Inwards, David J.

AbstractOur phase III trial reported that autograft‐absolute lymphocyte count (A‐ALC) improved survival post‐autologous peripheral blood hematopoietic stem cell transplantation (APBHSCT) for a short‐term follow‐up of 2 years. We evaluated retrospectively in our phase III trial patients that the A‐ALC still confers survival benefit with a longer follow‐up. With a median follow‐up of 127.6 months, patients infused with an A‐ALC ≥ 0.5 × 109 cells/kg experienced better overall survival (HR = 0.392, 95% confidence of interval [CI]: 0.224–0.687, p < 0.001) and progression‐free survival (HR = 0.413, 95% CI: 0.253–0.677), p < 0.0004). This study supports that A‐ALC provides long‐term survival benefit post APBHSCT.

Abstract Background: Event-free survival at 24 months (EFS24) is an important clinical endpoint in newly diagnosed diffuse large B-cell lymphoma and follicular lymphoma, and patients who achieve EFS24 with frontline immunochemotherapy have minimal loss of lifetime compared to age- and sex-matched general population. However, the prognostic role of EFS24 in mantle cell lymphoma (MCL) has not been well studied, possibly due to the perception of continued relapse pattern and poor survival outcome of MCL historically. A recent study from our group demonstrated evolving frontline therapy pattern from 2002-2009 ("Era 1") to 2010-2015 ("Era 2") which was associated with improved EFS and overall survival (OS) in Era 2. In the current study, we sought to explore the prognostic role of EFS24 in the two eras. Methods: Patients with newly diagnosed MCL from 9/2002 through 6/2015 were identified from Molecular Epidemiology Resource (MER), a prospective cohort study of the University of Iowa/Mayo Clinic Lymphoma SPORE. OS was defined as time from diagnosis (or the EFS24 defining event where applicable) to death from any cause and was analyzed using the Kaplan-Meier method. Expected OS accounting for age and sex was generated in R by using the general US population as the reference group. Observed versus expected OS was summarized by using standardized mortality ratio (SMR) and 95% confidence intervals (CI) of observed to expected deaths. Cumulative incidence of lymphoma-specific death was analyzed using Gray's test, with deaths from all other causes treated as competing events. Results: A total of 343 patients were included, 175 from Era 1 (median follow-up 13.0 years) and 168 from Era 2 (median follow-up 6.9 years). Age, sex and simplified MIPI score were similar between the 2 groups. Patients diagnosed in Era 2 had better OS, with a 5-year OS of 68.4% vs 59.2% (simplified MIPI-adjusted hazard ratio 0.68, 95% CI 0.50-0.93). Patients diagnosed in both eras had inferior OS compared to the general population, with an SMR of 3.26 (95% CI 2.70-3.89, P&lt;0.001) in Era 1 and 2.63 (95% CI 2.03-3.36, P&lt;0.001) in Era 2. Patients diagnosed in Era 1 who achieved EFS24 (n=98) still had inferior OS compared to the general population, with an SMR of 2.23 (95% CI 1.67-2.92, P&lt;0.001) (Figure 1A). In contrast, for patients diagnosed in Era 2 who achieved EFS24 (n=99), no evidence of OS difference was found compared to the general population, with an SMR of 1.31 (95% CI 0.78-2.07, P=0.31) (Figure 1B). The primary cause of death after diagnosis was lymphoma-related for patients diagnosed in both eras. The 5-year rate of lymphoma-related death was 28.8% in Era 1 and 20.5% in Era 2. In patients who were diagnosed in Era 1 and achieved EFS24, the primary cause of death after achieving EFS24 remained to be lymphoma-related, with a 5-year rate of 19.8% compared to 6.2% for lymphoma-unrelated causes (Figure 1C). In contrast, in patients who were diagnosed in Era 2 and achieved EFS24, the rate of lymphoma-related death was no longer higher than that of lymphoma-unrelated death, with a 5-year rate of 2.1% vs 5.5%, respectively (Figure 1D). In a sensitivity analysis restricted to only patients who received standard frontline immunochemotherapy, similar results were obtained. For example, in patients who achieved EFS24, the SMR compared to the general population was 2.89 (95% CI 2.00-4.04, P&lt;0.001) in Era 1 and 0.89 (95% CI 0.43-1.64, P=0.82) in Era 2. The 5-year rates of deaths due to lymphoma-related vs lymphoma-unrelated causes were 20.7% vs 6.2% in Era 1 and 1.3% vs 4.9% in Era 2. Conclusions: MCL survival outcome has improved for patients first diagnosed in the more recent era (2010-2015, compared to 2002-2009), likely due to improved frontline therapy as well as better salvage treatments (such as lenalidomide and BTK inhibitors). In the more recent treatment era, patients who achieved EFS24 had survival approaching the age- and sex-matched general population. In addition, these patients had a low risk of dying from lymphoma and were more likely to die from other causes. Longer follow-up (e.g., in Era 2) and external validation in other series are necessary to confirm the prognostic role of EFS24. With more efficacious salvage treatment options and likely continued improvement of OS in MCL, EFS24 may become an important clinical endpoint in frontline therapy of MCL. Figure 1 Figure 1. Disclosures 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; Novartis: Research Funding; InnoCare: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; MorphoSys: Research Funding. Maurer: Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Nanostring: Research Funding. Link: Novartis, Jannsen: Research Funding; Genentech/Roche: Consultancy, Research Funding; MEI: Consultancy. Farooq: Kite, a Gilead Company: Honoraria. Paludo: Karyopharm: 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; Tess Therapeutics: 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. Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding; Genentech: 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.

Abstract Background: While extranodal involvement by mantle cell lymphoma (MCL) is relatively common, involvement of the central nervous system (CNS) is rare (&lt;5% of cases), with limited treatment options. We report the outcomes of 36 patients (pts) with CNS involvement compared to 72 matched control MCL pts without CNS involvement. Methods: MCL pts with CNS involvement seen at Mayo Clinic between 1/1995-9/2020 were identified using the Mayo Data Explorer tool. CNS involvement was defined by tissue biopsy confirmed CNS MCL, CSF analysis demonstrating lymphoma cells, and/or neuroimaging findings compatible with CNS involvement. A 2:1 control group of MCL pts without CNS involvement, matched by age (+/- 2 years) and year of diagnosis (+/- 1 year), was selected among all MCL cases. Medical records were reviewed for baseline characteristics, treatment modalities, and outcomes. Kaplan-Meier method was used for time to event analysis. Wilcoxon test was used to compare continuous variables and Chi square test was used for categorical variables. Results: Out of 1,753 pts with MCL, 36 (2%) had evidence of CNS involvement, including 4 pts with CNS involvement at initial MCL diagnosis. Baseline characteristics of pts with CNS involvement (CNS MCL group) and those without CNS involvement (control group) are shown in Table 1. At MCL diagnosis, non-CNS extranodal involvement was seen in 30 (83%) pts in the CNS MCL group (24 pts with 1 site and 6 pts with ≥ 2 sites), with bone marrow being the most common extranodal site of involvement (n=24, 67%). For the control group, 54 (75%) pts had extranodal involvement (44 pts with 1 site and 10 pts with ≥ 2 sites), and bone marrow was also the most common extranodal site of involvement (n=50, 69%). Notably, advanced stage disease (stage 3-4) was more commonly seen in the CNS MCL group (n=32, 97%) than in the control group (n=59, 83%) (p=0.04) at MCL diagnosis. Blastoid variant was present in a higher proportion of pts in the CNS MCL group (n=11, 31%) compared to the control group (n=8, 11%) (p=0.02). The CNS MCL group also presented with a higher median serum LDH at diagnosis (239 U/L [range 153-1901] vs. 187 U/L [range 124-588], p=0.02), and higher Ki-67 (40% [range 15-100] vs. 30% [range 10-90], p=0.04) compared to the control group. The most common frontline treatment regimen was anthracycline-based therapies (i.e. R-CHOP, Nordic regimen, R-hyperCVAD) for both groups (58% in CNS MCL group and 56% in control group). 14 (39%) pts in the CNS MCL group underwent autologous stem cell transplant in CR1 vs. 31 pts (43%) in the control group. Similar use of rituximab maintenance was seen in both groups (31% in CNS MCL group and 25% in control group). Median total lines of therapy from initial MCL diagnosis was 3 (range 1-9) in CNS MCL group and 2 (range 1-9) in the control group. The median follow-up from MCL diagnosis was 134 months (95% CI:119-163) for the entire cohort. Median OS from MCL diagnosis was 50.3 months (95% CI: 20.9-71.1) for the CNS MCL group compared to 97.1 months (95% CI: 82.6-192.7; p=&lt;0.001) for the control group (Figure 1). Median time from MCL diagnosis to CNS involvement was 25 months (range 0-167). Median OS from CNS involvement was 4.7 months (95% CI: 2.3-6.7). At last follow up, 31 (86%) pts were deceased from the CNS MCL group, compared to 38 (52%) pts in the control group. For the CNS MCL group, the causes of death were CNS lymphoma in 10 (32%) pts, systemic lymphoma in 9 (29%) pts, treatment-related complication in 7 (23%) pts, and other/unknown in 5 (16%) pts. For the control group, the causes of death were systemic lymphoma in 15 (39%) pts, treatment-related in 2 (5%) pts, and other/unknown in 21 (55%) pts. Conclusion: In pts with MCL, CNS involvement is associated with worse outcomes as evident by a shorter median OS from initial MCL diagnosis (50 months vs. 97 months). Involvement of the CNS by lymphoma is an important contributor for the shorter OS as suggested by the median OS of only 5 months from CNS involvement. Advanced stage, blastoid variant, elevated LDH, and elevated Ki67 at MCL diagnosis were features more commonly seen in the CNS MCL cohort. Validation of risk factors at initial MCL diagnosis associated with CNS involvement and exploring the role of CNS prophylaxis are important topics for further investigation. Figure 1 Figure 1. Disclosures Paludo: Karyopharm: Research Funding. Wang: Novartis: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; MorphoSys: Research Funding; InnoCare: Research Funding; 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; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding. 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. 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. 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. Habermann: Seagen: Other: Data Monitoring Committee; Tess Therapeutics: 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.

Abstract Backgrounds: Autologous stem cell transplant (ASCT) has been the standard treatment approach for patients with relapsed or high-risk lymphoma for several decades. Despite the improvement in supportive care, age has remained one of the critical factors that determines transplant eligibility and outcomes. Herein, we explored the transplant-related outcomes of patients with lymphoma aged 70 years or older at our institution and compared to those with younger ages. Methods: In this retrospective single center study, we include all patients with diagnosis of lymphoma who underwent ASCT between January 2000 and February 2021 at Mayo Clinic, Rochester, Minnesota. In addition to data obtained from the transplant database, we abstracted data from electronic medical record. We described relevant clinical characteristics and transplant associated outcomes including engraftment, transplant related mortality, relapse incidence, and survival outcomes. We compared the key transplant related outcomes with patients at the younger age group between 65 and 70 years old. Results: A total of 196 patients with lymphoma aged 70 years or older underwent ASCT between January 2000 and February 2021. The median age of patients at the time of ASCT was 72.4 (70.0-78.7) years with 24 patients (12.2%) being older than 75 years old. Of 196 patients, 76 (38.8%) had Charlson comorbidity index of 3 or higher and 10 (5.1%) had performance status of 2 or higher at the time of ASCT. Table 1 summarizes the relevant baseline clinical characteristics of 196 patients in this cohort including the comparison with younger patients (age 65-70 years old, n=296). The most common transplant indication in this cohort was relapsed diffuse large B cell lymphoma. The majority of patients (91.3%) received peripheral blood graft with a median CD34+ cell dose of 5.14x10 6 cells/kg which was significantly lower than younger patients (P=0.01). The rate of neutrophil and platelet engraftment was 99.0% and 98.8% with corresponding median time to engraftment of 13 days for both cell lineages. The 30- and 100-day non-relapse mortality (NRM) of the entire cohort was 1.5% (95%CI 0-3.2%) and 4.6% (95%CI 1.6-7.5%) not statistically different between 70-75 years old and 75 years or older cohorts. With the median follow-up duration of 48 months, the 2-year event free survival (EFS) and overall survival (OS) was 55.9% (95%CI 49.2-63.5%) and 67.4% (95%CI 61.0-74.5%), respectively. Patients from the 70 years old or older cohort had similar EFS but inferior OS compared to the 65-70 years old cohort. However, there was no difference in EFS and OS between 70-75 and &gt;75 years old cohorts. There was overall an improved trend of 30-day NRM, 2-year EFS and 2-year OS over the 3 different transplant periods (Figures). Although not statistically significant, patients who underwent ASCT between 2000 and 2006 had a trend towards higher 30-day NRM compared to patients who were transplanted at later time points (7.3% vs 0%, P=0.06). The major causes of death included progressive lymphoma, infection, and conditioning regimen related organ toxicities. Conclusion: Outcomes of ASCT in older patients with lymphoma have improved over time with an excellent 30-day NRM (0%) in the past recent years. The major cause of treatment failure after ASCT was progressive disease. With appropriate patient selection, ASCT in older patients is feasible and provides acceptable outcomes comparable to the patients from younger age group. Figure 1 Figure 1. Disclosures Paludo: Karyopharm: Research Funding. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding.

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&lt;0.001) and were less likely to be managed at an academic center (ET=40% vs DT=53% vs SUR= 51%, p&lt;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 &gt; 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&lt;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: Novel genetic classifications of diffuse large B-cell lymphoma (DLBCL) highlight the molecular complexity beyond cell of origin and provide new therapeutic implications. Next generation trials may incorporate novel agents for different genetic subtypes based on the pathogenesis mechanisms. For example, with the LymphGen classification, the MCD, BN2, ST2, and EZB subtypes are predicted to be susceptive to PI3K/mTOR targeting (Wright 2020). However, PI3K inhibitors have not been tested in the frontline, although data on the mTOR inhibitor everolimus were encouraging (Alliance 1085). We launched a phase 1/1b trial (NCT04323956) to investigate the feasibility of combining a novel PI3K inhibitor parsaclisib with standard R-CHOP immunochemotherapy and to seek an efficacy signal. Methods: Adult patients with newly diagnosed DLBCL were eligible if any of the following was present: 1) non-GCB subtype per the Hans algorithm; 2) expression of either Myc (≥40%) or Bcl2 (≥50%) by immunohistochemistry; or 3) MYC rearrangement by FISH. High grade B-cell lymphoma with MYC and BCL2 and/or BCL6 rearrangements, regardless of morphology, was also eligible. All patients received parsaclisib plus R-CHOP. Phase 1 followed a 3+3 design and the primary endpoint was maximum tolerated dose (MTD) of parsaclisib. Dose levels tested were level 1 (20 mg QD, d1-10; starting level) and level 2 (20 mg QD, d1-14). MTD was defined as the dose level below the lowest dose that induced dose limiting toxicity (DLT) in at least one-third of patients. The primary endpoint in phase 1b is complete response (CR) rate by PET. Results: From July 2020 to June 2021, 15 patients were enrolled, 9 in phase 1 and 6 in phase 1b. The median age at diagnosis was 56 years (range 20-79), and 7 (47%) were female. One patient (7%) had ECOG PS ≥2, 7 (47%) had elevated LDH, 7 (47%) had &gt;1 extranodal site, 13 (87%) had stage III/IV, and 7 (47%) had high-intermediate or high risk International Prognostic Index. Pathology was DLBCL in 13 patients (2 with concurrent follicular lymphoma) and high grade B-cell lymphoma with MYC and BCL2 and/or BCL6 rearrangements in 2 patients. Four (27%) had non-GCB subtype, 7 (47%) had Myc or Bcl2 single expression, 8 (53%) had Myc/Bcl2 double expression, and 5 (33%) had MYC rearrangement (2 with concurrent BCL2 and/or BCL6 rearrangements). In phase 1, 3 patients were enrolled at dose level 1 and 6 patients were enrolled at dose level 2. No DLT was observed. Therefore, MTD was not reached, and dose level 2 was selected for phase 1b dose expansion. Six patients were enrolled in phase 1b to date. At the data cutoff date of 7/22/2021, 8 patients completed all 6 cycles of treatment, 1 competed 5 cycles, 3 completed 3 cycles, 2 completed 2 cycles, and 1 completed 1 cycle. Treatment-related adverse events (AE) are summarized in Table 1. The most common hematological AE included lymphopenia (60%), anemia (53%), neutropenia (53%), and thrombocytopenia (27%), and the most common non-hematological AE included nausea (67%), alopecia (40%), constipation (33%), fatigue (33%), dyspepsia (20%), and peripheral sensory neuropathy (20%). The most common grade 3 or 4 AE included lymphopenia (47%), neutropenia (33%), and anemia (13%). One 80-year-old female required parsaclisib dose reduction in cycle 3 and subsequent parsaclisib discontinuation as well as cyclophosphamide and doxorubicin dose reductions due to febrile neutropenia (no source of infection was identified). No other patients required dose reductions. The median follow-up was 3.7 months (range 0.8-10.7). Thirteen patients were evaluable for interim response by PET. The objective response rate was 92%, with 8 (62%) CR and 4 (31%) partial response (PR). One (8%) patient progressed before cycle 2 following a transient clinical response (shrinking palpable mass). Among those who achieved an objective response at interim, 7 patients were evaluable for end of treatment response and all 7 maintained a response, with 6 (86%) CR and 1 (14%) PR. Conclusions: Parsaclisib and R-CHOP combination therapy was generally well tolerated, with no DLT observed in phase 1 and no major safety concerns in both phase 1 and the ongoing phase 1b expansion. The preliminary efficacy signal of objective response appears encouraging in a small cohort of high risk patients. Parsaclisib plus R-CHOP can be an experimental arm for future frontline DLBCL trials investigating genetic subtype-driven novel therapies. Figure 1 Figure 1. Disclosures Wang: Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; InnoCare: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Genentech: Research Funding; MorphoSys: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. King: Celgene/BMS: Research Funding. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Tun: Gossamer Bio, Acrotech: Consultancy; Mundipharma, Celgene, BMS, Acrotech, TG therapeutics, Curis, DTRM: 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: 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. OffLabel Disclosure: Parsaclisib is an investigational agent used in this clinical trial.

Abstract Introduction: Novel therapeutic agents such as immune checkpoint inhibitor (ICI) and brentuximab vedotin (BV) are active in classic Hodgkin lymphoma (cHL), including in patients that relapse after autologous stem cell transplant (ASCT). However, optimal management strategy is unclear for patients with relapsed or refractory (RR) cHL post-ASCT. The aim of the study is to determine the impact of novel agents relative to conventional therapy and allogeneic stem cell transplant (allo-SCT) on survival outcomes of patients with cHL who relapsed after ASCT. Methods: Patients with RR cHL who underwent ASCT between 06/1993 and 10/2017 at 3 Mayo Clinic sites were included. Clinical characteristics, treatment information, and outcome data were abstracted. For patients who relapsed after ASCT, the post-relapse progression free survival (PFS) and overall survival (OS) were analyzed using the Kaplan-Meier method and Cox proportional hazards models. Statistical analyses were done in JMP v15.2.1 and EZR v1.54. Results: A total of 332 patients with RR cHL who underwent salvage therapy and ASCT were identified. After a median post-ASCT follow-up of 8.6 years (range 6.8-9.7), 136 (41%) patients had a relapse or disease progression after ASCT. Patient characteristics of the 136 cases are summarized in the Table. The median age at post-ASCT relapse was 34 years (range 20-73), and 77 (57%) were male. 59 (43%) relapsed within 6 months and 77 (57%) relapsed after 6 months following ASCT. 59 (45%) had an extranodal site involvement at relapse. 14 (10%) had therapy with ICI or BV as salvage therapy prior to ASCT or maintenance therapy post-ASCT. The median post-relapse PFS and OS was 0.8 (95% CI 0.6-1.1) and 3.2 years (95% CI 2.2-5.5) years, respectively. Compared to patients who relapse after 6 months, patients who relapsed within 6 months of ASCT had worse post-relapse PFS (median 0.5 [0.3-0.7] vs 1.3 [0.9-1.9] years, p=0.0003) and OS (median 1.3 [0.5-2.2] vs 6.4 [3.7-10.4] years, p=0.0003). Extranodal site involvement at relapse was not associated with post-relapse PFS (median 0.7 [0.5-1.2] vs 0.9 [0.6-1.3] years, p=0.28) but was associated with worse post-relapse OS (median 2.7 [1.5-4.2] vs 6.4 [2.6-NA] years, p=0.006). Prior therapy with ICI or BV was not associated with post-relapse PFS (median 0.6 [0.3-NA] vs 0.8 [0.6-1.1] year, p=0.8) and OS (median NR [1.0-NA] vs 3.2 [2.2-5.5] years, p=0.5). After post-ASCT relapse, the median lines of subsequent therapy were 2 (range 1-12). For first post-ASCT salvage therapy, novel agents (ICI or BV), compared to other therapies, were associated with superior post-relapse PFS (median 1.7 [0.7-3.6] vs 0.7 [0.5-1.0] years, p=0.004) and OS (median 7.6 [4.7-NA] vs 3.2 [2.2-5.6], p=0.02). Allo-SCT following first post-ASCT relapse (n=9) was not associated with improvement in post-relapse PFS (median 2.2 years [0.3-NA] vs 0.8 [0.6-1.1] years, p=0.1) or OS (median NR [0.5-NA] vs 5.1 [3.2-7.3] years, p=0.7). Patients who received ICI or BV at any point post-ASCT relapse had significantly better post-relapse OS (median 7.6 [4.3-16.7] vs 2.2 [1.4-3.7] years, p=0.004) compared to those who never received any novel agent (Figure 1A). In contrast, allo-SCT at any point post-ASCT relapse (n=27) did not improve post-relapse OS (median 5.6 [2.7-NA] vs 4.7 [2.7-7.3] years, p=0.3) (Figure 1B). In multivariate Cox regression models adjusted for age and sex, exposure to ICI and/or BV was associated with superior post-relapse OS (HR 0.5, 95% CI 0.3-0.8, p=0.007); however, allo-SCT was not associated with improvement in post-relapse OS (HR 0.8, 95% CI 0.4-1.5, p=0.5). Conclusions: Patients relapsing within 6 months of ASCT and those with extranodal involvement at relapse had inferior OS after post-ASCT relapse. Prior therapy with novel agents did not impact post-relapse survival outcomes. In the setting of post-ASCT relapse, novel therapeutic agents significantly improved survival outcomes while allo-SCT did not. Future multicenter studies are needed to explore the role of novel agents and allo-SCT in patients with RR cHL post-ASCT relapse. Figure 1 Figure 1. Disclosures Wang: Eli Lilly: Membership on an entity's Board of Directors or advisory committees; InnoCare: Research Funding; 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; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Paludo: Karyopharm: Research Funding. Tun: Gossamer Bio, Acrotech: Consultancy; Mundipharma, Celgene, BMS, Acrotech, TG therapeutics, Curis, DTRM: Research Funding. Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding. Habermann: Tess Therapeutics: Other: Data Monitoring Committee; Morphosys: Other: Scientific Advisory Board; Incyte: Other: Scientific Advisory Board; Seagen: Other: Data Monitoring Committee; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. 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, 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. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: 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&lt;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&lt;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&lt;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 Background Primary bone diffuse large B cell lymphoma (DLBCL) is a variant of extranodal non-Hodgkin lymphoma (NHL) that is relatively rare, accounting for 3-15% of extranodal NHL and less than 1% of all NHL. Patients often present with pain and swelling or pathologic fracture of the affected area of the skeleton, and B symptoms are often less prevalent. Many cases are limited stage at presentation. Patients are usually treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) or similar induction therapy. Based on older studies showing improved outcomes associated with the addition of radiation (many completed prior to the rituximab era), patients often still receive combined-modality therapy today. However, it remains unknown whether consolidative radiation therapy (RT) confers additional benefit following rituximab-based chemoimmunotherapy (CIT) induction. We sought to address this question in a multicenter retrospective study. Methods We conducted a retrospective analysis of outcomes in a modern cohort of patients who underwent treatment for primary bone DLBCL using chemotherapy regimens in the rituximab era either with or without consolidative RT. Data was collected from 13 academic medical centers in the U.S., with patients treated between 2005 and 2019. Patients were identified using each institution's hematologic malignancy registries. Analysis was limited to patients with primary bone DLBCL, with stage I-II disease (primary site +/- locoregional lymph nodes) that could be encompassed in a radiation field. Patients who received CIT alone or CIT followed by RT were included. Treatment selection was at the treating physician's discretion. Electronic medical records were reviewed for: demographics, chemotherapy regimens, radiation treatments, and PET scan data. Local IRB approval was obtained at sites. All data was distributed in a de-identified fashion. The primary outcomes were overall survival (OS), and relapse-free survival (RFS). Secondary outcomes included: response after induction CIT induction and the need for additional therapies. Chi-square test analysis was used to compare categorical variables and the Wilcoxon rank-sum test was used for continuous and ordinal measures. Survival curves were estimated using the Kaplan-Meier method and compared between groups via the log-rank test. Multi-variable analysis (MVA) for OS and RFS was performed using RT vs no RT, PET status post CIT (negative vs positive) and rituximab in induction (Y/N) as variables. Results A total of 127 patients were included: 91 who received CIT and radiation (RT group), and 36 who received CIT alone (no RT group). The median age of patients at diagnosis in the RT group and no RT group was 58.5 and 57.0, respectively. For CIT, the majority of patients received R-CHOP (84%). Despite focusing on 2005-2019, a small percentage of patients (5 - 14%) in each group (RT and no RT) did not receive rituximab with their induction therapy. The OS at 10 years was 74.5% in the RT group and 86.5% in the no RT group (p = 0.29). The RFS at 10 years was 70.9% in the RT group and 78.2% in the no RT group (p = 0.85). Among the 91 patients who received RT, 67 (77.0%) received a dose of 36 Gy or higher. There was no difference in OS (p = 0.63) or RFS (p = 0.90) in patients who received &gt; 36 Gy vs &lt; 36 Gy of radiation. On MVA for OS, RT was not associated with improved OS, although rituximab as part of induction was (p = 0.048). On MVA for RFS, neither RT nor rituximab were associated with improved RFS. For rituximab the trend was in the direction of rituximab benefit (p = 0.11). Conclusion Our results demonstrate that, in the rituximab era, patients with limited stage primary bone DLBCL have excellent outcomes overall. In this study, neither RFS or OS appeared to be improved with the addition of consolidative RT. Rituximab, however, was associated with improved OS on MVA. Outcomes do not appear to differ based on the dose of RT (&gt; 36 Gy vs &lt; 36 Gy). Our data suggests that RT may have less benefit for primary bone DLBCL in the rituximab era, although it is possible that a subset of patients may benefit from consolidative radiation therapy. A larger data set would likely be needed to evaluate this. We plan to present data regarding PET responses at the meeting. Figure 1 Figure 1. Disclosures Lunning: Acrotech: Consultancy; AstraZeneca: Consultancy; Myeloid Therapeutics: Consultancy; Janssen: Consultancy; Morphosys: Consultancy; Novartis: Consultancy; Karyopharm: Consultancy; Kyowa Kirin: Consultancy; Verastem: Consultancy; Kite, a Gilead Company: Consultancy; Celgene, a Bristol Myers Squibb Co.: Consultancy; Spectrum: Consultancy; Daiichi-Sankyo: Consultancy; Beigene: Consultancy; Legend: Consultancy; ADC Therapeutics: Consultancy; TG Therapeutics: Consultancy; AbbVie: Consultancy. Cashen: Secura Bio, ADC Therapeutics: Consultancy. Bartlett: Autolus: Research Funding; Bristol Myers Squibb: Research Funding; Celgene: Research Funding; Forty Seven: Research Funding; Genentech: Research Funding; Janssen: Research Funding; Kite, a Gilead Company: Research Funding; Merck: Research Funding; Millennium: Research Funding; Pharmacyclics: Research Funding; Seagen: Consultancy, Research Funding; Roche/Genentech: Consultancy; ADC Therapeutics: Consultancy, Research Funding. Caimi: XaTek: Patents & Royalties: Royalties from patents (wife); Amgen Therapeutics.: Consultancy; ADC Theraputics: Consultancy, Research Funding; Genentech: Research Funding; TG Therapeutics: Honoraria; Seattle Genetics: Consultancy; Verastem: Consultancy; Kite Pharmaceuticals: Consultancy. Rodgers: MJH Lifesciences: Consultancy. Barr: Morphosys: Consultancy; Gilead: Consultancy; Genentech: Consultancy; TG Therapeutics: Consultancy; Janssen: Consultancy; Beigene: Consultancy; Bristol Meyers Squibb: Consultancy; Seattle Genetics: Consultancy; AstraZeneca: Consultancy; Abbvie/Pharmacyclics: Consultancy. Epperla: Verastem: Speakers Bureau; Beigene: Speakers Bureau; Karyopharm: Other: Ad Board; Genzyme: Honoraria. Hill: AstraZenica: Consultancy, Honoraria; Celgene (BMS): Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel Support, Research Funding; Pfizer: Consultancy, Honoraria; Gentenech: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Epizyme: Consultancy, Honoraria; Incyte/Morphysis: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding. Karmali: BMS/Celgene/Juno: Consultancy, Research Funding; Epizyme: Consultancy; Karyopharm: Consultancy; Janssen/Pharmacyclics: Consultancy; Morphosys: Consultancy, Speakers Bureau; AstraZeneca: Speakers Bureau; BeiGene: Consultancy, Speakers Bureau; EUSA: Consultancy; Takeda: Research Funding; Genentech: Consultancy; Roche: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding, Speakers Bureau. Portell: Acerta/AstraZeneca: Research Funding; Xencor: Research Funding; Abbvie: Research Funding; Aptitude Health: Honoraria; Morphosys: Honoraria; Targeted Oncology: Honoraria; SeaGen: Research Funding; BeiGene: Honoraria, Research Funding; Merck: Honoraria, Research Funding; Pharmacyclics: Honoraria; Kite: Honoraria, Research Funding; TG Therapeutics: Honoraria, Research Funding; Genentech: Research Funding; VelosBio: Research Funding. Fenske: Pharmacyclics: Consultancy; AstraZeneca: Speakers Bureau; Servier Pharmaceuticals: Consultancy; MorphoSys: Consultancy; Adaptive Biotechnologies: Consultancy; KaryoPharm: Consultancy; CSL Therapeutics: Consultancy; TG Therapeutics: Consultancy, Speakers Bureau; Bristol-Myers Squibb: Speakers Bureau; Sanofi: Speakers Bureau; Seattle Genetics: Speakers Bureau; Biogen: Consultancy; ADC Therapeutics: Consultancy; Kite (Gilead): Speakers Bureau; Beigene: Consultancy; AbbVie: Consultancy.

Abstract The autograft absolute lymphocyte count (A-ALC) ≥ 0.5 x 10 9 cells/kg is a survival prognostic factor for lymphoma patients undergoing autologous peripheral blood hematopoietic stem cell transplantation (APBHSCT). However, the A-ALC ≥ 0.5 x 10 9 cells/kg has not been tested as prognostic factor against double hit/triple hit lymphomas (DHL/THL). Thus, we set up to investigate if A-ALC ≥ 0.5 x 10 9 cells/kg is a prognostic factor for overall survival (OS) and progression-free survival (PFS) for DHL/THL post-APBHSCT. From January 2012 until December 2020, we identified 77 DHL/THL patients treated with APBHSCT. All patients required to have the diagnosis of DHL/THL by FISH for rearrangements of MYC, BCL2, and BCL6. Of the 77 patients, 62 patients were classified as DHL and 15 patients as THL. Of the DHL, 82 % (52/68) had the MYC/BCL2 and 16% (10/62) the MYC/BCL6 rearrangements. Dividing the cohort into two groups (A-ALC ≥ 0.5 x 10 9 cells/kg and A-ALC &lt; 0.5 x 10 9 cells/kg), both groups were balanced in regard to de novo versus transformed histology (p = 0.3), cell of origin (p = 0.6), DHL and THL (p = 0.6), MYC/BCL2; MYC/BCL6; and MYC/BCL2/BCL6 rearrangements (p = 0.6), first line chemotherapy (p = 0.2), salvage chemotherapy (p = 0.5), disease status prior to APBHSCT (CR1, CR, and PR) (p = 0.07), stem cell mobilization (Plerixafor versus not) (p = 0.6), and infusion of CD34 count (p = 0.2). With a median follow-up of 20.4 months (range, 0.4-94.5 months) for the entire cohort and with a median follow-up of 33.5 months (range, 3.5-94.5 months) for the patients that remained alive, DHL/THL patients infused with A-ALC ≥ 0.5 x 10 9 cells/kg experienced superior OS (HR = 0.251, 95%CI 0.117-0.539, P &lt; 0.0004) and PFS (HR = 0.347, 95%CI 0.160-0.753, P &lt; 0.007). The 5-year OS rates for the A-ALC ≥ 0.5 x10 9 cells/kg group was 73% (95% confidence interval [CI], 52%-87%) and for the A-ALC &lt; 0.5 x10 9 cells/kg group was 18% (95% CI, 7%-39%) (Figure 1A). The 5-year PFS rates for the A-ALC ≥ 0.5 x10 9 cells/kg group was 73% (95% CI, 59%-85%) and for the A-ALC &lt; 0.5 x10 9 cells/kg group was 13% (95% CI, 5%-33%) (Figure 1B). Multivariate analysis showed that A-ALC was an independent predictor for OS (HR =0.178, 95%CI 0.052-0.614, p &lt;0.005) and PFS (HR = 0.400, 95%CI 0.189-0.850, p &lt;0.02). Our study showed that A-ALC is a prognostic factor for survival in DHL/THL patients undergoing APBHSCT. Our current practice for all lymphoma patients is not only to collect enough stem cell for hematologic engraftment, but also A-ALC ≥ 0.5 x 10 9 cells/kg to improve clinical outcomes post-APBHSCT. Figure 1 Figure 1. Disclosures Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Paludo: Karyopharm: Research Funding.