Link, Brian K.

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 An association has been identified between the diagnosis-to-treatment interval (DTI) and prognostic clinical factors and outcomes in patients with previously untreated diffuse large B-cell lymphoma (DLBCL) (Maurer et al, JCO 2018). This association can result in inadvertent selection bias in clinical trials to exclude patients with aggressive disease due to the inability to delay treatment long enough to fulfill enrollment criteria, compromising the validity of clinical trial study results to the general population. A similar concern exists in the relapsed/refractory (r/r) DLBCL setting regarding patient selection bias against patients with aggressive disease requiring immediate treatment following relapse or progression. Here we examine the time from progression after immunochemotherapy (IC) to the initiation of first salvage chemotherapy and its association with outcome. Patients and Methods: Newly diagnosed patients were prospectively enrolled within 9 months of diagnosis in the University of Iowa/Mayo Clinic Lymphoma SPORE Molecular Epidemiology Resource (MER), now a subcohort of the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study, and followed for progression/relapse, retreatment, and death. This analysis includes patients with their first r/r DLBCL following frontline IC who initiated aggressive salvage chemotherapy as identified and included in a previous publication (Farooq et al, BJH 2017). The progression-to-treatment interval (PTI) was defined as the time in days from date of progression from IC to initiation of salvage therapy. The date of progression was defined as either a) the date biopsy was obtained for patients who had a biopsy to confirm progressive disease or b) the date of the scan or clinical examination indicating progression in patients who did not have a biopsy performed. Event-free survival (EFS) was defined as time from initiation of first salvage therapy to progression or relapse, initiation of new anti-lymphoma therapy, or death due to any cause; overall survival (OS) was defined as time from initiation of salvage therapy until death due to any cause. Results: 162 patients with r/r DLBCL enrolled in the MER from 2002-2012 who initiated aggressive salvage chemotherapy with intent to transplant and had confirmed dates for both progression after IC and start of salvage therapy were evaluated. Median age at first progression for these patients was 64 years (range 36-76) and 104 (64%) were male. Median time from diagnosis to first progression on IC was 6.7 months (IQR: 4.6-12.7). Initial salvage therapy was R-ICE (80%), R-DHAP (8%), rituximab, oxaliplatin, cytosine arabinoside, and dexamethasone (ROAD) (6%), and other (7%). At a median follow-up of 49 months from initiation of salvage therapy (IQR: 33-74), 116 patients had died (72%). Median PTI was 6 days (IQR: 2-13). 110 patients (68%) had biopsy confirmation of disease prior to initiating salvage therapy; median PTI was 2 days (IQR: 1-7) for patients who had biopsy confirmation vs. 7 days (IQR: 3-16) in patients without biopsy confirmation, Wilcoxon p=<0.0001. There was no difference in OS from initial salvage therapy between patients who did not have biopsy confirmation (HR=1.09, 95% CI: 0.74-1.60, p=0.68) compared to patients with biopsy confirmation. Patients with short PTI (0-6 days) had significantly worse overall survival from initiation of salvage therapy (median OS = 7.6 months, HR=2.10 (95% CI: 1.43-3.08) compared to patients who initiated therapy 7 or more days from progression (median OS = 29.7 months), logrank p<0.0001. This association remained consistent (HR=2.20, 95% CI: 1.48-3.26, p<0.0001) after adjusting for age and biopsy confirmation of progression. Short PTI was also associated with inferior response rate to initial salvage therapy (51% vs. 65%, p=0.058), lower rate of proceeding to transplant after initial salvage therapy (33% vs. 55%, p=0.0063), lower rate of being event-free 24 months from initial salvage therapy (16% vs 33%, p=0.011) and lower rate of ever proceeding to transplant (44% vs. 59%, p=0.057). Conclusions: A short progression-to-treatment interval is strongly associated with inability to proceed to transplant and inferior overall survival in r/r DLBCL. These results have implications for the design and interpretation of clinical trials in the relapsed/refractory setting. Figure. Figure. Disclosures Maurer: Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Research Funding. Ansell:Trillium: Research Funding; Merck & Co: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Pfizer: Research Funding; Celldex: Research Funding; Takeda: Research Funding. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cerhan:Nanostring: Research Funding; Celgene: Research Funding; Jannsen: Other: Scientific Advisory Board.

Abstract Background Age has long been recognized as a poor prognostic factor in diffuse large B-cell lymphoma (DLBCL) and more recently, a lower baseline quality of life (QOL) in patients with aggressive lymphomas has been associated with an inferior overall survival (OS) (Thompson et al, 2018). Older patients with DLBCL are a heterogeneous population and commonly have comorbid conditions. A concerted effort to identify prognostic factors specific to this population is needed, including QOL. Event free survival at 24 months (EFS24) is a well validated endpoint in DLBCL (Maurer et al, 2014) and is clinically relevant in older patients. We hypothesized that baseline clinical factors and QOL would be associated with EFS24 this patient group. Methods Newly diagnosed lymphoma patients were prospectively enrolled within 9 months of diagnosis into the University of Iowa/Mayo Clinic Lymphoma SPORE Molecular Epidemiology Resource (MER). Patients ≥70 years of age with DLBCL were utilized in this study. All pathology was reviewed by a lymphoma hematopathologist. Clinical variables were abstracted from the medical record. QOL was assessed at enrollment using a single item Linear Analogue Self-Assessment (LASA) and the 27-item Functional Assessment of Cancer Treatment-General questionnaire (FACT-G), which includes physical, social, emotional, and functional well-being domains. QOL scores were converted to a 0-100 scale to facilitate modeling. QOL was analyzed in patients who completed 80% of the FACT-G questions. Characteristics of the study population were compared using the Wilcoxon rank sum test. Odds ratios (ORs) and 95% confidence intervals (CI) were used to estimate the associations of clinical and continuous QOL variables with failure to achieve EFS24 using logistic regression models, with a stepwise approach to identify parsimonious multivariate models. Results A total of 389 patients ≥70 years were identified with DLBCL in the MER from 2002-2015; patient characteristics are described in the Table. In the entire study population, univariate predictors of EFS24 failure included age (OR per 10 years=1.85, 95% CI: 1.26-2.71), ECOG PS ≥2 (OR=4.78, 95% CI: 2.92-7.83), elevated LDH (OR=3.59, 95% CI: 2.27-5.65), stage III-IV (OR=1.94, 1.25-3.02), bulky disease (OR=2.86, 95% CI: 1.43-5.72), international prognostic index (OR=8.71 for IPI 5 vs IPI 0, 95% CI: 3.04-24.9), and receipt of an anthracycline (OR=0.25, 95% CI: 0.12-0.51), while none of the other variables in the Table, including the QOL variables, were statistically significant. In a stepwise multivariate analysis, only ECOG PS ≥2 (OR= 3.56, 95% CI: 2.09-6.06) and elevated LDH (OR=2.86, 95% CI: 1.78-4.60) remained significant predictors of EFS24 failure. QOL data were available on 220 patients, with 120 completing QOL questionnaires prior to receipt of chemotherapy. Compared to participants who completed their FACT-G before the initiation of chemotherapy, the median FACT-G physical (85.7 v. 71.4, p=0.005) and functional (71.4 vs 57.1, p=0.008) scores were lower in participants completing FACT-G after initiation of therapy, were higher on FACT-G emotional (79.2 vs 83.3, p=0.03), and showed no differences on FACT-G social (89.3 vs 91.7, p=0.60) or FACT-G total score (78.2 vs 74.1, p=0.17). Given these differences, we restricted the QOL analysis to those with pre-treatment data. In univariate analysis, the LASA score (OR= 0.98, 95% CI: 0.84-1.14), the FACT-G total (OR=0.99, 95% CI: 0.96-1.01), physical (OR=0.98, 95% CI: 0.97-1.00), social (OR=1.00, 95% CI: 0.98-1.03), emotional (OR= 1.00, 95% CI: 0.98-1.02), and functional (OR=0.99, 95% CI: 0.98-1.01) scores were not associated with EFS24 failure. In a stepwise multivariate analysis of clinical variables in patients with pretreatment QOL scores, only ECOG PS ≥2 (OR=3.56, 95% CI: 1.30-9.72) and female sex (OR=0.37, 95% CI: 0.16-0.85) were associated with failure to achieve EFS24. Conclusions In patients aged 70 years and older, ECOG PS and LDH were the strongest independent predictors of failure to achieve EFS24. As expected, physical and functional scores were lower in patients who completed their QOL after initiation of treatment. Restricting the analysis to patients with pre-treatment data, QOL was not associated with failure to achieve EFS24. Additional studies are needed to identify the most robust clinical predictors of EFS24, while QOL does not appear to be an important predictor of EFS24. Disclosures Reagan: Seattle Genetics: Research Funding. Maurer:Morphosys: Research Funding; Celgene: Research Funding; Nanostring: Research Funding. Cerhan:Celgene: Research Funding; Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board.

Abstract PURPOSE Urgency to initiate therapy has to be weighed against the time required for screening and consenting to enroll a patient onto a clinical trial. Exclusion of patients with rapidly progressive or symptomatic disease may lead to selection of patients with less aggressive disease. We recently identified that a short diagnosis to treatment interval (DTI) is associated with adverse clinical factors and inferior outcome in patients with diffuse large B-cell lymphoma (DLBCL) (Maurer et al, JCO 2018); shorter time to treatment was also found to be associated with outcome in other aggressive lymphomas, including mantle cell lymphoma (MCL), in the National Cancer Database (Olszewski et al, BJH 2018). Here we assess the association of DTI with clinical variables and outcome in MCL from an observational cohort with validation in patients enrolled on an NCTN clinical trial. PATIENTS AND METHODS Newly diagnosed patients with MCL were prospectively enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE Molecular Epidemiology Resource (MER), now a subcohort of the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study. Patients initially managed with observation were excluded. DTI was defined as the time in days from date of first lymphoma-containing biopsy to the initiation of therapy. Associations of DTI with clinical factors and outcome were examined using a 14 day split based on the previous MER study of DTI in DLBCL. Odds ratios (OR) and Cox model hazard ratios (HR) are reported. Outcome was assessed using event-free survival (EFS) where events were defined as progression/relapse, initiation of new anti-lymphoma therapy, or death due to any cause. A validation cohort was assembled from patients enrolled in CALGB (Alliance) clinical trial 50403. Protocol therapy was high dose chemotherapy with autologous hematopoietic stem cell transplantation (ASCT) consolidation and post-ASCT rituximab followed by bortezomib as either consolidation or maintenance. DTI was defined as time from diagnosis to study registration and outcome was assessed using progression-free survival (PFS) as defined on the clinical trial. RESULTS 271 patients with MCL enrolled in the MER from 2002-2015 and initiated treatment within 100 days of diagnosis. Median age at diagnosis was 64 years (range 36-76), 211 (78%) were male, and 92% were stage III-IV; MIPI was Low (41%), Intermediate (36%) and High (23%). Induction therapy was R-CHOP based (50%), B-R based (16%), HyperCVAD based (8%), 2-CDA based (11%), and other (15%). Median EFS of the cohort was 41 months (95% CI: 34-46). Median DTI was 26 days (IQR: 14-38) and 28% enrolled within 14 days of diagnosis, exhibiting a longer DTI than DLBCL patients enrolled in the MER during the same time period. Short DTI (0-14 days) was associated with adverse clinical factors including ECOG PS 2-4 (OR=5.74, 95% CI: 2.51-13.1, p<0.0001), elevated LDH (OR=2.30 95% CI: 1.25-4.22, p=0.0072), and higher MIPI score (OR=1.48, 95% CI: 1.04-2.07, p=0.025) but was not significantly associated with age, sex, B-symptoms, or stage (all p>0.30). Short DTI was also associated with inferior EFS (HR=1.78, 95% CI: 1.27-2.49, p=0.0008) which remained significant after adjusting for MIPI score (HR=1.72, 95% CI: 1.23-2.41, p=0.0016). In the validation cohort, 144 patients enrolled on 50403 within 100 days of diagnosis from 2006-2010. Median age at diagnosis was 59 years (range 29-69), 77% were male, and 97% were stage III-IV; MIPI was Low (51%), Intermediate (31%) and High (17%). Median PFS of the cohort was 84 months (95% CI: 50-109). Median DTI was 35 days (IQR: 22-46) and 11% enrolled within 14 days of diagnosis. Short DTI (0-14 days) was associated with PS (OR=9.00, 95% CI: 1.18-69.0, p=0.034) and) higher MIPI score (OR=2.09, 95% CI: 1.08-4.04, p=0.029) but not elevated LDH (OR=1.27, 95% CI: 0.43-3.74, p=0.66). Short DTI was associated with inferior PFS (HR=2.21, 95% CI:1.19-4.09, p=0.011) which remained clinically significant after adjusting for MIPI score (HR=1.85, 95% CI: 0.98-3.47, p=0.056). CONCLUSION A short diagnosis-to-treatment interval is strongly associated with adverse clinical factors and poor outcome in newly diagnosed MCL in the MER. Clinical trials are encouraged to facilitate enrollment of patients with short DTI to avoid potential selection bias. Support: U01 CA195568, P50 CA097274, U10CA180821, U10CA180882; ClinicalTrials.gov Identifier: NCT00310037 (CALGB 50403) Figure. Figure. Disclosures Maurer: Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Research Funding. Kaplan:Bayer Pharmaceuticals: Consultancy. Cohen:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Pharmacyclics: 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; Bristol-Myers Squibb: Research Funding; AbbVie: 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; 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; BioInvent: Consultancy; Takeda: Research Funding. Martin:Gilead: Consultancy; Kite: Consultancy; Seattle Genetics: Consultancy; AstraZeneca: Consultancy; Janssen: Consultancy; Bayer: Consultancy. Kahl:Abbvie: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy; Acerta: Consultancy; Juno: Consultancy; Celgene: Consultancy; Genentech: Consultancy; Seattle Genetics: Consultancy; CTI: Consultancy; ADC Therapeutics: Consultancy. Bartlett:ImaginAB: Research Funding; Bristol-Meyers Squibb: Research Funding; Novartis: Research Funding; Immune Design: Research Funding; Janssen: Research Funding; Merck & Co: Research Funding; Forty Seven: Research Funding; Novartis: Research Funding; Pharmacyclics: Research Funding; Affimed: Research Funding; Astra Zeneca: Research Funding; Pharmacyclics: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Millennium: Research Funding; Genentech: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: 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. Leonard:Karyopharm: Consultancy; Biotest: Consultancy; Bayer: Consultancy; Pfizer: Consultancy; ADC Therapeutics: Consultancy; Novartis: Consultancy; AstraZeneca: Consultancy; Juno: Consultancy; BMS: Consultancy; Sutro: Consultancy; MEI Pharma: Consultancy; Genentech/Roche: Consultancy; Celgene: Consultancy; Gilead: Consultancy; United Therapeutics: Consultancy.

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 Abstract 775 Introduction: WW has been an initial strategy for advanced stage FL because randomized trials showed no clear benefit for immediate initiation of therapy with single agent alkylators when compared to deferring therapy (Brice, JCO 1997; Ardeshna, Lancet 2003), although a recent trial raises questions about WW in the era of rituximab (R) based frontline therapies (Ardeshna, ASH Meeting 2010). Methods: The NLCS is a prospective, multicenter, observational study collecting data on 2,738 newly diagnosed pts with FL diagnosed from 2004–2007 at 265 US sites (80% non-academic). Initial management decisions were made by the treating physician and were categorized as WW (for pts who did not receive therapy in the 90 period following diagnoses and were coded by physicians as WW) or active therapy (AT) including: R alone, R-chemotherapy (RChemo), or other. Baseline clinical factors and treatment setting were compared for WW and AT pts using multivariable logistic regression. Kaplan-Meier (KM) estimation and Cox models were used to evaluate progression-free survival (PFS), time to 2nd and 3rd line management strategy (TT2, TT3), transformation-free survival (TFS), PFS following 1st AT, and overall survival (OS). Due to differences between WW and AT groups, adjusted Cox regression models are presented for the primary analysis of study endpoints controlling for sex, community vs. academic practice site, FL grade, and FLIPI. All time to event analyses were calculated from the 90 day period following diagnosis to allow enrollment in WW, and PFS was calculated from the starting point to the clinician's recording of progressive disease (PD) or death. Results: Among 1,737 pts presenting with stage III/IV FL in the analysis population, 237 underwent WW and 1,500 received AT immediately following diagnosis including: 241 pts treated with R, 1046 with RChemo, 26 with radiation, and 187 other therapies. Multivariable logistic regression demonstrated that the following pt characteristics were predictive of selection of WW rather than initial AT: age > 60 years, no B-symptoms, FL grade 1 or 2, ECOG PS = 0, ≤1 extranodal sites involved, and LDH ≤ULN (all p < 0.05). Median PFS and TT2 were 27 and 35 months for WW, and 64 months and not reached for AT. With a median follow-up of 55 months, 17% of WW pts and 19% of AT pts have died, with no significant difference in OS between WW and AT (p = 0.31). Compared with WW, RChemo improved PFS: adjusted Hazard Ratio (HR) = 0.36, TFS: HR=0.65, TT2: HR=0.48, and TT3: HR=0.53, all p<0.01. For most of the 145 WW pts that later initiated an AT, PD was recorded as the reason for treatment (83%). ATs following WW were: R (51, 35%), RCVP (21, 14%), RCHOP (16, 11%), R + other chemo (23, 16%), investigational (15, 10%), chemo alone (9, 6%), radiation (8, 6%), BMT (1, 1%), or other therapy (1, 1%). The median PFS for R was 42 months when given at diagnosis and 55 months when given following WW. The median PFS for RChemo was 71 months when given at diagnosis and 37 months when given following WW. After adjustment for FLIPI, FL grade, sex, practice setting, and type of treatment, WW adversely affected PFS following 1st AT, H=2.02, p <0.0001. Conclusions: FL pts in the US who undergo initial WW are treated at a median of nearly 3 years. Median PFS following RChemo, but not R is shorter when utilized after period of WW than at diagnosis – albeit in different clinical circumstances. Additional follow-up is needed to assess the tradeoff of this time without therapy with as yet no observable differences in OS. Disclosures: Sinha: CELGENE: Research Funding. Friedberg:Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees. Link:Genentech: Consultancy. Flowers:Spectrum: Consultancy, Research Funding; Millennium/Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Genentech/Roche (unpaid): Consultancy; Novartis: Research Funding; Seattle Genetics: Consultancy.

Abstract Abstract 97 Background: There is no consensus or standard of care for front-line therapy for FL as demonstrated by our initial publication of the National LymphoCare Study (NLCS) showing that strategies used in newly diagnosed FL patients (pts) in the US included: watchful waiting (17.7%), rituximab (R) with chemotherapy (51.9%), R alone (13.9%), radiation therapy (5.6%), chemotherapy (3.2%), or a clinical trial (6.1%). Given the lack of observational data comparing the effectiveness of front-line R-chemotherapy regimens, we examined the outcomes for patients with stage III/IV FL receiving R with cyclophosphamide, vincristine, and prednisone (RCVP), R with cyclophosphamide, doxorubicin, vincristine, and prednisone (RCHOP), or R with a fludarabine-based regimen (RFlu) as first-line therapy. Methods: The NLCS is a prospective, multicenter, observational study collecting data on 2,738 previously untreated patients (pts) with FL diagnosed from 2004 to 2007 at 265 sites in the US. Initial management decisions were made by the treating physician without protocol-specified treatment assignments. Descriptive statistics for the baseline characteristics of pts who received RCVP, RCHOP, and RFlu were compared using Pearson Chi-square tests. A generalized logistic model was used to identify baseline factors of clinical interest (FLIPI, sex, practice setting [academic vs. community]) that were correlated with treatment. Kaplan–Meier estimation was used to evaluate progression-free survival (PFS) and overall survival (OS) for the treatment regimens; comparisons for the 2-year landmark estimates were obtained using a Wald statistic. PFS was defined as the number of days from diagnosis up to and including the date of progressive disease (PD) as assessed by the treating physician or death from any cause. Pts who had not yet experienced PD at the time of analysis were censored at the date of the most recent response assessment. To evaluate the effects of treatment on PFS and OS, Cox proportional hazards models were used controlling for FLIPI, sex, community or academic practice setting, and maintenance R or observation following treatment. Results: Of the 2,738 pts enrolled in NLCS, 926 pts were identified as having stage III/IV FL and having received the regimens of interest. Within this cohort 60% received RCHOP (n=558), 27% received RCVP (n=247) and the remaining 13% received RFlu (n=121). Baseline characteristics were correlated with induction treatment and whether a patient received subsequent R maintenance. Women (odds ratio [OR]=1.50, 95%CI 1.05–2.13) and pts aged >60 years (OR=2.36, 95%CI 1.64–3.38) more commonly received RCVP than RCHOP, and pts with LDH > upper limit of normal (OR=1.75, 95%CI 1.02–3.03) more commonly received RCHOP than RFlu. A greater % of pts receiving RCVP (61%) had poor-risk FLIPI (3–5) vs. RCHOP (49%) or RFlu (44%). In this cohort, 60% of RCVP, 43% of RCHOP, and 46% of RFlu pts received maintenance R. The overall response rates for RCVP, RCHOP, and RFlu were 88%, 94%, and 96%, respectively, and 2-year PFS was 72% (95% CI 66–78%) for RCVP, 78% (95%CI 74–81%) for RCHOP, and 76% (95%CI 67–-83%) for RFlu. There were no significant differences in PFS between treatments after adjustment (p= 0.07). However, with a median follow-up of 58 months there were significant differences in unadjusted OS (p=0.03), with 2-year OS probabilities of 88% (95%CI 84–92%) for RCVP, and 91% (84–95%) for RFlu, and 94% (92–96%) for RCHOP (Figure A). After adjustment for sex, FLIPI, practice setting, and maintenance use, the OS benefits of RCHOP persisted over RCVP HR=1.67 (95%CI 1.15–2.42) but not RFlu HR=0.94 (0.53–1.68). The benefits of RCHOP were even more pronounced in poor risk FLIPI pts (Figure B). Conclusions: First-line R-chemotherapy regimens in clinical practice have high overall response rates and high 2-year PFS and OS. With 4.75 years of follow-up in this large pt cohort, these regimens appear similar in response rates and early PFS and OS with suggestions that RCHOP may provide benefits over RCVP particularly for poor risk patients. Disclosures: Sinha: Celgene: Research Funding. Friedberg:Genentech: Consultancy; astellas: ; Lilly:; Abbott/Trubion:; Seattle Genetics: Honoraria; Cephalon: Consultancy. Hirata:Roche: Equity Ownership; Genentech Inc/Roche: Employment. Flowers:Seattle Genetics: Consultancy; Millennium/Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Genentech/Roche (unpaid): Consultancy; Novartis: Research Funding; Spectrum: Consultancy, Research Funding.

Abstract Abstract 429 BACKGROUND: While standard clinical prognostic factors such as those included in the International Prognostic Score (IPS) predict outcome in cHL patients, predicting the outcome of patients might be further refined using biological factors. We therefore tested whether pretreatment serum cytokines, that measure the biological activity of the tumor as well as the host response, could provide additional prognostic information in cHL patients. METHODS: Newly diagnosed cHL patients were prospectively enrolled in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER). Serum cytokines were measured from pretreatment blood draws using a multiplex ELISA (Invitrogen, Camarillo, CA). Thirty cytokines, including pro-inflammatory, Th1 and Th2 associated cytokines, were analyzed using the Luminex-100 system Version 1.7 (Luminex, Austin, TX). Data analysis was performed using the MasterPlex QT 1.0 system (MiraiBio, Alameda, CA). The assay was also performed on research serum draws from 50 non-lymphoma epidemiology controls enrolled on a corresponding lymphoma etiology case-control study. The upper limit of normal for each cytokine was defined as the 95th percentile from the control distribution. Clinical data were abstracted using a standard protocol and all patients were followed systematically for event-free (progression, retreatment, or death due to any cause) and overall survival (EFS and OS, respectively). Cox proportional hazards models were used to evaluate the association between cytokines and outcome. RESULTS: 140 HL patients with cHL diagnosed between September 2002 and February 2008 with available pretreatment serum were included. The median age was 40 years (range 18–89) and 53% were male. Seventy-seven patients (55%) had limited stage disease and 63 (45%) had advanced disease. One hundred and twenty one patients (86%) were treated with ABVD chemotherapy, while the remainder received the Stanford V regimen (9%), BEACOPP (4%) or MOPP chemotherapy (2%). At a median follow-up of 47 months (range 0–87), 25 patients (18%) had an event and 16 patients had died (11%). The serum levels of 12 cytokines (EGF, FGFb, GCSF, HGF, IL-6, IL-8, IL-12, IL-2R, IP-10, MIG, TNFa and VEGF) were significantly higher in cHL patients than controls. When correlated with clinical factors, IL-2R, IP-10, MIG, IL-6 and HGF were associated with an increased sedimentation rate, B-symptoms, advanced stage and splenic involvement. Elevated IL-8 levels were associated with bulky disease. Elevated levels of HGF, IL-6, IL-8, IL-2R, IP-10 and MIG were all associated with a poorer EFS, however only IL-2R (p=0.002) and IL-6 (p<0.001) were independently prognostic for both EFS and OS. Furthermore, using IL-6 and IL-2R in a 2-cytokine model (see Figure), patients with elevation of both cytokines had a dramatically greater likelihood of early relapse and death than those with normal levels or elevations of only one of the cytokines (1-year EFS 40% compared to 97% and 93% respectively, p<0.0001; 2-year OS 49% compared to 98% and 95%, p<0.0001). While elevated IL-6 and IL-2R levels correlated with the IPS (p=0.002), this 2-cytokine model remained independently predictive of prognosis. In fact, when only good risk patients (IPS 0–3) were considered, the 2-cytokine model remained predictive of patients at risk for early relapse (1-year EFS 54% versus 95% and 97%, p<0.0001). CONCLUSION: Elevated pretreatment serum cytokines are associated with an increased likelihood of disease relapse and an inferior survival in patients with cHL. The pretreatment cytokine profile, particularly serum levels of IL-6 and IL-2R, may identify cHL patients at high risk for early disease relapse who may benefit from novel therapeutic approaches. Disclosures: No relevant conflicts of interest to declare.

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% - -