ALBERT

Description: Introduction: Smoking is a potential risk factor for the development of non-Hodgkin lymphoma (NHL), and prior studies have reported inferior survival in tobacco users with certain subtypes of the disease (Taborelli et al, BMC Cancer, 2017; Ollberding et al, Br J Haematol, 2013). For instance, tobacco smokers with NHL had an inferior overall survival (OS) compared to non-smokers in a series of 471 patients who were managed up front with either chemotherapy (68%), radiation (27%), or observation, and this appeared to be most pronounced in patients with follicular lymphoma and in those with a 20+ pack year smoking history (Geyer et al, Cancer, 2010). The impact of tobacco use on survival specifically in patients with mantle cell lymphoma (MCL) has not been well studied. We conducted a multicenter study in MCL and evaluated the prognostic impact of tobacco use. Methods: We included patients with MCL from 12 sites who were ≥18 years old and for whom smoking status was known at the time of diagnosis. Cases were evaluated for reported smoking status at the time of diagnosis (active smoker, prior smoker, or never smoker) and standard baseline clinical prognostic data were obtained for each patient. Descriptive statistics were generated for these characteristics and were then compared across smoking status using chi-squared tests, Fisher's exact tests, or ANOVA, where appropriate. Overall survival (OS) and progression free survival (PFS) were estimated using the Kaplan-Meier method, and were compared using log-rank tests. Results: Of 946 included patients, 456 (48.2%) reported never using tobacco, 360 (38.7%) reported prior tobacco use, and 130 (13.7%) reported active tobacco use at the time of diagnosis. Median age was 59 in the active smoker group, 65 in prior smokers, and 61 in never smokers (p 〈 0.001). Any major medical comorbidity (defined as the presence of CAD, CHF, diabetes, CKD, ESRD, COPD, DVT, prior malignancy, or cirrhosis) was present in 59 (45.4%) of the active smokers, 143 (39.7%) of the prior smokers, and 140 (30.7%) of the never smokers (p = 0.002). Intensive induction regimens were used in 58.2% of active smokers, 47.2% of prior smokers, and 58.4% of never smokers (p=0.007). There were no significant differences between groups in regards to sex, race, ECOG performance status, Ann Arbor stage, time to first treatment, and use of auto transplant in first remission. Patients with no prior history of tobacco use were less likely to have a high risk MIPI score at diagnosis (26% high risk) compared to prior smokers (39.5%) and active smokers (32.5%, p=0.019). With a median follow up of 3.5 years after diagnosis, there was no significant difference between the 3 groups with regards to PFS or OS (Figure 1). Five-year OS in the never smoker group was 79.8% (95% CI: 74.8%, 83.9%) vs 75.1% (64.5%, 82.9%) in the active smoker group, and 80.6% (74.6%, 85.3%) in the prior smoker group (log rank p = 0.4079). Five- year progression free survival was 50.4% (44.6%, 56.0%) in the never smoker group, 42.5% (32.2%, 52.5%) in the active smoker group, and 50.2% (43.5%, 56.6%) in the prior smoker group (log rank p= 0.3595). Conclusions: Our data suggest that active or prior smoking does not significantly impact OS or PFS in patients with MCL. This study is limited by the fact that amount of current or former tobacco use was not available and it is not known how many current tobacco users ultimately stopped smoking during the course of their treatment. Future studies should incorporate more specific information regarding smoking history including pack-years and time between discontinuation of tobacco use and date of diagnosis. While tobacco use and other modifiable cardiovascular risk factors should be addressed as appropriate for all patients with MCL, current and former tobacco users can still achieve prolonged PFS and OS and may be candidates for intensive treatments after consideration of their other comorbidities and disease-specific risk factors. Disclosures Calzada: Seattle Genetics: Research Funding. Kolla:Amgen: Equity Ownership. Bachanova:Gamida Cell: Research Funding; GT Biopharma: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Incyte: Research Funding; Celgene: Research Funding; Novartis: Research Funding; Kite: Membership on an entity's Board of Directors or advisory committees. Gerson:Seattle Genetics: Consultancy; Abbvie: Consultancy; Pharmacyclics: Consultancy. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Mundipharma: Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Takeda: Research Funding; Merck: Research Funding; Mundipharma: Honoraria; Bayer: Consultancy, Research Funding; Seattle Genetics: Honoraria, Research Funding. Danilov:Celgene: Consultancy; Abbvie: Consultancy; TG Therapeutics: Consultancy; Bayer Oncology: Consultancy, Research Funding; Gilead Sciences: Consultancy, Research Funding; Janssen: Consultancy; AstraZeneca: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Aptose Biosciences: Research Funding; Bristol-Meyers Squibb: Research Funding; MEI: Research Funding; Pharmacyclics: Consultancy; Verastem Oncology: Consultancy, Other: Travel Reimbursement , Research Funding; Curis: Consultancy; Takeda Oncology: Research Funding; Seattle Genetics: Consultancy. Grover:Seattle Genetics: Consultancy. Karmali:Astrazeneca: Speakers Bureau; Takeda, BMS: Other: Research Funding to Institution; Gilead/Kite; Juno/Celgene: Consultancy, Speakers Bureau. Hill:Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Amgen: Research Funding; TG therapeutics: Research Funding; AstraZeneca: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celegene: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Research Funding; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Ghosh:Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; Seattle Genetics: Consultancy, Speakers Bureau; Genentech: Research Funding; Celgene: Consultancy, Research Funding, Speakers Bureau; Forty Seven Inc: Research Funding; Gilead/Kite: Consultancy, Speakers Bureau; Spectrum: Consultancy, Speakers Bureau; AbbVie: Consultancy, Speakers Bureau; T G Therapeutics: Consultancy, Research Funding; Astra Zeneca: Speakers Bureau. Park:BMS: Consultancy, Research Funding; Rafael Pharma: Membership on an entity's Board of Directors or advisory committees; G1 Therapeutics: Consultancy; Teva: Consultancy, Research Funding; Gilead: Speakers Bureau; Seattle Genetics: Research Funding, Speakers Bureau. Epperla:Pharmacyclics: Honoraria; Verastem Oncology: Speakers Bureau. Hamadani:Pharmacyclics: Consultancy; ADC Therapeutics: Consultancy, Research Funding; Merck: Research Funding; Celgene: Consultancy; Janssen: Consultancy; Medimmune: Consultancy, Research Funding; Sanofi Genzyme: Research Funding, Speakers Bureau; Otsuka: Research Funding; Takeda: Research Funding. Kahl:TG Therapeutics: Consultancy; BeiGene: Consultancy; Seattle Genetics: Consultancy; ADC Therapeutics: Consultancy, Research Funding. Martin:Janssen: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy; Teneobio: Consultancy; Celgene: Consultancy; Karyopharm: Consultancy. Flowers:Karyopharm: Consultancy; Denovo Biopharma: Consultancy; Burroughs Wellcome Fund: Research Funding; AbbVie: Consultancy, Research Funding; Gilead: Consultancy, Research Funding; Spectrum: Consultancy; AstraZeneca: Consultancy; Pharmacyclics/Janssen: Consultancy, Research Funding; Bayer: Consultancy; Acerta: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Optimum Rx: Consultancy; Millenium/Takeda: Research Funding; Eastern Cooperative Oncology Group: Research Funding; National Cancer Institute: Research Funding; V Foundation: Research Funding; BeiGene: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; TG Therapeutics: Research Funding. Cohen:Genentech, Inc.: Consultancy, Research Funding; Janssen Pharmaceuticals: Consultancy; Takeda Pharmaceuticals North America, Inc.: Research Funding; Gilead/Kite: Consultancy; LAM Therapeutics: Research Funding; UNUM: Research Funding; Hutchison: Research Funding; Astra Zeneca: Research Funding; Lymphoma Research Foundation: Research Funding; ASH: Research Funding; Seattle Genetics, Inc.: Consultancy, Research Funding; Bristol-Meyers Squibb Company: Research Funding.

Description: Introduction: Time to treatment (TTT) is an important prognostic factor in patients with newly diagnosed diffuse large B-cell lymphoma (Maurer et al JCO 2018) where patients who initiate therapy quickly after diagnosis have an inferior event free survival compared to those who do not require such immediate treatment initiation. More recently, TTT has shown to be associated with adverse clinical factors and inferior outcomes in mantle cell lymphoma (MCL; Maurer, et al ASH, 2018). However, there is a paucity of data on the impact of TTT on overall survival (OS). We sought to validate these findings and to evaluate the impact of TTT on survival outcomes in newly diagnosed patients with MCL. Methods: We included patients from 12 medical centers in the United States with MCL diagnosed between January 1, 2000, and January 1, 2018, who had information on the TTT and initiated treatment within 60 days of diagnosis (to exclude patients whose treatment was purposefully deferred). TTT was defined as the time in days from first lymphoma diagnosis to initiation of therapy. Patients who received treatment within 14 days were categorized into short TTT group. We compared differences between the two groups (TTT 14 days and ≤ 60 days, longer TTT group) using chi-squared test, Fisher's exact tests, or ANOVA tests as appropriate. OS was defined as the time from diagnosis to death or last follow-up. Patients not experiencing an event were censored at their last known follow-up. OS was determined using the Kaplan-Meier method, and univariable and multivariable models were developed to identify predictors of OS. Results: Of 1,168 patients with newly diagnosed MCL, seven hundred fifty-five patients met the inclusion criteria and were included in this analysis, including 205 (27%) with short TTT and 550 (73%) with longer TTT. Median time to treatment was 7 days (range, 0-14) for the short TTT group vs 31 days for the longer TTT group (range, 15-60 days). The median age for the entire cohort was 63 years, 75% of patients were male, and 93% of patients had ECOG 0-1. The proportion of patients with stage 4 disease (93 vs 86%, p=0.015), elevated LDH (58 vs 39%, p3 cytogenetic abnormalities (29 vs 14%, p=0.005), B symptoms (47 vs 29%, p

Description: Introduction Mantle cell lymphoma (MCL) frequently impacts elderly patients (median age of diagnosis is 68), and management of these patients can be difficult due to the presence of comorbidities in this group. Presence of comorbidities is associated with inferior outcomes in many hematologic malignancies but there has not been a systematic assessment of comorbidities in MCL. We utilized the Charlson Comorbidity Index (CCI) to describe the presence of comorbidities in MCL patients and to explore their impact on patient outcomes. Methods We included patients with MCL evaluated at Emory between January 1, 2000 and December 31, 2016. Patients with limited or inadequate follow-up or for whom data to determine the CCI were inadequate were excluded. We determined the CCI at the time of initiation of treatment for all patients with MCL and excluded "lymphoma" from this calculation. Patients were categorized into severity classes based on their summed scores. The median score of 1 was used to delineate the "low" and "high" CCI groups. For each group (low and high CCI), we evaluated baseline demographic, clinical and treatment characteristics and identified specific toxicity-related outcomes including: failure to complete induction chemotherapy, unplanned hospitalizations, or treatment related toxicities. Progression-free (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method, and we assessed for the impact of CCI score on PFS and OS using Cox proportional hazards models. Results Of 178 patients with MCL, 129 were male (73.3%) and median age was 61 (32-86). One hundred forty patients (86.4%) had stage IV disease. Among the 99 reported values, 31 patients (31.3%) had an elevated LDH, and ECOG PS was 0 in 47 patients, 1 in 66 patients, and 2-4 in 8 patients. Induction therapy was R-HyperCVAD (n=79; 45.4%), R-CHOP (n=49; 28.2%), BR (n=13; 7.5%) RCHOP/RDHAP (n=3; 1.7%) and Other (N=29; 16.7%). The CCI scores for the whole cohort were 0 in 78 pts (43.8%), 1 in 57 pts (32%), 2 in 24 pts (13.5%) and 3+ in 19 pts (10.7%; See Figure 1). One hundred thirty-five patients (75.8%) patients had a low CCI score (0-1) and 43 patients (24.2%) had a high CCI score (〉1). Compared to patients with a low CCI, those with high CCI were older (median 67 years vs 59 years, p 0.3). Conclusion CCI score was not shown to be a reliable predictor of unplanned hospitalizations, premature cessation of chemotherapy, or OS in our cohort, although many of our patients had very limited comorbidities. These results suggest that patients with limited comorbid conditions can likely be successfully managed with appropriate supportive care and should be considered for the most effective regimens. Future studies with a larger patient population with increased number of comorbidities may improve our ability to detect the impact of CCI on these outcomes and explore the relative contribution of specific comorbidities in MCL. Disclosures Calzada: Seattle Genetics: Research Funding. Flowers:BeiGene: Research Funding; Burroughs Wellcome Fund: Research Funding; Abbvie: Consultancy, Research Funding; Abbvie: Research Funding; Pharmacyclics/ Janssen: Consultancy; Millennium/Takeda: Research Funding; Gilead: Consultancy; Genentech/Roche: Consultancy; Janssen Pharmaceutical: Research Funding; Genentech/Roche: Research Funding; OptumRx: Consultancy; Acerta: Research Funding; Gilead: Research Funding; Denovo Biopharma: Consultancy; Celgene: Research Funding; Bayer: Consultancy; Spectrum: Consultancy; Karyopharm: Consultancy; National Cancer Institute: Research Funding; TG Therapeutics: Research Funding; Eastern Cooperative Oncology Group: Research Funding; Pharmacyclics: Research Funding; V Foundation: Research Funding. Cohen: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; Infinity Pharmaceuticals: 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; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: 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; Novartis: 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; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Takeda: Research Funding; BioInvent: Consultancy; BioInvent: Consultancy; Seattle Genetics: 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.

Description: Introduction: While most patients with mantle cell lymphoma (MCL) receive therapy shortly after diagnosis, a subset of patients with indolent-behaving disease can safely defer treatment (Calzada et al, 2018). In this subgroup, a lack of evidence to support the decision-making behind the choice of therapy has led to a wide diversity in treatments. We evaluated the importance of treatment intensity in patients with MCL who defer initial therapy. Methods: We included patients ≥ 18 years old with MCL from 11 academic centers and defined the deferred subgroup as patients who started therapy ≥ 90 days after diagnosis. Patients who received high dose cytarabine as part of their induction or autologous stem cell transplantation (ASCT) in first remission were considered to have received intensive therapy while all other approaches were non-intensive. We identified differences between the baseline characteristics of the two groups using Fisher's exact tests, chi-squared tests, and t-tests as appropriate. We calculated progression-free (PFS) and overall survival (OS) from the date of diagnosis using the Kaplan-Meier method and compared the two groups using the log-rank test. Univariate and multivariate Cox proportional hazards models were performed for PFS and OS. Results: Of 968 identified patients with MCL, 233 did not initiate therapy within 90 days of diagnosis and were considered deferred. Deferred patients had a lower Ann Arbor stage (p

Description: Introduction: Prior series have identified CD30 expression by immunohistochemistry (IHC) is associated with improved overall survival (OS) in patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL; 5-year OS: 79% vs 59% in CD30(-) patients, Hu et al, Blood 2013). It is unclear, however, whether CD30(+) status is retained throughout the course of the disease. Conversely, it is also unknown whether patients with CD30(-) tumors at diagnosis may present with CD30(+) disease upon relapse. As there is a currently approved antibody-drug conjugate targeting CD30, brentuximab vedotin, an improved understanding of CD30 expression in DLBCL may inform therapy options for relapsed (and potentially newly diagnosed) patients. Here, we evaluated patients with relapsed DLBCL with available tissue samples, including those with paired tissue samples from the time of diagnosis to assess for CD30 status for the duration of their disease course. Methods: This cohort included patients ≥ 18 years old with relapsed DLBCL for whom biopsy samples and clinical data were available. Tissue samples at diagnosis and from time of relapse were collected from our institution's pathology archive, and IHC-staining for CD30 expression was performed on all available involved tissue. CD30 status was assessed using a comprehensive form including assessment of percentage of CD30(+) cells and distribution of staining within each cell. Both neoplastic and surrounding non-neoplastic cells were evaluated. All assessment of CD30 staining was completed by one hematopathologist. We also collected comprehensive clinical, demographic and pathologic data for each patient. Results: We identified 25 patients with relapsed/refractory DLBCL with available tissue samples from the time of relapse, including 12 patients with available paired diagnostic tissue. Among all patients, the median age at diagnosis was 58 years (range 34-76), 48% were male, 56% were stage III/IV, and 62% presented with B-symptoms. Eighty-eight percent of patients received R-CHOP as frontline therapy. Cell of origin by the Hans algorithm was germinal center B-cell-like (GCB) for 9 patients, non-GCB for 5 patients, and unknown for 11 patients. After pathologic review, all 25 samples were CD30-negative at relapse, including all 12 paired samples which were CD30-negative at diagnosis and relapse, suggesting that CD30 expression does not appear to be acquired at the time of relapse in DLBCL patients who present with CD30-negative disease. Conclusions: This retrospective, single-center cohort analysis suggests that patients with newly diagnosed DLBCL with tumors negative for CD30 expression retain CD30-negative status at relapse. Thus, assaying biopsies at relapse for CD30 positivity by IHC to investigate candidacy for salvage treatment with brentuximab vedotin in a patient with a tumor previously CD30(-) may be of limited value. Alternative computer-aided methods to assess CD30 expression in samples that are considered negative by conventional IHC may better identify the presence of CD30 among patients with relapsed DLBCL. Disclosures Calzada: Seattle Genetics: Research Funding. Flowers:Seattle Genetics: Research Funding; Optum Rx, Seattle Genetics, Genentech/Roche: Consultancy; Spectrum, Janssen, Infinity, AbbVie, Acerta, Pharmacyclics, TG Therapeutics: Research Funding; Celgene Corporation: Consultancy, Honoraria; Millennium: Consultancy, Research Funding; Gilead: Consultancy, Research Funding. Cohen:Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium/Takeda: 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; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity: 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; Bristol-Myers Squibb: Research Funding.

Description: Background: Early progression of disease (POD) in patients (pts) with mantle cell lymphoma (MCL) following intensive frontline treatment has been associated with inferior survival (Dietrich et al Ann Oncol 2014 and Visco et al Br J Haematol 2019), but the optimal time point to define early POD and the predictive significance of early POD following less intensive frontline treatment is not well established. We compare outcomes after all frontline treatments in a large MCL cohort categorized by time to progression and describe outcomes by class of second line treatment for pts with primary refractory disease. Methods: Clinical and outcome data for MCL pts treated between 2000 and 2017 were collected from 12 US centers. Overall survival (OS), defined from time of 1st progression, and secondary progression free survival (PFS2), defined from 1st progression to 2nd progression or death, were estimated by Kaplan-Meier and compared by log-rank test. Univariable and multivariable analyses were performed using Cox proportional hazards models for OS. 95% confidence intervals were calculated for all estimates and displayed in square brackets. We defined intensive treatment as high dose cytarabine in frontline therapy and/or autologous stem cell transplant in 1st remission. Pts were categorized into three groups: (a) refractory disease to frontline therapy or POD within 6 months of frontline therapy was termed primary refractory (PRF); (b) POD between 6 to 24 months of therapy was termed POD24 and (c) POD beyond 24 months was termed POD〉24. Salvage therapy was categorized as chemoimmunotherapy (CIT) for pts treated with CIT alone, BTK inhibitor (BTKi) for pts treated with BTKi single agent or in combination, and lenalidomide / bortezomib for pts treated with one or both agent +/- anti-CD20 therapy. Results: Of 1,168 pts with MCL, 457 pts had relapsed and were included in this analysis. The median age was 62, 77% were male, and ECOG PS was 0/1 in 94%. Median follow-up was 2.6 years (yr) after first progression. The most common induction regimens were R-HyperCVAD (26%), R-CHOP (24%), bendamustine and rituximab (19%), and R-M-CHOP (10%). Frontline treatment was intensive in 54%. Sixty five pts (14%) were PRF, 153 (34%) had POD24, and 239 (53%) had POD〉24. Additional baseline characteristics and comparison between groups are summarized in Table 1. The median OS was 1.3 yr [0.9-2.4] for PRF pts, 3 yrs [2-6.8] for POD 24, and 8 yrs [6.2-not reached (NR)] for POD〉24 (p24 pts (p

Description: INTRODUCTION The optimal frontline treatment for mantle cell lymphoma (MCL) is not clearly defined. Bendamustine + rituximab (BR) is commonly used as initial therapy. The role of maintenance rituximab (MR) after BR is not agreed upon due to limited data supporting this practice, whereas MR improves overall survival (OS) after autologous stem cell transplant (ASCT) and after R-CHOP for elderly patients who do not receive ASCT. Preliminary results from a subgroup analysis of the randomized phase 3 MAINTAIN study revealed neither a progression-free survival (PFS) nor OS benefit for MR as compared to observation for MCL pts (Rummel, ASCO 2016). In follicular lymphoma patients, however, there does appear to be a PFS benefit to rituximab maintenance following BR. Given these disparate results, we sought additional data to evaluate the role of rituximab maintenance following BR in MCL METHODS MCL pts treated at 12 U.S. medical centers with frontline BR who achieved a complete response (CR) or partial response (PR) and who did not receive consolidative ASCT from 2011 - 2017 were included. Use of MR was based on individual physician/patient preferences. Baseline pt characteristics were compared using chi-squared test, Fisher's exact tests, or ANOVA. Descriptive statistics, comparisons, and OS using the Kaplan-Meier method were stratified by response status as determined by the treating site (complete response (CR) only, partial response (PR) only, and CR/PR). RESULTS Among 135 pts responding to frontline BR who did not complete subsequent ASCT, 80% achieved complete remission (CR) and 20% had a partial remission (PR). Median age was 70 (range 45 - 93) years and 66% were male. Baseline MIPI score was low (13%), intermediate (38%), or high (49%) among patients with available data (n = 92) and did not differ between treatment cohorts. Among responding patients, 78 (58%) received MR and 57 (40%) were observed. With a median follow up of 3.1 years, median OS was not reached for pts responding to BR (with CR or PR) who received MR vs. 6 years for those who received no maintenance (Figure Panel A, P = 0.0013). Use of MR vs. observation was associated with a significant improvement in OS for pts in PR at the end of induction therapy (Figure Panel B, median not reached vs. 1.7 years, P = 0.006), but there was no statistically significant OS difference for pts in CR (Figure Panel C, median not reached vs. 9.6 years, P = 0.2575). In multivariable analysis, MIPI score

Description: Introduction: Previously, we reported that CD30 expression was not acquired at time of relapse in patients with diffuse large B-cell lymphoma (DLBCL) utilizing conventional immunohistochemistry (IHC; Calzada et al., ASH 2016). However, novel approaches to detection of CD30 expression may improve the detection of low levels of expression and thus may have implications regarding the use of CD30-directed therapies in DLBCL and other lymphomas. We utilized a computational tissue analysis mechanism to evaluate CD30 expression using patient samples that had previously been considered CD30 negative by IHC. Methods: We included patients with relapsed DLBCL with available archived tissue samples from the time of relapse (and when feasible, from the time of diagnosis) that was sufficient to prepare a slide for staining. CD30 IHC staining was completed for all involved tissue at Emory using our standard antibody (Ber-H2). Samples were manually annotated to indicate regions for inclusion and exclusion in image analysis. CD30 status was assessed by Flagship Biosciences using their proprietary CD30/DLBCL computational tissue analysis (cTA) algorithm. The primary endpoint for this analysis was the number and percentage of CD30+ cells in each tissue sample. Clinical, demographic and laboratory variables were also collected for each case, and overall survival (OS) was estimated using the Kaplan-Meier method. We divided the cohort into CD30 high vs. low expression using the median percentage of CD30+ cells and also performed a cut point analysis to identify a clinically significant cut-off for high vs. low using an outcome-oriented approach (Contal 1999). Results: We included 25 patients with relapsed/refractory DLBCL (including 9 with available paired tissue from the time of initial diagnosis). Among all patients, the median age at diagnosis was 58 years (range 34-76), 72% presented with elevated LDH, 56% were Stage III/IV, 62% had B-symptoms, and 83% had extranodal disease (not including bone marrow). The median time from diagnosis to relapse was 9.4 months. Eighty-eight percent of patients received R-CHOP as frontline therapy. Cell of origin by the Hans algorithm was germinal center B-cell-like (GCB) for 9 patients, non-GCB for 5 patients, and unknown for 11 patients. Utilizing conventional IHC, none of the diagnostic or relapsed samples had detectable CD30 expression. Upon image analysis, 11/19 available samples were CD30-positive at relapse using ≥0.1% as a cutoff. Range of percentage of CD30 positive cells was 0.1 to 23.6%, and the median percentage of CD30 positive cells was 0.25%. Among the 9 patients with paired samples, 5 were positive at diagnosis and 5 were positive at relapse. One patient went from negative to positive and 1 patient transitioned from positive to negative. Most patients who were positive at baseline were still positive at relapse, and the median change in percentage of CD30+ cells between diagnosis and relapse was 0.35%. There were no statistical differences between the CD30 high vs low patients with regards to baseline patient- or disease-related characteristics or time to relapse using the median value of 0.25 as the cut point. In addition, CD30 expression was not associated with OS from the date of relapse or from diagnosis (p=0.406 & p=0.316, respectively). None of the included patients were treated with brentuximab vedotin or any other CD30-directed therapy. Conclusions: This analysis identifies a novel way to detect CD30 expression in patients with DLBCL and suggests that more patients may be CD30+ than previously thought. Prior studies in T-cell lymphoma suggest that even patients with a very low percentage of CD30+ cells may respond to CD30-directed treatment (Kim 2017), although expression using this novel method was not part of those studies. Assaying the CD30 status of relapsed/refractory DLBCL using this novel platform in a larger cohort is warranted as patients with such low level CD30 expression may benefit from future evaluation of CD30-directed treatments. Figure. Figure. Disclosures Calzada: Seattle Genetics: Research Funding. Flowers:Genentech/Roche: Research Funding; Janssen Pharmaceutical: Research Funding; Acerta: Research Funding; BeiGene: Research Funding; Gilead: Consultancy; Pharmacyclics: Research Funding; OptumRx: Consultancy; Karyopharm: Consultancy; V Foundation: Research Funding; Abbvie: Research Funding; Eastern Cooperative Oncology Group: Research Funding; Gilead: Research Funding; Millennium/Takeda: Research Funding; Pharmacyclics/ Janssen: Consultancy; National Cancer Institute: Research Funding; Burroughs Wellcome Fund: Research Funding; TG Therapeutics: Research Funding; Genentech/Roche: Consultancy; Celgene: Research Funding; Spectrum: Consultancy; Abbvie: Consultancy, Research Funding; Bayer: Consultancy; Denovo Biopharma: Consultancy. Cohen:Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: 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; Janssen: Research Funding; BioInvent: Consultancy; BioInvent: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Research Funding; Infinity Pharmaceuticals: 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; Takeda: Research Funding; 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; Bristol-Myers Squibb: Research Funding.

Description: 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

Description: Introduction: Most patients (pts) with diffuse large B cell lymphomas (DLBCL) are cured with first line chemoimmunotherapy including an anthracycline and rituximab. Pts who obtain complete remission (CR) but latter relapse often can be cured with salvage therapy and autologous hematopoietic cell transplantation (auto-HCT). This management paradigm often is applied to pts with primary treatment failure (PTF). However, this group is heterogeneous and detailed data on outcomes in current era is needed to identify the DLBCL pts for whom novel therapeutic strategies should be designed. Methods: Fifteen US academic medical centers contributed pts to the REgistry of diFfuse large B cell lymphoma with prImary treatmeNt failurE (REFINE) collaboration. REFINE retrospectively captured patient, disease and treatment characteristics and treatment response as assessed by treating physician. Eligible pts were ≥ 18 years diagnosed with DLBCL during 2008-2015, who received upfront cheomoimmunotherapy including anthracycline and CD20-directed antibody and developed one of 3 patterns of PTF: relapse 〈 6 months following CR (early relapse- ER); only partial remission (PR) or stable disease (SD) with upfront therapy (residual disease-RD); progressive disease (PD) while receiving upfront therapy (primary progression-PP). Pts with HIV infection, primary CNS lymphoma or lymphoma transforming from a more indolent histology were excluded. Results: Patient characteristics for the 331 cases are summarized in Table 1. Median follow up of survivors was 18.9 months. R-CHOP was the upfront treatment for 87.6% of pts. Nearly all pts (94.6%) received salvage therapy after PTF and prior to any HCT, with a median of 1 and range 0 to 5 regimens. Response to first salvage regimen was CR in 19.9%, PR in 21.8%, SD in 9.0% and PD in 40.8%. Only 15.1% of pts were enrolled in clinical trials. One hundred and thirty-two pts (39.9%) underwent auto-HCT and 33 (10.0%) allogeneic-HCT (8 after failure of auto-HCT). Two-year overall survival (OS) from time of PTF was 45.5% (95% C.I. 34.5-56.5%) for ER, 30.6% (95% C.I. 20.0-41.2%) for RD and 18.5% (95% C.I. 11.4-25.6%) for PP (P