Bock, Allison M.

Abstract Introduction: The clinical presentation of mantle cell lymphoma (MCL) is heterogeneous, ranging from indolent disease that does not require immediate treatment to rapidly progressive disease that responds poorly to aggressive immunochemotherapy. Several small retrospective studies suggested that active surveillance or delayed treatment is feasible in select patients with an indolent disease course. A shorter diagnosis-to-treatment interval (DTI) is a strong predictor for inferior survival in patients with aggressive non-Hodgkin lymphomas such as diffuse large B-cell lymphoma (DLBCL) and peripheral T-cell lymphoma (PTCL), which likely correlates with an aggressive disease biology and clinical presentation. However, the impact of DTI on survival has not been well studied in patients with MCL. In this study, we utilized the National Cancer Database to investigate the feasibility of active surveillance or delayed treatment in patients with MCL and to explore the potential impact of DTI on survival of MCL patients requiring treatment. Methods: The National Cancer Database was used to identify adult patients (≥ 18 years) with MCL diagnosed from 2004 through 2017. Patients were divided into three groups based on their time to initial treatment: early treatment [ET] (treatment started within 3 months), delayed treatment [DT] (treatment started after 3 months) and surveillance [SUR] (watch and wait without treatment). Baseline clinical characteristics were compared between the 3 groups using Chi-square test. Survival analysis was performed using the Kaplan-Meier method and log-rank test. Statistical analysis was performed using SPSS version 25. Results: A total of 27,867 patients with newly diagnosed MCL were included in this study, 995 patients (4%) in the SUR group, 21,425 patients (77%) in the ET group, and 1,052 patients (4%) in the DT group. There were no major differences in the baseline characteristics among the three groups including demographics (age, sex, ethnicity), socioeconomic factors (annual income, insurance status, place of residence), comorbidity scores, and Ann Arbor stage. Compared to patients in the SUR and DT groups, patients in the ET group were more likely to have B symptoms (ET=27% vs DT=16% vs SUR=8%, p<0.001) and were less likely to be managed at an academic center (ET=40% vs DT=53% vs SUR= 51%, p<0.001) (Table 1). The median follow-up was 38.2 months for the entire cohort. There was a significant difference in OS among the three groups, with a median OS of 107 months (95% CI = 92.7-122.7) in the SUR group, 84.9 months (95% CI = 74.2-95.7) in the DT group, and 68.9 months (95% CI = 66.8-70.9) in the ET group (p=0.001) (Figure 1A). Among patients in the DT group, a shorter DTI was associated with a trend of inferior OS, with a median OS of 82 months (95% CI = 73.2-90.8) for those with a DTI of 3-12 months and not reached (95% CI not calculable) for those with a DTI > 12 months (p=0.095) (Figure 1B). Among the ET group, a shorter DTI was associated with shorter OS, with a median OS of 53 months (95% CI = 50.2-55.8) for patients with a DTI ≤ 15 days, 71.7 months (95% CI = 67.1-76.3) for those with a DTI of 16-30 days, and 87.1 months (95% CI= 82.8-91.4) for patients with a DTI of 31-90 days (p<0.001) (Figure 1C) Conclusion: In this retrospective analysis, patients with newly diagnosed MCL who were managed with an active surveillance strategy or delayed therapy had a better survival compared to patients who underwent early therapy. These findings validate the feasibility of delayed therapy in select patients with MCL. In patients who undergo early therapy, a shorter DTI is associated with an inferior survival outcome, mirroring findings in DLBCL and PTCL. A shorter DTI is likely associated with more aggressive disease biology and clinical presentation. Figure 1 Figure 1. Disclosures Munoz: 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; Gilead/Kite Pharma, Kyowa, Bayer, Pharmacyclics/Janssen, Seattle Genetics, Acrotech/Aurobindo, Beigene, Verastem, AstraZeneca, Celgene/BMS, Genentech/Roche.: Speakers Bureau; Millennium: Research Funding; Janssen: Research Funding; Seattle Genetics: 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; Physicians' Education Resource: Honoraria; Seattle Genetics: Honoraria; Targeted Oncology: Honoraria; OncView: Honoraria; Kyowa: Honoraria. Paludo: Karyopharm: 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. Nowakowski: Nanostrings: Research Funding; Blueprint Medicines: Consultancy; TG Therapeutics: Consultancy; Kymera Therapeutics: Consultancy; Incyte: Consultancy; Zai Labolatory: Consultancy; Daiichi Sankyo: Consultancy; Bantham Pharmaceutical: Consultancy; Karyopharm Therapeutics: Consultancy; Curis: Consultancy; Selvita: Consultancy; Ryvu Therapeutics: Consultancy; Kyte Pharma: Consultancy; Genentech: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Celgene/Bristol Myers Squibb: Consultancy, Research Funding; MorphoSys: Consultancy. Wang: 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; MorphoSys: Research Funding; Genentech: Research Funding; Novartis: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; InnoCare: Research Funding.

Abstract Introduction: Mantle cell lymphoma (MCL) is an uncommon hematological malignancy with an estimated incidence of 1 per 100,000 persons per year in the United States and represents only about 5% of all non-Hodgkin lymphomas. Several studies have shown that treatment at academic centers and a higher hospital case volume are associated with improved outcomes for uncommon hematological malignancies, probably due to increased provider expertise and access to novel therapies. Treatment of MCL can be complex given the heterogenous nature of the disease and a frequent need for autologous stem cell transplantation in eligible patients. However, the impact of treatment at an academic center and facility patient volume on the survival of patients with MCL has not been well studied in large cohorts. In this study, we utilized the National Cancer Database (NCDB) to investigate the impact of treatment at an academic center and treatment facility volume on the overall survival (OS) of patients with MCL. Methods: The NCDB was used to identify adult patients (≥ 18 years) with newly diagnosed MCL from 2004 through 2017. For facility patient volume analysis, patients were divided into groups based on the average number of new MCL patients seen annually: Tercile 1 [T1] (1-3 patients/year), Tercile 2 [T2] (4-5 patients/year) and Tercile 3 [T3] (≥6 patients/year). Treating centers were divided into Academic and Non-academic using the NCDB definitions. Academic centers were defined as centers that accessions more than 500 newly diagnosed cancer cases per year, participate in postgraduate medical education in at least four program areas including internal medicine and surgery and participates in cancer-related clinical trials. The primary endpoint was overall survival (OS). Survival analysis was performed using the Kaplan-Meier method and Cox hazards proportional model. Statistical analysis was performed using SPSS version 25. Results: We identified 22,752 patients with MCL during the study period. 9,484 (42%) patients were treated at academic centers and 13,070 (57%) were treated at non-academic centers. In terms of facility patient volume 10,948 patients (48%) were in the T1 group, 4,637 (20%) were in the T2 group and 7,166 (31%) were in the T3 group. No significant differences were found in baseline demographics (age, gender, race/ethnicity, comorbidity scores), socioeconomical variables (insurance type, median income, area of residence) and disease-related factors (B-symptoms, Ann Arbor stage) between patients treated academic vs nonacademic centers, or between patients in T1 vs T2 vs T3 groups. Notably, compared to lower volume facilities, T3 facilities were more likely to be academic centers (T3: 81% vs T2: 42% vs T1: 16%, p<0.001) . After a median follow-up of 3.4 years, the median overall survival (OS) was 5.6 years for the entire cohort. The median OS was inferior for patients treated at lower volume facilities (4.1 years for T1, 5.1 years for T2 and 9.0 years for T3, p<0.001) (Figure 1A). Similarly, the median OS was shorter for patients treated at non-academic centers vs academic centers (4.3 years vs 7.5 years respectively, p<0.001) (Figure 1B). In a multivariate analysis, treatment at a lower patient volume facility (Hazard ratio [HR] Q1= 1.26 [95%CI = 1.18-1.34]) and treatment at a non-academic center (HR = 1.1, 95%CI = 1.01-1.12) were both independent prognostic factors of inferior OS, after adjusting for demographics (age, gender, ethnicity, area of residence) and socioeconomic variables (income and insurance status). Conclusion: Patients with MCL treated at academic and higher volume facilities had a higher OS compared to patients treated at non-academic and lower volume facilities.. Additional research is needed to fully understand the mechanisms behind these differences. Patients with MCL may benefit from an early referral to academic and high-volume centers. Figure 1 Figure 1. Disclosures Munoz: Merck: Research Funding; Portola: Research Funding; Genentech: Research Funding; Incyte: Research Funding; Janssen: Research Funding; Seattle Genetics: 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; Gilead/Kite Pharma, Kyowa, Bayer, Pharmacyclics/Janssen, Seattle Genetics, Acrotech/Aurobindo, Beigene, Verastem, AstraZeneca, Celgene/BMS, Genentech/Roche.: Speakers Bureau; Millennium: Research Funding; Pharmacyclics: Research Funding; Celgene: Research Funding; Physicians' Education Resource: Honoraria; Gilead/Kite Pharma: Research Funding; Kyowa: Honoraria; Bayer: Research Funding; Seattle Genetics: Honoraria; OncView: Honoraria; Targeted Oncology: Honoraria. Paludo: Karyopharm: 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. Nowakowski: Daiichi Sankyo: Consultancy; Zai Labolatory: Consultancy; TG Therapeutics: Consultancy; Blueprint Medicines: Consultancy; Nanostrings: Research Funding; MorphoSys: Consultancy; Kymera Therapeutics: Consultancy; Incyte: Consultancy; Ryvu Therapeutics: Consultancy; Kyte Pharma: Consultancy; Genentech: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Celgene/Bristol Myers Squibb: Consultancy, Research Funding; Selvita: Consultancy; Curis: Consultancy; Karyopharm Therapeutics: Consultancy; Bantham Pharmaceutical: Consultancy. Wang: Novartis: 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; Genentech: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; MorphoSys: Research Funding; InnoCare: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Introduction: VEXAS syndrome (vacuoles, E1 ubiquitin ligase, X-linked, autoinflammatory, somatic) is a newly recognized inflammatory disorder caused by somatic mutations in the UBA1 gene. Bone marrows from these patients reveal a range of morphological changes in hematopoietic precursor cells. In this study, we aim to assess the laboratory indices and morphologic spectrum of bone marrow pathology in VEXAS syndrome. Methods: We identified 16 cases of VEXAS syndrome. All cases had confirmed UBA1 mutation. We reviewed bone marrow biopsies corresponding to the date of diagnosis. This study was approved by the Mayo Clinic Institutional Review Board. Results: All patients were male with a median age of 73 years - associated autoimmune disorders included Sweet syndrome, inflammatory arthritis, relapsing polychondritis and granulomatosis with polyangiitis. 14/16 patients had anemia with median hemoglobin of 10.4 (Range: 6.7- 14.1 g/dL). 15/16 had macrocytosis with median MCV 110.4 (Range: 94.8- 123.1 /fL). 5/16 had thrombocytopenia with median platelet count 174 (Range: 20- 500 x10^9/L). 7/16 had leukopenia with median WBC 3.65 (Range: 2.4- 11.6 x10^9/ L). The ESR and CRP medians were 61.0 mm/hr and 81.5 mg/L, respectively. Karyotype was performed in 12 patients of which 11 were normal and the remaining case showed a complex karyotype. An NGS panel targeting the most frequent myeloid disorder associated gene mutations was negative in 10/15 cases. GS for myeloid mutations revealed pathogenic mutations in 5 patients, involving genes TET2 (2/5), DNMT3A (2/5), and TP53 (1/5). Conclusions: Bone marrow findings in VEXAS syndrome, in this series of 16 patients, are individually non-specific, yet when taken altogether in the overtly abnormal cases, are very suggestive when the clinical index of suspicion is high. In such scenarios, the combined clinical and bone marrow findings should prompt discussion and consideration for UBA1 mutation testing given the significant clinical implications for patient management and prognosis. Disclosures Patnaik: StemLine: Research Funding; Kura Oncology: Research Funding. Warrington: Eli Lilly: Research Funding; Kiniksa: 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.