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: 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: 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: Mantle cell lymphoma (MCL) is a rare form of lymphoma with no current standard of care. As a result, clinical trials are critical to improving our understanding of the disease and its management. However, clinical trial participation is often limited due to lack of access to studies, restrictive eligibility criteria, and decisions by treating physicians or patients not to participate. We evaluated the rate of enrollment and outcomes associated with clinical trial participation of patients with MCL at 12 US Medical Centers. Methods: We included patients from 12 medical centers in the United States with MCL diagnosed between January 1, 2000, and January 1, 2018, who were ≥ 18 years old, received any induction therapy, and for whom it was known whether initial treatment was on a clinical trial (CT) or not. We compared differences between the two groups (CT vs not) using Fisher's Exact and Chi-square tests as appropriate. We defined overall survival (OS) as time from diagnosis to death. Patients not experiencing an event were censored at their last known follow-up. OS was determined using the Kaplan-Meier method, and univariate and multivariable models were developed to identify predictors of OS. Results: Eight hundred twelve patients were included in this analysis, including 164 (20%) patients who participated in a clinical trial during initial therapy. Rate of participation ranged from 4% to 36% across contributing sites. Median age for the entire cohort was 62 years, 572 (74%) of patients were male, and 95% of patients had ECOG 0-1. MCL International Prognostic Index (MIPI) risk score was high in 163 patients (31%), and 84% of patients had stage IV disease. Ki67 was 〉30% in 169/225 (43%) patients with available data, and 19% of patients (65/271) had a complex karyotype with 〉 3 chromosomal abnormalities. Four hundred sixteen (53%) of patients received an intensive induction regimen (defined as initial treatment with a high-dose cytarabine-containing regimen and/or receipt of autologous hematopoietic cell transplantation as consolidation), including 333 patients (43%) who underwent transplant consolidation. Patients with an increased lactate dehydrogenase (LDH) level (p 3 cytogenetic abnormalities (p=0.015) were less likely to participate in clinical trials, but there was no significant difference in rates of participation based on MIPI (p=0.49) or ECOG performance status (p=0.22; Table). Patients treated on study were less likely to receive an intensive regimen compared to those treated off study (p=0.002). Median time to treatment from diagnosis was 35 days for patients enrolled on trial and 31 days for patients not enrolled on trial (p=0.83). With a median follow-up of 3.8 years, the median OS was 13.6 years (95% CI: 11.5-21.1) for patients not treated on a trial and not reached (95% CI: 9.9 - Not Reached) for patients treated on trial (Figure; p=0.036). In a multivariable model including clinical trial participation, MIPI, time to initial treatment, and receipt of an intensive induction regimen, only clinical trial participation (HR 0.54, 95%CI: 0.31-0.93; p=0.028) and high risk MIPI score (HR 4.24, 95% CI: 2.37-7.56; p

Description: Background:There are multiple prognostic markers used to risk stratify pts with mantle cell lymphoma (MCL) including the MCL International Prognostic Index (MIPI) which divides newly diagnosed patients into three groups based on available clinical and laboratory data.Complex karyotype (CK) defined as equal to or greater than 3 chromosomal abnormalities has also been associated with inferior outcomes in MCL although its association with MIPI is lesswell-described. We conducted a multicenter analysis of MCL pts to assess the relative contributions of MIPI, CK and Ki67 as predictors of progression-free (PFS) and overall survival (OS). Methods:Untreated pts atleast18 years of age with MCL from 5 academic centers diagnosed between 1993 and 2015 who had available data describing MIPI, Ki67, and cytogenetics were included. Patients with 3 or more chromosomal abnormalities were defined as having CK. High Ki67 was defined as immunohistochemistry staining 〉30%. We described the associations between MIPI risk group, CK, Ki67, and other clinical factors of interest as predictors of PFS and OS in univariate and multivariable models. Results:Of 92 eligible MCL patients, 30 (32.6%) had low-risk, 36 pts (39.1%) had intermediate-risk, and 26 pts (28.3%) had high-risk MIPI scores. Ki67 index was 〉30% in 44.6% of patients, and 17.4% had CK. Neither Ki67 〉 30% (p=0.548) norpresence of CK (p=0.409) wereassociated with MIPI risk category. In the low-risk MIPI subgroup, 37% of patients had Ki67 〉 30% and 10% had CK. Induction regimens included: R-HyperCVAD (n=15), R-CHOP/R-DHAP (n=7), Nordic regimen (n=13), R-CHOP (n=10), B-R (n=19), and others (n=28). Thirty-two patients (39%) had an autologous stem cell transplant (ASCT) in first remission. Median PFS for the entire cohort was 3.8 years, and median OS has not yet been reached. Median PFS for was 2.2 years, 2.5 years, and 7.9 years for patients with high-, intermediate-, and low- risk MIPI scores, respectively, at diagnosis. Median PFS was 2.4 years for patients with Ki67 〉 30% and 7.9 years for patients with Ki67 〈 30%. Median PFS was 1.3 years for patients with CK and 4.3 years for patients without CK. High risk MIPI (p=0.042), CK (p=0.002), and Ki67 index 〉 30% (p=0.002) were all associated with inferior PFS in a univariable analyses (See Figure). In a multivariable analysis (See Table) Ki67 〉30% (HR=3.66, p 30% and CK are independently associated with inferior outcomes in MCL. In this analysis, MIPI risk score was not independently associated with PFS or OS when considering these additional prognostic markers, which needs to be confirmed in other retrospective and prospective cohort studies. Our high-risk MIPI patients, in general, have an improved outcome compared to prior reports. (Hoster2008, 2014;Lex2014), suggesting that alternative markers may play an important role in MCL risk-assessment. Efforts to incorporate additional patients and develop a new prognostic model in MCL are underway. Figure Figure. Figure Figure. Disclosures Danilov: Pharmacyclics: Consultancy; Astra Zeneca: Research Funding; Takeda: Research Funding; GIlead Sciences: Research Funding; ImmunoGen: Consultancy; Dava Oncology: Honoraria; Prime Oncology: Honoraria. Hamadani:Janssen: Consultancy; Celgene: Honoraria, Research Funding; Takeda Pharmaceuticals: Research Funding. Flowers:TG Therapeutics: Research Funding; Genentech: Consultancy, Research Funding; Infinity: Research Funding; Millenium/Takeda: Research Funding; Mayo Clinic: Research Funding; NIH: Research Funding; Roche: Consultancy, Research Funding; Pharmacyclics, LLC, an AbbVie Company: Research Funding; ECOG: Research Funding; AbbVie: Research Funding; Acerta: Research Funding; Gilead: Consultancy, Research Funding. Cohen:Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity: 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; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium/Takeda: 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; Bristol-Myers Squibb: Research Funding.