Allmer, Cristine

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: Lymphoma survivors are at risk for long term and late effects which may negatively impact quality of life (QOL). Few studies have assessed the impact of change in health behaviors (physical activity (PA), alcohol and smoking) on QOL, specifically in lymphoma survivors. Methods: Patients were prospectively enrolled <9 months of diagnosis into the Lymphoma SPORE Molecular Epidemiology Resource cohort. At baseline and 3-year follow-up (FU3), patients self-reported QOL, smoking, alcohol use and PA. At FU3, survivors reported change in health behaviors since diagnosis. The Godin Leisure Score Index (LSI) was calculated as a measure of PA (Pophali et al. ASH 2017); modeled by tertile. QOL was measured via FACT-G; the total and sub-scales [emotional (EWB), functional (FWB), physical (PWB), and social/family well-being (SFWB)] scores were transformed to a 0-100 scale. Patients who completed <80% of QOL questions were excluded. The association of QOL with health behaviors was evaluated using Kruskal-Wallis test (categorical) and Spearman's rank correlation (continuous). Results: At baseline, 2805 participants were evaluable for QOL of which 2025 were evaluable at FU3. The median age at diagnosis was 62 (IQR 52-69) years. Majority were males (N=1148, 56.8%), with advanced stage III-IV disease (N=941, 62%) and ECOG performance status <2 (N=1935, 96%). At baseline, smoking status was current (N=237), former (N=802), never (N=1310) or not available (NA, N= 456). Current smokers had a significantly lower median QOL scores compared to former and never smokers for EWB (75 vs 79 vs 79, p<0.01), FWB (71 vs 79 vs 79, p<0.01), PWB (86 vs 89 vs 89, p=0.02), SFWB (86 vs 90 vs 89, p=0.02) and total FACT-G (67 vs 82 vs 82, p<0.01). The median number of pack years smoked among current &former smokers was 15.6 (range 0.5-126). There was a significant negative correlation of pack years smoked with FWB (p=0.05), and total FACT-G (p=0.04). At FU3, current smokers had significantly lower median scores compared to former and never smokers for FWB (80 vs 86 vs 86, p=0.01), PWB (89 vs 93 vs 93, p<0.01) and total FACT-G (82 vs 86 vs 87, p<0.01). EWB (83 vs 88 vs 88, p=0.12) and SFWB (83 vs 86 vs 86, p=0.12) were also lower than never and former smokers but not statistically significant. Smoking status was decreased (N=30), increased (N=0) and unchanged (N=1439) at FU3. There was no association of change in smoking with change in QOL. At baseline, alcohol use status was current (N=1189), former (N=506), never (N=518) and NA (N=592). Current alcohol users had the highest FWB (79 vs 75 vs 75, p<0.01) vs former and never users. Former users vs current and never users had the lowest PWB (86 vs 89 vs 89, p<0.01), SFWB (88 vs 89 vs 92, p<0.01) and total FACT-G (80 vs 83 vs 82, p<0.01). EWB was similar in all 3 groups. Among current & former alcohol users, the average number of drinks/week was 3.4. There was no association of the number of drinks/week with QOL except positive correlation with PWB (p=0.01). At FU3, alcohol use was reported as increased (N=40), decreased (N=312) and no change (N=875). There was no association between change in alcohol use and change in QOL. At baseline, participants with PA in the high vs low LSI tertile had significantly better median scores for FWB (79 vs 75, p=0.01), SFWB (93 vs 89, p<0.01) and total FACT-G (83 vs 82, p<0.01). At FU3, participants in the high vs low LSI tertile had significantly better scores on all subscales and total FACT-G with a significant positive correlation between the continuous LSI and QOL (FACT-G total and subscales). PA was reported as increased (N=107), decreased (N=394) and no change (N=495). There was a significant association of increase in PA with change in PWB (p<0.01), EWB (p=0.01), FWB (p<0.01) and total FACT-G (p<0.01) from baseline to FU3, but not with change in SFWB (p=0.06). In a sensitivity analysis, QOL was modeled for health behaviors in the subset of patients with QOL assessed prior to treatment; results were consistent with the QOL in all patients. Conclusions: Health behaviors in lymphoma survivors are significantly associated with QOL: better QOL is associated with not smoking, more PA, and moderate alcohol use. Current alcohol consumption, as opposed to former alcohol use, may be related to overall health status. An increase in PA after lymphoma diagnosis is associated with an increase in the QOL. Thus, modification of health behaviors has the potential to impact QOL in lymphoma survivors. Figure. Figure. Disclosures Cerhan: Celgene: Research Funding; Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board.

Abstract Introduction: The addition of Rituximab to chemotherapy has significantly improved the outcome of patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL). Patients treated with immunochemotherapy for DLBCL who achieve EFS24 (event-free for 2 years after diagnosis) have an overall survival equivalent to that of the age- and sex-matched general population. Relapses after achieving EFS24 have been considered to be unusual but have been understudied. We sought to define the rate, clinical characteristics, treatment pattern, and outcomes of such relapses. Methods: 1448 patients with newly diagnosed DLBCL from March 2002 to June 2015 were included. Patients were enrolled in the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma SPORE, treated per physician choice (predominantly R-CHOP immunochemotherapy) and followed prospectively. An event was defined as progression or relapse, unplanned re-treatment after initial therapy, or death from any cause. Cumulative incidence of relapse and non-relapse mortality after achieving EFS24 were analyzed as competing events using Gray's test in the EZR software. Post-relapse survival was defined as time from relapse to death from any cause and analyzed using Kaplan-Meier method in SPSS (V22). Results: Among the 1448 patients, 1260 (87%) had DLBCL alone at diagnosis, and 188 (13%) had concurrent indolent lymphoma (follicular lymphoma 115, marginal zone lymphoma 18, chronic lymphocytic leukemia 14, lymphoplasmacytic lymphoma 4, unspecified 37) at diagnosis. After a median follow-up of 83.9 months, 896 patients achieved EFS24. For all 896 patients who achieved EFS24, the cumulative incidence of relapse (CIR) was 5.7%, 9.3% and 13.2%, respectively, at 2, 5 and 10 years after achieving EFS24. Patients with concurrent indolent lymphoma at diagnosis had a higher CIR compared to those with DLBCL alone at diagnosis (10.2 vs 4.8% at 2 years, 15.7 vs 8.0% at 5 years, 28.8 vs 9.7% at 10 years, P<0.001; Figure 1). There were a total of 84 patients who relapsed after achieving EFS24. The median age at initial diagnosis was 66 years (range 35-92), and 48 (57%) were male. At diagnosis, 11 (13%) had ECOG PS >1, 37 (50%) had LDH elevation, 62 (74%) were stage III-IV, 14 (17%) had more than 1 extranodal site, and 26 (31%) were poor risk by R-IPI score. There were 58 patients with DLBCL alone at diagnosis who relapsed after achieving EFS24, and 38 (75%) relapsed with DLBCL, 13 (25%) relapsed with indolent lymphoma (predominantly follicular lymphoma), and pathology was unknown in 7 patients. In contrast, there were 26 patients with concurrent indolent lymphoma at diagnosis who relapsed after achieving EFS24, and 9 (41%) relapsed with DLBCL, 13 (59%) relapsed with indolent lymphoma, and pathology was unknown in 4 patients. In the 47 patients who relapsed with DLBCL after achieving EFS24, 45% received intensive salvage chemotherapy, 19% received regular intensity chemotherapy, 9% received CNS directed chemotherapy, and 36% went on to receive autologous stem cell transplant (ASCT). In the 26 patients who relapsed with indolent lymphoma after achieving EFS24, 27% were initially observed, 54% received regular intensity chemotherapy, 4% received intensive salvage chemotherapy, and 19% received ASCT after subsequent progression. The median post-relapse survival (PRS) for all patients with a relapse after achieving EFS24 was 38.0 months (95% CI 27.5-48.5). The median PRS for patients who relapsed with DLBCL and indolent lymphoma after achieving EFS24 were 29.9 (19.9-39.9) and 89.9 (NR-NR) months, respectively (P=0.002; Figure 2). Conclusions: Relapses after achieving EFS24 in patients with DLBCL were uncommon in the rituximab era. Patient with DLBCL alone at diagnosis can relapse with either DLBCL or indolent lymphoma (3:1 ratio). Patients with concurrent DLBCL and indolent lymphoma at diagnosis had a significantly higher CIR, and relapses with DLBCL and indolent lymphoma were similar (2:3 ratio). Even with high intensity salvage chemotherapy and consolidative ASCT, patients who relapsed with DLBCL had a significantly worse survival compared to those who relapsed with indolent lymphoma. Late relapses with DLBCL remain clinically challenging, with a median survival of 2.5 years after relapse. Figure 1. Figure 1. Disclosures Maurer: Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Research Funding. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Ansell:Takeda: Research Funding; Pfizer: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Celldex: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Merck & Co: Research Funding; Bristol-Myers Squibb: Research Funding. Cerhan:Celgene: Research Funding; Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding.

Abstract Background: The frequency of preventive health practices (PHP), including age-appropriate screening for malignancies and immunizations, and compliance with PHP guidelines in lymphoma survivors is not known. We hypothesized that lymphoma survivors are more compliant with PHP than the general population but PHP rates may differ based on patient, disease and treatment characteristics. Methods: We identified eligible lymphoma patients from the SPORE Molecular Epidemiology Resource (MER) cohort, in which they were prospectively enrolled within <9 months of diagnosis. Survivors self-reported their PHP (colon, breast, and prostate cancer screening and influenza immunization) in the 3-year follow-up questionnaire (FU3). Per US Preventative Task Force guidelines, survivors were considered eligible for colon cancer screening if they were >50 years and compliant if they had fecal occult blood test <1 year or sigmoidoscopy/colonoscopy <10 years of FU3. Eligible female survivors age 50-75 were considered compliant if they had a mammogram after lymphoma diagnosis. Since USPTF recommended against PSA for prostate cancer screening in 2012, males aged 55-69 prior to 2012 were eligible and considered compliant if PSA test was <1 years of FU3. Survivors who received influenza vaccine <1 year of FU3 were considered compliant. Chi-square test was used to compare characteristics of compliant vs non-compliant patients; p value <0.05 was considered statistically significant. Results: Of 4248 lymphoma patients enrolled in the MER from 2002 to 2012, 2038 participants completed FU3. 1105 (54%) were male. The median age at diagnosis was 61 (IQR 51-69) years. There were equal numbers of indolent (N=1002) and aggressive (N=995) histologies with follicular (N=515, 25%) and diffuse large B-cell (N=427, 21%) being the most common. Majority (N=1221, 60%) had advanced stage (Ann Arbor III-IV) disease. 469 (23%) had events prior to FU3 and majority 1777 (88%) had received lymphoma treatment prior to FU3. Of 2038 survivors who completed FU3, 1576 (79%) reported having colon cancer screening in their lifetime. 1328 (91%) of 1570 eligible survivors were compliant, 124 (9%) were not and 118 had missing information. Survivors of age >60 years (93% vs 88%, p<0.001), those with indolent lymphomas (93% vs 90%, p=0.046), or diagnosed between 2010-2012 (94% vs 90% 2002-2009, p=0.007) were more likely to be compliant. There was no difference in colon cancer screening by sex, events prior to FU3 or treatment prior to FU3. 872 (96%) of 933 female survivors reported having a breast exam and 836 (91%) had a mammogram at least once in their lifetime. 495 (96%) of 561 eligible female survivors were compliant, 23 (4%) were not and 43 had missing information. There was no difference in mammographic screening based on age (<=60 vs >60), histology (indolent vs aggressive), events prior to FU3, treatment prior to FU3 or year of diagnosis (2010-2012 vs 2002-2009). 737 (78%) of 1105 male survivors had a PSA test at least once in their lifetime. 115 (71%) of 216 eligible men were compliant, 47 (29%) were not and 54 had missing information. There was no difference in PSA screening by age (<=60 vs >60), histology (indolent vs aggressive), events prior to FU3, and treatment prior to FU3. 1818/2038 (90%) survivors had received an influenza vaccine in their lifetime. 1567 (81%) were compliant, 373 (19%) were not and 98 had missing information. Survivors >60 years of age (87% vs 75%, p<0.001) and those with indolent lymphoma (83% vs 78%, p=0.015) were more likely to be compliant. There was no difference in influenza vaccination by sex, events prior to FU3, treatment prior to FU3, and year of diagnosis (2010-2012 vs 2002-2009). As a comparison in the US general population [Figure], between 2002-2015 the highest rates published by the Center for Disease Control are 62% for colon cancer screening (2015), 75% for mammography (insured, 2003) and influenza vaccination 42% (2015). Per the American Cancer Society, the highest rate of PSA screening was 54% (2010). Conclusion: Lymphoma survivors have high compliance with PHP recommendations compared to the general population. Although older individuals and those with indolent histologies were more likely to receive influenza vaccination and colon cancer screening, this difference was not seen in breast and prostate cancer screening practices. Lymphoma treatment and events did not seem to affect the frequency of PHP among survivors. Figure. Figure. Disclosures Cerhan: Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding.

Abstract The International Prognostic Factor Index (IPI) predicts survival in DLBCL in patients treated with chemotherapy. The Revised IPI (R-IPI) has been reported to be a simpler and more accurate predictor of outcome in patients treated with immunochemotherapy (rituximab and anthracycline-based chemotherapy). We evaluated the predictive value of the IPI and the R-IPI in an observational cohort of unselected patients treated with R-CHOP. Consecutive, newly diagnosed patients age 18 years and older with DLBCL were prospectively offered enrollment into our Lymphoma SPORE Registry. Pathology was centrally reviewed, and composite lymphomas and history of concurrent or prior cancers were excluded. All patients were actively followed for progression free progression (PFS) and overall survival (OS). Here we report on patients enrolled from 9/2002 – 6/2006. 229 patients with a median age of 62 years (range 20–93) were evaluated. 56% were >60 years of age, 16% had a performance score ≥2, 54% had an elevated LDH, 19% had >1 extranodal site, and 51% were stage III/IV. During follow-up, there were 63 progressions (28%) and 45 deaths (20%), and the median follow-up time for living patients was 34 months (range 6–61 months). As shown in the table and figure, the IPI and R-IPI were predictive for both PFS and OS (all p<0.001). The predictive ability of the IPI as measured by 3-year concordance index was stronger for the IPI (0.71) compared to the R-IPI (0.67) and the bootstrap 95% confidence interval for the difference (0.01, 0.08) indicates that this difference was statistically significant. While all factors in the IPI were statistically significant (p<0.05) predictors of OS individually, when included in a multivariate model, an elevated LDH (HR=1.5; p = 0.32) and >1 extranodal sites (HR=1.0; p = 0.96) were no longer significant; similar results were obtained for PFS. The IPI remains a strong predictor of PFS and OS in the immunochemotherapy era. Figure Figure Group % Pats 3 Y PFS HR 95% CI 3 Y OS HR 95% CI Standard IPI Low (0,1) 41% 87% 1.0 ref 93% 1.0 ref Low-Int (2) 22% 62% 3.1 (1.4, 6.8) 74% 4.2 (1.6, 11.1) High-Int (3) 21% 60% 3.1 (1.4, 6.8) 77% 3.4 (1.2, 9.7) High (4,5) 15% 39% 7.2 (3.4, 15.2) 47% 10.2 (4.0, 26.5) R-IPI Very good (0) 11% 96% 1.0 ref 100% 1.0 ref Good (1,2) 53% 74% 6.2 (0.8, 46.0) 84% - - Poor (3–5) 36% 52% 13.5 (1.8, 98.9) 65% - -

Abstract Background: CpG 7909 is a synthetic 24 mer oligodeoxynucleotide designed to provide optimal activation of immune mechanisms through the TLR9 receptors on B-cells and plasmacytoid dendritic cells. In vitro CpG can upregulate CD20 expression as well as stimulate the immune system. Radioimmunotherapy (RIT) with anti-CD20 radioimmunoconjugates such as Zevalin produces responses in approximately 80% of patients with relapsed indolent lymphoma; however, only 30% obtain a complete response and 20% have long-term disease free survival. Objectives: To combine CpG 7909 with rituximab and Zevalin to enhance the response to RIT. Patients and Methods: Patients were eligible if they had biopsy proven relapsed, refractory, or residual CD20+ NHL. Disease types included relapsed indolent and aggressive B-cell NHL. Patients were required to have measurable disease, a platelet count >150,000, and an absolute neutrophil count >1,500. This was a phase I study where all patients received a standard dose of Zevalin (0.4mCi/kg with a maximum of 32mCi for patients over 80kg) along with a phase I dose of CpG 7909. Four dose levels were studied—0.08mg/kg; 0.16mg/kg; 0.32mg/kg; and 0.48mg/kg. CpG was dosed on Day 6, 13, 20, and 27; rituximab was provided Day 1, 8, and 15; indium-111 Zevalin on Day 1 and 8 (followed by indium-111 Zevalin imaging); and yttrium-90 Zevalin on Day 15. Response was assessed at week 4 and week 12. Patients are also being assayed pre- and post-CpG and at multiple time points up to 1 year following treatment for changes in T-cell, NK-cell, and cytokine levels. Results: A total of 30 patients have now been enrolled—6 at each of the first 3 dose levels and 12 at dose level 4. Three pts had relapsed diffuse large cell (DLC) and 27 pts were relapsed indolent. One of the first 6 patients at dose level 4 (0.48mg/kg) had a dose limiting toxicity (DLT - hematologic with full recovery). The other 5 patients at dose level 4 did not have DLT; and thus, 0.48mg/kg was determined to be the dose for further studies. An additional 6 patients at dose level 0.48mg/kg were accrued. Response information is available on the first 26 pts and the median follow-up is 12.4 months (range, 0–30.8). The overall response rate, to date, is 92% (24/26) – 66% (2/3) for the DLC pts and 96% (22/23) for the indolent pts. The complete remission rate is 58% (15/26). After follow-up, 7 of the 26 patients have progressed and one has died of relapsed NHL; therefore, 73% (19/26) remain in response and overall survival is 97% (29/30). As part of the study, we performed indium-111 Zevalin imaging before CpG and after 1 dose of CpG (prior to the yttrium-90 Zevalin) to evaluate the effect of CpG on the biodistribution of the radioimmunoconjugate. In the first 24 patients treated to date, review of the paired gamma camera images does not show any significant effects of CpG on tumor or normal organ biodistribution. To date, there has been no significant differences in T-cell, NK-cell, and cytokine activation by CpG dose level. Summary: CpG 7909 can be safely combined with Zevalin RIT in patients with advanced stage relapsed B-cell NHL.

Abstract Abstract 2656 Background Treatment of non-Hodgkin lymphoma (NHL) can lead to development of cardiovascular disease (CVD). We sought to describe the cumulative incidence of CVD in adult NHL survivors diagnosed in the recent treatment era (since 2002) and identify clinical and treatment predictors for its development. Methods All patients were from the Mayo component of the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). The MER offers enrollment to all consecutive patients with newly diagnosed NHL who are US residents and age >18 years. Clinical data from the time of diagnosis and treatment data are abstracted from medical records using a standard protocol. Patients are prospectively contacted via telephone or in person per protocol every 6 months for the first 3 years from diagnosis and yearly afterwards to assess disease status and development of comorbid conditions. CVD events, including heart failure (HF), myocardial infarction (MI), arrhythmia, pericarditis, and valvular heart disease, occurring after diagnosis were identified during follow-up and validated against medical records. HF was validated with the Cardiovascular Health Study Criteria and/or the Framingham Criteria. MI was validated using case definition standards of coronary heart disease, while arrhythmia, pericarditis, and valvular heart disease were validated using clinical definitions. The prevalence of CVD and associations between CVD and clinical characteristics (sex, age) and treatment (radiation, anthracyclines) were performed using Cox models with a competing risk approach. Results 1164 patients with NHL were enrolled into the MER at Mayo Clinic between 9/1/2002–2/28/2008. 646 were male (56%) and median age at diagnosis was 62 years (range 20–93). Median follow-up of all cases was 59 months (range 1–105). 131 patients reported CVD prior to the diagnosis of NHL and were excluded from analyses. An additional 76 patients did not have follow-up and were excluded. Of the 957 remaining patients, 75 (7.8%) self-reported a new diagnosis of CVD. Of these, 71 cases had available medical records. 57 of the 71 reviewed cases (80%) were validated (18 HF, 9 MI, 21 arrhythmia, 2 pericarditis, and 10 valvular heart disease). Cumulative incidence of CVD at 1, 3, 5, and 7 years was 1.3%, 3.7%, 5.2%, and 7.4%, respectively. Median time from NHL diagnosis to CVD was 26.5 months (range 1–84). Older age was associated with increased risk of overall CVD (p-value<0.001). Gender (p=0.59), radiation therapy (p=0.61), and anthracycline treatment (p=0.25) were not associated with the incidence of overall CVD. Among types of CVD, anthracycline use was associated with development of HF (HR=5.30; p-value=0.008) and arrhythmia (HR=2.68; p-value=0.04). Radiation was associated with development of arrhythmia (HR=2.73; p-value=0.03), while older age was associated with development of HF (HR=1.36 per 5 year increment; p-value=0.003) and arrhythmia (HR=1.25 per 5 year increment; p-value=0.02). Conclusions The risk of CVD in patients with NHL is approximately 1% per year after the initial diagnosis of lymphoma. The most commonly occurring CVDs in this cohort of NHL survivors were arrhythmia and HF. Treatment with anthracyclines and radiation are associated with increased risk of developing some types of CVD. 80% of self-reported CVD events in NHL survivors were validated using epidemiologic criteria. Future studies will include building models incorporating comorbid health conditions and lifestyle factors to determine risk of CVD as well as the impact of CVD on quality of life. Disclosures: No relevant conflicts of interest to declare.

Abstract We have recently reported that event-free survival at 24 months from diagnosis (EFS24) is a robust endpoint for assessment of disease related outcome for newly diagnosed patients with diffuse large B-cell lymphoma (DLBCL) treated with anthracycline-based immunochemotherapy (IC). Patients who achieve EFS24 following IC have a subsequent overall survival that is equivalent to the age and sex matched general population. The IPI was developed in the pre-rituximab era using OS/EFS endpoints. While the IPI is associated with outcome in the IC era, the original survival estimates for the IPI risk groups are outdated. The IPI is also a discrete risk classifier, with only 6 possible groups. Here we remodel the IPI using EFS24 as the endpoint in a large international cohort of patients treated with IC. This model provides an individual level 0-100% risk of failing to achieve EFS24 for each patient and can be used for patient prognosis, treatment stratification, and risk assessment. Methods Newly diagnosed DLBCL patients treated with immunochemotherapy from the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource, NCCTG N0489 clinical trial, GELA LNH2003B program, and a Lyon, France based hospital registry were included in the original EFS24 study. Patients with a relapse, progression, unplanned re-treatment, or death due to any cause within 730 days of diagnosis were considered a failure for the EFS24 endpoint. Patients alive and progression/relapse free at 730 days from diagnosis with no subsequent treatment following initial IC were considered a success for the EFS24 endpoint. Variables selected for potential model inclusion were the IPI components (age, stage, ECOG PS, number of extranodal sites, and LDH), as well as standard clinical variables typically reported in studies of DLBCL: presence of B-symptoms, bone marrow involvement, bulky disease (>10 cm), and sex. The IPI24, a prognostic model for EFS24, was developed using logistic regression models. Model building began by fitting the classic IPI score (0-5), then allowing individual IPI variables to carry different model weights and number of categories, followed by dropping insignificant variables, finally adding any additional significant variables. Model performance was assessed using bias corrected c-statistics, AIC, and R2 values. Model selection was done using the complete case set with multiple imputation on the full dataset used to refine parameter estimates for the final model. Results 1596 total patients were available for modeling. The median age was 62 (range 18-93) and 53% were male; 33% were IPI 0-1, 25% were IPI 2, 25% were IPI 3, and 17% were IPI of 4-5. The failure rate for achieving EFS24 was 29%. All variables but sex (p=0.33) were univariately associated with EFS24 (p<6.4x10-5). The original IPI had good prognostic ability for EFS24 (c=0.696, p=2.2x10-32). Allowing multiple categories for ECOG PS, stage, and age (continuous) improved model fit and prognostic ability (c=0.727). The number of extranodal sites was not significant when IPI variables were modeled separately and was removed from the model. Sex and bulky disease were additional significant variables when added to the model. Thus, the final IPI24 model contained the following risk predictors: male sex, ECOG PS (0 vs. 1 vs 2 vs 3-4), stage (I vs. II, vs. III vs. IV), LDH (elevated vs. normal range), bulky disease > 10cm, and age (continuous). This model resulted in improved fit and prognostic ability (c=0.749) over the standard IPI (c=0.696, bootstrap p<0.001). Model validation was performed on an additional 158 patients from the SPORE MER and showed good concordance (c=0.697). Additional validation is planned in a larger set of independent patients. Conclusion The IPI24, generated using standard clinical variables, yields an individual risk prediction for failing to achieve EFS24 following IC for treatment of DLBCL. The IPI24 has superior prognostic ability to the standard IPI and can be implemented in the clinic using a nomogram or as a simple electronic application. Disclosures: No relevant conflicts of interest to declare.

Abstract Background: There are a number of ongoing clinical trials assessing next-generation immunochemotherapy (IC) regimens (i.e. RX-CHOP) in DLBCL. In addition to standard clinical trial workup, some trials require central pathology review and/or molecular phenotyping before treatment assignment and/or initiation of therapy. There is concern that these studies may be biasing patient selection due to missing patients with aggressive disease who require immediate therapy and cannot delay their treatment to enroll on a study. Here we examine clinical characteristics and outcome stratified by the time from diagnosis to initiation of therapy from a large observational cohort of patients with DLBCL from the R-CHOP era. Methods: Patients were prospectively enrolled in the University of Iowa / Mayo Clinic SPORE Molecular Epidemiology Resource (MER) within 9 months of diagnosis and followed for relapse, retreatment, and death. Clinical management at diagnosis and subsequent therapies were per treating physician. This analysis includes patients with stage II-IV DLBCL or primary mediastinal B-cell lymphoma (PMBCL) who underwent front-line anthracycline based IC; patients with primary CNS lymphoma, PTLD, or a component of low-grade lymphoma were excluded. Time from diagnosis to treatment was defined as the time from date of first lymphoma-containing biopsy to the initiation of IC therapy; delayed therapy was defined as initiating therapy more than 14 days after diagnosis. Event-free survival was defined as time from diagnosis until progression, retreatment, or death due to any cause. EFS24 was defined as progression free status 24 months from diagnosis. Results: 720 patients with stage II-IV newly diagnosed DLBCL or PMBCL and treated with IC were enrolled in the MER from 2002-2012. Median age at diagnosis was 62 years (range 18-92) and 399 patients (55%) were male. 541 patients (75%) had stage III/IV disease and IPI at diagnosis was 0-1 in 166 patients (23%), 2 in 221 patients (31%), 3 in 222 patients (31%) and 4-5 in 111 patients (15%). 233 of 395 patients (59%) were GCB per Hans. At a median follow-up of 73 months, (range 0-163), 349 (49%) patients had an event and 267 patients died (37%); 37% of patients failed to achieve EFS24. Median time from initial lymphoma diagnosis to initiation of IC was 14 days (range 0-79, IQR=8-23). Patients with delay in therapy (>14 days from diagnosis) were more frequently female (50%, p=0.0051) and older than patients who initiated therapy within 14 days from diagnosis (median age at diagnosis of 63 years vs. 60 years, p=0.0008). Patients with delay in treatment initiation had universally less aggressive disease characteristics, including earlier stage, non-elevated LDH, 0-1 extranodal sites, absence of B-symptoms, lower ECOG PS, and lower IPI (see table). In addition, patients with delayed therapy were enriched for GCB subtype per Hans algorithm (p=0.056). Patients with initiation of therapy within 14 day of diagnosis had significantly worse outcome (EFS24 failure=44%) compared to patients with delayed time to initiation of therapy (EFS24 failure=28%, p<0.0001, figure), which remained significant after adjusting for either IPI or aaIPI (both p<0.005). The association between delayed time to initiation of therapy and EFS24 was observed in both GCB (EFS24 failure = 42% vs. 27%, p=0.019) and non-GCB (EFS24 failure = 46% vs. 27%, p=0.014) subsets by Hans. The lower event rate in delayed therapy patients results in an approximately 10% loss of power if the study was powered based on all patients regardless of timing from diagnosis to therapy. Conclusions: Patients with delayed therapy from diagnosis have less aggressive clinical characteristics compared to patients who initiate treatment within 14 days from diagnosis. Studies with a lengthy trial work-up including central pathology review period may be selecting patients with less aggressive disease based on the patient's ability to delay treatment to complete study enrollment requirements. Furthermore, selection of patients with less aggressive disease may result in underpowered studies due to a lower event rate (fewer events) than expected. This retrospective analysis would suggest that trials in DLBCL should consider streamlined enrollment and therapy initiation to avoid potential selection bias and loss of power. Further assessment of implications on trial design and outcomes by cell of origin in this setting is ongoing. Table Table. Figure Figure. Disclosures Maurer: Kite Pharma: Research Funding; Celgene: Research Funding. Ansell:BMS, Seattle Genetics, Merck, Celldex and Affimed: Research Funding. Nowakowski:Morphosys: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Research Funding.