Mwangi, Raphael

Abstract Activated B cell (ABC) type diffuse large B cell lymphoma (DLBCL), double hit lymphoma (DHL) and double expressor lymphoma (DEL) have poor outcomes to frontline R‐CHOP but impact of these molecular features on outcomes of relapsed/refractory (R/R) disease is not well‐characterized. We evaluated the association of diagnostic cell of origin (COO), double hit and double expressor status with overall survival after first relapse in DLBCL patients who were enrolled into the Molecular Epidemiology Resource (MER) cohort. COO was available from immunohistochemistry (IHC) using Hans criteria or gene expression profiling (GEP) (Nanostring) on the diagnostic FFPE biopsy. Of 373 pts with R/R DLBCL, 278 had COO by IHC: 152 were GCB, 107 were non‐GCB. One hundred and fourty had COO by GEP: 44 were ABC, 65 were GCB and 13 were unclassifiable. Nineteen out of 163 (12%) were DHL; 30 out of 135 (22%) had DEL. COO, either by IHC (2 years OS GCB: 45% [CI 95 : 38–54] vs. non‐GCB: 44% [CI 95 :36–55], p > 0.05) or GEP (2 years OS ABC: 42% [CI 95 : 29–59] vs. GCB: 40% [CI 95 : 30–54], p > 0.05), was not associated with difference in OS. DHL (2 years OS 16 [CI 95 :6–45] vs. 45% [CI 95 : 34–59], p < 0.01) and DEL (2 years OS 33% [CI 95 : 20–56], vs. 50% [CI 95 : 41–60], p < 0.05) had lower OS than non‐DHL and non‐DEL/non‐DHL counterparts, respectively. COO by IHC or GEP was not associated with OS in R/R DLBCL while DHL and DEL were adverse prognostic markers in DLBCL at first relapse.

Abstract An enhanced understanding of the molecular heterogeneity of diffuse large B-cell lymphoma (DLBCL) has opened the door to clinical trials evaluating novel agents with subtype-specific activity. It is an emerging question whether core needle biopsies (CNB) can adequately meet the increasing tissue requirements of these clinical trials. This can potentially lead to selective enrollment of patients who can undergo excisional biopsy (EB). It is also important to know whether patients who can undergo extensive diagnostic work up differ in their disease characteristics and outcomes from those who cannot. In this observational study, we describe the characteristics, outcomes, and adequacy of diagnostic tissue in patients with newly diagnosed DLBCL and primary mediastinal large B-cell lymphoma who underwent EB vs CNB. Of the 1061 patients, 532 (49.8%) underwent EB and 529 (50.1%) underwent CNB. A significantly higher proportion of patients with CNB had advanced stage disease, an international prognostic index of ≥3, and inadequate tissue for molecular analyses. Patients with CNB had significantly worse 5-year event-free survival (67.6% vs 56.9%; hazard ratio [HR], 0.76; confidence interval [CI]95, 0.6-0.9, P &lt; .001) and 5-year overall survival (76.4% vs 69.2%; HR, 0.8; CI95, 0.6-0.9, P &lt; .001). Thus, patients who underwent CNB have poor-risk features and inferior outcomes on frontline chemoimmunotherapy, are more likely to have inadequate tissue for molecular analyses, and might not meet the tissue requirements of biomarker-driven clinical trials. Thus, the increasing tissue requirements of biomarker-driven clinical trials may result in the exclusion of patients with high-risk DLBCL who need novel agents.

Abstract Low-grade B-cell lymphomas other than follicular and small lymphocytic lymphoma (LGBCL) account for 10% of all B-cell non-Hodgkin lymphomas. Despite improvements in survival outcomes for these patients, little is known about cause of death (COD) in the rituximab era. For a better understanding, we studied 822 newly diagnosed patients with marginal zone, lymphoplasmacytic, and unclassifiable low-grade B-cell lymphoma prospectively enrolled in the University of Iowa/Mayo Clinic Specialized Program of Research Excellence Molecular Epidemiology Resource from 2002 to 2015. COD was assigned based on medical record review using a standard protocol. At a median follow-up of 107 months, 219 (27%) patients had died. The incidence of lymphoma-related deaths when pooling across subtypes was lower than non–lymphoma-related deaths (10-year incidence, 8.0%; 95% confidence interval [CI]: 6.2-10.4 vs 13.6%; 95% CI: 11.2-16.6). The incidence of lymphoma-related deaths varied by subtype, ranging from 3.7% at 10 years in extranodal marginal zone lymphoma to 19.3% in lymphoplasmacytic lymphoma/Waldenström macroglobulinemia. Patients with early progression or retreatment events, defined using event-free survival at 24 months from diagnosis, had significantly higher likelihood of lymphoma-related death compared with patients without early events (10-year estimate: 19.1% vs 5.1%, respectively; P &lt; .001), whereas the rates for non–lymphoma-related death were comparable in patients with or without early events (10-year estimates: 11.0% vs 15.3%, respectively). In conclusion, the most common COD in LGBCLs in the first decade after diagnosis was for causes other than lymphoma. Progression or retreatment within the first 2 years of diagnosis was a strong predictor for risk of lymphoma-related death.

Abstract BACKGROUND: Mantle cell lymphoma (MCL) is a B-cell non-Hodgkin lymphoma with variable clinical outcomes. Commonly used risk stratification tools (Ki67 IHC, MIPI) in newly diagnosed MCL are not frequently used when selecting therapy, resulting in treatment choice being dictated by age and co-morbidities rather than disease biology. The MCL35 risk score was developed as a more reliable measure of proliferation and has been shown to be prognostic and can risk stratify younger transplant eligible MCL patients into three groups with significantly different overall survival (OS; Scott et al. 2017; Holte et al. 2018) but has not been evaluated in older transplant ineligible patients. We report results evaluating the prognostic value of the MCL35 assay in older MCL patients (≥65) treated with frontline bendamustine/rituximab (BR). METHODS: Archived tissue samples from 119 patients age ≥65 years treated with BR from collaborating Lymphoma/Leukemia Molecular Profiling Project (LLMPP) sites and the LEO/MER cohort were collected and analyzed using the MCL35 assay and stratified into three distinct risk groups (low, standard, and high risk). Association between MCL35 proliferation scores and OS were estimated by the Kaplan-Meier method and hazard ratios were calculated. Associations between Ki67, s-MIPI, p53 IHC status, morphology and OS were also evaluated. RESULTS: The MCL35 assay was run on tissue samples from 119 patients. Median patient age was 74 (range 65-93) and 69.5% were male. Ki67 was &lt;30% in 29 patients (24%) and ≥30% in 90 patients (76%). Simplified MIPI (s-MIPI) score was 0-3 in 21 patients (24%), 4-5 in 42 patients (48%) and ≥6 in 25 patients (28%). Thirty-one did not have sufficient data to calculate a s-MIPI score. MCL35 was low risk in 51 patients (43%), standard risk in 39 patients (33%) and high risk in 29 patients (24%). Eleven patients had blastic morphology, 7 had pleomorphic morphology and the remainder were classic morphology (n=56). Of 57 samples with p53 IHC staining 7 (12.3%) were positive. At a median follow up of 33.4 months, 82 patients were alive and 35 had died. Patients with high risk MCL35 score had inferior OS compared to low risk (HR 2.27, 95% CI: 1.03-5.00; p=0.042) while standard risk was not statistically significant compared to low risk (HR 0.87, 95% CI: 0.37-2.0; p=0.740)(Figure 1). Ki67 IHC using a cutoff of ≥ 30% and 10%-29% was not significantly associated with OS compared to Ki67 &lt;10% ( Ki67 ≥ 30% vs. Ki67 &lt; 10%, HR 0.87, 95% CI: 0.12-6.41; p=0.892, Ki67 ≥ 10%-29% vs. Ki67 &lt; 10%, HR 0.32, 95% CI: 0.04-2.83; p=0.303), however high s-MIPI score (≥6) (s-MIPI ≥6 vs. s-MIPI 0-3, HR 3.86, 95% CI 1.20-12.5; p=0.024) and positive p53 IHC (HR: 9.51, 3.26-27.7; p &lt;0.001) were both associated with poor OS. Eighteen cases were blastic/pleomorphic by morphology, 12 of which were in the high-risk group by MCL35, and this subset also had worse survival than classic MCL (p=0.0052). CONCLUSIONS: These results suggest high risk MCL35 score is a prognostic biomarker of poor OS in patients &gt;65 with MCL treated with BR. Conversely, Ki67 was not significantly associated with OS in these patients. Additional clinical validation using a larger sample size from the E1411 study is planned. If similar results are found, the MCL35 assay in combination with s-MIPI and p53 status may have utility in stratifying patients into risk adapted treatment arms in future prospective clinical trial designs. 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. Villa: Janssen: Honoraria; Gilead: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Seattle Genetics: Honoraria; Celgene: Honoraria; Lundbeck: Honoraria; Roche: Honoraria; NanoString Technologies: Honoraria. 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. Cohen: Janssen, Adicet, Astra Zeneca, Genentech, Aptitude Health, Cellectar, Kite/Gilead, Loxo, BeiGene, Adaptive: Consultancy; Genentech, BMS/Celgene, LAM, BioINvent, LOXO, Astra Zeneca, Novartis, M2Gen, Takeda: Research Funding. Hill: Celgene (BMS): Consultancy, Honoraria, Research Funding; Epizyme: Consultancy, Honoraria; Gentenech: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel Support, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; Incyte/Morphysis: Consultancy, Honoraria, Research Funding. Raess: Scopio Labs: Research Funding. Scott: Celgene: Consultancy; NanoString Technologies: Patents & Royalties: Patent describing measuring the proliferation signature in MCL using gene expression profiling.; BC Cancer: Patents & Royalties: Patent describing assigning DLBCL COO by gene expression profiling--licensed to NanoString Technologies. Patent describing measuring the proliferation signature in MCL using gene expression profiling. ; Rich/Genentech: Research Funding; Janssen: Consultancy, Research Funding; Incyte: Consultancy; Abbvie: Consultancy; AstraZeneca: Consultancy. Rimsza: NanoString Technologies: Other: Fee-for-service contract.

Abstract Introduction: Central nervous system (CNS) relapse is an uncommon but devastating complication occurring in about 2-10% of patients with diffuse large B-cell lymphoma (DLBCL). The CNS-IPI is a validated prognostic tool used to identify patients at high risk of CNS relapse. MYC and BCL2/BCL6 rearrangements (double-hit lymphoma- DHL) and non-GCB (NGCB) cell of origin may be at higher risk of CNS relapse. However, the ability of these molecular data to refine CNS-IPI risk prediction has not been assessed. In this study, we aimed to describe the impact of DHL and NGCB cell of origin in the incidence of CNS relapse in patients with newly diagnosed DLBCL. Methods: A retrospective review was conducted to identify patients with newly diagnosed DLBCL from 01/01/2002 - 06/30/2015 using the University of Iowa/Mayo Clinic Lymphoma Molecular Epidemiology Resource database. Patients with primary CNS lymphoma or with CNS involvement at diagnosis were excluded. All patients received chemoimmunotherapy. Clinical, biological, laboratory and radiological data were abstracted including the occurrence of CNS relapse. CNS IPI risk score categories were defined as low- (≤1) intermediate- (2-3) and high-risk (≥4) as originally described (Schmitz et al, JCO 2016). Cell of origin (COO) classification into GCB and non-GCB subtypes was performed using Hans algorithm and/or NanoString data. Characteristics between groups were compared using Kruskal-Wallis or Chi-squared test as appropriate. Survival analysis was performed using Cox proportional hazards model and the Kaplan Meier method. Statistical analysis was performed using SAS version 9.4M5 and R version 4.0.3. Results: We identified a total of 1,360 patients with newly diagnosed DLBCL. Patients had a median age of 62 years (range 18-93 years), were predominantly male (56%), had a performance status &lt;2 (84%), had stage III/IV disease (61%) and an elevated LDH (56%) at diagnosis. Fluorescent in situ hybridization data was present for 65% of patients. Among patients with available data, DHL and NGCG COO represented 2.8% and 36% of the cohort, respectively. CNS IPI high- and intermediate-risk categories were present in 12.4% and 52% of the patients, respectively. R-CHOP was the most common upfront chemotherapy (n=980, 72%). The median follow-up for the entire cohort was 84.9 months (IQR: 58.9-120.9). Overall, 50 patients (3.6%) had a CNS relapse during the study period. Lymphoma relapsed in the CNS in 3.0% (95% CI:2.1-4.4), 4.7% (95% CI: 3.4-6.3) and 4.9% (95% CI: 3.7-6.6)% of patients with CNS-IPI score of intermediate/high risk at 1, 3 and 5 years following the diagnosis of DLBCL. In patients with low risk CNS-IPI, 1.1% (95% CI: 0.4-2.5), 1.7% (95% CI: 0.9-3.4) and 1.7% (95% CI: 0.9-3.4) had a CNS relapse at 1, 3 and 5 years following DLBC diagnosis. Patients with CNS relapse were more likely to have elevated LDH (76% vs 56%, p=0.008), advanced stage (78% vs 61%, p=0.01), adrenal involvement (8% vs 2.4%, p=0.014) and have a CNS IPI intermediate risk (68% vs 51%), and high risk (16% vs 12.3%, p=0.014) at the time of initial diagnosis compared to patients without CNS relapse. Patients with CNS relapse had similar rates of DHL (4% vs 2.7%, p=0.17) and NGCB cell of origin (42% vs 36.2%, p=0.52) compared to patients without CNS relapse. In the multivariable analysis, the strongest predictors for CNS relapse were CNS IPI high risk (Hazard Ratio [HR]= 3.6, 95%CI= 1.4-9.7) and CNS IPI intermediate risk (HR= 3.15, 95%CI= 1.46-6.81). DHL and NGCB cell of origin were not associated with a significantly higher risk of CNS relapse (HR= 1.79, [95%CI=0.42-7.59] and HR= 1.26, [95%CI=0.62-2.57], respectively). Conclusion: CNS relapse was an uncommon occurrence in patients with DLBCL who were treated with chemoimmunotherapy. CNS IPI intermediate- and high-risk scores remain the strongest predictors of CNS relapse in patients with DLBCL after adjusting to biological high-risk variables including DHL and NGCB cell of origin. Larger studies are required to validate our findings due to the low incidence of CNS relapse in our cohort. Figure 1 Figure 1. Disclosures Farooq: Kite, a Gilead Company: Honoraria. Maurer: Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Genentech: Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Nanostring: 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: Tess Therapeutics: Other: Data Monitoring Committee; Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Novak: Celgene/BMS: 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&lt;0.01, Table 1). At a median follow-up time (of living patients) of 113 months, 93 patients had died. The 2-year OS was 13.9% for patients with primary progression, which was significantly worse compared to that of patients with EOT PR (2-year OS 41.7%) or early relapse (2-year OS 44%), (P=0.001)(Figure 1A). In patients with early relapse, the 2-year OS was not significantly different among those who relapsed with 3 months, between 3-6 months, or between 6-12 months (Figure 1B). Conclusion Our data suggest that broadly defined primary refractory DLBCL has heterogenous survival outcomes. DLBCL patients with primary progressive disease represent an ultra-high risk group that has particularly poor survival outcomes with current standard salvage regimens. Novel therapies such CAR T-cell therapy or targeted agents should be studied in this patient population. In contrast, patient who only achieve PR at EOT and those who relapse within 1 year of achieving CR had better OS. A fraction of these patients may still have chemosensitive disease and benefit from salvage chemotherapy and ASCT. The survival difference in the two groups also has important implications for clinical trial design. The definition of primary refractory DLBCL in clinical trials should be carefully and clearly defined. When evaluating novel therapies in single arm trials, the benchmark for efficacy (i.e., historical outcomes) may differ according to the population included in the trial (e.g., time to refractory status). Figure 1 Figure 1. Disclosures Maurer: BMS: Research Funding; Genentech: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Bennani: Vividion: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Verastem: Other: Advisory Board; Purdue Pharma: Other: Advisory Board; Kymera: Other: Advisory Board. Cerhan: Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding; Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding. Witzig: Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding; Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees. Habermann: Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Tess Therapeutics: Other: Data Monitoring Committee; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Wang: Genentech: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; InnoCare: Research Funding; MorphoSys: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding. Nowakowski: Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene, NanoString Technologies, MorphoSys: Research Funding.

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

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

The World Health Organization Classification of Tumours of Haematopoietic and Lymphoid Tissues (WHO 2017) included updated criteria for diagnosis and classification of post-transplant lymphoproliferative disorders (PTLDs). This study evaluated the clinicopathologic spectrum using WHO 2017 criteria and adult PTLD patients’ outcomes over 30 years between 1987 and 2017 at Mayo Clinic (Rochester, MN). Patients were retrospectively reviewed for clinical features, outcomes, and diagnostic pathology material and classified based on WHO 2017 criteria. A total of 227 patients were diagnosed with PTLD, with a median time from transplant to PTLD of 45 months. PTLD occurred >1 year after transplant in 149 (66%) patients. Monomorphic PTLD was the most common subtype (173, 76%), with diffuse large B cell lymphoma as the commonest morphology (n = 137). Epstein-Barr virus was positive in 61% of total cases and 90% of PTLD that developed within 1 year from transplant. The median event-free survival (EFS) and overall survival for the entire cohort were 21 months (95% confidence interval [CI]: 9–35) and 82 months (95% CI: 39–115), respectively. The EFS or overall survival was not impacted by Epstein-Barr virus status but differed based on WHO subtypes and year of diagnosis. Management changed over time with increased use of rituximab or chemotherapy + immunosuppression reduction as initial therapy. When compared to the matched general population and de novo diffuse large B cell lymphoma, patients not achieving EFS 24 status (no progression/treatment or death within 24 mo of diagnosis) had a worse standardized mortality ratio 16.75 (95% CI: 13.91–20) versus SMR 1.72 (95% CI: 1.26–2.28) in those who achieved EFS24. Cause of death was mostly attributed to non-lymphoma–related causes in those achieving EFS 24.