients treated with standard R-CHOP (Thanarajasingam et al, ASH 2015, abs 1456). Isolated CNS relapse is associated with significant morbidity and mortality. New treatment regimens with agents that cross the blood-brain barrier (BBB) are needed. The combination of lenalidomide with R-CHOP (R2CHOP) has shown promising results in activated B-cell (ABC) type DLBCL in phase 2 studies and is currently being evaluated in randomized trials. Lenalidomide crosses the BBB and has been demonstrated to have single-agent activity in relapsed CNS lymphoma. Accordingly, the addition of lenalidomide to R-CHOP may decrease the risk of CNS relapse. Here we characterize the combined incidence of isolated CNS relapse in a population of DLBCL patients who received R2CHOP for induction therapy in two independent phase 2 studies. Methods We analyzed the incidence of isolated CNS relapse in patients with histologically-confirmed DLBCL enrolled in two R2CHOP phase 2 trials - one conducted by Mayo Clinic (MC) and the other by Italian Lymphoma Foundation (FIL) - in the context of clinical variables that included age, gender, disease stage, cell of origin, and administration of CNS prophylaxis. We assessed CNS-International Prognostic Index (CNS-IPI) factors (age, stage, lactate dehydrogenase level, ECOG performance status, extranodal sites, adrenal/kidney involvement) and classified patients into groups of low, intermediate, and high risk of CNS relapse. The risk of CNS relapse in R2CHOP-treated patients was then estimated and compared against published rates in RCHOP-treated patients based on CNS-IPI score. Results One hundred thirty-six patients with DLBCL from both cohorts (87 MC patients, 49 FIL patients) were included in this analysis. Mean age was 65 and median follow-up in 104 patients still alive was 48.2 months (range: 2.1-88.5). 61.8% of patients were male; 86.0% had stage III disease or higher; 44.1% had ECOG performance status of 0; cell of origin phenotype by immunohistochemistry according to Hans algorithm was germinal center B-cell (GCB), non-GCB (ABC), and not available in 43.4%, 36.8%, and 19.8%, respectively; 14.7% received intrathecal (IT) methotrexate for CNS prophylaxis per local practice. No patients received intravenous methotrexate. 10.3%, 71.3%, and 18.4% of patients were classified into low, intermediate, and high-risk CNS-IPI groups, respectively. Only one of 136 patients developed isolated CNS relapse, corresponding to an estimated incidence of CNS relapse of 0.007 (0.7%). Conclusions Despite a large proportion of patients with intermediate and high risk of CNS relapse treated in both phase 2 studies, induction therapy with R2CHOP in patients with DLBCL is associated with a lower-than-expected rate of isolated CNS relapse. The latter is unlikely to be explained by use of IT chemotherapy, which is considered to be marginally effective in this setting and was implemented only in a small proportion of patients. This suggests that addition of CNS-penetrating small molecules, such as lenalidomide, to R-CHOP may decrease the risk of CNS relapse. Disclosures Chiappella: Celgene: Speakers Bureau; Teva: Speakers Bureau; Roche: Speakers Bureau; Pfizer: Speakers Bureau; Janssen-Cilag: Speakers Bureau; Amgen: Speakers Bureau. Nowakowski:Morphosys: Research Funding; Celgene: Research Funding; Bayer: Consultancy, Research Funding. Cavallo:Janssen-Cilag: Honoraria; Onyx: Honoraria; Celgene: Honoraria. Gaidano:Roche: Consultancy, Honoraria, Speakers Bureau; Karyopharm: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau. Spina:Mundipharma: Membership on an entity's Board of Directors or advisory committees, Other: Speaker Fee; Teva Pharmaceuticals Industries: Membership on an entity's Board of Directors or advisory committees, Other: Speaker Fee. Vitolo:Takeda: Other: Honoraria for lectures; Gilead: Other: Honoraria for lectures; Janssen: Membership on an entity's Board of Directors or advisory committees, Other: Honoraria for lectures; Roche: Membership on an entity's Board of Directors or advisory committees, Other: Honoraria for lectures.

Abstract Background: Limited data exist to describe the clinical features and outcomes for elderly pts with FL. The FLASH group performed a prospectively planned pooled analysis of IPD from first-line RCTs and examined associations between age (<= 70 vs. > 70 years), clinical characteristics and FL outcomes. Methods: We identified 18 randomized controlled multicenter clinical trials in the FLASH database which enrolled elderly pts (> 70 yrs). From these 18 studies, 5922 previously untreated FL pts were included for this analysis. Complete response (CR) at 24 and 30 months were defined as whether the pt achieved and remains in CR at 24 months and 30 months after initiation of induction treatment. PFS24 is defined as proportion of pts progression-free and alive at 24 months post-randomization. Time to progression (TTP) and overall survival (OS) were defined as time from randomization to the date of progression (censoring for death without progression) and date of death due to any cause, respectively. Progression-free survival (PFS) was defined as time from randomization to the date of progression or death, due to any cause, whichever comes first. Non-lymphoma death was defined as death without prior progression. Early disease outcomes, i.e. CR24, CR30, and PFS24 were primary outcomes; secondary outcomes were TTP, OS, and PFS. For time-to-event outcomes, Kaplan-Meier method and log-rank test were used for univariate estimation and comparison; stratified Cox proportional hazard modeling was used for multivariable analyses. Cumulative incidence methods were used to model PFS while treating disease progression as the primary event of interest and non-lymphoma death as a competing risk. For binary outcomes, multivariable logistic regression was used to estimate the association between age groups and outcomes. Variable adjusted in the regression models are FLIPI score without the age component, ECOG performance status (>= 2 vs < 2), and rituximab use. Results: Among 5922 previously untreated FL pts from 18 RCTs, 63% (n = 3728) were <= 60, 28% (n = 1652) 61-70, and 9% (n = 542) > 70 yrs. Pts age > 70 (vs. <= 70) more commonly had elevated LDH (42% vs 36%, p = 0.02), hemoglobin < 12 g/dL (27% vs 19%, p < 0.0001), ECOG PS >= 2 (8.8% vs 5.0%, p = 0.0004), and elevated β2-microglobulin (68% vs 49%, p < 0.001), less often had > 4 lymph nodes involved (54% vs 65%, p < 0.001), and had similar FLIPI scores without age component (p = 0.17). There were no significant differences between groups in: Ann Arbor stage (94% vs 95% stage III/IV) or rituximab use (62% vs 58%). Median survival follow-up was 5.6 yrs. Pts > 70 yrs did not differ from pts <= 70 in rates of CR24 (27% vs 30%, p=0.32), CR30 (29% vs 31%, p=0.55) or PFS24 (63% vs. 67%, p=0.10). Median TTP was 3.8 and 4.0 years for pts > 70 and <= 70, respectively (HR=1.08, 95% CI 0.96-1.23, p=0.20). With a median OS of 14.6 years for all pts, median OS was 7.4 and 15.7 years for pts > 70 and <= 70, respectively (HR=2.35, 95% CI=2.03-2.73, p<0.001). PFS was statistically significantly different but clinically similar at median 3.1 and 3.8 years for pts > 70 and <= 70, respectively (HR=1.26, 95% CI =1.12-1.41, p<0.001). Further investigation showed the difference in PFS was due to higher incidence of non-lymphoma death in pts > 70 with no difference in disease progression (Figure). In regression models, adjusting for rituximab use, ECOG PS >= 2, and FLIPI score without the age component, age > 70 was a significant predictor of OS and PFS (due to higher incidence of non-lymphoma death), but not PFS24, CR24 or CR30 (Table). Conclusions: FL pts > 70 yrs treated on trials have similar early disease outcomes to younger patients. There is no disease-specific outcome difference between age groups. Age alone should not disqualify patients from standard treatments or RCTs. Disclosures Flowers: Genentech: Consultancy, Research Funding; NIH: Research Funding; Mayo Clinic: Research Funding; TG Therapeutics: Research Funding; Millenium/Takeda: Research Funding; ECOG: Research Funding; Acerta: Research Funding; Pharmacyclics, LLC, an AbbVie Company: Research Funding; Roche: Consultancy, Research Funding; AbbVie: Research Funding; Infinity: Research Funding; Gilead: Consultancy, Research Funding. Ou:Mayo Clinic: Employment. Shi:Mayo Clinic: Employment. Hochster:Genentech: Consultancy, Other: Consultancy fees for advisory boards for GI cancer and bevacizumab with amounts within Yale University de minims guidelines. Brice:Roche: Honoraria; Takeda Pharmaceuticals International Co.: Honoraria, Research Funding; Bristol Myers-Squibb: Honoraria; Gilead: Honoraria; Seattle Genetics: Research Funding. Hiddemann:Roche: Other: Grants; Roche: Membership on an entity's Board of Directors or advisory committees; Genentech: Other: Grants. Marcus:Takeda: Consultancy, Speakers Bureau; Roche: Consultancy, Speakers Bureau. Kimby:Abbvie: Consultancy, Honoraria; Jansen: Consultancy, Honoraria; Celgene: Honoraria; Baxalta: Consultancy; Gilead: Honoraria. Herold:Gilead: Other: Personal fees from member advisory board; Celgene: Honoraria; Genentech: Other: Grants; Roche: Honoraria, Other: Grants. De Bedout:Celgene: Employment. Nielsen:Hoffmann-La Roche: Employment. Morschhauser:Roche: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Servier: Consultancy, Honoraria; Gilead Sciences: Consultancy, Honoraria; Janssen: Honoraria. Rummel:Mundipharma GmbH: Other: Personal fees, Research Funding; Roche Pharma AG: Other: Personal fees, Research Funding. Vitolo:Gilead: Other: Honoraria for lectures; Takeda: Other: Honoraria for lectures; Roche: Membership on an entity's Board of Directors or advisory committees, Other: Honoraria for lectures; Janssen: Membership on an entity's Board of Directors or advisory committees, Other: Honoraria for lectures. Salles:Celgene: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Gilead: Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Roche/Genentech: Consultancy, Honoraria, Research Funding; Mundipharma: Honoraria. Sargent:Celgene: Research Funding.

Abstract Background Rituximab in combination with chemotherapy has been shown to improve overall survival (OS) in pts with FL compared with chemotherapy alone. The effect of MR was evaluated in randomized clinical trials (RCTs) with conflicting results regarding OS. In a previous systematic review and meta-analysis of summary (aggregate) data we demonstrated an OS benefit of MR treatment in pts with relapsed or refractory FL and an improved progression free survival (PFS) in both untreated and relapsed refractory FL. However, pts' disease and treatment characteristics may interact with the effect of MR. To improve identification of sub-groups of pts who may benefit from MR treatment, and to evaluate factors that interact with the effect of MR we conducted an international IPD (raw data) meta-analysis of RCTs of MR for pts with FL. We present the first analysis of this meta-database. Methods In June 2014, we updated an electronic search in Pubmed and the Cochrane Library, conference proceedings and database of clinical trials for randomized trials comparing MR to observation. The investigators of eleven trials that fulfilled inclusion criteria were invited to cooperate. Results of one trial were not reported and this trial could not be included in the meta-analysis. Seven study groups participated in this collaborative project and contributed data on individual pts, including disease characteristics, past treatment, response, survival and adverse events. We examined the effect of pt, disease and treatment characteristics by performing a series of Cox regression analyses stratified by trial. In a sensitivity analysis we combined the assessed log hazard ratios (HR) using a log-rank test for each study and combined the results using a fixed effect meta-analysis. Results We obtained data for 2323 patients randomized in 7 trials of MR compared to observation after induction therapy. The median follow up ranged from 28-114 months. The median age was 57 years (23 - 85 years), and 41% were older than 60 years. 50% of pts were women, 97% had WHO performance status 0-1; 1195 (53%) pts received CHOP/RCHOP, 453 (20%) CVP/R CVP; 1755 (77%) received rituximab containing induction; 33% of pts received 1st induction, 67% ≥2nd. Overall, pts less than 60 years of age (vs. ≥60 years) (p < 0.0001), and women (p = 0.001) had a better prognosis. There was no interaction between sex and the effect of MR (p = 0.65). Pts treated with MR had an improved OS compared to observation (HR 0.76, 95% CI 0.62-0.93, p=0.008, Figure). This was demonstrated also in a sensitivity analysis of 10 studies fulfilling inclusion criteria. There was no statistically significant heterogeneity of treatment effect between trials (p=0.15). In an analysis by treatment line (1st vs. ≥2nd), the estimated effect of MR among patients who received ≥2nd induction was HR of 0.70 (95% CI 0.55 - 0.91), compared to 0.90 (95% CI 0.65 - 1.25) among patients who received 1st induction. However, this difference was not statistically significant (p=0.25). Analysis by the inclusion of rituximab in induction demonstrated among patients who received rituximab in induction a HR of 0.82 (95% CI 0.63 – 1.06), and among those who received induction without rituximab a HR of 0.68 (95% CI 0.49 – 0.93). This difference was not statistically significant (p= 0.35). Analysis by chemotherapy regimen demonstrated an estimated effect for MR among patients who received RCHOP/CHOP of 0.79, 95% CI 0.58 – 1.06, and after RCVP/CVP of 0.65, 95% CI 0.42 – 1.02, with no statistically significant difference between these sub-groups (p = 0.50). Conclusions This is the first report of the collaborative group of maintenance therapy for FL patients. Based on individual patient data, this study demonstrated an improved OS with MR therapy for patients with FL. A sensitivity analysis with all 10 eligible trials supported these results. Results support the effectiveness of MR among patients after their 1st induction as well as after ≥2nd induction, and irrespective of inclusion of rituximab in induction, and the chemotherapy regimen. These results are consistent with those of the summary data meta-analysis that was previously published. The wider CI and lack of statistical significance within sub-groups could be attributed to the sample size. Figure: Pooled HR of death of MR compared to observation in patients with follicular lymphoma. In one study there were no events in one group and it is not represented in the forest plot. Figure:. Pooled HR of death of MR compared to observation in patients with follicular lymphoma. In one study there were no events in one group and it is not represented in the forest plot. Disclosures Vidal: Roche: unrestricted grant Other. Shpilberg:Roche: Consultancy, Research Funding.