Cerhan, James R.

Purpose The Mayo Clinic Biobank was established to provide a large group of patients from which comparison groups (ie, controls) could be selected for case–control studies, to create a prospective cohort with sufficient power for common outcomes and to support electronic health record (EHR) studies. Participants A total of 56 862 participants enrolled (21% response rate) into the Mayo Clinic Biobank from Rochester, Minnesota (77%, n=43 836), Jacksonville, Florida (18%, n=10 368) and La Crosse, Wisconsin (5%, n=2658). Participants were all Mayo Clinic patients, 18 years of age or older and US residents. Findings to date Overall, 43% of participants were 65 years of age or older and female participants were more frequent (59%) than males at all sites. Most participants resided in the Upper Midwest regions of the USA (Minnesota, Iowa, Illinois or Wisconsin), Florida or Georgia. Self-reported race among Biobank participants was 90% white. Here we provide examples of the types of studies that have successfully utilised the resource, including (1) investigations of the population itself, (2) provision of controls for case–control studies, (3) genotype-driven research, (4) EHR-based research and (5) prospective recruitment to other studies. Over 270 projects have been approved to date to access Biobank data and/or samples; over 200 000 sample aliquots have been approved for distribution. Future plans The data and samples in the Mayo Clinic Biobank can be used for various types of epidemiological and clinical studies, especially in the setting of case–control studies for which the Biobank samples serve as control samples. We are planning cohort studies with additional follow-up and acquisition of genetic information on a large scale.

Abstract Background Anthracyclines are one of the most effective chemotherapeutic agents but can lead to a decline in cardiac function. Two-dimensional (2D) speckle tracking echocardiography derived strain can predict cancer therapeutics-related cardiac dysfunction (CTRCD). However, little is known about the role of three-dimensional (3D) strain imaging in this setting. Purpose To evaluate different methods of Left Ventricular Ejection Fraction (LVEF) and strain, and to identify the best strain parameter for the prediction of CTRCD in this group of patients during treatment with anthracycline based chemotherapy. Methods Patients with Hodgkin's or non-Hodgkin's lymphoma receiving anthracycline based chemotherapy were enrolled. 2D-and 3D echocardiography was performed at 3 time points: baseline, at the completion of chemotherapy and at 1 year. 2D- and 3D LVEF (2D Modified Quinones, M-mode, 2D Biplane, 3D Philips, 3D GE and 3D TomTec), peak systolic left and right ventricular longitudinal, radial and circumferential strain and strain rate were measured. CTRCD was defined as a decrease in LVEF >10% to an absolute value of <53%. Lin's Concordance Correlation Coefficient (CCC) was calculated to compare LVEF methods. ANOVA, uni and multivariate analysis was performed. Results A total of 130 patients (79 males, mean age 57±16 years) were enrolled; 104 non-Hodgkin.3D Philips and GE (CCC 0.88 [0.84, 0.92]), 3D Philips and biplane (CCC 0.84 [0.79, 0.89]), 3D Philips and Modified Quinones (CCC 0.86 [0.82, 091]) as well as 3D Philips and M-mode (CCC 0.77 [0.70, 0.85]) showed strong correlation for LVEF. 15 patients (12%) developed CTRCD. Mean cumulative anthracycline dose was 263±65 mg/m2. 2D and 3D global longitudinal and circumferential peak systolic strain, 2D global longitudinal systolic and early diastolic strain rate, 2D global early diastolic strain rate, 2D right ventricular longitudinal peak systolic strain and systolic strain rate, 2D global radial peak systolic strain and systolic strain rate measured at the completion of chemotherapy were independent predictors of the development of CTRCD at 1 year post-chemotherapy. The strongest predictors of CTRCD were 3D global longitudinal and circumferential strain either individually (area under the curve, 0.90 and 0.95 respectively) or combined (area under the curve, 0.95) at the completion of chemotherapy; a cutoff value of <-18% in 3D global longitudinal strain had a sensitivity of 82% and specificity of 99%, while for 3D global circumferential peak systolic strain of <-24% had a sensitivity of 82% and specificity of 95%. Conclusions To our knowledge this is the first prospective trial that shows that 3D EF correlates well with other EF methods and 3D strain predicts cardiac toxicity in this group of patients with a very good sensitivity and specificity. Acknowledgement/Funding Department of Cardiovascular Medicine-Mayo Clinic Rochester MN

Abstract Background Disease characteristics, treatment patterns, and outcomes of follicular lymphoma (FL) patients (pts) aged >80 years (yrs) are infrequently reported. Further, the original Follicular Lymphoma International Prognostic Index (FLIPI) has not been formally studied in pts aged >80 yrs. Also, whether FLIPI is associated with overall survival (OS) in pts aged >80 yrs is unknown. Patients/Methods We used the National LymphoCare Study—a Genentech-sponsored, prospective, multicenter registry of FL pts across the United States without study-specific treatment—to comprehensively analyze FL pts aged >80 yrs. Using Pearson chi-squared tests, associations of age groups with disease characteristics and overall response rate (ORR) were examined. Median progression-free survival (PFS) and OS by treatment regimen were estimated using the Kaplan-Meier method. Cox proportional hazards regression that were adjusted for baseline disease factors were used to assess treatment differences in PFS, lymphoma-related mortality (LRM, which includes both disease and treatment-related deaths), and OS, as well as the significance of age by treatment interactions. FLIPI and a prognostic model that was constructed based on the findings were used to predict outcomes. Results Of 2649 evaluable pts, 209 (8%) were aged >80 yrs. Compared with pts aged ≤60, pts aged >80 yrs were more likely to be Caucasian, to have worse performance status, to have lower hemoglobin (Hgb) value (<12 g/dL), to have less advanced stage, and were less likely to be treated at academic institutions. When treated, pts aged >80 yrs had lower ORR compared with younger pts and were less likely to receive rituximab + chemotherapy (P <.001) or anthracyclines (P <.001). Use of maintenance rituximab was not significantly different between pt groups when rituximab induction was given (61% for pts aged ≤60, 38% for pts aged >80, P=.11), but it was more frequent in pts aged >80 yrs when rituximab + chemotherapy induction was administered (44% for pts aged ≤60, 59% for pts aged >80, P=.04). After adjusting for maintenance use, sex, and baseline factors, age significantly differentiated PFS impact of observation, rituximab monotherapy, and rituximab + chemotherapy (P=.01). No treatment regimen provided superior PFS or OS in pts aged >80 yrs. With a median follow-up of 6.5 yrs for all pts (4.3 yrs for pts aged >80 yrs), 5-year OS was 59% and 92%for patients aged >80 and ≤60 yrs, respectively. OS in pts aged >80 yrs varied based on FLIPI score (log-rank test, P=.01; Figure 1). Interestingly, the percentage of deaths that were disease-related was 40% in pts aged >80 yrs, which was comparable to the percentage in pts aged ≤60 yrs of 48%. Cox modeling showed that lower Hgb, B symptoms, and male sex predicted worse OS (P<.01) but not PFS in pts aged >80 yrs. Recognizing that males have inferior OS compared with females in the general population, we constructed a prognostic model composed only of B symptoms and Hgb level <12 (low risk=no factors; high risk=1 or more factors; P<.0001; Figure 2). FLIPI and the proposed prognostic model significantly differentiated both OS and LRM (Table 1). Conclusions In the largest, prospectively published study of FL pts aged >80 yrs, OS, PFS, ORR, and treatment selection varied compared with younger pts. Surprisingly, the proportion of deaths attributed to lymphoma in these older FL pts was 40%. FLIPI was associated with outcome in pts aged >80 yrs and so was a proposed prognostic model comprising lower Hgb and B symptoms. Independent validation of this model is required, and additional prospective studies that are designed for the oldest old are warranted. Disclosures: Nabhan: Genentech Inc.: Advisory Board Other, Honoraria. Byrtek:Genentech, a member of the Roche group: Employment, Equity Ownership; Roche: Equity Ownership, stock options, stock options Other. Dawson:Genentech: Employment; Roche: Equity Ownership. Link:Genentech: Consultancy; Millenium: Consultancy; Pharmacyclics: Consultancy; Spectrum: Consultancy; Genentech: Research Funding; Millenium: Research Funding; Pharacyclics: Research Funding. Zelenetz:GSK: Consultancy; Celgene: Consultancy; Cephalon: Consultancy; Gilead: Consultancy; Seattle Genetics: Consultancy; Sanofi-Aventis: Consultancy; Genentech: Research Funding; GSK: Research Funding; Roche: Research Funding; Cancer Genetics: Scientific Advisor Other. Cerhan:Genentech: Scientific Advisory Board of the National LymphoCare Study Other. Flowers:Abbott, Celgene, Millennium/Takeda, Sanofi, Spectrum, Janssen: Research Funding; Celgene, Genentech Bio-oncology: Consultancy.

Abstract Background: We previously demonstrated that putative clinical epidemiologic exposures associated with leukemia risk are prevalent among AML patients, and some are associated with unique cytogenetic risk group and with clinical phenotype (Finn, Cancer Epidemiol, 2015). Herein, we studied genome-wide DNA methylation in a cohort of AML patients to evaluate the association of individual hyper- and hypo-methylated CpG sites with epidemiologic exposures and overall survival. Methods: The Mayo Clinic AML Epidemiology Cohort is a highly annotated retrospective case series of 295 consecutive patients (pts) with AML diagnosed and treated at Mayo Clinic Florida and Arizona, with central cytogenetics performed in all cases. The prevalence of clinical epidemiologic exposures, past medical and family history as well as medication use and lifestyle was systematically obtained. After IRB approval, we interrogated the cytogenetic database and successfully obtained leukemia DNA from available remnant diagnostic cytogenetic cell pellets in a cohort of 148 AML patients in the Mayo epidemiology case series and performed an assessment of genome-wide DNA methylation using the Infinium HumanMethylation450K BeadChip. Samples were processed using the R Bioconductor package 'minfi' using Subset Within Array Quantile Normalization (PMID: 22703947). Individual CpGs that did not reach a detection p-value of <0.05 were filtered out. An internal control was included on each array to control for significant batch effects. To determine differential methylation status of 473,864 individual CpG sites (after exclusion of 11,648 that did not pass detection p-value QC), CpG sites with low interpatient variability, a standard deviation <0.05 of methylation values, and an interquartile range <0.05 of methylation values and X/Y chromosome probes were excluded from analysis. Epidemiologic and important clinical variables occurring in at least 10 pts or previously-identified as of unique interest but in fewer than 10 pts were evaluated, including sex, BMI, performance status and comorbidities, tobacco and alcohol use, family history of hematologic malignancy, medications of interest, history of toxin exposure, and history of immunosuppression and/or solid organ transplant or of secondary and therapy-related AML (t-AML). Associations of differential hypo or hypermethylation at 281,259 CpG sites with epidemiologic exposures/clinical variables were evaluated using Spearman's test of correlation (continuous or ordinal exposures), a Wilcoxon rank sum test (dichotomous exposures), or a Kruskal-Wallis rank sum test (multi-category exposures). A Bonferroni correction was applied for multiple testing, after which p <1.8 x 10-7 was considered as significant. To reduce the likelihood of false-negative findings, we additionally considered p <5 x 10-6 as indicating suggestive evidence of an association. CpG sites and associated gene and function was determined using Illumina manifest file & www.ncbi.nlm.nih.gov/gene. Results: Statistically significant associations (p <1.8 x 10-7) with individual epidemiologic and clinical exposures were identified for 109 unique CpG sites, corresponding to differential methylation in the genes listed in Table. Specifically, obesity (predominantly hypomethylation), specific cytogenetic lesions and risk group, and gender were highly significantly associated with unique CpG methylation status, but not smoking, toxin exposure, family history, comorbidity or performance status, secondary or t-AML, immunosuppression, medication use, of family history in the analysis. A further 353 unique CpG sites had defined suggestive associations (ongoing analysis). We also identified 8 additional CpG sites where differential methylation was associated with overall survival (p <5 x 10-6, Table). Conclusion: Obesity, cytogenetic lesions, and sex are associated with differential methylation of unique CpG sites at AML diagnosis, using stringent univariate statistical criteria. Significant CpG sites were identified in genes previously linked to AML biology and prognosis (DOCK6, HOXB3, MIR10A, FOXN3/CHES1, GPX1, MYST2/KAT7, PTPRD), but some represent novel findings in AML. These preliminary results suggest an association of some AML risk factors and clinical variables with unique gene methylation and will undergo validation in a prospective AML epidemiology dataset. Disclosures Cerhan: Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding; Celgene: Research Funding. Foran:Agios: Research Funding; Xencor, Inc.: Research Funding.

Abstract Background: Bendamustine and rituximab (BR) is a commonly chosen frontline treatment for grade 1-2 (G 1-2) follicular lymphoma (FL). This regimen resulted in significantly longer progression-free survival (PFS) and less toxicity compared to R-CHOP in the STiL trial [Rummel et al., 2013] and similar results were observed when comparing BR vs. R-CHOP/R-CVP in the confirmatory BRIGHT trial [Flinn et al., 2014, updated ASCO 2017]. Importantly, patients (pts) with grade 3A (G 3A) FL were excluded from these studies, yet the conclusions are often extrapolated to the treatment of G 3A pts. Notably, G 3A pts were included in the GALLIUM trial which used both bendamustine as well as CHOP backbones. Several retrospective studies of FL pts treated with frontline R-CHOP have demonstrated equivalent or improved overall survival (OS) for G 3A relative to G 1-2 FL (Koch et al., 2016, Mustafa et al., 2017, Yuan et al., 2017, Maeshima et al., 2013). Early disease progression after diagnosis and treatment with frontline R-CHOP has been identified as a strong predictor of poor OS in FL pts [Casulo et al. 2015], but has not been assessed in pts treated with frontline BR. We retrospectively evaluated outcomes of a large cohort of FL pts treated with frontline BR and stratified the results based on histologic grade and early vs. late progression. Methods: We reviewed medical records of adult (age >18) pts with FL treated with frontline BR at 18 US cancer centers. There was no central pathology review; each academic institution confirmed the diagnosis and grade of FL. Pts with unknown grade, grade 3B, or cutaneous FL were excluded. Baseline characteristics between grades were evaluated with the Chi-Square test for categorical variables and the Mann-Whitney U for continuous variables. Outcomes were calculated from time of initiation of BR. Patients were grouped according to whether or not they had progression of disease within 24 months of BR initiation (POD24). OS and PFS were estimated using the Kaplan-Meier method and compared using the log-rank test. Results: 687 pts were included (616 G 1-2, 71 G 3A). Median age at diagnosis was 60 years (range 21-94) with 53% men. The median time from diagnosis to treatment with BR was 1 month (range 0-139). The median duration of follow up for the entire cohort was 39 months. Characteristics including age, gender, ethnicity, ECOG, stage, LDH, and FLIPI are shown in the Table, and did not significantly differ between G 1-2 and G 3A pts. Rates of complete response (CR) and partial response (PR) to BR were similar between G 1-2 and G 3A (72%/22% vs. 66%/21%, respectively, p=0.114) but progressive disease (PD) was higher in G 3A pts (11.9%) relative to G 1-2 (4.8%, p=0.025). As shown in the Figure (A and B), 3-year PFS and OS was significantly longer for G 1-2 vs. G 3A pts (75% vs. 65%, log rank p= 0.035 and 90% vs. 86%, log rank p=0.007, respectively). Seventy-six (12.3%) of the 616 G 1-2 pts and 13 (18.3%) of the 71 G 3A pts experienced POD24 (p=0.19). For pts with both G 1-2 and G 3A FL, POD24 was associated with inferior OS (3-year OS 95% vs. 57% for G 1-2 pts, log rank p<0.0001 and 3-year OS 93% vs. 37% for G 3A pts, log rank p<0.0001) compared to patients without POD24. Conclusions: G 3A FL pts have an inferior OS and are significantly more likely to have PD to frontline BR compared to G 1-2, which differs from the published experience with R-CHOP. Similar to outcomes after frontline treatment with R-CHOP, POD24 after frontline BR for FL is associated with very poor OS. Future studies are needed to address optimal frontline management of pts with G3A as well as for pts with any grade FL with POD24 after frontline BR. Disclosures Nastoupil: Novartis: Honoraria; Genentech: Honoraria, Research Funding; Gilead: Honoraria; Celgene: Honoraria, Research Funding; TG Therappeutics: Research Funding; Karus: Research Funding; Merck: Honoraria, Research Funding; Spectrum: Honoraria; Janssen: Research Funding; Juno: Honoraria. Cerhan:Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding; Nanostring: Research Funding. Maurer:Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Research Funding. Smith:Genentech: Research Funding; Incyte Corporation: Research Funding; Portola Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding; Merck Sharp and Dohme Corp.: Consultancy, Research Funding; Acerta Pharma BV: Research Funding; Seattle Genetics: Research Funding. Lossos:Affimed: Research Funding. Portell:TG therapeutics: Research Funding; Amgen: Consultancy; Kite: Research Funding; AbbVie: Research Funding; BeiGene: Research Funding; Acerta: Research Funding; Genentech/Roche: Consultancy, Research Funding; Infinity: Research Funding. Calzada:Seattle Genetics: Research Funding. Cohen:Bristol-Myers Squibb: Research Funding; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioInvent: Consultancy; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Research Funding; BioInvent: Consultancy. Ghosh:Spectrum: Consultancy; SGN: Consultancy, Research Funding, Speakers Bureau; Pharmacyclics, an Abbvie Company: Consultancy, Research Funding, Speakers Bureau; TG Therapeutics: Honoraria, Research Funding; Celgene: Consultancy; Juno: Consultancy, Research Funding; Abbvie: Consultancy, Speakers Bureau; Genentech: Research Funding; F. Hoffman-La Roche Ltd: Research Funding; PCYC: Consultancy, Research Funding, Speakers Bureau; Gilead: Consultancy, Speakers Bureau; Forty seven Inc: Research Funding. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Merck, Takeda, Celgene, Seattle Genetics, Bayer: Research Funding. Caimi:Kite Pharma: Other: Advisory Board Participation; Genentech: Other: Advisory Board PArticipation, Research Funding; Celgene: Speakers Bureau; Kite Pharma: Other: Advisory Board Participation. Danilov:Gilead Sciences: Consultancy, Research Funding; Aptose Biosciences: Research Funding; Bayer Oncology: Consultancy, Research Funding; Astra Zeneca: Consultancy; Genentech: Consultancy, Research Funding; Takeda Oncology: Research Funding; TG Therapeutics: Consultancy; Verastem: Consultancy, Research Funding. Martin:AstraZeneca: Consultancy; Seattle Genetics: Consultancy; Janssen: Consultancy; Kite: Consultancy; Gilead: Consultancy; Bayer: Consultancy. Kamdar:Seattle Genetics: Speakers Bureau; Genentech: Consultancy. Kahl:AstraZeneca: Consultancy; Acerta: Consultancy; Juno: Consultancy; CTI: Consultancy; Celgene: Consultancy; Gilead: Consultancy; Seattle Genetics: Consultancy; Abbvie: Consultancy; Genentech: Consultancy; ADC Therapeutics: Consultancy. Hill:Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract Backgroud. The treatment landscape of mantle cell lymphoma (MCL) has significantly changed in last decades. Improvement in diagnosis and understanding of disease biology has been coupled with emergence of new therapeutic options, including targeted agents. While MCL outcome data comes primarily from clinical trials (CT), the impact of therapeutic advances on pattern of care (POC) and outcome in MCL in the general population is not well characterized. This study sought to characterize changes in pattern of care and outcomes of patients with MCL in a prospective observational series in the rituximab era. Methods. The study included consenting adult patients with newly diagnosed MCL that were prospectively enrolled into the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE) Molecular Epidemiology Resource, from 09/01/2002 to 06/30/2015. Demographic, clinical and prognostic factors were abstracted, and all patients were actively followed for re-treatment, relapse and death. Since bendamustine-rituximab (BR) regimen starting to be used in 2010, we defined patients enrolled from 09/01/2002 to 12/31/2009 as era 1 and those enrolled 01/01/2010 to 06/30/2015 as era 2. Baseline characteristics and outcomes, evaluated in terms of event free survival (EFS), overall survival (OS) and cause of death, were analyzed and compared between the two eras identified. Results. 348 patients with newly diagnosed MCL were enrolled. Five patients had no available data for front-line treatment and were excluded. The analysis was thus conducted on 343 patients: 169 patients were diagnosed in era 1 with a median follow-up of 131.2 months vs. 174 in era 2 with a median follow-up of 58.9 months. Baseline clinical characteristics and MIPI score were similar across the two eras ( Table 1). Frontline induction treatment was significantly different in the two eras. BR use was 0 vs 49 (28.2% ), R-CHOP/CHOP like regimen in 89 (52.7%) vs 45 (25.9%), high-dose cytarabine (HiDAC)-based therapy in 1 (0.6%) vs 28 (16.1%), intensified regimens (HyperCVAD) in 16 (9.5%) vs 8 (4.5%), other regimens (including R-cladribine, R-fludarabine-mitoxantrone, rituximab monotherapy) in 35 (20.7%) vs 13 (7.5%) patients in era 1 vs era 2 respectively. Non-systemic treatment (observation, surgery or radiation only) was performed in 25 (14.8%) vs 31 (17.8%), while 9 (8%) vs 12 (7.7%) patients were enrolled in clinical trials, in era 1 vs era 2 respectively. Autologous stem cell transplantation (ASCT) as consolidation of first line treatment or use of Rituximab maintenance was not different between Era 1 and Era 2. Among the entire cohort of 343 MCL patients, 3y-EFS and 3y-OS were 51.9% (95% IC 46.7-57.6) and 73.5 (95% CI 68.8-78.4), respectively (Figure 1). 3y-EFS was 45.9% (95% CI 39.0-54.1%) vs 58.4 (95% CI, 51.2-66.6%) in Era 1 vs Era 2 (HR 0.69 (0.51-0.92), p=0.006), 3y-OS was 70.9% (95% CI, 63.4-78.1%) vs 76.1% (95% CI, 69.7-83.1%) in Era 1 vs Era 2 (HR 0.87 (0.61-1.24), p=0.26), respectively (Figure 1). In a univariate analysis, high risk simplified MIPI was prognostic of lower EFS and OS in both the era groups. Conclusion. The BR regimen entered front line therapy of MCL resulting in decline of R-CHOP use in the MER. While rates of ASCT remain similar over the two eras, high dose cytarabine usage in induction therapy has increased. While POC in MCL continue to evolve, the introduction of bendamustine and high-dose citarabine based regimens resulted in an improvement in EFS but not OS in this observational cohort-based analysis. Findings in this study are important for design and planning of future clinical trials incorporating novel agents in induction therapy of MCL. Figure 1. Figure 1. Disclosures Cohen: Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioInvent: Consultancy; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Bristol-Myers Squibb: Research Funding; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Research Funding; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioInvent: Consultancy; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cerhan:Celgene: Research Funding; Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding.

Abstract Introduction Primary testicular lymphoma (PTL) and testicular involvement of systemic lymphoma (secondary testicular lymphoma, STL) are uncommon. Most testicular lymphomas are aggressive B-cell lymphomas and portend a high risk of extranodal relapse, including CNS relapse. As such, when testicular lymphoma is identified, the management strategy is often changed to include CNS prophylaxis. It is, therefore, essential to evaluate testicular involvement in diagnosis and staging. F-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) is a standard imaging modality to stage aggressive lymphoma. Physiologic testicular FDG activity can be challenging to distinguish from involvement by lymphoma given a wide range of normal. An imaging threshold for testicular PET uptake would be clinically relevant and would help guide management. We compare testicular FDG avidity in testicular lymphoma with physiologic testicular FDG avidity. Methods Records of patients (pts) diagnosed with PTL or STL from 2002-2018 enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE Molecular Epidemiology Resource were reviewed, yielding 36 pts with testicular lymphoma. Physiologic testicular avidity by FDG PET/CT was determined from analysis of 70 randomly selected patients who received FDG PET/CT from 2013-2018 prior to treatment for non-lymphoma indications including pulmonary nodule, lung carcinoma, head & neck squamous cell carcinoma, gastrointestinal carcinomas, and metastatic melanoma, without known hematologic malignancy, testicular pathology, or history of testicular infection/surgery by medical chart review. Imaging parameters compared in this analysis were SUVmax and SUVmean. All FDG PET/CT exams were reviewed centrally by a nuclear medicine radiologist and a radiology resident. Results Of the 36 pts with testicular lymphoma, 19 had an orchiectomy prior to FDG PET/CT and 7 pts did not have a staging FDG PET/CT scan. Of the 10 pts with intact testes at the time of staging FDG PET/CT, 1 pt with low-grade lymphoma was excluded. 9 pts with aggressive lymphomas were included in this analysis: 7 pts with diffuse large B cell lymphoma (DLBCL), and 1 pt each with Burkitt lymphoma and peripheral T-cell lymphoma, not otherwise specified. Testicular lymphoma was diagnosed by orchiectomy in 3 pts, and by percutaneous biopsy in 3 pts. 3 pts did not have tissue sampling of testes or scrotal contents, but had an overtly FDG-avid testicle highly suggestive of lymphomatous involvement. These 3 pts had biopsy-proven lymphoma in parotid, bone marrow, and stomach, respectively, with mean testicular SUVmax 6.8 among the 3 pts. The median age in this analysis cohort was 62 years (range 35-88). Of the 7 analyzed DLBCL pts, 6 were non-germinal center B-cell, and 1 was germinal center B-cell. The 70 control pts had a median age of 55 years (range 18-90). In known testicular lymphoma cases and control pts, SUVmax and SUVmean were assessed from the most FDG-avid testicle. Median SUVmax for the testicular lymphoma cases was 13.3 (range 5.5-29.9), compared to a median of 3.8 (range 2.1-5.5) for controls (Wilcoxon p <0.0001). Median SUVmean for testicular lymphoma was 9.2 (range 3.3-18.6), compared to a median of 3.1 (range 1.8-4.8) for controls (Wilcoxon p <0.0001) (Figure). Based on this dataset, an SUVmax cutoff of 5.0 has a sensitivity of 100% (95% CI 66.3-100) and a specificity of 98.6% (98% CI 92.3-99.9) for the detection of testicular involvement by an aggressive lymphoma. Conclusions FDG PET/CT shows significantly greater FDG avidity for testicular aggressive lymphomas as compared with physiologic testicular FDG uptake in this single institution study with centralized radiology review of cases and controls. Testicular FDG avidity greater than an SUVmax 5.0 in staging aggressive lymphoma is highly suggestive for testicular involvement, warranting follow-up clinical exam and ultrasound, at a minimum. In addition, testicles with SUVmax <5.0 in a patient with known lymphoma but no symptoms or signs of testicular involvement should be considered negative for the purposes of staging and treatment planning. A pragmatic limitation of this study is that most patients with testicular involvement of lymphoma underwent orchiectomy prior to FDG PET/CT scan, which decreased our sample size. Larger, pooled studies would be helpful to validate these clinically relevant findings. Figure. Figure. Disclosures Witzig: Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cerhan:Celgene: Research Funding; Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding.

Abstract Background: To address the current and long-term unmet health needs of the growing population of patients diagnosed with non-Hodgkin lymphoma (NHL) and NHL survivors, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/) with recruitment at eight centers (Cornell University, Emory University, Mayo Clinic, MD Anderson, University of Iowa, University of Miami, University of Rochester, and Washington University). Here we report on the first two years of enrollment. Methods: All patients ≥18 years with NHL (exclusive of chronic lymphocytic leukemia) newly diagnosed within 183 days of enrollment are eligible. LEO reviews all pathology diagnoses; annotates and harmonizes all cases with clinical, epidemiologic, pathology and treatment data; builds a NHL tumor bank that includes an H&E slide, a formalin-fixed, paraffin-embedded tissue sample and extracted tumor DNA and RNA; collects peripheral blood and banks DNA, serum, plasma and buffy coat in a central biorepository; and prospectively follows patients regularly to ascertain disease progression/relapse, retreatment, transformation, second cancers, survival, updated exposures, and patient-reported outcomes. We examined the demographics, clinical characteristics, and NHL subtypes for patients enrolled in the first two years (2015-2017) in LEO Cohort and compared these characteristics to population-based registry data from the United States Surveillance, Epidemiology, and End Results (SEER) Program for 2011-2015. We also examined baseline body mass index (BMI), comorbidities and quality of life (QOL) measured with the Functional Assessment of Cancer Therapy - General (FACT-G) scores (0-100 scale) overall and by NHL subtype that were collected in LEO but not available in SEER or any other large, prospective US NHL cohort. Results: From 2015-2017, LEO enrolled 3244 NHL patients across 47 states (Figure) with a median age at diagnosis of 62 years (range, 18-94 years) and 55.9% male. Based on self-identified race/ethnicity, 85% of the participants were White, 7.4% were Black/African American, 2.6% were Asian, and 3.5% other or more than one race; 9.9% were Hispanic (regardless of race). The most common subtypes were diffuse large B-cell (DLBCL, 33.9%), follicular (FL, 22.2%), mantle cell (MCL, 9.3%), marginal zone (MZL, 8.3%), T-cell (TCL, 10.9%), and all other NHL subtypes (other NHL, 15.3%). These distributions were all within 5% of SEER data, except that 6.8% of participant in LEO were in the age 80+ years group compared to 18.5% in SEER (Table). The overall prevalence of self-reported comorbidities at enrollment was 13.5% for heart disease (range, 12.1% for FL to 16.6% for MCL), 8.8% for diabetes (range, 7.1% for FL to 9.8% for DLBCL), 4.6% for osteoporosis (range, 3.0% for MCL to 6.3% for MZL), and 5.9% for autoimmune disease (range, 2.0% for MCL to 12.6% for MZL). The median BMI was 27.9 kg/m2 (range, 26.7 kg/m2 for TCL to 28.3 kg/m2 for MZL). A total of 2151 participants completed the FACT-G with a median score of 78.7 (range, 75.9 for TCL to 83.3 for MZL). Complete IPI data were available on 2296 participants: 40.4% IPI 0-1, 32.7% IPI 2, 18.3% IPI 3, 8.7% IPI 4-5. Overall, 73.7% of participants were initially treated with systemic therapy (range, 40.0% for MZL and 91.8% for DLBCL); 14.5% were initially managed with observation (range, 1.4% DLBCL and 31.8% for FL); and 2.0% were initially manage with radiotherapy (range, 0.2% for MCL and 3.8% for DLBCL). Outcomes are being prospectively collected. Conclusions: LEO is a large and diverse cohort of newly diagnosed NHL patients and the first two years of enrollment reflects the broader United States NHL population. Enrollment is ongoing. This unique resource will enable examination of the interactions among a broad array of clinical and molecular factors and their impact on multiple outcomes, to improve prognostication, identify new approaches to improve outcomes and survivorship, and facilitate clinical trials using this infrastructure. Disclosures Flowers: Acerta: Research Funding; Pharmacyclics/ Janssen: Consultancy; OptumRx: Consultancy; Janssen Pharmaceutical: Research Funding; V Foundation: Research Funding; Burroughs Wellcome Fund: Research Funding; Spectrum: Consultancy; Eastern Cooperative Oncology Group: Research Funding; Abbvie: Consultancy, Research Funding; Bayer: Consultancy; Millennium/Takeda: Research Funding; Abbvie: Research Funding; Celgene: Research Funding; Gilead: Consultancy; BeiGene: Research Funding; Karyopharm: Consultancy; Denovo Biopharma: Consultancy; Genentech/Roche: Consultancy; Gilead: Research Funding; Genentech/Roche: Research Funding; National Cancer Institute: Research Funding; TG Therapeutics: Research Funding; Pharmacyclics: Research Funding. Nastoupil:TG Therappeutics: Research Funding; Merck: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Janssen: Research Funding; Spectrum: Honoraria; Gilead: Honoraria; Genentech: Honoraria, Research Funding; Karus: Research Funding; Novartis: Honoraria; Juno: Honoraria. Kahl:Acerta: Consultancy; Genentech: Consultancy; Seattle Genetics: Consultancy; Juno: Consultancy; CTI: Consultancy; ADC Therapeutics: Consultancy; Gilead: Consultancy; Celgene: Consultancy; AstraZeneca: Consultancy; Abbvie: Consultancy. Casulo:Celgene: Research Funding; Gilead: Honoraria. Friedberg:Bayer: Honoraria. Lossos:Affimed: Research Funding. Martin:Seattle Genetics: Consultancy; Kite: Consultancy; Janssen: Consultancy; Gilead: Consultancy; Bayer: Consultancy; AstraZeneca: Consultancy. Leonard:Bayer: Consultancy; Celgene: Consultancy; Biotest: Consultancy; United Therapeutics: Consultancy; BMS: Consultancy; MEI Pharma: Consultancy; Juno: Consultancy; Sutro: Consultancy; Karyopharm: Consultancy; ADC Therapeutics: Consultancy; Pfizer: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy; Genentech/Roche: Consultancy; Novartis: Consultancy. Bernal-Mizrachi:Kodikaz Therapeutic Solutions: Consultancy, Equity Ownership; Takeda Pharmaceutical Company: Research Funding. Maurer:Morphosys: Research Funding; Nanostring: Research Funding; Celgene: Research Funding. Cerhan:Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding.

Abstract Background: PTLD is the most common malignancy, other than non-melanoma skin cancer, complicating solid organ transplantation (SOT) and has been one of the most commonly observed fatal consequences in SOT. The clinical presentations, management strategies, histologies, causes of death and outcomes are diverse (Dierickx D, Habermann TM. N Engl J Med 2018;378:549-62). The 2017 WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues has redefined the categories as non-destructive PTLDs (plasmacytic hyperplasia, infectious mononucleosis, and florid follicular hyperplasia), polymorphic PTLD, monomorphic PTLD: B-cell neoplasms (diffuse large B-cell lymphoma, Burkitt lymphoma, high-grade B-cell lymphoma, plasmablastic lymphoma, plasma cell myeloma, plasmacytoma, and other) and T-cell neoplasms (peripheral T-cell lymphoma NOS, hepatosplenic T-cell lymphoma, other), and classic Hodgkin lymphoma (CHL) PTLD. We report the outcomes and long-term follow-up of patients from a single institution based on these categories whose pathology was retrospectively reviewed and reclassified based on the WHO 2017 classification. Methods: Patients with SOT who were diagnosed with PTLD at Mayo Clinic (Rochester, MN) were identified through the Mayo Clinic Lymphoma Data base and the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER). The histology was re-reviewed in 80% of the cases (RLK) and classified according to the WHO Classification of Tumours of Haematopoietic an Lymphoid Tissues 2017. Cases were considered "PTLD, unclassified" if the histology could not be confidently classified based on pathology material available for review. Indolent small B-cell lymphomas were not included among the PTLDs except for EBV-positive marginal zone lymphoma. Cox proportional hazards models were used to assess the association of clinical factors in overall survival (OS). Results: 233 patients diagnosed with PTLD between 1987 and 2017 were identified. The median age at the time of diagnosis of PTLD was 54 years (range 16 to 84) with 85 patients (36%) over the age of 60. 156 (67%) were male. The transplanted organs were kidney (41%), kidney/pancreas (5%), liver (29%), heart (9%), lung (7%), and other (8%). PTLD occurred late (more than one year after transplantation) in 66%. There were 69 stage I, 19 stage II, 8 stage III, and 128 stage IV patients. 84% presented with extranodal disease. 21% had involvement of the engrafted organ. 64% of the patients developed a PTLD that was EBV positive by in situ hybridization. Initial approaches to management included reduction of immunosuppression (N=55), chemotherapy/immunochemotherapy (N=71), reduction in immunosuppression with rituximab (N=58), single agent rituximab (N=14), and radiation therapy (N=5). At a median follow-up of 87 months (range 9-289), 139 (60%) patients had died. All six CHL-PTLD patients are alive, two of whom had an event. The median overall survival (OS) was 85 months (95% CI: 39-144) in 177 monomorphic B-cell lymphoma PTLD, 95.5 months (95% CI: 40-not reached) in 24 polymorphic PTLD, and 60 months in 8 non-destructive PTLD cases. In contrast, the median overall survival was 12 months (95% CI: 4-200) in 8 monomorphic T cell and 3 months (95% CI: 1-unreached) in 9 unclassified PTLD cases. Conclusion: PTLD is a heterogeneous group of immunodeficiency-associated lymphoproliferative disorders. The overall survival in non-destructive, polymorphic, and monomorphic PTLD were similar. Monomorphic T/NK cell types had inferior outcomes. Figure. Figure. Disclosures Maurer: Morphosys: Research Funding; Nanostring: Research Funding; Celgene: Research Funding. Ansell:Celldex: Research Funding; Merck & Co: Research Funding; Takeda: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Pfizer: Research Funding. Cerhan:Celgene: Research Funding; Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board.

Abstract Background Diffuse large B cell lymphoma post-transplant lymphoproliferative disorder (DLBCL-PTLD) represents a fatal complication after a solid organ transplant (SOT). Approximately 50% of DLBCL-PTLD can be related to Epstein Barr Virus (EBV) infection. However, the EBV status is not taken into account in the DLBCL-PTLD categorization, although increasing evidence suggests its critical role in biological, clinical and prognostic aspects of the disease. In this single center retrospective study, we compared clinical and histological features, as well as outcomes of DLBCL-PTLDs by EBV status. Methods This study focused on patients with SOT who were diagnosed with DLBCL-PTLD at Mayo Clinic (Rochester, MN). Patients were identified through the Mayo Clinic Lymphoma Data base and the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER), between 1989 and 2017. The histology was re-reviewed (RLK) and classified according to the WHO Classification or Tumours of Haematopoietic and Lymphoid Tissues 2017. Cell of origin (COO) was performed by Hans algorithm. EBV RNA in situ hybridization (EBER) was performed. Cox proportional hazards models were used to assess the association of clinical factors in overall survival (OS). Results 148 DLBCL-PTLD were identified. The median age at SOT and at the time of PTLD diagnosis were 50 years (range: 15-71) and 56 years (range: 18-82), respectively. The median time to PTLD diagnosis from SOT was 38 months (range: 1-499). The types of SOT included renal (44%), liver (36%), cardiac (9%), renal/pancreas (5%), pancreas (8%), lung (7%) and multiorgan (4%). 62% were stage III-IV, 30% had elevated LDH and 67% had an IPI >1. 88% of patients presented with extranodal disease, and 16% had involvement of the grafted organ. Eighty-three (56%) cases were EBV positive. The COO information was available on 35 cases. The non-GCB subtype was identified in 24 cases and GCB subtype in 11 cases. The initial treatment was as follows: reduction in immunosuppression (12%), immunosuppression reduction with rituximab (26%), rituximab alone (5%), chemotherapy with or without rituximab (35%). Patients with EBV positive PTLD were more likely to have grafted organ involvement (20% vs. 8%, p=0.047) and late PTLD (occurring after 12 months from SOT - 60% vs. 8%, p<0.001) than patients with EBV negative PTLD. There was no association between EBV status and age, sex, stage, LDH, and extranodal site involvement. At a median follow-up of 80 months (range 9-269), 83 patients (56%) had died. The 5-year survival rate from PTLD diagnosis was 56% (95% CI: 48-65%). The median OS was 85 months (95% CI: 37-148). There was no difference in OS in patients with EBV positive PTLD (median OS=84.7 months, HR=1.21, 95% CI: 0.77-1.92) versus patients with EBV negative DLBCL-PTLD (median OS=85.4 months, p=0.41). Conclusion Our study assessed the impact of EBV status on the presentation and clinical outcome of DLBCL-PTLD in a 148-patient single-institution cohort. 56% of cases were EBV positive. EBV positivity was associated with grafted organ involvement and late PTLD diagnosis. Patients with EBV-negative and EBV-positive disease had similar survival from PTLD diagnosis. Disclosures Maurer: Celgene: Research Funding; Morphosys: Research Funding; Nanostring: Research Funding. Cerhan:Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding.