Wang, Yucai

7522 Background: Patients with newly diagnoseddiffuse large B-cell lymphoma (DLBCL) who achieve event-free survival at 24 months (EFS24) following immunochemotherapy (IC) have excellent overall survival (OS) similar to that of age- and sex-matched general population. The standard of care for patients with relapsed or refractory (RR) DLBCL following frontline IC is salvage therapy followed by autologous stem cell transplant (ASCT). The goal of this study is to evaluate the role of progression-free survival (PFS) at 24 months (PFS24) as a landmark after ASCT in patients with RR DLBCL. Methods: Patients with RR DLBCL after frontline R-CHOP or R-CHOP-like IC who underwent salvage therapy and ASCT at Mayo Clinic or University of Iowa between 07/2000 and 4/2020 were identified from institutional lymphoma transplant databases. Clinical characteristics, treatment information, and outcome data were abstracted. Post-ASCT PFS, OS, and post-relapse survival (PRS) were plotted by Kaplan-Meier method, and cumulative incidences of relapse vs non-relapse mortality (NRM) and different causes of death were compared accounting for competing events. Statistical analyses were performed in EZR v1.54. Results: A total of 437 patients were identified. Median age at ASCT was 61 years (range 19-78), and 280 (64%) were male. After a median post-ASCT follow up of 8.0 years (95% CI 7.2-8.7), 215 patients had a relapse (or disease progression), 180 within 2 years and 35 after 2 years. For the entire cohort, post-ASCT relapse rate was much higher than NRM rate (48.1 vs 9.1% at 5-year). Median PFS and OS after ASCT was 2.7 and 5.4 years, respectively. Lymphoma was the primary cause of death after ASCT. In contrast, for patients who had achieved PFS24 (n = 220), rates of post-PFS24 relapse and NRM were similar (14.8% and 12.3% at 5-year). Median PFS and OS after achieving PFS24 was 10.0 and 11.5 years, respectively. Lymphoma related and unrelated death rates were similar after achieving PFS24 (Table). For all patients who had a post-ASCT relapse, median PRS was 0.7 years (95% CI 0.5-0.9), and late relapse ( > 2 vs ≤2 years after ASCT) was associated with better PRS (median 2.3 [1.7-4.8] vs 0.5 [0.3-0.7] years, p < 0.001). Conclusions: Post-ASCT PFS24 is an important prognostic predictor of post-ASCT outcomes in patients with RR DLBCL following frontline IC.[Table: see text]

6539 Background: The impact of insurance status on survival in diffuse large B‐cell lymphoma (DLBCL), the most common aggressive lymphoma, has not been evaluated after the implementation of the Affordable Care Act (ACA). The aim of this study is to compare overall survival (OS) in patients across insurance status groups and in the periods before and after the ACA. Methods: Adult patients with newly diagnosed DLBCL were identified from the National Cancer Database. The analysis was restricted to patients 64 years of age or younger as most patients 65 years or older are eligible for Medicare under the ACA. The 2004-2017 period was chosen to represent the immunochemotherapy era preceding and following the ACA. Logistic regression was used to explore associations between abstracted variables and insurance status groups. The Kaplan-Meier method and Cox proportional hazards model were used for survival analysis. Results: 93,692 adults (age < 64 years) with newly diagnosed DLBCL and known insurance status were identified (41.3% female, median age 54 years [range: 18 – 64], 81.8% White and 12.1% Black). 7,211 (7.7%) patients were uninsured, 64,744 (69.1%) had private insurance, 11,936 (12.7%) had Medicaid, and 9,801 (10.5%) had Medicare. When compared to insured patients (private insurance, Medicaid or Medicare), uninsured patients were more likely to have a median household outcome of < $38,000 [OR 1.93 (95% CI 1.79-2.07)], less likely to receive chemotherapy [OR 0.69 (0.64-0.77)], more likely to be male [OR 1.14 (1.07-1.21)], more likely to be non-White [OR 1.30 (1.20-1.40], and more likely to present with stage III or IV disease [OR 1.24 (1.16-1.32)]. Uninsured patients had an inferior OS [HR 1.21 (95% CI 1.15-1.27)] when compared to insured patients after adjustment for baseline comorbidity (Charlson-Deyo score ≥2), advanced stage, treatment with chemotherapy, and sociodemographic factors including sex, age, race, household income, facility type (academic/community), and location (urban/rural). With a median follow-up time of 14.8 years (95% CI 14.6-not reached), median OS was lower in uninsured patients [13.4 years (12.3-not reached) vs 14.8 years (14.7-not reached); p < 0.0001]. Despite the lack of major changes in DLBCL therapies, a diagnosis after the implementation of the ACA (in 2010 or later) was associated with a superior OS when compared with the outcomes of patients diagnosed in 2010 or earlier [HR 0.93 (95% CI 0.90-0.95)]. Similarly, five-year OS was superior in the insured group [HR 0.93 (95% CI 0.89-0.96)]. Conclusions: Uninsured patients with DLBCL and < 64 years old had inferior OS when compared with insured patients, and uninsured status emerged as an independent risk factor for inferior OS. Our data highlight the independent effect of insurance disparities - a potential indicator of variations in access to health care - on survival in DLBCL.

e13569 Background: Progress in understanding the molecular biology of DLBCL has led to development of complex molecular classifications that rely on sequencing methods. These molecular clusters are defined by activation of distinct pathways and may aid in selecting targeted therapy. In the molecular era, tissue requirements in clinical trials have increased to ensure sufficient tissue for molecular testing, potentially resulting in bias for enrollment of patients with larger excisional biopsies (EB). We examined the impact of tissue biopsy method on outcomes of DLBCL in a prospective observational study. Methods: Consecutive adult patients with DLBCL within 9 months from their initial diagnosis were enrolled into the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). Demographics, clinical variables, type of tissue biopsy (EB vs. core needle biopsy (CNB)) for initial diagnosis and initial treatment were recorded at baseline. Pts were contacted every 6 months from the date of diagnosis for first 3 years and then annually thereafter. Study objectives were event free survival (EFS) and overall survival (OS) by tissue biopsy method. Results: A total of 1061 patients with newly diagnosed DLBCL, from 2002 to 2015, were included. The table lists baseline characteristics of the cohort. 593 (56%) pts underwent EB and 468 (44%) underwent CNB for initial diagnosis. A significantly higher proportion of patients receiving CNB had performance status >=2, advanced stage, high risk disease by international prognostic index (IPI), abnormal lactate dehydrogenase. Median time from diagnosis to treatment initiation (DTI) was significantly shorter in the CNB group (13 days) than EB group (19 days). 2-year EFS (60% vs 75%, HR 0.75 (0.6-0.9), p <0.01) was significantly lower in CNB than EB group. There was a trend towards lower OS (75% vs 80%, HR: 0.8 (0.6-0.95), p =0.049) in CNB than EB group. Conclusions: Patients undergoing CNB are more likely to have higher risk disease, shorter DTI and survival compared to those undergoing EB. A need for large amount of diagnostic tissue in biomarker driven clinical trials may result in disproportional exclusion of high risk DLBCL pts who have inferior outcomes after standard treatment and could potentially benefit from novel agents, resulting in overperformance of the control arm. The need for tissue must be carefully balanced against resulting selection bias.[Table: see text]

e19527 Background: While extra nodal involvement by MCL is relatively common, involvement of the central nervous system (CNS) is a rare ( < 5% of cases) complication with limited treatment options. We report the outcomes of a large cohort of patients (pts) with CNS MCL. Methods: MCL pts with CNS involvement seen at Mayo Clinic between 1/1/1995-9/16/2020 were identified. CNS involvement was defined by histologically confirmed CNS MCL, CSF analysis demonstrating lymphoma cells, and/or neuroimaging findings compatible with CNS lymphoma. Medical records were reviewed for baseline characteristics, treatment, and outcome. Kaplan-Meier method was used for time to event analysis. Results: Out of 1,753 pts with MCL, 36 (2%) had CNS involvement by MCL. Median age at MCL diagnosis was 64 years (range 36-83) and 26 were male (72%). At MCL diagnosis, non-CNS extranodal involvement was seen in 30 pts, 24 with 1 site and 6 with ≥ 2 sites; 24 had bone marrow involvement. 11 (31%) pts had blastoid variant. Median Ki-67 was 40% (range 15-100%). MIPI score was available in 17 pts [low risk (n = 5, 29%), intermediate risk (n = 9, 53%), high risk (n = 3, 18%)]. The most common frontline regimen for MCL was R-CHOP and 14 (39%) pts underwent autologous stem cell transplant in CR1. The incidence of CNS involvement was overall similar over the study period. Median time from MCL diagnosis to CNS involvement was 25 months (m) (range 0-167). 4 (11%) pts presented with CNS involvement at initial diagnosis and 32 presented at relapse (12 isolated CNS relapse and 20 concurrent CNS and systemic relapse. Abnormal CSF was noted in 27 (87%) pts [consistent with MCL diagnosis (n = 26), atypical lymphocytes (n = 1)]. Abnormal CNS imaging was reported in 27 (75%) pts [leptomeningeal (n = 18), leptomeningeal and parenchymal (n = 5), parenchymal (n = 2), ocular (n = 2)]. First line CNS-directed therapy data was available in 33 (92%) pts. 12 (34%) received intrathecal (IT) therapy alone, 19 (54%) received systemic +/- IT therapy, 2 (6%) received radiation alone, and 2 (6%) pts received no treatment (hospice). The overall CNS response to therapy was CR in 13 (42%) pts, PR in 3 (10%), SD in 8 (26%), and PD in 7 (22%) pts. Three pts received BTK inhibitors [ibrutinib (n = 2) or acalabrutinib (n = 1)] as the first CNS-directed therapy. One patient achieved a CR with a response lasting 4 m, another patient achieved a PR with response lasting 10 m. CNS response data was not available in the remaining pts. Median follow up from CNS involvement was 72 m (95% CI: 41-NR). Median EFS for the 1 st CNS-directed therapy was 3.7 m (95% CI: 1.6-6.1). At last follow up, 30 pts were deceased. The cause of death was CNS lymphoma in 10 (33%) pts and systemic lymphoma in 9 (30%) pts. Median OS from CNS involvement was 4.7 m (95% CI: 2.3-6.7). Conclusions: CNS involvement by MCL has dismal outcomes as evident by a median OS of approximately 5 m. BTK inhibitors may have a role in treatment of this rare complication, but further prospective investigation is needed.

Abstract The utility of the chronic lymphocytic leukemia-international prognostic index (CLL-IPI) in predicting outcomes of individuals with Rai 0 stage CLL and monoclonal B-cell lymphocytosis (MBL) is unclear. We identified 969 individuals (415 MBL and 554 Rai 0 CLL; median age, 64 years; 65% men) seen at Mayo Clinic between 1 January 2001 and 1 October 2018, and ascertained time to first therapy (TTFT) and overall survival (OS). After a median follow up of 7 years, the risk of disease progression needing therapy was 2.9%/y for MBL (median, not reached) and 5%/y for Rai 0 CLL (median, 10.4 years). Among patients with low, intermediate, and high/very high-risk CLL-IPI risk groups, the estimated 5-year risk of TTFT was 13.5%, 30%, and 58%, respectively, P&lt; .0001 (c-statistic = 0.69); and the estimated 5-year OS was 96.3%, 91.5%, and 76%, respectively, P&lt; .0001 (c-statistic = 0.65). In a multivariable analysis of absolute B-cell count with individual factors of the CLL-IPI, the absolute B-cell count was associated with shorter TTFT (hazard ratio [HR] for each 10 × 109/L increase: 1.31; P&lt; .0001) and shorter OS (HR: 1.1; P = .02). The OS of the entire cohort was similar to that of the age- and sex-matched general population of Minnesota (P = .17), although Rai 0 CLL patients with high and very high-risk CLL-IPI score had significantly shorter OS (P= .01 and P= .0001, respectively). The results of this study demonstrate the ability of CLL-IPI to predict time from diagnosis to first treatment (an end point not affected by therapy) in a large cohort of patients whose only manifestation of disease is a circulating clonal lymphocyte population.

Introduction: Richter transformation (RT) refers to transformation of chronic lymphocytic leukemia (CLL) to diffuse large B-cell lymphoma (DLBCL) or other aggressive lymphomas. The incidence, clinical characteristics, and outcomes of RT with CNS involvement remain undefined. Methods: Biopsy-confirmed RT diagnosed from 4/1993 to 4/2018 was identified from the Mayo Clinic CLL database. RT cases with CNS involvement were further reviewed, with clinical characteristics, treatment and follow-up data abstracted. Overall survival (OS) was defined as time from CNS involvement to death from any cause and analyzed using the Kaplan-Meier method. Results: Among 204 CLL patients with biopsy-proven RT, 15 patients had documented CNS involvement by imaging (parenchymal n=11, ocular n=1, parenchymal and ocular n=1, leptomeningeal n=1, cranial and spinal nerve roots n=1). Biopsy confirmation of CNS involvement was available in 11 patients. Of these 15 patients, 10 had CNS involvement at initial RT diagnosis, and 5 patients developed CNS involvement at RT progression, with a median time from RT diagnosis to CNS involvement of 14.9 months (range 2.8-41.1). Prior to RT, 11 patients (73.3%) received no treatment for CLL, 3 (53.4%) received chemoimmunotherapy (CIT) only (1-3 lines), and 1 patient (6.7%) received CIT (1 line) and ibrutinib. CLL FISH results were available in 9 patients, with del(17p) in 2, trisomy 12 in 2, del(13q) in 3, and normal results in 2. One patient had TP53 mutation (FISH result unavailable). IgHV mutation status was known in 3 patients and 1 was unmutated. The median time to RT was 4.4 years (range 0-11.4). The median age at RT diagnosis was 70 years (range 59-78), and 9 (60%) were male. The histology of RT was DLBCL in all 15 patients (diagnosed by CNS biopsy in 8 and other biopsies in 7), with GCB subtype in 6 and non-GCB subtype in 3. MYC rearrangement was detected in 4 of 6 patients tested, and 2 of those also had BCL-2 rearrangement (MYC/BCL-2 double hit). Of the 10 patients with CNS involvement at initial RT diagnosis, 4 had isolated CNS involvement (confirmed by brain biopsy [n=2] or vitreous biopsy [n=2]). All 4 patients were treated with high dose (HD) methotrexate (MTX) based regimen, and 3 patients achieved complete remission (CR) and underwent autologous stem cell transplant with continued CR, while 1 patient achieved partial remission and received whole brain radiotherapy (WBRT) at disease progression. Six patients had both systemic and CNS involvement (confirmed by brain biopsy [n=2] or CSF examination [n=2] in 4; the other 2 were diagnosed by imaging). All 6 patients received CNS directed therapy (HD MTX [n=5] or WBRT [n=1]) as well as systemic therapy (R-CHOP [n=5] or HyperCVAD [n=1]), with varied short duration of disease control (Figure 1A). Of the 5 patients who developed CNS involvement at RT progression (after 1-2 lines of therapy including first-line R-CHOP), 2 had isolated CNS involvement (1 was confirmed by CSF examination and the other was by imaging only). Both were treated with HD MTX based regimen, and 1 achieved a durable remission of 2 years but eventually had CNS relapse, while the other had no response and received WBRT with limited benefit. Three patients had both systemic and CNS involvement (2 were confirmed by CSF examination and the other was by imaging only), and all 3 patients were treated with HD MTX based regimen but all had CNS disease progression within 3 months (Figure 1A). The OS after CNS involvement for all 15 RT patients was 9.4 months (95% CI 2.3-19.1). Patients with CNS involvement at initial RT diagnosis had numerically longer OS compared to patients who developed CNS involvement at RT progression (median OS 13.0 vs 4.1 months, P = 0.137; Figure 1B). Patients with isolated CNS involvement had better OS compared to patients with both CNS and systemic involvement (median OS 32.0 vs 5.3 months, P = 0.009; Figure 1C). Three of the 4 patients who only had isolated CNS involvement at the time of RT diagnosis have ongoing long term remission and survival (Figure 1A). Conclusions: In this large series of RT, approximately 1 in 14 patients had CNS involvement. Patients with isolated CNS involvement appeared to have favorable long term outcome; however, RT patients with both systemic and CNS involvement had extremely poor survival. The incidence, molecular characteristics, and optimal management of RT with CNS involvement in the novel agent era warrant future multicenter studies. Disclosures Wang: Incyte: Research Funding; Innocare: Research Funding; Novartis: Research Funding. Parikh:GlaxoSmithKline: Honoraria; Pharmacyclics: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; MorphoSys: Research Funding; TG Therapeutics: Research Funding; Merck: Research Funding; AbbVie: Honoraria, Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; Verastem Oncology: Honoraria. Kay:Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; MEI Pharma: Research Funding; Sunesis: Research Funding; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees. Witzig:AbbVie: Consultancy; MorphSys: Consultancy; Immune Design: Research Funding; Karyopharm Therapeutics: Research Funding; Incyte: Consultancy; Spectrum: Consultancy; Celgene: Consultancy, Research Funding; Acerta: Research Funding. Nowakowski:MorphoSys: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Celgene/BMS: Consultancy, Research Funding; Kite: Consultancy; Denovo: Consultancy; Kymera: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other; Curis: Consultancy; Seattle Genetics: Consultancy; Nanostrings: Research Funding. Ansell:Trillium: Research Funding; AI Therapeutics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Takeda: Research Funding; ADC Therapeutics: Research Funding; Seattle Genetics: Research Funding; Bristol Myers Squibb: Research Funding. Kenderian:MorphoSys: Research Funding; Sunesis: Research Funding; Tolero: Research Funding; BMS: Research Funding; Juno: Research Funding; Gilead: Research Funding; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding; Torque: Consultancy; Humanigen: Consultancy, Patents & Royalties, Research Funding; Lentigen: Research Funding; Mettaforge: Patents & Royalties. Ding:DTRM: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; Octapharma: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Research Funding; Abbvie: Research Funding.

Introduction: Richter's syndrome (RS) represents transformation of chronic lymphocytic leukemia (CLL) into a highly aggressive lymphoma with dismal prognosis. Transcriptomic alterations have been described in CLL but most studies focused on peripheral blood samples with minimal data on RS-involved tissue. Moreover, transcriptomic features of RS have not been well defined in the era of CLL novel therapies. In this study we investigated transcriptomic profiles of CLL/RS-involved nodal tissue using samples from a clinical trial cohort of refractory CLL and RS patients treated with Pembrolizumab (NCT02332980). Methods: Nodal samples from 9 RS and 4 CLL patients in MC1485 trial cohort were reviewed and classified as previously published (Ding et al, Blood 2017). All samples were collected prior to Pembrolizumab treatment. Targeted gene expression profiling of 789 immune-related genes were performed on FFPE nodal samples using Nanostring nCounter® Analysis System (NanoString Technologies, Seattle, WA). Differential expression analysis was performed using NanoStringDiff. Genes with 2 fold-change in expression with a false-discovery rate less than 5% were considered differentially expressed. Results: The details for the therapy history of this cohort were illustrated in Figure 1a. All patients exposed to prior ibrutinib before the tissue biopsy had developed clinical progression while receiving ibrutinib. Unsupervised hierarchical clustering using the 300 most variable genes in expression revealed two clusters: C1 and C2 (Figure 1b). C1 included 4 RS and 3 CLL treated with prior chemotherapy without prior ibrutinib, and 1 RS treated with prior ibrutinib. C2 included 1 CLL and 3 RS received prior ibrutinib, and 1 RS treated with chemotherapy. The segregation of gene expression profiles in samples was largely driven by recent exposure to ibrutinib. In C1 cluster (majority had no prior ibrutinb), RS and CLL samples were clearly separated into two subgroups (Figure 1b). In C2 cluster, CLL 8 treated with ibrutinib showed more similarity in gene expression to RS, than to other CLL samples treated with chemotherapy. In comparison of C2 to C1, we identified 71 differentially expressed genes, of which 34 genes were downregulated and 37 were upregulated in C2. Among the upregulated genes in C2 (majority had prior ibrutinib) are known immune modulating genes including LILRA6, FCGR3A, IL-10, CD163, CD14, IL-2RB (figure 1c). Downregulated genes in C2 are involved in B cell activation including CD40LG, CD22, CD79A, MS4A1 (CD20), and LTB, reflecting the expected biological effect of ibrutinib in reducing B cell activation. Among the 9 RS samples, we compared gene profiles between the two groups of RS with or without prior ibrutinib therapy. 38 downregulated genes and 10 upregulated genes were found in the 4 RS treated with ibrutinib in comparison with 5 RS treated with chemotherapy. The top upregulated genes in the ibrutinib-exposed group included PTHLH, S100A8, IGSF3, TERT, and PRKCB, while the downregulated genes in these samples included MS4A1, LTB and CD38 (figure 1d). In order to delineate the differences of RS vs CLL, we compared gene expression profiles between 5 RS samples and 3 CLL samples that were treated with only chemotherapy. RS samples showed significant upregulation of 129 genes and downregulation of 7 genes. Among the most significantly upregulated genes are multiple genes involved in monocyte and myeloid lineage regulation including TNFSF13, S100A9, FCN1, LGALS2, CD14, FCGR2A, SERPINA1, and LILRB3. Conclusion: Our study indicates that ibrutinib-resistant, RS-involved tissues are characterized by downregulation of genes in B cell activation, but with PRKCB and TERT upregulation. Furthermore, RS-involved nodal tissues display the increased expression of genes involved in myeloid/monocytic regulation in comparison with CLL-involved nodal tissues. These findings implicate that differential therapies for RS and CLL patients need to be adopted based on their prior therapy and gene expression signatures. Studies using large sample size will be needed to verify this hypothesis. Figure Disclosures Zhao: Merck: Current Employment. Blumenschein:Merck: Current Employment. Yearley:Merck: Current Employment. Wang:Novartis: Research Funding; Incyte: Research Funding; Innocare: Research Funding. Parikh:Verastem Oncology: Honoraria; GlaxoSmithKline: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; AbbVie: Honoraria, Research Funding; Merck: Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Kenderian:Sunesis: Research Funding; MorphoSys: Research Funding; Humanigen: Consultancy, Patents & Royalties, Research Funding; Gilead: Research Funding; BMS: Research Funding; Tolero: Research Funding; Lentigen: Research Funding; Juno: Research Funding; Mettaforge: Patents & Royalties; Torque: Consultancy; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding. Kay:Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; MEI Pharma: Research Funding; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Ding:DTRM: Research Funding; Astra Zeneca: Research Funding; Abbvie: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees.

Introduction: In 2017, a two-dose recombinant zoster vaccine (RZV) containing glycoprotein E (gE) and a novel adjuvant was approved to prevent herpes zoster and its complications in adults ≥50 years of age in the US. There are limited data on the immunogenicity and safety of RZV in patients with chronic lymphocytic leukemia (CLL). Methods: Between 8/15/2018 and 11/4/2019, RZV-naïve patients with CLL and monoclonal B-cell lymphocytosis (MBL) seen at Mayo Clinic, Rochester, MN were enrolled in this IRB-approved study. All participants received two doses of vaccine, at 0 and 2 months after enrollment. Cell-mediated immunity was measured by dual-color interferon γ (IFN- γ) and interleukin 2 (IL-2) FLUOROSpot in peripheral blood mononuclear cells (PBMC) after depletion of ≥50% leukemic B cells. Results were reported in spot forming cells (SFC)/106 PBMC in wells stimulated with gE overlapping peptides or varicella zoster virus (VZV) inactivated cell lysate. Response rate was defined as the proportion of participants who achieved a ≥2-fold increase in IFN- γ or IL-2 SFC/106 PBMC one month after the second dose of vaccine compared with pre-vaccination baseline levels. We also determined the geometric mean fold rise (GMFR) and geometric mean count (GMC) of SFC /106 PBMC at baseline and 90 days after the first dose of vaccine. Two cohorts were enrolled: Cohort 1 consisted of individuals with previously untreated MBL and CLL; and Cohort 2 consisted of CLL participants who were on Bruton tyrosine kinase inhibitor (BTKi) therapy. We compared the response data to historic age-and sex-matched healthy controls who received RZV. Chi-square or Fisher's exact tests measured differences in response rates and Kruskall-Wallis tested for differences in continuous variables. Among CLL participants, multivariable regression analysis was used to investigate the association between day 90 SFC and prior BTKi treatment, accounting for age at RZV, age at CLL diagnosis, sex, and day 0 SFC. Results: Sixty-one participants were enrolled. Paired samples were available for 41 participants (22 in Cohort 1 and 19 [18 ibrutinib and 1 acalabrutinib] in Cohort 2), and 68 age- and sex-matched healthy controls. Baseline characteristics of MBL/CLL participants are shown in Table 1. Compared to healthy controls, participants with MBL/CLL had a significantly lower IFN-γ VZV-specific response rate (41% vs. 63%, p=0.03) and IFN-γ gE-specific response (56% vs. 96%, p&lt;0.001); although there were no differences in IL-2 response rates to VZV (51% vs 68%, p=0.09) or gE (95% vs. 100%, p=0.14, Table 2). There were differences in GMFR between participants with MBL/CLL and controls that reached statistical significance for IFN-γ and IL-2 gE-specific responses and borderline significance for IFN-γ VZV-specific responses (Table 2). VZV-specific response rates did not significantly differ between individuals with untreated MBL/CLL and those receiving BTKi (52% vs. 28%, p=0.12 for IFN- γ; (62% vs. 39%, p=0.15 for IL-2), nor did IL-2 gE-specific responses (96% vs. 95%, p=1.0). However, untreated MBL/CLL participants had significantly higher IFN- γ gE-specific response rate compared to BTKi-treated individuals (73% vs. 37%, p=0.02, Table 2). IFN- γ and IL-2 VZV- and gE-specific SFC GMC was significantly higher at Day 90 compared to Day 0 in all vaccinees, although the magnitude of response was significantly lower in MBL/CLL participants compared to healthy controls (Table 3). Among participants with MBL/CLL, age at diagnosis, age at receipt of RZV, and sex did not predict response to vaccination after accounting for prevaccination values. No serious adverse events were noted among MBL/CLL participants while on this study. Additional analyses including determination of humoral immunogenicity and long-term follow up to ascertain risk of herpes zoster infection are ongoing at this time. Conclusion: RZV was associated with lower cell mediated immunogenicity in MBL/CLL participants compared to healthy older adults. Among individuals with CLL, BTKi treatment was associated with decreased cell mediated immunogenicity of the vaccine. Given the inferior response rates, an additional dose of RZV may be considered to boost responses and should be studied in this patient population. Disclosures Johnson: GSK: Research Funding. Ding:Abbvie: Research Funding; Astra Zeneca: Research Funding; DTRM: Research Funding; alexion: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; Octapharma: Membership on an entity's Board of Directors or advisory committees; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Membership on an entity's Board of Directors or advisory committees. Kenderian:Humanigen: Consultancy, Patents & Royalties, Research Funding; Torque: Consultancy; Novartis: Patents & Royalties, Research Funding; Kite: Research Funding; Gilead: Research Funding; Juno: Research Funding; BMS: Research Funding; Tolero: Research Funding; Mettaforge: Patents & Royalties; Lentigen: Research Funding; MorphoSys: Research Funding; Sunesis: Research Funding. Wang:Novartis: Research Funding; Incyte: Research Funding; Innocare: Research Funding. Kay:Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Abbvie: Research Funding; MEI Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding. Levin:GSK: Research Funding. Kennedy:ICW Ventures: Research Funding. Weinberg:GSK: Research Funding. Parikh:GlaxoSmithKline: Honoraria; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; TG Therapeutics: Research Funding; Merck: Research Funding; AbbVie: Honoraria, Research Funding; MorphoSys: Research Funding; Verastem Oncology: Honoraria; Pharmacyclics: Honoraria, Research Funding; Genentech: Honoraria; Ascentage Pharma: Research Funding.

Background: Clinical factors including previous history of AF, heart failure, hypertension, valvular heart disease, increased age and male gender increase the risk of AF in CLL patients (Shanafelt, Leukemia and Lymphoma 2017). Treatment with Bruton tyrosine kinase inhibitors (BTKi) such as ibrutinib has also been associated with an increased risk of AF in CLL. We evaluated the role of artificial intelligence electrocardiography (AI-ECG) in predicting ibrutinib-induced AF (and, for reference, AF unrelated to ibrutinib) in patients with CLL. Methods: We identified two cohorts of CLL patients using the Mayo Clinic CLL Database. Cohort 1 included patients evaluated within 12 months of CLL diagnosis who did not ever receive ibrutinib. Cohort 2 included patients who were treated with ibrutinib. The electrocardiographic signature of AF in sinus rhythm was detected by an AI-ECG algorithm previously developed using a convolutional neural network (Attia, Lancet 2019). The baseline AI-ECG AF score (positive defined as &gt;0.10 on a scale of 0-1 which offers best balance between sensitivity and specificity per Attia et al.) was computed based on ECGs obtained within 10 years prior to CLL diagnosis (Cohort 1) or 10 years prior to initiation of ibrutinib therapy (Cohort 2). Patients with AF at baseline, missing data, or with ECGs previously used to train the AI algorithm were excluded. Reverse Kaplan Meier diagrams were plotted for both cohorts grouped by AI-ECG positivity. Cox proportional hazards were fitted to assess the predictive ability of AI-ECG in both cohorts. Results: After screening 2,739 patients and applying exclusion criteria (126 patients had baseline AF) a total of 1,149 patients with median 4 (interquartile range [IQR] 2-9) baseline ECGs were included in the analysis (Figure 1A). Cohort 1 included 951 patients with a median follow up of 3.0 (IQR 0.6-7.0) years and positive baseline AI-ECG in 546 (57%) patients. Cohort 2 included 198 patients with a median follow up of 1.6 (IQR 0.7-3.2) years and positive baseline AI-ECG in 91 (46%) patients. In Cohort 1, the median age was 67 years (IQR 58-72), 681 (72%) of patients were men, 68% had low/intermediate risk CLL-International Prognostic Index (IPI), and 32% had high/very high-risk CLL-IPI. In Cohort 2, the median age was 69 years (IQR 62-75), 139 (70%) of patients were men, 13% had low/intermediate risk CLL-IPI, and 87% had high/very high-risk CLL-IPI. AF occurred during follow up in 164 patients (17%) in Cohort 1 and 46 patients (23%) in Cohort 2. In both Cohorts 1 and 2, a positive baseline AI-ECG significantly increased the incidence of AF during follow up (log rank &lt;0.001) (Figure 1B and C). Hazard ratios (for positive vs. negative AI-ECG) were 33.9 (95% confidence interval [CI] 15.0-76.6) for Cohort 1 and 14.8 (95% CI 5.3-41.3) for Cohort 2. Conclusion: The addition of AI to a standard 12-lead ECG obtained during normal sinus rhythm - an inexpensive and ubiquitous test - predicts the occurrence of future AF in patients with CLL. This holds true irrespective of BTKi -based therapy and has important implications for the management of CLL patients. Disclosures Ding: Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; DTRM: Research Funding; Astra Zeneca: Research Funding; Abbvie: Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees. Kenderian:BMS: Research Funding; Gilead: Research Funding; Novartis: Patents & Royalties, Research Funding; Mettaforge: Patents & Royalties; Juno: Research Funding; MorphoSys: Research Funding; Lentigen: Research Funding; Sunesis: Research Funding; Tolero: Research Funding; Kite: Research Funding; Humanigen: Consultancy, Patents & Royalties, Research Funding; Torque: Consultancy. Wang:Novartis: Research Funding; Innocare: Research Funding; Incyte: Research Funding. Kay:Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Abbvie: Research Funding; MEI Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kapoor:Cellectar: Consultancy; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Celgene: Honoraria; GlaxoSmithKline: Research Funding. Parikh:MorphoSys: Research Funding; Janssen: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Merck: Research Funding; AbbVie: Honoraria, Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; Verastem Oncology: Honoraria; GlaxoSmithKline: Honoraria; TG Therapeutics: Research Funding; Pharmacyclics: Honoraria, Research Funding.