Farooq, Umar

Abstract Background: Most indolent non-Hodgkin lymphomas (NHL) are considered incurable and are characterized by relapse and remission. Quality of life (QOL) can be affected by disease burden, side effects of treatment, and psychosocial effects of living with an incurable cancer. However, little is known about QOL in this population. We sought to describe QOL at diagnosis, change in QOL over time, and determinants of QOL in patients with indolent NHL. Methods: Newly diagnosed lymphoma patients were prospectively enrolled within 9 months of diagnosis in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource. Eligibility criteria included age ≥18 years; exclusion criteria included HIV-positive, non-US residency, and inability to complete surveys in English. All pathology was reviewed by a hematopathologist. Patients with indolent B-cell NHL were included in this analysis. QOL was measured at baseline (BL) and 3 year follow-up (FU3) with the Functional Assessment of Cancer Therapy-General scale (FACT-G), which measures 4 QOL domains: physical, social/family, emotional, and functional well-being (WB), and a single item Linear Analogue Self-Assessment (LASA) for measuring overall QOL. Patients who did not complete ≥80% of FACT-G questions were excluded. Clinical data were abstracted according to a standard protocol and patients were systematically followed for events (progression, re-treatment, and death). CLL patients were excluded for event analysis due to differing definitions of outcome (progression/retreatment vs. time to first treatment). Treatment was defined as any systemic therapy (including chemotherapy, targeted agents, or antibody therapy) or radiation. QOL scores were transformed to a 0-100 scale with 100 representing the best WB or QOL for analysis. Change in QOL was assessed using the raw difference in QOL scores (i.e., FU3-BL) on the 0-100 scale with positive change scores representing improvements; minimally important difference was defined as 7 points on the transformed FACT-G subscales per previously established cutoffs (Yost and Eton, Eval & Health Prof. 2005 Jun;28:172-91). Changes in QOL from BL to FU3 were assessed using one-sample t-test of change scores vs zero. Results: 1050 patients with indolent NHL enrolled between 9/02-12/2012 and with both pre-treatment and 3 year QOL were included. QOL was collected after initiation of therapy in 215 patients (20%) and prior to therapy in 835 (80%). Subtype was 41% CLL/SLL, 32% grade 1-2 FL, 14% extranodal marginal zone, and 13% other (lymphoplasmacytic lymphoma and other). Median age was 62 years and 55% were male. At the FU3 assessment, 577 patients (55%) had received treatment, 42 (4%) transformed, and 53 (25%) had an event. Emotional WB significantly improved from BL to FU3 (mean +5.9, SD 13.3, p<0.001) while social/family WB significantly decreased (mean -4.8, SD 20.5, p<0.001). Functional WB, physical WB, overall FACT-G, and overall QOL LASA were not significantly different at FU3. These findings were similar in those who were treated vs. those who were observed. We also assessed the results stratified by non-CLL patients who had progression or retreatment between BL and FU3. In patients with an event in the first 3 years, emotional WB had a significant improvement from BL to FU3 (mean +3.6, SD 13.6, p=0.002) and overall QOL LASA decreased (mean -4.0, SD 20.0, p=0.01). In patients without an event, improvements were reported in functional WB (mean +2.1, SD 18.2, p=0.01), physical WB (mean +2.5, SD 13.9, p=0.001), emotional WB (mean +7.0, SD 15.0, p<0.001), and overall QOL LASA (mean +1.1, SD 11.4, p=0.03), while social/family WB decreased (mean -6.2, SD 20.3, p<0.001). Sensitivity analysis showed that results were consistent in the subset of patients who had BL QOL collected prior to initiating therapy. While many changes were statistically significant, they were small in magnitude; only the improvement in emotional WB in the entire cohort approached clinical significance and met that criterion in those without an event. Conclusions: In this large sample of patients with indolent lymphoma, QOL generally remained stable from diagnosis to FU3 while emotional WB showed improvement, suggesting psychosocial adaptation by the patient. Mean score changes in functional WB, physical WB, emotional WB, social/family WB, and overall QOL were more pronounced in patients without an event in the first 3 years since diagnosis. Disclosures Shanafelt: Hospira: Research Funding; AbbVie: Research Funding; Celgene: Research Funding; GlaxoSmithKline: Research Funding; Genentech: Research Funding; Jannsen: Research Funding; Pharmacyclics: Research Funding.

Abstract Introduction: Although increased physical activity (PA) is associated with improved quality of life in cancer survivors, knowledge about the impact of PA on survival in lymphoma patients is limited. We studied the impact of usual adult PA and PA at 3 years after diagnosis on overall (OS) and lymphoma-specific (LSS) survival in lymphoma patients. Methods: Lymphoma patients were prospectively enrolled within 9 months of diagnosis into the Lymphoma SPORE Molecular Epidemiology Resource (MER) cohort. At baseline, patients reported their usual level of mild, moderate and strenuous PA during most of their adult life and (for survivors) again at the 3 year follow-up (FU3), which we used to calculate the Godin Leisure Score Index (LSI). At FU3, patients also self-reported change in PA since diagnosis as increase, decrease or no change. LSI was modeled as a continuous score (per 10-point change) and by tertile. Survival was measured as time from diagnosis (for baseline PA) and time from FU3 (for FU3 PA) until death due to any cause and due to lymphoma. We evaluated the association of PA with outcome using Kaplan-Meier curves as well as hazard ratios (HRs) and 95% confidence intervals (CI) from Cox models stratified by lymphoma subtype and adjusted for age and sex (and baseline PA for change models). Results: Of 4087 patients enrolled in the MER at the Mayo Clinic from 2002-2012, 3129 had baseline PA data (3060 evaluable for LSI), and 1845 (1395 evaluable for LSI) had FU3 PA data. In the baseline cohort, 57.6% of the patients were male. The median age at diagnosis was 62 years (range 18-92 years). The majority had ECOG performance status <2 (95%), no B-symptoms (85.8%) and advanced disease (63% stage III-IV) at diagnosis. The subtypes included were CLL/small lymphocytic (25.9%), follicular (18.1%), diffuse large B-cell (16.8%), marginal zone (8.1%), Hodgkin (6.9%), mantle cell (4.8%), T-cell (5%) and other (14.3%) lymphomas. The median LSI was 28 (range 0-57) at baseline and 25 (range 0-67) at FU3 with a median change in LSI of -2 (range -57 to 61). At a median follow-up of 84 months from diagnosis (IQR 59-119 months) in the cohort with baseline PA, there were 806 total deaths (271 in pts with FU3 PA) and 423 lymphoma deaths (104 in pts with FU3 PA). When analyzed as a continuous variable, baseline LSI was associated with OS (HR 0.95, 95% CI 0.91-0.99) and LSS (HR 0.95, 95% CI 0.90-1.01). LSI by tertiles was associated with OS (p<0.0001, Figure 1a), and patients in the high LSI compared to the low LSI tertile had superior OS (HR 0.81, 95% CI 0.68-0.97) and LSS (HR 0.81, 95% CI 0.63-1.04). For prognosis after 3 years, continuous LSI at FU3 was also associated with superior OS (HR 0.84, 95% CI 0.77-0.92) and LSS (HR 0.76, 95% CI 0.65-0.89). LSI at FU3 by tertiles was associated with OS (p<0.0001, Figure 1b), and patients in the high LSI compared to the low LSI tertile had superior OS (HR 0.51, 95% CI 0.34-0.77) and LSS (HR 0.33, 95% CI 0.16-0.67). A change in LSI from baseline to FU3 PA was associated with superior OS (HR 0.84, 95% CI 0.76-0.92) and LSS (HR 0.74, 95% CI 0.64-0.87) after FU3. Change in LSI by tertiles was associated with OS (p=0.0007, Figure 1c). Compared to patients with stable LSI (change of LSI between -10 and 5 points from baseline, n=429), patients who increased LSI by > 5 (n=464) had improved OS (HR 0.67, 95% CI 0.45-1.00) and LSS (HR 0.47, 95% CI 0.23, 0.94), while patients who decreased LSI by >10 (n=477) had no association with OS or LSS. Self-reported change in PA from baseline to FU3 was associated with OS (p<0.0001, Figure 1d); compared to no change, an increase in PA was not associated with OS (HR 0.79, 95% CI 0.42-1.48) or LSS (OR 0.73, 0.26-2.07), while a reduction in PA was associated with inferior OS (HR 1.94, 95% CI 1.49-2.53) and LSS (HR 2.51, 95% CI 1.62-3.88). After excluding patients with any events through FU3, the associations for the PA change and OS remained significant for change in LSI (HR 0.91, 95%CI 0.83-1.00) and self-reported decrease in PA (HR 1.83, 95%CI 1.32-2.53). Conclusions: Patients with a higher level of usual PA during adult life have significantly better OS and LSS after lymphoma diagnosis compared to those who are less physically active. Higher PA in 3-year survivors is also associated with improved survival, while a reduction in physical activity is associated with worse outcomes. These data support an important role for PA in lymphoma survivorship and also provide a strong rationale for a PA intervention trial in lymphoma patients. Figure 1 Figure 1. Disclosures Cohen: LAM Therapeutics, Inc: Research Funding; Takada: Research Funding; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bioinvent: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees. Flowers: Spectrum: Consultancy; OptumRx: Consultancy; Acerta: Research Funding; Onyx: Research Funding; Janssen Pharmaceutical: Research Funding; V Foundation: Research Funding; TG Therapeutics: Research Funding; National Cancer Institute: Research Funding; Burroughs Welcome Fund: Research Funding; Genentech/Roche: Consultancy, Research Funding; Gilead: Consultancy; Research to Practice: Research Funding; Millennium/Takeda: Research Funding; National Institutes Of Health: Research Funding; Prime Oncology: Research Funding; Educational Concepts: Research Funding; Abbvie: Consultancy, Research Funding; Pharmacyclics LLC, an AbbVie Company: Research Funding; Seattle Genetics: Consultancy; Eastern Cooperative Oncology Group: Research Funding; Celgene: Consultancy, Research Funding; Infinity: Research Funding; Bayer: Consultancy; Clinical Care Options: Research Funding. Cerhan: Janssen: Other: Scientific Advisory Board (REMICADELYM4001); Janssen: Other: Multiple Myeloma Registry Steering .

Abstract Disease progression after frontline therapy for Diffuse large B‐cell lymphoma (DLBCL) is a clinically significant event. Patients who experience early progression or have refractory disease have especially poor outcomes. Simple, clinically applicable prognostic tools are needed for selecting patients for consideration for novel therapies and prognostication in the relapsed/refractory (R/R) setting. Model building was performed in patients from the Surrogate endpoints in aggressive lymphoma (SEAL) consortium with disease progression after frontline immunochemotherapy. The primary endpoint was overall survival (OS) measured from date of progression. Validation was performed in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) and Danish National Lymphoma Register (LYFO) cohorts. Model performance was assessed using time‐dependent concordance indices (c‐statistic) and calibration with metrics evaluated at 2 years from progression. Note, 1234 of 5112 patients treated with frontline immunochemotherapy in the SEAL consortium developed progressive disease. Time to progression on immunochemotherapy and age at progression were strongly associated with post‐progression OS (both p < 0.001). A prognostic model was developed incorporating spline fit for both variables. The model had good concordance in the discovery (0.67) and validation sets (LYFO c = 0.64, MER c = 0.68) with generally good calibration. Time to progression on frontline therapy is strongly associated with post‐progression OS in DLBCL. We developed and validated a simple to apply clinical prognostic tool in the R/R setting. The useful prediction of expected outcomes in R/R DLBCL and can inform treatment decisions such as considerations for CAR‐T therapy as well as trial designs. The model is available in smartphone‐based point of care applications.

Background: Aggressive lymphomas are potentially curable; however, long-term effects of treatment and the disease may adversely affect patients' quality of life (QoL). We investigated QoL at baseline, and up to nine years after diagnosis in survivors of aggressive lymphomas. Methods: Patients newly diagnosed with lymphoma were prospectively enrolled within nine months of diagnosis in the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE) and systematically followed. Patients were enrolled from September 1, 2002 until June 30, 2015. Eligibility criteria included being a United States resident, English-speaking, no history of HIV, and aged 18 years and older. All pathology was reviewed by a lymphoma hematopathologist. Aggressive lymphoma subtypes included in this analysis were diffuse large B-cell lymphoma (DLBCL), Follicular lymphoma grade III, Hodgkin lymphoma, T-cell lymphoma, other non-Hodgkin lymphoma not otherwise specified (NOS), other B-cell lymphoma NOS, and composite lymphomas. We assessed QoL using the Functional Assessment of Cancer Therapy-General (FACT-G) scale at baseline enrollment, and 1, 2, 3, 6, and 9 years post-diagnosis. FACT-G measures well-being (WB) in four domains-physical (PWB), social/family (SFWB), emotional (EWB), and functional (FWB), which are added to create a total (TOT) score. Those who completed &lt;80% of FACT-G questions at any given time point were excluded. "Survivor" was defined as alive at 1, 2, 3, 6, and 9 year follow-up with no active disease or treatment within six months of a given time point. Because patients could be enrolled at any time within the first 9 months from diagnosis, the timing of initial QoL assessment was variable with respect to the start of lymphoma treatment. We estimated longitudinal change in QoL using mixed models incorporating scores from all available time points. The minimally important difference (MID) of 5 points for TOT and 2 points for each of the domains was used to determine clinical significance. Scores were compared to United States (US) general population normative data. All statistical analyses were performed using SAS (v 9.4). Results: From September 1, 2002 to June 30, 2015, 3,028 patients with aggressive lymphomas were prospectively enrolled in the MER, of which 2,018 completed the FACT-G baseline assessment (47% prior to therapy initiation). Of these patients, 1,144 at 1 year, 1,002 at 2 years, 943 at 3 years, 562 at 6 years, and 289 at 9 years post-diagnosis completed the FACT-G at both baseline and each of the respective time points after diagnosis, and met the definition of survivor. The median age at diagnosis of patients analyzed was 59 years (range 18-93). The cohort included 844 female patients (42%). DLBCL comprised 44% of cases, Hodgkin lymphoma 19%, T-cell lymphoma 11%, composite lymphomas 8%, other B-cell NOS 6%, other non-Hodgkin lymphoma NOS 7%, and Follicular lymphoma grade III 5%. QoL increased from baseline enrollment; the largest increase was seen from baseline to 1 year after diagnosis with a statistically and clinically significant mean TOT score difference of 6.7 points. This mean increase in TOT scores sustained over time with an increase of 7.8 points above baseline at 9 years after diagnosis. At baseline, PWB, EWB, and FWB scores were significantly lower in patients with aggressive lymphomas compared to the US general population, and SFWB scores were significantly higher (all p &lt;0.01); however, only SFWB and EWB score differences were clinically significant as defined by MID. SFWB showed only a mild decline from baseline over the course of 9 years. Despite this, all SFWB scores were statistically and clinically significantly higher than the US general population at 1, 2, 3, 6, and 9 years after diagnosis (all p &lt;0.01 and MID &gt;2). Patients with aggressive lymphomas TOT scores at baseline did not differ from the US general population, while TOT scores at 1, 2, 3, 6, and 9 years post-diagnosis were statistically and clinically significantly higher. Overall, the results in the pre-treatment QoL subset were consistent with the cohort as a whole. Conclusions: In survivors of aggressive lymphomas, QoL improved primarily in the first year after diagnosis, and sustained over the course of nine years. QoL in survivors of aggressive lymphomas is higher than the United States general population at 1, 2, 3, 6, and 9 years after diagnosis. Figure Disclosures Maurer: Pfizer: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees; Celgene / BMS: Research Funding; Kite: Membership on an entity's Board of Directors or advisory committees. Farooq:Kite, a Gilead Company: Honoraria. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding.

Background: Indolent B-cell lymphomas are a group of neoplastic disorders that account for approximately one-third of non-Hodgkin lymphomas in the Western world. They are clinically indolent but pathologically diverse and generally composed of follicular lymphoma (FL), extranodal marginal zone lymphoma (EMZL), lymphoplasmacytic lymphoma (LPL), nodal marginal zone lymphoma (NMZL), splenic marginal zone lymphoma (SMZL), and small lymphocytic lymphoma. The overall prognosis is favorable in most patients, but others can have a more aggressive disease with associated progression, relapse, or histologic transformation. We have previously reported that the most common cause of death in FL was lymphoma. Here we report on the cause of death (COD), in other non-follicular indolent B-cell lymphomas (NFIBL) during the first decade of the rituximab era. Methods: Participants were from the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). From 2002 -2015, MER offered enrollment to all patients with newly diagnosed lymphoma who were US residents and age &gt;18 years. Patients were treated per physician choice and followed prospectively. An event was defined as progression or relapse, initiation of 2nd line therapy, or death from any cause. EFS24 was defined using event-free survival at 24 months from diagnosis. Overall survival was defined as the time from diagnosis until death due to any cause. Overall survival from EFS24 was defined as time from event defining date (achieving EFS24 or early event). For decendents, copies of the death certificate or medical records associated with death were reviewed. Cumulative incidence estimates of the cause of death in NFIBL were calculated as competing risks utilizing the cuminc function from the cmprsk package in R version 3.6.2. COD was categorized as a result of lymphoma (progression or therapy-related) vs. other causes vs. unknown/missing. Results: 820 patients with newly diagnosed NFIBL were enrolled in this study. The subtypes included extranodal marginal zone (EMZL, N = 362), unclassifiable low-grade B-cell lymphoma (LGBCL-U, N = 202), lymphoplasmacytic lymphoma (LPL, N = 92), nodal marginal zone lymphoma (NMZL, N = 80), and splenic marginal zone lymphoma (SMZL, N = 84). The median age at diagnosis was 63 years (range 18-92), and 50.5% were male. Baseline clinicopathologic characteristics showed that the LDH was abnormal in 19.3%, hemoglobin was abnormal in 33.8%, and 62.8% had stage III-IV disease. The IPI score was 0-1 in 51%, 2 in 36.6%, 3 in 10.6%, and 4-5 in 1.8%. At a median follow-up of 83 months (range 0-193), 172 (21%) patients had died, and the primary cause of death was non-lymphoma related in 87 (50.6%), lymphoma related 48 (27.9%), and unknown in 37 (21.5%). When examining all subtypes combined, the 10-year estimate for lymphoma related death was 7% (95% CI: 5.2-9.5) which was lower than the rate of non-lymphoma related death (10 years estimate 14%, 95% CI: 11.3-17.4), Figure 1A, Table 1. The 10-year estimate of lymphoma related death varied by subtype, ranging from 2.7% in EMZL to 16.3% in LPL (table 1), while non-lymphoma related death at 10 years ranged from 10.2% in EMZL to 22.5% in SMZL; only in LPL was the lymphoma related rate higher than the non-lymphoma. Patients who failed to achieve EFS24 from diagnosis had significantly higher rates of lymphoma related death (18% at 10 years from failure, 95% CI: 11.7-29.1, Figure 1B) compared to patients who achieved EFS24 (3.9% at 10 years from achieving EFS24, 95% CI: 2.3-6.8, Figure 1C). Rates were similar by EFS24 for non-lymphoma related death (14.5%, 95% CI: 11.0-19.0 vs. 11.2, 95% CI: 6.3-19.7). Figure 1B-C. Conclusion: The most common cause of death in NFIBL at 10 years was unrelated to lymphoma, in contrast to our previous data in follicular lymphoma which showed lymphoma as the most common cause of death at 10 years. However, similar to follicular lymphoma, patients with NFIBL who failed to achieve EFS24 to frontline therapy had significantly increased risk of lymphoma related death. Further research into the cause of death in NFIBL is warranted. Disclosures Maurer: Celgene / BMS: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Witzig:Celgene: Consultancy, Research Funding; MorphSys: Consultancy; AbbVie: Consultancy; Incyte: Consultancy; Acerta: Research Funding; Karyopharm Therapeutics: Research Funding; Immune Design: Research Funding; Spectrum: Consultancy. Novak:Celgene/BMS: Research Funding. Farooq:Kite, a Gilead Company: Honoraria. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding.

Background: Axi-cel is an autologous anti-CD19 chimeric antigen receptor (CAR) T cell therapy approved for the treatment of patients (pts) with relapsed/refractory large B cell lymphoma (LBCL) with ≥ 2 prior systemic therapies. ZUMA-1 is the multicenter, single-arm, registrational Phase 1/2 study of axi-cel in pts with refractory LBCL. In a 2-year analysis of ZUMA-1 (median follow-up, 27.1 months; N=101), axi-cel demonstrated objective response, complete response (CR), and ongoing response rates of 83%, 58%, and 39%, respectively (Locke et al. Lancet Oncol. 2019). Here, we present additional survival follow up and recovery of normal, polyclonal B cells from ongoing responders in ZUMA-1. Methods: Eligible pts with refractory large B cell lymphoma (diffuse large B cell lymphoma, primary mediastinal B cell lymphoma, transformed follicular lymphoma) underwent leukapheresis at enrollment and subsequently received low-dose conditioning chemotherapy (fludarabine and cyclophosphamide) followed by a target dose of 2 × 106 anti-CD19 CAR T cells/kg (Neelapu et al. NEJM. 2017; NCT02348216). The primary endpoint was objective response rate (ORR), and the first response assessment was 4 weeks post infusion. Response assessments were performed per protocol up to 24 months or disease progression, whichever occurred first. For pts in ongoing response beyond Month 24, response assessments continued per institutional standard-of-care (SOC). Blood levels of CAR T cells were quantified using polymerase chain reaction and B cells were characterized using flow cytometry in pts with ongoing responses and evaluable samples. Results: A total of 111 pts were enrolled, and axi-cel was administered to 101 pts. As previously reported in the ZUMA-1 2-year analysis, among pts who received axi-cel, the median time from axi-cel infusion to both objective response and CR was 1.0 month (range, 1 - 12 months; Locke et al. Lancet Oncol 2019). When the entire enrolled population (N = 111) was included on an intent-to-treat basis, the median manufacturing time was 17 days (range, 14 - 51; n = 110 as manufacturing was not feasible for 1 pt). Additionally, among the 111 pts, the median time from enrollment/leukapheresis to objective response and CR was 1.7 months (range, 0.7 - 12.9) and 1.9 months (range, 0.7 - 13.3), respectively. Responses have been durable, and with a minimum of 3 years of follow-up (median, 39.1 months), the median overall survival (OS) was 25.8 months, and the 3-year OS rate was 47%. Importantly, no axi-cel-related secondary malignancies have been reported. As previously reported, pts in ongoing response after 2 years had significantly greater peak CAR T cell expansion in blood 7 - 14 days after axi-cel infusion than did those with relapse (P = 0.014) or no response (P = 0.0003; Locke et al. Lancet Oncol 2019). Blood samples from 22 pts in ongoing response (per institutional SOC) at ≥ 3 years were available for analysis of CAR T cells and evaluation of B cell recovery. All evaluable pts had detectable B cells in blood at 3 years post axi-cel. Notably, 91% of pts in ongoing response at 3-year follow-up demonstrated recovery of polyclonal B cells measured by presence of both kappa and lambda light chains on non-malignant CD19+CD20+ B cells. The median kappa-lambda ratio of 1.6 and relative levels of key B cell subsets, including memory and naive B cell immunophenotypes, suggested reconstitution of B cell repertoire, consistent with published data from healthy individuals (Deneys et al. J Immunol Methods 2001; Scott et al. J Clin Pathol 2018). Additionally, 15/22 (68%) had both minimal levels of detectable CAR gene-marked cells and detectable polyclonal B cells in blood. Altogether, these findings support the hypothesis that persistence of functional CAR T cells is not necessary for durable remissions of LBCL. Overall survival and translational findings with ≥ 4 years of follow-up will be presented. Conclusions: Axi-cel produced rapid responses and longterm disease control in pts with refractory LBCL. Most responses occurred by the first assessment, and the brief time elapsed between enrollment and response supports both the speed and success of manufacturing. Furthermore, axi-cel-treated pts with ongoing responses at ≥ 3 years showed evidence of restoration of a normal B cell compartment and clearance of functional CAR T cells, a critical component of the long-term safety of CD19-directed CAR T cell therapies. Disclosures Locke: Kite, a Gilead Company: Consultancy, Research Funding; Wugen: Consultancy; Calibr: Consultancy; Allogene: Consultancy; Cellular Biomedicine Group: Other: Consultancy with grant options; GammaDelta Therapeutics: Consultancy; Celgene/Bristol-Myers Squibb: Consultancy; Novartis: Consultancy. Ghobadi:Celegene: Consultancy; Wugen: Consultancy; Atara: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding, Speakers Bureau; EUSA: Consultancy. Miklos:Novartis: Consultancy, Other: Travel support, Research Funding; Allogene Therapeutics Inc.: Research Funding; Juno-Celgene-Bristol-Myers Squibb: Consultancy, Other: Travel support, Research Funding; Janssen: Consultancy, Other: Travel support; Miltenyi Biotec: Research Funding; Pharmacyclics: Consultancy, Other: Travel support, Patents & Royalties, Research Funding; Adaptive Biotech: Consultancy, Other: Travel support, Research Funding; Kite-Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Research Funding. Oluwole:Pfizer: Consultancy; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Spectrum Pharmaceuticals: Consultancy; Bayer: Consultancy. Lin:Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Merck: Research Funding; Vineti: Consultancy. Hill:Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Honoraria, Research Funding. Timmerman:Merck: Research Funding; Corvus: Current equity holder in publicly-traded company; Marker Therapeutics: Current equity holder in publicly-traded company; Immune Design: Honoraria; Celldex Therapeutics: Consultancy; BMS: Other: Travel support, Research Funding; Spectrum Pharmaceuticals: Research Funding; Kite, a Gilead Company: Consultancy, Other: Travel support, Research Funding; Bluebird Bio: Current equity holder in publicly-traded company; Genmab: Current equity holder in publicly-traded company; Valor: Research Funding. Deol:Novartis: Consultancy; Kite, a Gilead Company: Consultancy. Reagan:Kite, a Gilead Company: Consultancy; Curis: Consultancy; Seattle Genetics: Research Funding. Stiff:Kite, a Gilead Company: Research Funding; Delta-Fly: Research Funding; Gamida Cell: Research Funding; Atara: Research Funding; Unum: Research Funding; Macrogenics: Research Funding; Amgen: Research Funding. Flinn:Celgene: Research Funding; TG Therapeutics: Consultancy, Research Funding; Trillium Therapeutics: Research Funding; Curio Science: Consultancy; Merck: Research Funding; Constellation Pharmaceuticals: Research Funding; BeiGene: Consultancy, Research Funding; ArQule: Research Funding; Kite Pharma: Consultancy, Research Funding; Genentech, Inc.: Research Funding; Pfizer: Research Funding; Calithera Biosciences: Research Funding; Agios: Research Funding; Karyopharm Therapeutics: Research Funding; AstraZeneca: Consultancy, Research Funding; Forty Seven: Research Funding; Forma Therapeutics: Research Funding; Loxo: Research Funding; F. Hoffmann-La Roche: Research Funding; Incyte: Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; Novartis: Research Funding; MorphoSys: Consultancy, Research Funding; Rhizen Pharmaceuticals: Research Funding; Yingli Pharmaceuticals ≠: Consultancy, Research Funding; Johnson & Johnson: Other; Roche: Consultancy, Research Funding; Vincera Pharma: Consultancy; Gilead Sciences: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Iksuda Therapeutics: Consultancy; Great Point Partners: Consultancy; Curis: Research Funding; Nurix Therapeutics: Consultancy; Portola Pharmaceuticals: Research Funding; Acerta Pharma: Research Funding; Juno Therapeutics: Consultancy, Research Funding; Unum Therapeutics: Consultancy, Research Funding; Infinity Pharmaceuticals: Research Funding; IGM Biosciences: Research Funding; Takeda: Consultancy, Research Funding; Teva: Research Funding; Seattle Genetics: Consultancy, Research Funding; Triphase Research & Development Corp.: Research Funding; Verastem: Consultancy, Research Funding. Farooq:Kite, a Gilead Company: Honoraria. Goy:COTA: Consultancy, Current equity holder in publicly-traded company, Other: leadership role; Karyopharm: Research Funding; Genentech/Roche: Research Funding; Constellation: Research Funding; Bayer: Research Funding; CALBG: Research Funding; PracticeUpdate Oncology: Consultancy; RCCA/OMI: Current Employment; Acerta: Consultancy, Honoraria, Other: leadership role, Research Funding; AstraZeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: leadership role, Research Funding; Celgene: Honoraria, Research Funding; Hackensack UMC and University of Nebraska: Research Funding; Infinity: Research Funding; Xcenda: Consultancy; Infinity Verastem: Research Funding; Morphosys: Research Funding; AbbVie: Research Funding; MD Anderson: Research Funding; Regional Cancer Care Associates/OMI: Current Employment; Kite, a Gilead Company: Consultancy, Current equity holder in publicly-traded company, Honoraria, Other: leadership role, Research Funding; Janssen: Consultancy, Honoraria, Other: leadership role, Research Funding. McSweeney:Kite, a Gilead Company: Consultancy, Honoraria, Research Funding, Speakers Bureau; Colorado Blood Cancer Institute: Current Employment; Fred Hutchinson: Patents & Royalties. Munoz:Juno/Celgene/BMS: Consultancy, Research Funding, Speakers Bureau; Alexion: Consultancy; Beigene: Consultancy, Speakers Bureau; Fosunkite: Consultancy; Innovent: Consultancy; Acrotech/Aurobindo: Speakers Bureau; Kyowa: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Research Funding, Speakers Bureau; Pfizer: Consultancy; Verastem: Speakers Bureau; AstraZeneca: Speakers Bureau; Genentech/Roche: Research Funding, Speakers Bureau; AbbVie: Consultancy, Speakers Bureau; Merck: Research Funding; Portola: Research Funding; Incyte: Research Funding; Millenium: Research Funding; Kite, a Gilead Company: Consultancy, Research Funding, Speakers Bureau; Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; Bayer: Consultancy, Research Funding, Speakers Bureau; Seattle Genetics: Consultancy, Honoraria, Research Funding, Speakers Bureau. Siddiqi:Oncternal: Research Funding; TG Therapeutics: Research Funding; Janssen: Speakers Bureau; Seattle Genetics: Speakers Bureau; AstraZeneca: Consultancy, Research Funding, Speakers Bureau; BeiGene: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; Celgene: Consultancy, Research Funding; Juno: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding. Rossi:Gilead Sciences: Current equity holder in publicly-traded company; Kite, a Gilead Company: Current Employment. Bot:Kite, a Gilead Company: Current Employment; Gilead Sciences: Consultancy, Current equity holder in publicly-traded company, Other: Travel support . Zheng:Kite, a Gilead Company: Current Employment; Gilead Sciences: Current equity holder in publicly-traded company. Vezan:Merck: Current equity holder in publicly-traded company; Abbvie: Current equity holder in publicly-traded company; Kite, a Gilead Company: Current Employment, Honoraria, Other: Travel support. Bashir:Kite, a Gilead Company: Current Employment; OmniacPharmConsult Ltd: Current Employment, Current equity holder in private company. Kim:Kite, a Gilead Company: Current Employment; Gilead Sciences: Current equity holder in publicly-traded company. Chu:Kite, a Gilead Company: Current Employment; Gilead Sciences: Current equity holder in publicly-traded company; Amgen: Current equity holder in publicly-traded company; Celgene: Current equity holder in publicly-traded company. Neelapu:N/A: Other; Takeda Pharmaceuticals: Patents & Royalties; Acerta: Research Funding; Karus Therapeutics: Research Funding; Cellectis: Research Funding; Poseida: Research Funding; Unum Therapeutics: Other, Research Funding; Calibr: Other; Kite, a Gilead Company: Other: personal fees, Research Funding; Bristol-Myers Squibb: Other: personal fees, Research Funding; Merck: Other: personal fees, Research Funding; Novartis: Other: personal fees; Celgene: Other: personal fees, Research Funding; Pfizer: Other: personal fees; Allogene Therapeutics: Other: personal fees, Research Funding; Adicet Bio: Other; Legend Biotech: Other; Precision Biosciences: Other: personal fees, Research Funding; Incyte: Other: personal fees; Cell Medica/Kuur: Other: personal fees.

TPS8073 Background: Response rates to salvage immunochemotherapy in patients with DLBCL relapsing after or refractory (R/R DLBCL) to front line therapy remain unsatisfactory. Lenalidomide (Len) has significant single agent activity in relapsed/refractory DLBCL. The addition of lenalidomide (Len) days 1-7 to rituximab plus ifosfamide-carboplatin-etoposide (RICE) was shown to be feasible with promising efficacy in phase 1b study (Feldman T, et al. BJH, 2014). We developed phase I/II study to evaluate the safety and efficacy of the addition of Len (extended to 14 day schedule) to RICE (R2-ICE) for R/R-DLBCL patients who are candidates for stem cell transplant. Methods: The phase I portion was designed to determine the maximally tolerated dose Len in combination with RICE using the standard cohort 3+3 design. The escalation dose levels were 15 mg and 20 mg daily x 14 days. Prophylactic aspirin and growth factor support is mandatory. After 2 cycles of therapy response is evaluated with a PET/CT scan; the responding patients are eligible for 1-2 additional cycles of R2ICE as a bridging before HDC/SCT. The estimated overall response rate for two cycles of R-ICE in R/R DLBCL to RCHOP was estimated to be approximate 45%. We hypothesize that the addition of lenalidomide in the relapse setting could increase the overall response rate by approximately 20%. The one-stage design with an interim analysis being utilized in phase 2 requires 45 evaluable patients (one sided alpha = 0.09, power 90%). For Phase I, all types of B-cell lymphomas were eligible. For phase II portion only DLBCL patients are eligible per central pathology review. Other eligibility criteria include: received one line of previous anti-lymphoma therapy, ≥ 2 weeks from completion of prior anti-lymphoma therapy, candidate for HDC and SCT, adequate organ (creatinine clearance ≥ 60ml/min by Cockcroft-, total bilirubin ≤ 2 × ULN) and bone marrow function (ANC) ≥1500/mm3; platelet count ≥75,000/mm3). The use of steroids and/or rituximab up to 1 week prior to registration for management of symptoms is allowed. 9 patients cleared phase 1 without DLT and dose of 20 mg days 1 -14 was recommend for phase 2 part (RP2D) of the study. The phase 2 study passed interim futility analysis and accrual continues. Correlatives include cell of origin by Nanostring, Myc/bcl2 expression and by FISH and minimal residual disease. PET scans are centrally reviewed including metabolic tumor volume. Clinical trial information: NCT02628405 .

SummaryReduced‐intensity conditioning (RIC) allogeneic haematopoietic cell transplantation (allo‐HCT) is a curative option for select relapsed/refractory Hodgkin lymphoma (HL) patients; however, there are sparse data to support superiority of any particular conditioning regimen. We analyzed 492 adult patients undergoing human leucocyte antigen (HLA)‐matched sibling or unrelated donor allo‐HCT for HL between 2008 and 2016, utilizing RIC with either fludarabine/busulfan (Flu/Bu), fludarabine/melphalan (Flu/Mel140) or fludarabine/cyclophosphamide (Flu/Cy). Multivariable regression analysis was performed using a significance level of <0·01. There were no significant differences between regimens in risk for non‐relapse mortality (NRM) (P = 0·54), relapse/progression (P = 0·02) or progression‐free survival (PFS) (P = 0·14). Flu/Cy conditioning was associated with decreased risk of mortality in the first 11 months after allo‐HCT (HR = 0·28; 95% CI = 0·10–0·73; P = 0·009), but beyond 11 months post allo‐HCT it was associated with a significantly higher risk of mortality, (HR = 2·46; 95% CI = 0·1.32–4·61; P = 0·005). Four‐year adjusted overall survival (OS) was similar across regimens at 62% for Flu/Bu, 59% for Flu/Mel140 and 55% for Flu/Cy (P = 0·64), respectively. These data confirm the choice of RIC for allo‐HCT in HL does not influence risk of relapse, NRM or PFS. Although no OS benefit was seen between Flu/Bu and Flu/Mel 140; Flu/Cy was associated with a significantly higher risk of mortality beyond 11 months from allo‐HCT (possibly due to late NRM events).