Maurer, Matthew J.

Abstract Background: Follicular lymphoma (FL) exhibits significant clinical, cellular, molecular, and genetic heterogeneity. Our understanding of FL biology and molecular classifications of FL, to date, has largely been driven by pathologic classification (Grade 1-3b), genetic classification (m7-FLIPI), or gene expression profiling (IR-1/2; Huet-23), along with limited studies on small cohorts or targeted panels. In order to further understand the biological underpinnings and complexity of FL, large-scale and integrated whole exome sequencing (WES) and RNA sequencing (RNAseq) studies are needed. Using a highly-annotated cohort of 93 FL tumors with matched RNAseq, WES, and CyTOF data, we have explored the transcriptomic signature of purified FL B cells and identified unique molecular subsets that are defined by distinct pathway activation, immune content, and genomic signatures. Methods: Frozen cell suspensions from 93 untreated FL (Grade 1-3b) patients' tumor biopsies, enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE, were used for the study. DNA was isolated from whole tumor cell suspensions, and RNA was isolated from both whole tumor and B cell-enriched cell suspensions. RNAseq and WES were performed in the Mayo Clinic Genome Analysis Core. RNAseq and WES data were processed using a standard pipeline and novel driver genes were identified using Chasm+ driver analysis. Copy number variants were identified from WES data using GISTIC 2.0. NMF clustering and single sample gene set testing for B cell lineage and tumor microenvironment (TME) signatures were performed in R using the NMF and singscore packages. Results: Unsupervised clustering of RNAseq data identified three distinct expression programs which separated patient B cell samples into 3 groups: Group 1 (G1, n=20), Group 2 (G2, n=24), Group 3 (G3, n=43). While no clinical attributes were defined by any single group, G1 consisted of cases that had less aggressive characteristics (63% Stage I-II, 79% FLIPI 0-1). To identify unique transcriptional pathways driving the three expression programs, we scored gene level contributions to NMF expression programs and employed gene set enrichment analysis. This revealed significant pathway association with type-I IFN signaling (G1), DNA repair and stress response (G2), and epigenetic modulation (G3) as differentiating programs between the 3 groups (FDR q<0.001). VIPER master regulator activity inferencing revealed that these pathways were likely being controlled by differential activity in NF-kB, IRFs, STAT1, BCL6, and FOXO1. Each program significantly enriched for, but were not defined by, portions of specific germinal center programs, such as pre-memory (G1), light-zone-to-dark-zone transition (G2), and a pre-light-zone intermediate (G3). We next assessed the connection between B cell programs and the tumor microenvironment (TME) using available paired CyTOF data on 67 cases, which revealed an active TME in G1, with an abundance of CD8 T cell and NK cell populations, a wide variety of immune content in G2 that consisted mostly of Tfh and myeloid cells, and a poorly populated immune compartment in G3 compared to G1 and G2. Finally, somatic driver mutations and copy number alterations from WES were identified and associated with the three clusters. The three groups distinguished themselves by significant enrichment of copy number alterations (TNFAIP3-loss , 1q23-gain, 1q32-gain) in G2, while 10q-loss and mutations in BCL2 and chromatin modifiers (KMT2D and CREBBP) enriched in G3. G1, overall, had lower alteration burden and had weak associations with any specific alterations, suggesting an alternative mechanism for driving the G1 program. Conclusion: In this study, we have identified three unique FL tumor B cell groups, defined by specific transcriptional programs. Pathways such as inflammation, DNA damage response, and chromatin modification contribute most to the differences between B cell samples and group membership. Additionally, each program associated with specific genetic events as well as TME composition, highlighting potential drivers of these B cell states. This study improves the understanding of the mechanisms driving FL tumors and motivates further investigation into transcriptional consequences of genetic events as well as potential tumor intrinsic factors that may influence the TME. Figure 1 Figure 1. Disclosures Maurer: BMS: Research Funding; Genentech: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: 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. Rimsza: NanoString Technologies: Other: Fee-for-service contract. Link: MEI: Consultancy; Genentech/Roche: Consultancy, Research Funding; Novartis, Jannsen: Research Funding. Habermann: Tess Therapeutics: Other: Data Monitoring Committee; Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. King: Celgene/BMS: Research Funding. Cerhan: Genentech: Research Funding; Regeneron Genetics Center: Other: Research Collaboration; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding. Novak: Celgene/BMS: Research Funding.

Abstract Introduction Central nervous system relapse (secondary central nervous system lymphoma -SCNS) is an uncommon but devastating complication of aggressive B-cell lymphoma. Patients (Pts) with CNS-IPI 4-6 are at greatest risk (10.2% at 2 years). Intravenous high-dose methotrexate (HD-MTX) is widely used to mitigate SCNS risk but data supporting this practice are limited. Methods We performed a multicentre, retrospective study at 21 sites in Australia, Asia, North America and Europe. Chart or registry review was performed for consecutively diagnosed pts with diffuse large B-cell lymphoma (DLBCL) and CNS-IPI 4-6, high grade B-cell lymphoma (HGBL) with rearrangements of MYC+BCL2 and/or BCL6 and primary breast/testicular DLBCL irrespective of CNS-IPI. Pts were diagnosed between 2000-2020, 18-80 years at diagnosis, and treated with curative intent anti-CD20 based chemo-immunotherapy. Pts with CNS involvement at diagnosis were excluded. HD-MTX was defined as at least one cycle of intravenous MTX at any dose. Time to SCNS was calculated from date of diagnosis (all-pts), and from the end of frontline systemic lymphoma therapy, defined as 6x21 days from diagnosis (complete response (CR-pts)), until SCNS, systemic relapse, death, or censoring, whichever came first. Cumulative risk of SCNS was computed using the Aalen-Johansen estimator treating death and systemic relapses as competing events. Adjusted cumulative risks were obtained by using an inverse probability of treatment weighting approach. The average treatment effect was computed as the difference in adjusted 5-year risk of SCNS. Results - 2300 and 1455 pts were included in the all-pts and CR-pts analyses, respectively. Baseline demographics and details of therapy are summarised in Table 1. Except for a predominance of males, pts ≤60 years and pts with ECOG 0-1 in the HD-MTX vs no HD-MTX groups, the demographics and treatments were well balanced. At a median follow up of 5.9 years (range 0.0-19.1) and 5.5 years from diagnosis (range 0.0-18.7), 201/2300 and 84/1455 pts experienced CNS events in the all-pts and CR-pts analyses respectively. For all-pts(n=2300), CNS-IPI was 4-6 in 2052(89.2%), with R-CHOP-like therapy given to 93.8%. 410 pts (17.8%) received HD-MTX (265 HD-MTX alone, 145 in combination with intrathecal methotrexate (IT-MTX);435 received IT-MTX alone;1455 received neither. There were 32/410 and 169/1890 SCNS events, with median time from diagnosis to SCNS of 8.8 and 6.7 months in the HD-MTX and no HD-MTX groups respectively. 5-year OS was 70% (95% CI, 65-76%) and 55% (95% CI 53-57%) in HD-MTX and no HD-MTX groups respectively. There was no difference in the adjusted 5-year risk of SCNS between the HD-MTX and no HD-MTX groups (8.4% vs 9.1%, adjusted hazard ratio [HR] 0.71, p=0.100) (Figure 1). For CR-pts(n=1455), CNS-IPI was 4-6 in 1267(87.0%), with R-CHOP-like therapy given to 93.3%. 284 pts (19.5%) received HD-MTX (170 HD-MTX alone, 114 with IT-MTX);298 received IT-MTX alone;873 received neither. There were 16/284 and 68/1171 SCNS events, with median time from diagnosis to SCNS of 11.0 and 10.3 months in the HD-MTX and no HD-MTX groups respectively. 5-year OS was 74%(95% CI 67-81%) and 75%(95% CI 72-78%) in the HD-MTX groups and no HD-MTX groups respectively (adjusted HR 1.08, p=0.622). There was no difference in the 5-year risk of CNS relapse between the HD-MTX and no HD-MTX groups 5.0% vs 6.0% (adjusted HR 1.03, p=0.903) (Figure 2). Exploratory analysis of the impact of HD-MTX among the highest risk groups CNS IPI 5 (n=368), CNS-IPI 6 (n=59) and CNS-IPI 6 plus all pts with testicular, renal or adrenal involvement (n=349) did not reveal differences in SCNS rates in HD-MTX treated pts. Additional subgroup analyses will be presented at the meeting. Conclusions To our knowledge, this is the largest study of the efficacy of HD-MTX in reducing SCNS events focusing exclusively on high-risk pts. The overall incidence of CNS relapse observed was consistent with previous reports in similar patient cohorts at 9%. The use of HD-MTX did not lower SCNS rates overall or when analysis was confined to CR pts at completion of curative intent therapy to compensate for potential immortal bias associated with HD-MTX therapy. Despite the limitations of the non-randomized and retrospective design, it appears unlikely that HD-MTX is associated with a clinically meaningful reduction in SCNS rates in pts with high risk for SCNS. Figure 1 Figure 1. Disclosures Lewis: AstraZeneca: Consultancy, Honoraria; Novartis: Patents & Royalties: Conference attendance; Janssen: Honoraria, Patents & Royalties: Conference attendance; Roche: Consultancy, Honoraria. Villa: Janssen: Honoraria; Gilead: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Seattle Genetics: Honoraria; Celgene: Honoraria; Lundbeck: Honoraria; Roche: Honoraria; NanoString Technologies: Honoraria. Bobillo: F. Hoffmann-La Roche Ltd: Consultancy, Speakers Bureau; Gilead: Speakers Bureau. Ekstroem Smedby: Takeda: Consultancy; Janssen Cilag: Research Funding. Savage: Merck: Consultancy, Honoraria, Other: Institutional clinical trial funding; BMS: Consultancy, Honoraria, Other: Institutional clinical trial funding; AbbVie: Consultancy, Honoraria; Roche: Research Funding; Takeda: Other: Institutional clinical trial funding; Servier: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Astra-Zeneca: Consultancy, Honoraria; Beigene: Other: Institutional clinical trial funding; Genentech: Research Funding. Eyre: Beigene: Honoraria, Research Funding; Incyte: Consultancy; Secura Bio: Consultancy, Honoraria; Janssen: Honoraria; Gilead/KITE: Honoraria, Other: Travel support for conferences, Research Funding, Speakers Bureau; Loxo Oncology: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Honoraria, Other: Travel to conferences; AstraZeneca: Honoraria, Research Funding; Roche: Consultancy, Honoraria. Cwynarski: Incyte: Consultancy, Speakers Bureau; Gilead: Consultancy, Speakers Bureau; Atara: Consultancy; Celgene: Consultancy; Takeda: Consultancy, Other: travel to scientific conferences, Speakers Bureau; Kite, a Gilead Company: Consultancy, Other: travel to scientific conferences, Speakers Bureau; Janssen: Consultancy, Other: travel to scientific conferences; Roche: Consultancy, Other: travel to scientific conferences, Speakers Bureau; BMS/Celgene: Other: travel to scientific conferences. Stewart: Teva: Honoraria; Sandoz: Honoraria; Amgen: Honoraria; AstraZeneca: Honoraria; Novartis: Honoraria; Celgene: Honoraria; Gilead: Honoraria; Abbvie: Honoraria; Janssen: Honoraria; Roche: Honoraria. Bishton: Gilead: Honoraria, Other: Travel grants; AbbVie: Honoraria, Other: Travel grants; Celgene/BMS: Honoraria, Other: travel grants; Celltrion: Honoraria, Other: Travel grants; Takeda.: Honoraria, Other: Travel grants . Fox: F. Hoffmann-La Roche Ltd: Consultancy, Membership on an entity's Board of Directors or advisory committees. Joffe: Epizyme: Consultancy; AstraZeneca: Consultancy. Eloranta: Janssen Pharmaceutical NV: Other: NV. Sehn: Genmab: Consultancy; Novartis: Consultancy; Debiopharm: Consultancy. Manos: Bristol-Myers Squibb: Other: Travel and meetings. Hawkes: Specialised Therapeutics: Consultancy; Gilead: Membership on an entity's Board of Directors or advisory committees; Merck Sharpe Dohme: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Antigene: Membership on an entity's Board of Directors or advisory committees; Regeneron: Speakers Bureau; Bristol Myers Squib/Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck KgA: Research Funding; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Other: Travel and accommodation expenses, Research Funding, Speakers Bureau; Janssen: Speakers Bureau. Minson: Novartis: Research Funding; Hoffman La Roche: Research Funding. Dickinson: Celgene: Research Funding; Amgen: Honoraria; Takeda: Research Funding; Gilead Sciences: Consultancy, Honoraria, Speakers Bureau; MSD: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Other: travel, accommodation, expenses, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau. Øvlisen: Abbvie: Other: Travel expenses. Gregory: Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel fees, Speakers Bureau; Janssen: Consultancy; Novartis: Consultancy. Ku: Roche: Consultancy; Antegene: Consultancy; Genor Biopharma: Consultancy. Talaulikar: Roche: Honoraria, Research Funding; Jansenn: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Takeda: Honoraria, Research Funding; EUSA Pharma: Honoraria, Research Funding. Maurer: Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Genentech: Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Nanostring: Research Funding. El-Galaly: Abbvie: Other: Speakers fee; ROCHE Ltd: Ended employment in the past 24 months. Cheah: Roche: Consultancy, Honoraria, Other: advisory and travel expenses, Research Funding; Janssen: Consultancy, Honoraria, Other: advisory; MSD: Consultancy, Honoraria, Other: advisory, Research Funding; Gilead: Consultancy, Honoraria, Other: advisory; Ascentage pharma: Consultancy, Honoraria, Other: advisory; Beigene: Consultancy, Honoraria, Other: advisory; AbbVie: Research Funding; Celgene: Research Funding; AstraZeneca: Consultancy, Honoraria, Other: advisory; Loxo/Lilly: Consultancy, Honoraria, Other: advisory; TG Therapeutics: Consultancy, Honoraria, Other: advisory.

Abstract Background: Generalizability of results from clinical trials with narrow in-/exclusion criteria are a concern as significant deviations in efficacy or toxicity may occur when treatments are used in populations of elderly and more comorbid patients. The cost-effectiveness of novel therapies may also be less favorable if real-world treatment effects are inferior to clinical trial results. In diffuse large B-cell lymphoma (DLBCL), a recent US study showed that baseline organ function-based eligibility criteria had substantial impact on survival with ineligible patients being at higher risk of dying from progressive lymphoma (1). Aims: The present study explored the impact of commonly used in-/exclusion criteria in key completed and ongoing first line DLBCL trials on survival in a Danish population-based study of patients with de novo DLBCL. Patients and methods: DLBCL patients enrolled in the Danish Lymphoma Registry (LYFO) and treated with R-CHOP in the period 2008-19 were screened for completeness of data to match trial eligibility criteria. The key organ/hematology eligibility criteria of completed or ongoing all-comers DLBCL studies (REMoDL-B, Goya, Polarix and Hovon84) were collected (bilirubin, ALAT, creatinine, eGFR, leucocytes, neutrophils, thrombocytes and ECOG). First, high-level trial matching on disease risk group (Ann Arbor, bulky disease, international prognostic index (IPI)) and age-groups were performed so that patients assessed for trial eligibility had a relevant risk profile. Subsequently, patients were divided into eligible or ineligible based on selected in/exclusion criteria. For each trial, overall survival (OS) from treatment start were compared for eligible and ineligible patients using inverse probability of treatment weighted Kaplan-Meier and log-rank tests. Crude OS and OS adjusted for residual imbalances in IPI and age were estimated. When possible, the OS curves from standard arms of the original trials were superimposed on OS plots. For each trial, the Shapley value of each criterion was calculated, using the HRs as well as the 5y restricted loss of lifetimes (RLOLs). The Shapley value measures the average influence of each eligibility criterion on the estimated IPI- and age-adjusted HR/5y RLOL. Results: A total of 3,150 R-CHOP treated DLBCL patients without discordant low-grade lymphoma were identified in the surveyed period. A total of 1,666 patients (52.89% of surveyed population) were available for the REMoDL-B trial, 1,431 (45.43%) for Goya, 1,125 (35.71%) for Polarix, and 1,432 (45.46%) for Hovon84. The variations of numbers for each trial evaluation were explained by trial inclusion criteria and missing data in LYFO. Crude OS estimates for patients with and without all necessary information were similar (data not shown). OS curves for eligible and ineligible patients are shown in Figure 1 and, when possible, with superimposed trial results (Goya, REMoDL-B, Hovon84). Survival differences between trial eligible and ineligible patients were robust to further adjustment of imbalances in age and IPI. Associated crude and adjusted 2 and 5-year OS rates for trial eligible and ineligible are shown in Table 1. The largest numerical difference in 2-year crude OS between eligible and ineligible was observed in the REMoDL-B trial (ineligible had 26% lower 2-year OS rate). The largest numerical difference in 2-year OS adjusted for IPI and age between eligible and ineligible was observed for the Polarix trial (ineligible had 17% lower 2-year OS rate). The strongest drivers of OS differences between trial eligible and ineligible patients in terms of the tested eligibility criteria were thrombocyte count (HR-contribution calculated from Shapley values -0.11; -0.14) and ECOG (HR-contribution -0.09; -0.21). Liver function parameters (bilirubin and ALAT) had low impact on OS (HR-contribution 0.00; -0.05 and 0.00; 0.07). Conclusions: The present population-based study confirms that trial ineligible patients have worse survival even after adjustments in imbalances in age and disease risk category. Thus, trial eligibility criteria have substantial impact on generalizability of results to a wider unselected population. Interestingly, the trial eligible patients identified in the present study had very similar outcomes to R-CHOP treated patients in the original trials supporting the possible use of RWD as synthetic control arms. Figure 1 Figure 1. Disclosures Maurer: Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Nanostring: Research Funding; Genentech: Research Funding; Celgene: Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees. Jørgensen: Novartis: Consultancy; Gilead: Consultancy; Roche: Consultancy; Celgene: Consultancy. Larsen: BMS: Consultancy; Novartis: Consultancy; Celgene: Consultancy; Odense University Hospital, Denmark: Current Employment; Gilead: Consultancy. Clausen: Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel expences ASH 2019; Gilead: Consultancy, Other: Travel expences 15th ICML ; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Poulsen: Abbvie: Consultancy; Janssen: Consultancy. El-Galaly: Abbvie: Other: Speakers fee; ROCHE Ltd: Ended employment in the past 24 months.

Abstract Background Patients (pts) with aggressive B-cell non-Hodgkin lymphoma (NHL) progressing after anti-CD19 chimeric antigen receptor T (CART) cell therapy have poor prognosis and may benefit from new therapy options through clinical trials. However, in a single center report, only 12% of such pts were treated in trials (Chow et al. Am J Hematol, 2019). Identifying the reasons for this low enrollment is needed to design future studies for this population. Here, we evaluated the eligibility criteria for recent landmark trials for relapsed/refractory aggressive B-cell NHL to learn what eligibility barriers are present. Methods Pts with aggressive B-cell NHL who received FDA-approved CART cell therapy at Mayo Clinic (Rochester, Arizona, Florida) since 2018 and progressed after CART cell therapy were identified. The potential eligibility for the following key trials was evaluated: a) polatuzumab + bendamustine + rituximab, b) tafasitamab + lenalidomide, c) selinexor and d) loncastuximab. The eligibility for each trial was retrospectively assessed at the time of disease progression after CART cell therapy based on hemoglobin (Hb), absolute neutrophils count (ANC), platelet count (Plt), renal and liver function tests, ECOG performance status (PS), and central nervous system (CNS) involvement. Results Seventy-five pts had disease progression to axicabtagene ciloleucel (N=73, 97%) or tisagenlecleucel (N=2, 3%) and are included in this analysis. Median time to progression after CART was 2.1 months (IQR: 1.0 - 3.1). Thirteen (17%) pts were treated in clinical trials after progression following CART cell therapy, while 46 (61%) were treated off trials, and 16 (22%) pts never received any treatment after progression. At a median follow-up of 13.6 months (IQR: 9.1 - 26.7) from CART progression, the median overall survival (mOS) from CART progression was 5.8 months (95% CI 3.5 - 10.1) and 53 (71%) pts died. Thirty-eight pts (51%) did not meet eligibility criteria for any of the 4 recent landmark trials. Hematologic impairment was the most common barrier to inclusion of these patients in clinical trials: Hb < 9 g/dL n=23 (31%) or Hb < 10 g/dL n=36 (48%), ANC < 1.0 x 10 9/L n=19 (25%) or ANC < 1.5 x 10 9/L n=32 (43%), and Plt < 75 x 10 9/L n=30 (40%) or Plt < 90 x 10 9/L n=34 (45%). Renal (n=11, 15%) or liver dysfunction (n=5, 7%), CNS involvement (n=8, 11%) and ECOG PS > 2 (n=3, 4%) were less common reasons leading to exclusion from trials. Post CART trial ineligible pts had significantly shorter time to progression (median 1.7 months, IQR: 1.0 - 2.6 vs. 3.0 months IQR: 1.9 - 3.4, p < 0.01) and inferior overall response to CART (45% vs 67%, p = 0.06) compared to pts who met trial eligibility post CART. Baseline Hb (median Hb 9.5 g/dL, IQR: 8.5 - 10.5 vs. 10.9 g/dL, IQR: 9.7 - 12.2, p < 0.01) and Plt (median Plt 106 x 10 9/L IQR: 54 - 165 vs. 201 x 10 9/L IQR: 141 - 243, p < 0.01) were also significantly lower in pts ineligible for trials post CART. There were no significant differences between pts eligible or ineligible for trials with regards to age (median 59 vs. 60 years), number of prior therapies (median 3 vs. 3), prior autologous stem cell transplant (41% vs. 37%), bridging therapy (65% vs. 63%), baseline ANC (median 4,1 vs. 3,0 x10 9/L), or high-grade (grade ≥ 2) cytokine release syndrome (19% vs. 21%) or neurotoxicity (32%, vs. 42%), respectively. Survival after CART progression was significantly shorter (mOS 2.5 months, 95% CI: 1.6 - 5.1) for the 38 pts ineligible for trials compared to pts eligible for trials (mOS 10.6 months, 95% CI: 8.9 - NA), (p < 0.01). In the 59 pts who received therapy post CART progression, the mOS of pts treated on (n = 13) or off (n = 46) trials was 13.8 months (95% CI: 9.2 - NA) vs. 6.6 months (4.9 - 10.7), respectively (p = 0.047). Conclusion Approximately half of the pts (51%) with aggressive B-cell NHL progressing after CART cell therapy would have be excluded from landmark clinical trials. The current hematologic exclusion criteria are a major barrier to enrollment in clinical trials, which would exclude many pts who have disease progression within 3 months of CART cell therapy (ie, primary refractory disease), in whom cytopenia as a toxicity from therapy is prevalent. Given the known delayed hematologic recovery after CART cell therapy and the unmet need of pts progressing to CART cell therapy, the hematologic exclusion criteria should be adjusted to increase trial participation of this population, especially of those with primary refractory disease. Figure 1 Figure 1. Disclosures Munoz: Gilead/Kite Pharma, Kyowa, Bayer, Pharmacyclics/Janssen, Seattle Genetics, Acrotech/Aurobindo, Beigene, Verastem, AstraZeneca, Celgene/BMS, Genentech/Roche.: Speakers Bureau; Janssen: Research Funding; Pharmacyclics/Abbvie, Bayer, Gilead/Kite Pharma, Pfizer, Janssen, Juno/Celgene, BMS, Kyowa, Alexion, Beigene, Fosunkite, Innovent, Seattle Genetics, Debiopharm, Karyopharm, Genmab, ADC Therapeutics, Epizyme, Beigene, Servier: Consultancy; Seattle Genetics: Research Funding; Millennium: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding; Incyte: Research Funding; Portola: Research Funding; Merck: Research Funding; Celgene: Research Funding; Gilead/Kite Pharma: Research Funding; Bayer: Research Funding; Seattle Genetics: Honoraria; Physicians' Education Resource: Honoraria; Targeted Oncology: Honoraria; OncView: Honoraria; Kyowa: Honoraria. Murthy: CRISPR Therapeutics: Research Funding. Maurer: Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Nanostring: Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Genentech: Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees. Bennani: Purdue Pharma: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Vividion: Other: Advisory Board; Kymera: Other: Advisory Board; Verastem: Other: Advisory Board. Paludo: Karyopharm: Research Funding. Wang: Genentech: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; MorphoSys: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; InnoCare: Research Funding. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Witzig: Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding. Nowakowski: Celgene, NanoString Technologies, MorphoSys: Research Funding; Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees. Lin: Vineti: Consultancy; Takeda: Research Funding; Sorrento: Consultancy; Novartis: Consultancy; Juno: Consultancy; Legend: Consultancy; Janssen: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Merck: Research Funding; Gamida Cell: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding.

Abstract Background Diffuse large B-cell lymphoma (DLBCL) that fails to achieve a complete response (CR) or relapses early after standard immunochemotherapy (IC, e.g., R-CHOP or similar) is referred to as primary refractory DLBCL and has a poor prognosis. The clinical course with regards to frontline IC is heterogenous, and different definitions have been used in literature, e.g., progressive or refractory during therapy (narrow definition), or not achieving complete remission at the end of IC, or relapsing within 6 or 12 months after completing IC (broad definition). A small proportion of patients may still have chemosensitive disease and be able to achieve durable disease control with salvage chemotherapy followed by autologous stem cell transplant (ASCT). However, it is challenging to identify such patients, with clinical and molecular predictors highly needed. In this study, we examined the association of time to refractory status with survival outcomes in patients with primary refractory disease. Methods Adult patients with newly diagnosed DLBCL between 2002 and 2015 and seen at Mayo Clinic Rochester were identified from the prospective Molecular Epidemiology Resource (MER) cohort study of the University of Iowa/Mayo Clinic Lymphoma SPORE. The current study included patients with primary refractory disease, which was defined as no response to frontline IC (primary progression), partial response (PR) at end of treatment (EOT PR), or relapse with 12 months after achieving CR at EOT (early relapse). Clinical characteristics, treatment and response data, and follow-up data were abstracted from MER and collected by medical record review if needed. Clinical characteristics between groups were compared using Chi-square test. Overall survival (OS) was defined as the time from confirmation of refractory disease to the time of death from any cause and was analyzed using the Kaplan-Meier method. Results Out of 949 newly diagnosed DLBCL patients, 122 (12.8%) had primary refractory disease, 36 with primary progression, 36 with EOT PR, and 50 with early relapse. The baseline clinical characteristics are summarized in Table 1. No significant differences in age, gender, ECOG performance status, number of extranodal sites, stage, International Prognostic Index, or cell of origin were found between the 3 groups. The proportion of MYC2 and BCL2/BCL6 rearrangements or Myc/Bcl2 double expressor was small and not different among the 3 groups. Salvage therapies were mainly platinum based high-dose chemotherapy (e.g., R-ICE, R-DHAP, or similar) for systemic disease, MTX-based therapy for CNS relapse, or radiotherapy or resection for localized disease (Table 1). The response to salvage chemotherapy was significantly different between the 3 groups. The CR/PR rate was 8.6%/28.6% for patients with primary progression, 16.7%/46.7% for patients with EOT PR, and 35.6%/33.3% for patients with early relapse (P<0.01, Table 1). At a median follow-up time (of living patients) of 113 months, 93 patients had died. The 2-year OS was 13.9% for patients with primary progression, which was significantly worse compared to that of patients with EOT PR (2-year OS 41.7%) or early relapse (2-year OS 44%), (P=0.001)(Figure 1A). In patients with early relapse, the 2-year OS was not significantly different among those who relapsed with 3 months, between 3-6 months, or between 6-12 months (Figure 1B). Conclusion Our data suggest that broadly defined primary refractory DLBCL has heterogenous survival outcomes. DLBCL patients with primary progressive disease represent an ultra-high risk group that has particularly poor survival outcomes with current standard salvage regimens. Novel therapies such CAR T-cell therapy or targeted agents should be studied in this patient population. In contrast, patient who only achieve PR at EOT and those who relapse within 1 year of achieving CR had better OS. A fraction of these patients may still have chemosensitive disease and benefit from salvage chemotherapy and ASCT. The survival difference in the two groups also has important implications for clinical trial design. The definition of primary refractory DLBCL in clinical trials should be carefully and clearly defined. When evaluating novel therapies in single arm trials, the benchmark for efficacy (i.e., historical outcomes) may differ according to the population included in the trial (e.g., time to refractory status). Figure 1 Figure 1. Disclosures Maurer: BMS: Research Funding; Genentech: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: 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. Bennani: Vividion: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Verastem: Other: Advisory Board; Purdue Pharma: Other: Advisory Board; Kymera: Other: Advisory Board. Cerhan: Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding; Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding. Witzig: Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding; Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees. Habermann: Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Tess Therapeutics: Other: Data Monitoring Committee; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Wang: Genentech: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; InnoCare: Research Funding; MorphoSys: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding. Nowakowski: Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene, NanoString Technologies, MorphoSys: Research Funding.

Abstract Introduction: Up to 40% of newly diagnosed diffuse large B cell lymphoma (DLBCL) will relapse after frontline rituximab, doxorubicin, cyclophosphamide, vincristine, and prednisone (RCHOP), with subsequent poor prognosis. Identification of patients (pts) at high risk of relapse early in the treatment can allow for development of risk adapted therapies to improve outcomes. Positron Emission Tomography scan after 2 cycles of therapy (PET2) has been evaluated as a predictor of relapse but study treatments were heterogenous and results were conflicting. A substudy of CALGB 50303 trial did not find association of PET2 response by Deauville Score (DS) with survival in RCHOP and DA-EPOCH-R treated pts. In the UK National Cancer Research Institute Prospective Study, DS of 5 on PET2 predicted worse progression free survival but not overall survival (OS) in RCHOP-21 and RCHOP-14 treated pts. Here we report impact of PET2 response on outcomes in two large independent, prospective cohorts of newly diagnosed DLBCL treated homogenously with two RCHOP-based regimens of similar efficacy. Methods: Discovery was done in adult pts with DLBCL enrolled into a single arm phase 2 trial of lenalidomide plus standard RCHOP (R2CHOP) (MC078E, NCT00670358). The validation cohort comprised of adult pts with newly diagnosed DLBCL treated with standard RCHOP prospectively enrolled into the Mayo component of the University of Iowa/Mayo Clinic Molecular Epidemiology Resource (MER). Both MC078E and MER cohorts included patients who received at least 3-6 cycles of therapy and had a PET2. Pts who progressed on PET2 were excluded. End of treatment (EOT) PET was done 3-12 weeks after last cycle of therapy. The revised response criteria for malignant lymphoma (Cheson, et al 2007) was used to assess PET in MC078E. In MER, revised response criteria for malignant lymphoma (Cheson et al 2007) or Lugano classification was used, depending on era of diagnosis. Positive PET was defined as FDG uptake above background (Cheson 2007) or DS 4 or 5 (Lugano 2014). Study endpoints were event-free survival (EFS) and OS by PET2 status. Results: Out of 118 pts treated on MC078E, 102 had PET2 (MC078E). The median age at diagnosis was 64 years (range 19-87), 61 (60%) were male, 89 (87%) had advanced stage disease, 46 (45%) had international prognostic index (IPI) of 3-5. 58 (57%) were PET2 Negative (PET2-ve) and 44 (43%) were PET2 Positive (PET2+ve). At EOT PET, 83 (81%) had -ve PET and 15 (15%) had +ve PET. Out of 44 PET2+ve pts, 15 remained +ve at EOT PET. Out of 58 PET2-ve pts, 56 had EOT PET available and all were -ve. Out of 866 DLBCL pts enrolled into MER between August 2005 and June 2015, 621 were treated with RCHOP for 3-6 cycles and 272 had available PET2 (MER). The median age was 65 years (range 55-73), 152 (56%) were male, 174 (64%) had advanced stage, 103 (38%) had IPI 3-5. 186 (68%) were PET2-ve and 86 (32%) were PET2+ve. Out of 235 with EOT PET available, 182 (77%) had -ve EOT PET and 25 (11%) had +ve EOT PET. PET2+ve pts had higher odds of +ve EOT PET (OR: 17.4 (CI 95 8.3-40.0), p<0.001) and progression on EOT PET (OR: 4.3 (CI 95 1.9-10.2), p<0.001) in MER cohort. This analysis was not possible on MC078E as all PET2-ve had -ve EOT PET. In MC078E, 2-year EFS and OS were 69.5% (CI 95 61.1-79.1) and 88.1% (CI 95 82-94.7). In MER, 2-year EFS and OS were 71.6% (CI 95 67.7-76.8) and 82.3% (CI 95 79.3-85.3). Compared to PET2-ve, PET2+ve pts had significantly inferior EFS in both MC078E (HR 4.0, CI 95 2.1-7.88, p<0.0001, figure 1a) and MER (HR 2.9, CI 95 1.9-4.1, p<0.0001, figure 1c). Compared to PET2-ve , PET2+ve pts had a trend towards lower OS in MC078E (HR 2.0, CI 95 0.9-4.9, p=0.1, figure 1b) and a significantly lower OS in MER (HR 2.3, CI 95: 1.5-3.4, p<0.0001, figure 1d). In subgroup analysis of MC078E, PET2+ve pts had lower EFS and a trend towards lower OS in all subgroups except IPI 0-2 (Table 1). In MER, PET2+ve pts had lower EFS and OS in all the subgroups except stage I-II and IPI 0-2 (Table 1). Conclusions: Positive PET2 was associated with increased risk of disease progression and death in newly diagnosed DLBCL. Results of our study provide robust evidence of importance of PET2 as an early predictor DLBCL pts at high risk of progression in two independent prospective cohorts. PET2-guided risk-adapted strategies using chimeric antigen receptor T-cell therapy and bispecific antibodies may potentially improve outcomes, should be explored in clinical trials and results of our study serve as a benchmark for such studies. Figure 1 Figure 1. Disclosures Maurer: Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Nanostring: Research Funding; Celgene: Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees. Wang: Genentech: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; MorphoSys: Research Funding; InnoCare: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Cerhan: Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; Regeneron Genetics Center: Other: Research Collaboration; NanoString: Research Funding; Genentech: Research Funding. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Habermann: Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Tess Therapeutics: Other: Data Monitoring Committee; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Witzig: Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding; Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees. Nowakowski: Celgene, NanoString Technologies, MorphoSys: Research Funding; Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction: Clinical trials of novel salvage therapies (ST) have encouraging outcomes for relapsed/refractory classic Hodgkin lymphoma (R/R cHL) after autologous stem cell transplant (ASCT); yet studies comparing novel ST with conventional salvage chemotherapy are lacking. In a single center cohort, we demonstrated that bendamustine/brentuximab (BBV) had higher overall response rates (ORR) and complete response (CR) rates in ASCT-eligible R/R cHL (Desai et al JCO, 2021). Herein we report comparative outcomes of novel and conventional ST in R/R cHL who undergo ASCT, in a large multicenter retrospective cohort. Methods: Consecutive R/R cHL pts who underwent ASCT at 12 institutions across United States were included. Demographics and clinical variables at relapse including age, sex, B symptoms, stage, bulky disease (BD, single mass > 6 cm) extra nodal disease (END), primary refractory disease (PRD) and early relapse (ER, within 1 year) were recorded by electronic health records review. Study objectives were ORR, CR to first ST, post-ASCT PFS and OS by final ST. Time to event endpoints were defined from date of ASCT. Results: From 12 participating institutions, 853 pts of R/R cHL who underwent ASCT were eligible for this study. Median age was 33 (14-72) years, 457 (54%) were male, 446 (52%) had BD, 257 (30%) had advanced stage, 271 (32%) had END, 369 (43%) had B symptoms, 142 (17%) had PRD and 307 (36%) had ER. All 853 received at least 1 ST, 245 received 2 ST, 71 received 3 ST and 26 received 4 ST. Seven groups of ST were identified: 1. Conventional platinum-based chemotherapy (PBC) group including ICE, DHAP and ESHAP 2. BBV 3. Brentuximab Vedotin and nivolumab (BV/Nivo) 4. BV alone (BV) 5. gemcitabine-based chemotherapy (Gem) 6. checkpoint inhibitors (CPI) and 7. other miscellaneous agents (Misc). 1st ST was as follows: 553 had PBC; 69 had BBV; 48 had BV/Nivo; 65 had BV; 49 had Gem; 4 had CPI and 63 had Misc. There was no significant difference in the baseline characteristics by type of 1 st ST (data not shown). BBV had significantly higher ORR (92% vs 79%, p<0.001) and CR rate (80% vs 49%, p <0.001) compared to PBC. BV/Nivo had significantly higher CR rate (67% vs 49%, p <0.001) and a trend towards higher ORR (86% vs 79%, p = 0.1) compared to PBC. BV had significantly lower ORR (62% vs 79%, p <0.001) and CR rate (34% vs 49%, p <0.001) compared to PBC. There was no difference in ORR and CR rate of PBC, Gem, CPI and Misc agents. Final ST prior to ASCT was PBC in 451, BBV in 76, BV/Nivo in 48, BV in 87, CPI in 24, Gem in 90 and Misc in 64. Table 1 lists K-M estimates of 2-year survival probabilities for different Final ST groups. Median follow up was 3 (range 0.1-13) years. BV/Nivo group had significantly higher proportion of patients with PRD and BD than PBC, no other differences in baseline characteristics were identified amongst ST groups (data not shown). BV/Nivo (HR: 0.1 (CI 95:0.02-0.4), p<0.01) and CPI (HR: 0.12 (CI 95:0.03-0.5), p<0.01) had significantly higher PFS than PBC. There was no significant difference in PFS between other ST groups (Figure 1a). Type of ST was not significantly associated with difference in OS (Figure 1b). 536 pts underwent ASCT in CR, 273 underwent ASCT in partial response (PR) and 31 underwent ASCT with progressive disease (PD). Pre-ASCT PR (HR 1.6 (CI 95:1.3-2.6), p<0.001) and PD (HR: 4.1 (CI 95: 2.5-6.8), p<0.001) predicted significantly lower PFS compared to CR (Figure 2a). OS was also significantly lower in pts with pre-ASCT PR (HR 1.7 (CI 95: 1.2-1.6), p<0.001) and PD (HR 5.3 (CI 95: 2.8-10), p<0.001) (Figure 2b). Higher number of pre-ASCT ST predicted lower PFS (HR 1.3 (CI 95: 1.1-1.6), p<0.001) and OS (HR 1.5 (CI 95: 1.2-1.8), p<0.001). In pts with pre-ASCT CR, all 36 who had pre-ASCT CR after BV/Nivo were alive and relapse free for follow up of 0.1-5 yrs. BV/Nivo was associated with significantly higher PFS (HR 0.1 (CI 95: 0.01-0.7), p <0.05) but not OS compared to PBC in this subgroup. Increasing number of pre-ASCT ST predicted worse PFS (HR 1.5 (CI 95: 1.2-2.0), p<0.01) and OS (HR 2.2 (CI 95: 1.4-3.4), p<0.001) in this subgroup as well. Conclusions: BV/Nivo has a higher CR rate and better post-ASCT PFS compared to conventional chemotherapy and can lead to durable remissions in pts with pre-ASCT CR. BBV had a higher response rate and similar post-ASCT survival to conventional chemotherapy. BV had lower response rates compared to chemotherapy. Novel ST such as BV/Nivo and BBV may be preferable to conventional chemotherapy in R/R cHL. Figure 1 Figure 1. Disclosures Spinner: Notable Labs: Honoraria. Bachanova: FATE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Research Funding; KaryoPharma: Membership on an entity's Board of Directors or advisory committees; Gamida Cell: Membership on an entity's Board of Directors or advisory committees, Research Funding. Dorritie: SITC presentation: Honoraria; Genmab: Research Funding; University of Pittsburgh/UPMC Hillman Cancer Center: Current Employment; Janssen: Research Funding; F. Hoffman-La Roche Ltd: Research Funding; Juno/BMS: Research Funding; Kite, a Gilead Company: Research Funding; OncLive/Institutional Perspectives on Cancer presentation: Honoraria. Arai: Magenta Therapeutics: Research Funding. Maurer: Nanostring: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Celgene: Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees. Diefenbach: Genentech, Inc./ F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Research Funding; IMab: Research Funding; Morphosys: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Merck Sharp & Dohme: Consultancy, Honoraria, Research Funding; Perlmutter Cancer Center at NYU Langone Health: Current Employment; AbbVie: Research Funding; IGM Biosciences: Research Funding; Incyte: Research Funding; Trillium: Research Funding; Gilead: Current equity holder in publicly-traded company; MEI: Consultancy, Research Funding. Nowakowski: Kyte Pharma: Consultancy; Ryvu Therapeutics: Consultancy; Selvita: Consultancy; Curis: Consultancy; Karyopharm Therapeutics: Consultancy; Celgene/Bristol Myers Squibb: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; MorphoSys: Consultancy; Bantham Pharmaceutical: Consultancy; Daiichi Sankyo: Consultancy; Zai Labolatory: Consultancy; Incyte: Consultancy; Kymera Therapeutics: Consultancy; TG Therapeutics: Consultancy; Blueprint Medicines: Consultancy; Nanostrings: Research Funding. Advani: Astellas/Agensys: Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Bayer: Membership on an entity's Board of Directors or advisory committees; Bristol Myer Squibb: Membership on an entity's Board of Directors or advisory committees; Cell Medica: Membership on an entity's Board of Directors or advisory committees; Forty Seven: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genetech Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen Pharmaceutical: Research Funding; Juno: Membership on an entity's Board of Directors or advisory committees; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Kura: Research Funding; Kyowa: Membership on an entity's Board of Directors or advisory committees; Merck: Research Funding; Millenium: Research Funding; Pharmacyclics: Consultancy, Research Funding; Portola Pharmaceuticals: Consultancy; Regeneron: Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees.

Abstract Background: Vaccinations have been hypothesized to play a role in lymphoma etiology, but there are few studies, mixed results, and limited data on lymphoma subtypes. Herein, we investigate the association of vaccinations with risk of major lymphoma subtypes. Methods: We studied 2,461 lymphoma cases and 2,253 controls enrolled from 2002 to 2014. Participants self-reported history of vaccinations against hepatitis A, hepatitis B, yellow fever, and influenza. Polytomous logistic regression was used to estimate OR and 95% confidence intervals (CI), adjusting for potential confounders. Results: After multivariable adjustment, vaccination against influenza was inversely associated with lymphoma (OR = 0.82; 95% CI, 0.66–1.02), which was stronger for last vaccination 1+ years before enrollment (OR = 0.71; 95% CI, 0.56–0.91) and for >5 influenza vaccinations (OR = 0.56; 95% CI, 0.46–0.68). Ever vaccination against hepatitis A (OR = 0.81; 95% CI, 0.66–1.00) but not hepatitis B (OR = 0.97; 95% CI, 0.81–1.18) was associated with lymphoma risk, although more recent vaccinations were inversely associated with lymphoma risk for both hepatitis A (<6 years before enrollment, OR = 0.56; 95% CI, 0.40–0.77) and hepatitis B (<9 years before enrollment, OR = 0.72; 95% CI, 0.55–0.93). Ever vaccination against yellow fever was inversely associated with risk (OR = 0.73; 95% CI, 0.55–0.96), and this did not vary by time since last vaccination. Although there was no overall statistical evidence for heterogeneity of vaccination history by lymphoma subtype, the only statistically significant inverse associations were observed for influenza and yellow fever vaccinations with diffuse large B-cell and follicular lymphoma. Conclusions: Selected vaccinations were inversely associated with lymphoma risk, with time since last vaccination relevant for some of these vaccines. Impact: Vaccinations against hepatitis A, hepatitis B, yellow fever, and influenza are unlikely to increase lymphoma risk.

AbstractBecause there have been a dvances in frontline treatment for mantle cell lymphoma (MCL) over the last 2 decades, we sought to characterize the changes in frontline treatment patterns and their association with outcomes. Patients with newly diagnosed MCL from September 2002 through June 2015 were enrolled in a prospective cohort study, and clinical characteristics, treatment, and clinical outcomes were compared between patients diagnosed from 2002 to 2009 (Era 1) compared with 2010 to 2015 (Era 2). Patient age, sex, and simplified MCL International Prognostic Index (sMIPI) score were similar between the 2 groups. In patients age 65 years or younger, there was less use of rituximab plus hyperfractionated cyclophosphamide, vincristine, doxorubicin, and dexamethasone (R-Hyper-CVAD) (16.1% vs 8.8%) but more use of rituximab plus maximum-strength cyclophosphamide, doxorubicin, vincristine, and prednisone (R-maxi-CHOP) alternating with rituximab plus high-dose cytarabine (R-HiDAC), also known as the Nordic regimen, and R-CHOP alternating with rituximab plus dexamethasone, high-dose cytarabine, and cisplatin (R-DHAP) (1.1% vs 26.4%) and less use of R-CHOP or R-CHOP-like regimens (64.5% vs 35.2%) but more use of R-bendamustine (0% vs 12.1%) in Era 2 (P < .001). These changes were associated with improved event-free survival (EFS; 5-year EFS, 34.3% vs 50.0%; P = .010) and overall survival (OS; 5-year OS, 68.8% vs 81.6%; P = .017) in Era 2. In patients older than age 65 years, there was less use of R-CHOP or R-CHOP-like therapy (39.0% vs 14.3%) and nonstandard systemic therapy (36.6% vs 13.0%) but more use of R-bendamustine (0% vs 49.4%). These changes were associated with a trend for improved EFS (5-year EFS, 25.4% vs 37.5%; P = .051) in Era 2. The shift from R-CHOP or R-CHOP-like regimens to R-bendamustine was associated with improved EFS (5-year EFS, 25.0% vs 44.6%; P = .008) in Era 2. Results from this prospective cohort study provide critical real-world evidence for improved outcomes with evolving frontline patterns of care in patients with MCL.