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The prognostic relevance of diagnosis to treatment interval (DTI) in patients with newly diagnosed mantle cell lymphoma (MCL) is unknown. Hence, we sought to evaluate the impact of DTI on outcomes in MCL using 3 large datasets (1) the University of Iowa/Mayo Clinic Specialized Program of Research Excellence Molecular Epidemiology Resource, (2) patients enrolled in the ALL Age Asthma Cohort/CALGB 50403, and (3) a multisitecohort of patients with MCL. Patients were a priori divided into 2 groups, 0 to 14 days (short DTI) and 15 to 60 days (long DTI). The patients in whom observation was deemed appropriate were excluded. One thousand ninety-seven patients newly diagnosed with MCL and available DTI were included in the study. The majority (73%) had long DTI (n=797). Patients with short DTI had worse eastern cooperative oncology group performance status (ECOG PS ≥2), higher lactate dehydrogenase, bone marrow involvement, more frequent B symptoms, higher MCL International Prognostic Index (MIPI ≥6.2), and were less likely to receive intensive induction therapy than long DTI group. The median progression-free survival (2.5 years vs 4.8 years, p

The overall goal of the annual Transdisciplinary Research in Energetics and Cancer (TREC) Training Workshop is to provide transdisciplinary training for scientists in energetics and cancer and clinical care. The 2022 Workshop included 27 early-to-mid career investigators (trainees) pursuing diverse TREC research areas in basic, clinical, and population sciences. The 2022 trainees participated in a gallery walk, an interactive qualitative program evaluation method, to summarize key takeaways related to program objectives. Writing groups were formed and collaborated on this summary of the 5 key takeaways from the TREC Workshop. The 2022 TREC Workshop provided a targeted and unique networking opportunity that facilitated meaningful collaborative work addressing research and clinical needs in energetics and cancer. This report summarizes the 2022 TREC Workshop’s key takeaways and future directions for innovative transdisciplinary energetics and cancer research.

Supplemental Figure 2. CLL-CI correlates with OS across CLL patient subgroups (derivation dataset).

Supplemental Figure 1. CIRS correlates with outcomes in CLL (derivation dataset).

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Purpose:Comorbid medical conditions define a subset of patients with chronic lymphocytic leukemia (CLL) with poor outcomes. However, which comorbidities are most predictive remains understudied.Experimental Design:We conducted a retrospective analysis from 10 academic centers to ascertain the relative importance of comorbidities assessed by the cumulative illness rating scale (CIRS). The influence of specific comorbidities on event-free survival (EFS) was assessed in this derivation dataset using random survival forests to construct a CLL-specific comorbidity index (CLL-CI). Cox models were then fit to this dataset and to a single-center, independent validation dataset.Results:The derivation and validation sets comprised 570 patients (59% receiving Bruton tyrosine kinase inhibitor, BTKi) and 167 patients (50% receiving BTKi), respectively. Of the 14 CIRS organ systems, three had a strong and stable influence on EFS: any vascular, moderate/severe endocrine, moderate/severe upper gastrointestinal comorbidity. These were combined to create the CLL-CI score, which was categorized into 3 risk groups. In the derivation dataset, the median EFS values were 58, 33, and 20 months in the low, intermediate, and high-risk groups, correspondingly. Two-year overall survival (OS) rates were 96%, 91%, and 82%. In the validation dataset, median EFS values were 81, 40, and 23 months (two-year OS rates 97%/92%/88%), correspondingly. Adjusting for prognostic factors, CLL-CI was significantly associated with EFS in patients treated with either chemo-immunotherapy or with BTKi in each of our 2 datasets.Conclusions:The CLL-CI is a simplified, CLL-specific comorbidity index that can be easily applied in clinical practice and correlates with survival in CLL.

Supplemental Fig. 3. CLL-CI correlates with EFS in patient subgroups (validation set).

In patients with non-Hodgkin lymphoma (NHL), formal comorbidity assessment is recommended but is rarely done in routine practice. A simple, validated measure of comorbidities that standardized their assessment could improve adherence to guidelines. We previously constructed the three-factor risk estimate scale (TRES) in patients with chronic lymphocytic leukemia (CLL). Here, we investigated TRES in multiple NHL subtypes. Patients in the SEER-Medicare database with NHL diagnosed during 2008-2017 were included. Upper gastrointestinal, endocrine, and vascular comorbidities were identified using ICD-9/ICD-10 codes to assign TRES score. Patient characteristic distributions were compared by chi-square or t-test. Association of mortality and TRES score was assessed by Kaplan-Meier and multivariable Cox regression with competing risk. 40,486 patients were included. Median age was 77 years (interquartile range [IQR] 71-83 years). The most frequent NHL subtypes were CLL (28.2%), diffuse large B-cell (27.6%) and follicular lymphoma (12.6%). Median follow up was 33 months (IQR, 13-60 months). TRES was low, intermediate and high in 40.8%, 37.0% and 22.2% of patients, corresponding to median overall survival (OS) of 8.2, 5.3 and 2.9 years (P

Chimeric antigen receptor T-cell therapy (CART) has extended survival of patients with relapsed/refractory diffuse large B-cell lymphoma (DLBCL). However, limited durability of response and prevalent toxicities remain problematic. Identifying patients at high risk of disease progression, toxicity, and death would inform treatment decisions. Although the cumulative illness rating scale (CIRS) has been shown to correlate with survival in B-cell malignancies, no prognostic score has been independently validated in CART recipients. We retrospectively identified 577 patients with relapsed/refractory DLBCL indicated for CART at 9 academic centers to form a learning cohort (LC). Random survival forest modeling of overall survival (OS) and progression-free survival (PFS) was performed to determine the most influential CIRS organ systems and severity grades. The presence of a severe comorbidity (CIRS score ≥3) in the respiratory, upper gastrointestinal, hepatic, or renal system - herein termed "Severe4" - had the greatest impact on post-CART survival. Controlling for other prognostic factors (number of prior therapies, Eastern Cooperative Oncology Group performance status, BCL6 translocation, molecular subtype), Severe4 was strongly associated with shorter PFS and OS in the LC (hazards ratio [HR]=2.15 and 1.94, respectively; p

The chronic lymphocytic leukemia comorbidity index (CLL-CI) is an efficient, CLL-specific tool derived from the Cumulative Illness Rating Scale. The CLL-CI is based on the assessment of the organ systems found to be most strongly associated with event-free survival (EFS) in CLL: vascular, upper gastrointestinal, and endocrine, at the time of initiation of CLL therapy. The CLL-CI categorizes patients into low, intermediate, and high risk groups. In the present study, we have employed the CLL-CI in a population-based cohort comprising 4975 patients with CLL. We demonstrate that CLL-CI retains prognostic significance in this large cohort and is associated with overall survival (OS) and EFS from time of first therapy. Furthermore, CLL-CI associates with OS, EFS, and time to first treatment from diagnosis independently of the CLL International Prognostic Index. These findings support the use of the CLL-CI both in research and in clinical practice.

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. In this subgroup, we evaluated the importance of treatment intensity in patients with MCL who defer initial therapy. METHODS: Out of 1134 patients with MCL from 12 academic centers, we analyzed 219 patients who initiated therapy at least 90 days after diagnosis. Patients who received induction with high-dose cytarabine and/or autologous stem cell transplantation (ASCT) in first remission were considered to have received intensive therapy (n = 88) while all other approaches were non-intensive (n = 131). RESULTS: There was no difference in progression-free (PFS; P = .224) or overall survival (OS; P = .167) in deferred patients who received non-intensive vs. intensive therapy. Additionally, univariate and multivariate Cox proportional hazards models were performed for PFS and OS. Treatment at an academic center (HR 0.43, P = .015) was associated with improved OS in both univariate and multivariate models, while intensity of treatment was not associated with improved OS in either model. CONCLUSIONS: These results indicate that intensified initial treatment is not associated with improved survival after deferring initial therapy, although prospective studies are needed to determine which of these patients with MCL may benefit from intensive therapy.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of aggressive non-Hodgkin lymphoma. Combination chemotherapy with immunotherapy can be curative, however, nearly one-third of patients will have a disease that is refractory or will relapse (R/R) after standard first-line therapy. In second-line, the standard treatment strategy for fit patients has been high dose chemotherapy followed by autologous stem cell transplant for a quarter-century, however more than half of patients have chemotherapy-refractory disease with this approach. The patients not cured with current chemotherapy-based approaches may benefit from immunotherapy. Several classes of immunotherapy have been developed including antibody-drug conjugates, bispecific T-cell engaging antibodies, immune checkpoint inhibitors and chimeric antigen receptor T-cells. In the following review, we discuss the currently available immunotherapeutic options for patients with R/R DLBCL.

Central nervous system (CNS) involvement in Burkitt lymphoma (BL) poses a major therapeutic challenge, and the relative ability of contemporary regimens to treat CNS involvement remains uncertain. We described prognostic significance of CNS involvement and incidence of CNS recurrence/progression after contemporary immunochemotherapy using real-world clinicopathologic data on adults with BL diagnosed between 2009 and 2018 across 30 US institutions. We examined associations between baseline CNS involvement, patient characteristics, complete response (CR) rates, and survival. We also examined risk factors for CNS recurrence. Nineteen percent (120/641) of patients (age 18-88 years) had CNS involvement. It was independently associated with HIV infection, poor performance status, involvement of ≥2 extranodal sites, or bone marrow involvement. First-line regimen selection was unaffected by CNS involvement (P=0.93). Patients with CNS disease had significantly lower rates of CR (59% versus 77% without; P

Introduction Diffuse large B-cell lymphoma (DLBCL), the most common lymphoid cancer, is curable but has been treated with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP)-based chemotherapy for decades.1 DLBCL is a heterogeneous disease with distinct subtypes with differential responses to targeted therapy; however, this has not yet translated into standard therapy.2,3 Most frontline DLBCL trials employ an R-CHOP versus R-CHOP + X chemotherapy, which assumes X will either add to or synergize with chemotherapy and not antagonize or have significant added toxicity with chemotherapy.4 Notable examples include lenalidomide, ibrutinib, venetoclax, and bortezomib, among others. Other than rituximab, these trials have been disappointing, despite huge numbers of patients and high response rates in patients with relapsed disease. Moving the field beyond R-CHOP may require a targeted, subgroup-specific approach rather than a one-size-fits-all approach. The analysis of circulating tumor DNA (ctDNA) is a promising technological advance that may enable more flexible/adaptive approaches and should be incorporated into prospective trials.5

Chronic lymphocytic leukemia (CLL) is a common, indolent disease that typically presents with a proliferation of mature, immunologically dysfunctional CD5+ B-cells which preferentially occupy the bone marrow, peripheral blood and lymphoid organs. Immune dysfunction leads to an increase in autoimmune diseases which occur in approximately 10% of patients with CLL. Autoimmune cytopenias are the most common, but other organs may be affected as well. The treatment of these conditions typically depends on the extent of CLL and severity of symptoms, but generally consists of CLL-directed therapies, immunosuppression or both. CLL may also infiltrate extranodal sites in the body. Symptomatic extranodal CLL or extranodal disease which threatens normal organ function is an indication for initiation of CLL-directed therapy. The following review summarizes autoimmune and extranodal complications that can occur in patients with CLL and our suggested approach to their treatment.

Follicular lymphoma, the most common indolent lymphoma, though highly responsive to therapy is coupled with multiple relapses for the majority of patients. Advances in biologic understanding of molecular events in lymphoma cells and the tumor microenvironment, along with novel cellular and targeted therapies, suggest this may soon change. Here we first review the development of the molecular concepts and classification of follicular lymphoma, along with therapeutic development of treatments based on chemotherapy plus monoclonal antibodies targeting CD20. We then focus on developments over the last decade in further defining follicular lymphoma pathophysiology, leading to targeted therapeutics, as well as novel immunotherapeutic strategies effective against B cell lymphomas including follicular, particularly patients with advanced stage disease. Additional alterations beyond the hallmark t(14;18) translocation are necessary for development of follicular lymphoma. Epigenetic mutations are almost universally identified in follicular lymphoma, most commonly involving histone-lysine N-methyltransferase 2D (KMT2D, the histone acetyltransferases, cAMP response element-binding protein binding protein (CREBBP) and E1A binding protein P300 (EP300) and the histone methyltransferase enhancer of zeste homologue 2 (EZH2). Mutations are also commonly identified in other proliferation/survival pathways such as B-cell receptor, RAS, mTOR and JAK-STAT pathways, as well as immune escape mutations. The host immune response plays a key role as well, based on studies correlating various immune cell subsets and gene expression signatures with outcomes. Over the last decade, many therapeutic options beyond the commonly used bendamustine-rituximab induction regimen have become available or are being investigated. We focus on these newer agents in the relapsed setting. New antibody-based agents include the naked CD19 directed antibody tafasitamab, the CD79b directed antibody drug conjugate (ADC) polatuzumab vedotin and the CD47 directed antibody magrolimab that targets macrophages rather than FL cells directly. Immune modulation by lenalidomide has moved to earlier lines of therapy and in combinations. Several small molecule inhibitors of proliferation signal pathways involving PI3kinase and BTK have activity against FL. Apoptotic pathway modulators also have activity. With increasing recognition of the high rate of epigenetic mutations in FL, HDAC inhibition has a role. More importantly, the EZH2 inhibitor tazemetostat is FDA approved for FL after 2 prior lines of therapy. The most exciting data currently involve immune attack against follicular lymphoma by chimeric antigen receptor T-cells (CART) or bispecific antibody constructs. Given these multiple potentially non-crossreactive mechanisms, studies of rationally designed combination strategies hold the promise of improving outcomes and possibly cure of follicular lymphoma.

Although an expanding array of effective treatments has resulted in recent improvement in survival of patients with mantle cell lymphoma (MCL), outcomes remain heterogeneous, and identification of prognostic factors remains a priority. We assessed the prognostic impact of time to progression of disease (POD) after first-line therapy among 455 patients with relapsed MCL. Patients were categorized by duration of first remission as PRF/POD6, defined as progressive disease during induction or POD within 6 months of diagnosis (n = 65; 14%); POD6-24, defined as POD between 6 and 24 months after diagnosis (n = 153; 34%); and POD>24, defined as POD >24 months after diagnosis (n = 237; 53%). The median overall survival from POD (OS2) was 1.3 years (95% confidence interval [CI], 0.9-2.4) for patients with PRF/POD6, 3 years (95% CI, 2-6.8) for those with POD6-24, and 8 years (95% CI, 6.2-NR) for those with POD>24. Median OS2 was inferior in patients with early POD (defined as PRF/POD6 or POD6-24) after both intensive and less intensive frontline treatment. The prognostic performance of time until POD was replicated in an independent cohort of 245 patients with relapsed MCL, with median OS2 of 0.3 years (95% CI, 0.1-0.5) for PRF/POD6, 0.8 years (95% CI, 0.6-0.9) for POD6-24, and 2.4 years (95% CI 2.1-2.7) for POD>24. Early POD is associated with inferior OS2 in patients with relapsed MCL, identifying a high-risk population for future prospective studies.

Introduction: Medical comorbidities influence survival in CLL. We previously reported on a simplified CLL-specific comorbidity scale, the CLL-CI (Gordon et al. 2019), which required assessment of only three organ systems and was predictive of outcomes in a heterogeneous retrospective patient cohort. Herein we analyzed CLL-CI among patients treated with ibrutinib. Methods: This retrospective study included 339 CLL patients treated with ibrutinib at 9 academic centers between 2014-2019. Vascular, endocrine and upper-gastrointestinal organ systems were assessed at the time of ibrutinib initiation. Each was scored from 0 to 3, in order of increasing severity of dysfunction to generate the CLL-CI score (range, 0-9; Figure A). As established previously, CLL-CI≥2 was deemed high-risk. Event free survival (EFS) was measured from start of ibrutinib to development of new CLL-related symptoms, disease progression, start of a new therapy or death. Overall survival (OS) was measured from treatment initiation to death. Patients with no EFS or OS events were censored at last follow up. The Kaplan-Meier method and log-rank test were used to estimate and compare survival. Multivariable Cox regression was utilized to model EFS and OS. Differences between CLL-CI groups were evaluated with Wilcoxon rank sum and Fisher's exact tests. Results: Median age was 68 years (range, 30-91), 240 (71%) were treated in the relapsed/refractory setting (range of prior therapies, 0-10). Advanced Rai stage (3-4) was present in 206 (61%) and TP53 aberrancy was present in 93 (27%) patients at the start of ibrutinib therapy. Median follow up was 23 months (range, 1-71). CLL-CI score was high (≥2) in 202/339 patients (60%). Patient characteristics were well balanced between subgroups (CLL-CI In multivariate models adjusted for age, del(17p) and relapsed disease, high CLL-CI was associated with shortened EFS (HR=1.65; p=0.014, Figure) and OS (HR=1.73; p=0.1). CIRS score≥7 also correlated with EFS (HR=1.91; p=0.002) and OS (HR=2.78; p=0.006). Ibrutinib discontinuation rates due to adverse events were more frequent in patients with CLL-CI ≥2 (25% vs 14%; p=0.014). However, dose reduction rates were similar (24% vs 20%; p=0.51). Fifty-two deaths occurred: 40 in the high CLL-CI subgroup and 12 in the low CLL-CI subgroup. Cause of death was known in 31 patients. Death due to disease progression was more frequent in the high CLL-CI subgroup (28% vs 8%; p Since some of the key ibrutinib toxicities (atrial fibrillation, hypertension) may not have been accounted for in the CLL-CI we further elucidated their possible impact. Cardiac disease was significantly more prevalent among patients with high CLL-CI (37% vs 16%, p Conclusions: Here we present the largest cohort of CLL patients treated with ibrutinib in whom comorbidities have been systematically assessed. We find that the CLL-CI (which assesses endocrine, vascular and upper gastrointestinal conditions) correlates with survival and tolerance of therapy in this population. Unexpectedly, we found that hypertension and cardiac comorbidities did not improve CLL-CI's discriminatory power. This result combined with the simplicity of scoring the CLL-CI makes it an attractive tool for clinical practice. CLL-CI needs to be explored prospectively in patients treated with ibrutinib and other targeted therapies. Disclosures Patel: Genentech: Consultancy, Speakers Bureau; BeiGene: Consultancy; Celgene/BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Speakers Bureau; Adaptive Biotechnologies: Consultancy; AstraZeneca: Consultancy, Research Funding, Speakers Bureau; Pharmacyclics: Consultancy, Speakers Bureau; Kite: Consultancy. Cohen:Janssen, Adicet, Astra Zeneca, Genentech, Aptitude Health, Cellectar, Kite/Gilead, Loxo: Consultancy; Genentech, BMS, Novartis, LAM, BioInvent, LRF, ASH, Astra Zeneca, Seattle Genetics: Research Funding. Choi:Pharmacyclics/Abbvie: Research Funding; Genentech: Consultancy. Hill:BMS: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Research Funding; Takeda: Research Funding; Beigene: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding. Shadman:Mustang Bio, Celgene, Pharmacyclics, Gilead, Genentech, Abbvie, TG therapeutics, Beigene, Astra Zeneca, Sunesis, Beigene: Research Funding; Abbvie, Genentech, Astra Zeneca, Sound Biologics , Pharmacyclics, Verastem, ADC therapeutics, Beigene, Cellectar, BMS, Morphosys and Atara Biotherapeutics: Consultancy. Stephens:Innate: Consultancy; Gilead: Research Funding; Verastem: Research Funding; Janssen: Consultancy; Acerta: Research Funding; Pharmacyclics: Consultancy; MingSight: Research Funding; Beigene: Consultancy; Arqule: Research Funding; Juno: Research Funding; Karyopharm: Consultancy, Research Funding. Brander:Novartis: Consultancy, Other; NCCN: Other; Tolero: Research Funding; AstraZeneca: Consultancy, Honoraria, Other, Research Funding; Ascentage: Other, Research Funding; ArQule: Consultancy, Other, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Tolero: Research Funding; Teva: Consultancy, Honoraria; Novartis: Consultancy, Other; NCCN: Other; Verastem: Consultancy, Honoraria, Other, Research Funding; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Pfizer: Consultancy, Other; Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Other, Research Funding; MEI Pharma: Other, Research Funding; Juno/Celgene/BMS: Other, Research Funding; Genentech: Consultancy, Honoraria, Other, Research Funding; DTRM: Other, Research Funding; BeiGene: Other, Research Funding; Teva: Consultancy, Honoraria. Danilov:BeiGene: Consultancy; Pharmacyclics: Consultancy; Abbvie: Consultancy; Bristol-Myers Squibb: Research Funding; Rigel Pharmaceuticals: Consultancy; Astra Zeneca: Consultancy, Research Funding; Aptose Biosciences: Research Funding; Verastem Oncology: Consultancy, Research Funding; Takeda Oncology: Research Funding; Gilead Sciences: Research Funding; Bayer Oncology: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; TG Therapeutics: Consultancy; Nurix: Consultancy; Celgene: Consultancy; Karyopharm: Consultancy.

Clinical outcomes and predictors of survival in patients with newly diagnosed mantle cell lymphoma (MCL) treated in the rituximab era (2000-2015) at 12 US academic centers were assessed to identify determinants of survival across age groups. Objectives were to characterize and compare practice patterns, outcomes and prognostic factors for survival in younger patients (age < 65) and older patients (age ≥ 65 years). Among 1162 patients included, 697 were younger and 465 were older. In younger patients, 2-year progression free survival (PFS) and overall survival (OS) rates were 79% and 92% respectively; blastoid histology, ECOG ≥ 2, and lack of maintenance rituximab (MR) remained statistically relevant to poor OS on univariate analysis (UVA) and multivariate analysis (MVA). In older patients, 2-year PFS and OS rates were 67% and 86% respectively; lack of maintenance rituximab remained significantly associated with inferior PFS and OS on UVA and MVA (p < 0.001). Two-year PFS rates were 79%, and 67% and 2-year OS rates were 92% and 86% for ages < 65 and ≥ 65 respectively (p < 0.001). First-line high-dose cytarabine exposure and/or MR lessened the negative impact of age on survival. Taken collectively, survival outcomes for older patients remain inferior to those of younger patients in the rituximab era. However, maintenance rituximab and potentially high-dose cytarabine-based induction can mitigate the negative impact of age on survival.

Purpose: Comorbid medical conditions define a subset of patients with chronic lymphocytic leukemia (CLL) with poor outcomes. However, which comorbidities are most predictive remains understudied. Experimental Design: We conducted a retrospective analysis from 10 academic centers to ascertain the relative importance of comorbidities assessed by the cumulative illness rating scale (CIRS). The influence of specific comorbidities on event-free survival (EFS) was assessed in this derivation dataset using random survival forests to construct a CLL-specific comorbidity index (CLL-CI). Cox models were then fit to this dataset and to a single-center, independent validation dataset. Results: The derivation and validation sets comprised 570 patients (59% receiving Bruton tyrosine kinase inhibitor, BTKi) and 167 patients (50% receiving BTKi), respectively. Of the 14 CIRS organ systems, three had a strong and stable influence on EFS: any vascular, moderate/severe endocrine, moderate/severe upper gastrointestinal comorbidity. These were combined to create the CLL-CI score, which was categorized into 3 risk groups. In the derivation dataset, the median EFS values were 58, 33, and 20 months in the low, intermediate, and high-risk groups, correspondingly. Two-year overall survival (OS) rates were 96%, 91%, and 82%. In the validation dataset, median EFS values were 81, 40, and 23 months (two-year OS rates 97%/92%/88%), correspondingly. Adjusting for prognostic factors, CLL-CI was significantly associated with EFS in patients treated with either chemo-immunotherapy or with BTKi in each of our 2 datasets. Conclusions: The CLL-CI is a simplified, CLL-specific comorbidity index that can be easily applied in clinical practice and correlates with survival in CLL.

Chimeric antigen receptor T cell (CAR-T) therapy is approved for treatment of relapsed/refractory (R/R) diffuse large B cell lymphoma (DLBCL). Here we evaluate whether comorbidities, calculated using the Cumulative Illness Rating Scale (CIRS), predict survival for these patients. A retrospective chart review was performed at 4 academic institutions. All patients who underwent leukapheresis for commercial CAR-T therapy for R/R DLBCL were included. CIRS scores were calculated at the time of leukapheresis. High comorbidity was defined as either CIRS ≥7 or the presence of severe impairment (CIRS 3/4 in ≥1 system; CIRS-3+). Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method, and differences in curves were detected by the log-rank test. A total of 130 patients were analyzed, 56.9% with CIRS ≥7 and 56.2% with CIRS-3+. After a median follow-up of 13 months, the median PFS was 6.7 months, and the median OS was not reached. On univariable analysis, Eastern Cooperative Oncology Group (ECOG) performance status (PS) was associated with inferior PFS (hazard ratio [HR], 1.45; 95% confidence interval [CI], 1.03-2.05; P = .03) and OS (HR, 1.76; 95% CI, 1.17-2.64; P = .007). Higher CIRS (CIRS ≥7 or CIRS-3+) was associated with inferior OS (HR, 2.12; 95%, CI, 1.06-4.22; P = .03) and a nonsignificant trend in worse PFS (HR, 1.45; 95% CI, .87-2.44; P = .16). In multivariable analyses, CIRS ≥7 or CIRS-3+ and ECOG PS maintained independent prognostic significance. Comorbidities as determined by CIRS and ECOG PS predict inferior survival in patients receiving CAR-T therapy for R/R DLBCL.

Prospective identification of candidates for deferred therapy is not standardized and many patients receive immediate therapy regardless of risk. We conducted a retrospective, multi-center cohort analysis of MCL patients with comprehensive clinical data to examine the use and safety of deferred therapy for newly diagnosed patients. Previously untreated patients ≥18 years-old with MCL diagnosed in 1993-2015 at five academic sites were included. Of 395 patients, 72 (18%) received deferred therapy (defined as receipt of first treatment90 days following initial diagnosis). Patients receiving deferred therapy were more likely to have an ECOG performance status of 0 (67 versus 44% p = .001), have no B symptoms (83 versus 65% p = .003) and have normal LDH levels at diagnosis (87 versus 55% p .001). In multivariable analysis, deferred therapy was not associated with a significant difference in OS (HR 0.64: 95% CI 0.22-1.84, p = .407).

Background Risk stratification of newly diagnosed patients with mantle cell lymphoma (MCL) primarily is based on the MCL International Prognostic Index (MIPI) and Ki-67 proliferative index. Single-center studies have reported inferior outcomes in patients with a complex karyotype (CK), but this remains an area of controversy. Methods The authors retrospectively reviewed 483 patients from 5 academic centers in the United States and described the effect of a CK on survival outcomes in individuals with MCL. Results A CK was found to be associated with inferior overall survival (OS) (4.5 vs 11.6 years; P 30% (HR, 1.86; 95% CI, 1.06-3.28 [P = .03]) were associated with inferior PFS. Multivariable analysis did not identify any specific cytogenetic abnormalities associated with inferior survival. Conclusions CK appears to be independently associated with inferior outcomes in patients with MCL regardless of the intensity of induction therapy and receipt of ASCT. Cytogenetics should be incorporated into the workup of a new diagnosis of MCL and novel therapeutic approaches should be investigated for patients with CK. Cancer 2018;124:2306-15. © 2018 American Cancer Society.

Introduction: Comorbidities are common in CLL and associated with shorter overall survival (OS) and disease specific survival (Rotbain, Leukemia, 2021). Using an ensemble machine learning approach, we identified the comorbidities most strongly associated with event free survival (EFS) in CLL in order to construct the CLL-CI (Gordon et al, 2021). Our initial report included heterogeneously-treated derivation (N=570) and validation (N=167) cohorts of patients with CLL. Median EFS in the derivation cohort was 58, 33 and 20 months for low, intermediate and high-risk CLL-CI groups, respectively (p Methods: In our multicenter CLL cohort, we retrospectively analyzed patients from 10 academic centers who received targeted therapies, e.g. ibrutinib, acalabrutinib, idelalisib and venetoclax. Secondly, we now compiled a validation cohort which included patients from the Danish National CLL registry. CLL-CI score was assigned as previously reported (Gordon et al, 2021). Briefly, one point was assigned, if present, for any cumulative illness rating scale (CIRS) vascular comorbidity, moderate/severe upper gastrointestinal CIRS comorbidity and moderate/severe endocrine CIRS comorbidity, for a total maximum score of 3 (Fig. 1A). A score of 0 signifies low risk disease, 1-intermediated risk and 2-3-high risk. The Kaplan-Meier method and Cox models were used to estimate the association between CLL-CI, EFS (defined as death or next therapy) and OS. Results: CLL patients treated with targeted therapies (N=448) had a median age of 68 years (range, 26-91), 124 pts (28%) had TP53 aberrancy, 268 (60%) were treated in the relapsed/refractory (R/R) setting and 398 (89%) received ibrutinib. By CLL-CI group, 194 (43%) were low risk, 173 (39%) intermediate risk and 81 (18%) high risk. Median EFS was 57, 35 and 17 months for low, intermediate and high-risk groups, respectively (p The validation cohort (N=4975) included patients from the Danish CLL registry. Median age was 71 years, 1630 (33%) had low risk CLL-IPI and 425 (8.5%) had high or very-high risk CLL-IPI; 87% received chemoimmunotherapy. From time of diagnosis, in low, intermediate and high risk CLL-CI groups the median OS was not reached, 8.5 and 6 years, respectively (p Conclusions: Here we report that a novel comorbidity index, CLL-CI, predicts outcomes in patients with CLL treated with targeted therapies. Furthermore, we validate this index in a large National Registry. Thus, CLL-CI is a validated measure of comorbidity in CLL which provides important prognostic information for patients with early stage disease treated with a watch and wait approach and in patients with advanced stage disease receiving targeted therapies or chemoimmunotherapy. Figure 1 Figure 1. Disclosures Rotbain: Abbvie: Other: travel grants; AstraZeneca: Consultancy, Other: travel grants; Janssen: Other: travel grants . Shouse: Kite Pharma: Speakers Bureau; Beigene: Honoraria. Mei: Morphosys: Research Funding; BMS: Research Funding; Epizyme: Research Funding; TG Therapeutics: Research Funding; EUSA: Honoraria; Janssen: Honoraria; Beigene: Research Funding. Brander: Ascentage: Research Funding; Pfizer: Consultancy, Other: Biosimilars outcomes research panel; ArQule: Research Funding; DTRM: Research Funding; Genentech: Consultancy, Research Funding; BeiGene: Research Funding; Juno Therapeutics/Celgene/Bristol Myers Squibb: Research Funding; LOXO: Research Funding; MEI Pharma: Research Funding; TG Therapeutics: Consultancy, Research Funding; AstraZeneca: Research Funding; Verastem: Consultancy; NCCN: Other: panel member; Novartis: Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; AbbVie: Consultancy, Other: informCLL registry steering committee, Research Funding; ArQule/Merck: Consultancy. Hill: Incyte/Morphysis: Consultancy, Honoraria, Research Funding; Gentenech: Consultancy, Honoraria, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel Support, Research Funding; Celgene (BMS): Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria; Epizyme: Consultancy, Honoraria; Beigene: Consultancy, Honoraria, Research Funding. Choi: Abbvie: Other: Institution: Research Grant/Funding; Pharmacyclics: Other: Institution: Research Grant/Funding; Oncternal: Other: Institution: Research Grant/Funding; Velosbio: Other: Institution: Research Grant/Funding; Merck: Other: Institution: Research Grant/Funding; Geron: Other: Institution: Research Grant/Funding. Cohen: Genentech, BMS/Celgene, LAM, BioINvent, LOXO, Astra Zeneca, Novartis, M2Gen, Takeda: Research Funding; Janssen, Adicet, Astra Zeneca, Genentech, Aptitude Health, Cellectar, Kite/Gilead, Loxo, BeiGene, Adaptive: Consultancy. Stephens: Abbvie: Consultancy; Novartis: Research Funding; JUNO: Research Funding; Mingsight: Research Funding; Beigene: Membership on an entity's Board of Directors or advisory committees; Arqule: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; Epizyme: Membership on an entity's Board of Directors or advisory committees; Innate Pharma: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Consultancy; CSL Behring: Consultancy; Celgene: Consultancy; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding. Patel: Kite Pharma: Consultancy, Speakers Bureau; MEI Pharma: Consultancy; TG Therapeutics: Consultancy, Speakers Bureau; Abbvie: Consultancy; Janssen: Consultancy; Genentech: Consultancy; Bristol Myers Squibb: Consultancy, Speakers Bureau; BeiGene: Consultancy; Morphosys: Consultancy; Pharmacyclics: Consultancy; AstraZeneca: Consultancy, Research Funding, Speakers Bureau; ADC Therapeutics: Consultancy; Lilly: Consultancy. Shadman: Mustang Bio, Celgene, Bristol Myers Squibb, Pharmacyclics, Gilead, Genentech, Abbvie, TG Therapeutics, Beigene, AstraZeneca, Sunesis, Atara Biotherapeutics, GenMab: Research Funding; Abbvie, Genentech, AstraZeneca, Sound Biologics, Pharmacyclics, Beigene, Bristol Myers Squibb, Morphosys, TG Therapeutics, Innate Pharma, Kite Pharma, Adaptive Biotechnologies, Epizyme, Eli Lilly, Adaptimmune , Mustang Bio and Atara Biotherapeutics: Consultancy. Niemann: Novo Nordisk Foundation: Research Funding; CSL Behring, Genmab, Takeda, Octapharma: Consultancy; Abbvie, AstraZeneca, Janssen: Consultancy, Research Funding. Danilov: Abbvie: Consultancy, Honoraria; Beigene: Consultancy, Honoraria; Pharmacyclics: Consultancy, Honoraria; Rigel Pharm: Honoraria; Gilead Sciences: Research Funding; Bristol-Meyers-Squibb: Honoraria, Research Funding; Astra Zeneca: Consultancy, Honoraria, Research Funding; TG Therapeutics: Consultancy, Research Funding; Genentech: Consultancy, Honoraria, Research Funding; Takeda Oncology: Research Funding; Bayer Oncology: Consultancy, Honoraria, Research Funding; SecuraBio: Research Funding.

3117 Background: Activation of the RET proto-oncogene has been identified in multiple cancer types, for example, gene rearrangements in non-small cell lung cancer (NSCLC) and papillary thyroid cancer (PTC) and activating mutations in medullary thyroid cancer (MTC), amongst others. The recent FDA approval of two highly selective RET inhibitors, selpercatinib and pralsetinib has changed the treatment paradigm of RET-driven cancers, but the significance of historical prognostic factors is unknown. Herein, we analyzed the outcomes of patients with RET-altered cancers enrolled in phase I trials and assess the utility of prognostic scores. Methods: A retrospective analysis was performed of patients treated with selective RET inhibitors at the MD Anderson Cancer Center (MDACC). Baseline clinical factors and survival data were assessed. Overall and progression free survival (OS and PFS) were estimated using the Kaplan-Meier method and multivariable Cox models were constructed. For all a p-value of < 0.05 was consider significant. Results: Among 126 patients, median age was 58 years (range, 15-82), most with ECOG 0-1 (n = 124). RET-mutant MTC was most frequent (n = 81), followed by RET fusion-positive NSCLC (n = 30) and RET fusion positive thyroid cancer (n = 9). RET fusion partners were KIF5B (n = 17), CCD6 (n = 12) and NCOA4 (n = 7). RET M918T mutation was the most frequent (n = 50, 63%). Most patients were treated in the relapsed/refractory (R/R) setting (n = 85) and received a median of 1 prior line of therapy (range, 0-11). Median follow up was 20 months (range, 1-43). The estimated median PFS and OS were 24 and 35 months, respectively. Overall objective response rate was 64% (81/126), 2 complete response, 79 partial response, 32 had stable disease (25%) and 13 had progressive disease (PD). The following were associated with shorter PFS and OS: age ≥50 years (p < 0.05), albumin < 4 g/dL (p < 0.01), brain metastases (p < 0.0001), hemoglobin < 12 g/dL ( < 0.05), LDH > normal (p < 0.05), WBC ≥8 (p < 0.01), PD (p < 0.0001) and NSCLC (p < 0.01). The M918T mutation and ECOG > 0 were associated with shorter OS but not PFS (p < 0.05). > 3 metastatic sites and R/R disease were associated with inferior PFS (p = 0.04 and p = 0.01, respectively) but not OS. The Royal Marsden Hospital (RMH) and MDACC prognostic scores were significantly associated with PFS and OS (p < 0.01). In multivariable models including all variables significantly associated with PFS and OS (excluding LDH as this was only tested in 58 patients) albumin < 4 (HR 6.10, p = 0.013), brain metastases (HR 4.90, p = 0.027) and WBC ≥8 (HR 4.67, p = 0.031) were associated with inferior OS. NSCLC was significantly associated with inferior PFS (HR 5.45, p = 0.02). Conclusions: The RMH and MDACC prognostic scores predict OS in RET-aberrant cancers treated on early phase trials. Low albumin, WBC > 8 and brain metastases are significantly associated with inferior survival.

The majority of patients with non-Hodgkin lymphoma (NHL) and chronic lymphocytic leukemia (CLL) present with comorbidities. Many of them are poor candidates for intensive chemo-immunotherapy regimens, such as FCR (fludarabine, cyclophosphamide, rituximab). Still, most clinical trials aim to enroll 'fit' patients, who poorly represent the community oncology population. Areas covered: In the past decade, bendamustine hydrochloride, a cytotoxic agent with structural similarities to both alkylating agents and purine analogs, has received widespread use in therapy of NHL and CLL, and has demonstrated a relatively favorable toxicity profile. However, bendamustine has not been well studied in patients with hematologic malignancies who have comorbidities. Here we review the clinical data on use of bendamustine in older and unfit patients with NHL and CLL, and analyze whether there is an optimal dose of bendamustine in patients who have significant comorbidities, including renal dysfunction. Expert commentary: Reduced intensity regimens of bendamustine are effective in CLL patients with comorbidities and renal dysfunction. Even with the introduction of targeted therapies, bendamustine will likely continue to be an important therapeutic option in patients with comorbidities because of its tolerability, efficacy and cost.

Comorbidities influence survival in patients with chronic lymphocytic leukaemia (CLL) treated with chemo-immunotherapy or ibrutinib. While idelalisib has been studied in patients with comorbidities, their impact has not been investigated. We analysed 481 patients treated with idelalisib on two randomised trials (NCT01659021 and NCT01539512). Comorbidities were assessed using the Cumulative Illness Risk Scale (CIRS). Patients received idelalisib + anti-CD20 (rituximab or ofatumumab; n = 284) or anti-CD20 alone (n = 197). The median age was 69 years. We found that comorbidities did not significantly affect outcomes of idelalisib therapy. The objective response rate (ORR) was 79·3% versus 85·8%, the median progression-free survival (PFS) was 16·3 versus 19·1 months, and the median overall survival (OS) was 39·8 versus 49·8 months in patients treated with idelalisib who had a CIRS score of >6 versus ≤6, correspondingly. Treatment with idelalisib + anti-CD20 was associated with superior PFS and ORR when compared to anti-CD20 monotherapy in patients who had high comorbidities (CIRS score of >6) or at least one severe comorbidity (median PFS 16·3 vs. 6·9 months and 16·6 vs. 6·5 months; odds ratio 20·1 and 33·2; P < 0·0001). Thus, comorbidities do not portend inferior outcomes in patients with CLL treated with idelalisib in combination with anti-CD20 therapy.

Ibrutinib, the first in class of the oral covalent Bruton tyrosine kinase (BTK) inhibitors, has profoundly changed the treatment landscape of chronic lymphocytic leukemia (CLL). The phase III RESONATE and RESONATE-2 trials first demonstrated the superiority of ibrutinib over ofatumumab in the relapsed/refractory setting and over chlorambucil in older patients with de novo disease. The phase III ECOG–ACRIN trial extended these results to young, fit patients, demonstrating a significant survival advantage to ibrutinib plus rituximab over fludarabine, cyclophosphamide, and rituximab. Similarly, the Alliance trial demonstrated the superiority of ibrutinib over bendamustine with rituximab as frontline in elderly patients. Challenges with ibrutinib include toxicity, development of resistance, and need for indefinite therapy. The second generation BTK inhibitor acalabrutinib may cause less off-target toxicity. The ELEVATE TN trial demonstrated the superiority of acalabrutinib with or without obinutuzumab over chlorambucil and obinutuzumab as frontline therapy for elderly or comorbid patients. Promising early results from the phase II CAPTIVATE and CLARITY trials, which combined ibrutinib with venetoclax, suggest a future role for minimal residual disease (MRD) testing to determine treatment duration. The ongoing phase III GAIA/CLL13, ECOG EA9161, Alliance A041702, CLL17, and [ClinicalTrials.gov identifier: NCT03836261] trials will assess various combinations of ibrutinib/acalabrutinib, venetoclax, and anti-CD20 antibodies. These trials will answer key questions in the treatment of CLL: should novel agents in CLL be used in combination or sequentially? What is the best frontline agent? Can treatment be safely stopped with BTK inhibitors? Can undetectable MRD be used to determine treatment duration? In this review, we will discuss these and other aspects of the evolving role of BTK inhibition in CLL.

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.

Introduction: Outcomes in CLL are highly variable and influenced by both biologic and clinical factors. The Cumulative Illness Rating Scale (CIRS) is frequently used to assess comorbidities in CLL. Our group has demonstrated that CIRS correlates with survival in patients treated with either CIT or ibrutinib. Yet, CIRS has not become part of common clinical practice due to complexities in scoring since 14 systems need to be evaluated. Furthermore, the relative contribution of individual comorbidities to patient outcomes is unknown. Here we report the impact of specific comorbidities in a large cohort of CLL patients and propose a simplified CLL-comorbidity index (CLL-CI). Methods: We conducted a retrospective analysis of patients with CLL treated with either CIT or kinase inhibitors at 10 US academic medical centers between 2000-2018. CIRS score was calculated as in Salvi et al, 2008. Patients were randomly divided into a training-set (n=381) and validation-set (n=189). Random survival forests (RSF) were constructed on the training-set to select variables for Cox regression models. Discrimination of models was tested in the validation-set. CIRS score in each organ system, relapse/refractory (R/R) disease, treatment type, age, and del(17p) were included as features for RSF modeling of event-free survival (EFS), defined as time from treatment to death, disease progression or next therapy. For each RSF, features were scored and ranked according to variable importance (VI; the decrease in prediction accuracy when the specific variable is randomly permuted) and minimal depth (MD; the minimum distance between the root node of a tree and the first node that splits on the specific variable). After 200 RSF's, VI and MD ranks were averaged. Organ system variables whose average rank for both predictive measures was ≤10 were chosen for Cox regression modeling of EFS and OS. Three sets of Cox models were fit on the training data and applied to the validation-set to compute c-statistics depicting each model's ability to predict EFS. Cox models assessed the addition of either CIRS or CLL-CI to known prognostic factors. Results: The data set contained 614 patients; 570 (93%) with complete data were included in our analysis. Median age was 67 years (range 30-91). Median CIRS was 7 (range, 0-29) with CIRS≥7 in 302 patients (53%). Median follow up was 31 months. Del(17p) and/or TP53 mutation was present in 113 patients (20%) and 299 (52%) were assessed in the R/R setting. Ibrutinib was the most common treatment (n=338, 59%), followed by fludarabine (n=163) and bendamustine (n=116). In the training-set, four organ system variables ("musculoskeletal", "renal", "endocrine" and "upper GI"), were selected based on RFS average predictive measure ranks and summed to derive the CLL-CI score. Median CLL-CI was 2 (range, 0-11) in the training cohort with a value of 3 identified as the optimal cut-point for association with EFS; 236 (41%) had a high CLL-CI score (≥3). Cox models that included either CLL-CI or CIRS (alongside age, disease status, type of treatment, and del(17p)/TP53 mutation) yielded c-statistics of 0.68 (95% CI: 0.65-0.69) and 0.68 (95% CI: 0.65-0.70), respectively. These discrimination estimates were modestly superior to the model without a comorbidity variable (c-statistic, 0.64). In the complete data set, R/R disease and age were associated with decreased EFS (HR=2.14, p Conclusion: In this large data set, we utilized random forests to identify "musculoskeletal", "upper GI", "endocrine", and "renal" comorbidities as the most prognostic of EFS in patients with CLL. Using only these 4 CIRS variables, we developed and validated a simplified comorbidity score (CLL-CI) which performed similar to CIRS, but has lower complexity and therefore can be easily incorporated into clinical practice. Disclosures Patel: Sunesis: Consultancy; Pharmacyclics/Janssen: Consultancy, Speakers Bureau; AstraZeneca: Consultancy, Research Funding, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Genentech: Consultancy, Speakers Bureau. Persky:Sandoz: Consultancy; Morphosys: Other: Member, Independent Data Monitoring Committee; Debiopharm: Other: Member, Independent Data Monitoring Committee; Bayer: Consultancy. Cohen:Genentech, Inc.: Consultancy, Research Funding; Janssen Pharmaceuticals: Consultancy; Seattle Genetics, Inc.: Consultancy, Research Funding; Bristol-Meyers Squibb Company: Research Funding; 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. Choi:Rigel: Consultancy, Research Funding; Gilead: Consultancy, Speakers Bureau; Oncternal: Research Funding; Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; Genentech: Consultancy, Speakers Bureau; Abbvie: Consultancy, Research Funding, Speakers Bureau. Hill:Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Consultancy, Honoraria; Amgen: Research Funding; Takeda: Research Funding; Celegene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Research Funding; Kite: Consultancy, Honoraria; TG therapeutics: Research Funding. Shadman:Sunesis: Research Funding; Pharmacyclics: Consultancy, Research Funding; Celgene: Research Funding; ADC Therapeutics: Consultancy; Atara Biotherapeutics: Consultancy; Genentech: Consultancy, Research Funding; Gilead: Consultancy, Research Funding; Mustang Bio: Research Funding; Verastem: Consultancy; Astra Zeneca: Consultancy; AbbVie: Consultancy, Research Funding; BeiGene: Research Funding; TG Therapeutic: Research Funding; Sound Biologics: Consultancy; Acerta Pharma: Research Funding. Stephens:Acerta: Research Funding; Karyopharm: Research Funding; Gilead: Research Funding. Brander:Tolero: Research Funding; MEI: Research Funding; Acerta: Research Funding; Genentech: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Research Funding; Novartis: Consultancy; Pharmacyclics LLC, an AbbVie Company: Consultancy; BeiGene: Research Funding; DTRM Biopharma: Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Teva: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria, Research Funding. Danilov:Celgene: Consultancy; Curis: Consultancy; Bayer Oncology: Consultancy, Research Funding; Seattle Genetics: Consultancy; AstraZeneca: Consultancy, Research Funding; Gilead Sciences: Consultancy, Research Funding; Verastem Oncology: Consultancy, Other: Travel Reimbursement , Research Funding; Janssen: Consultancy; Pharmacyclics: Consultancy; Aptose Biosciences: Research Funding; Bristol-Meyers Squibb: Research Funding; TG Therapeutics: Consultancy; Takeda Oncology: Research Funding; MEI: Research Funding; Abbvie: Consultancy; Genentech: Consultancy, Research Funding.

Background: BL is associated with a high risk of primary or secondary CNS involvement, warranting intrathecal (IT) and/or systemic therapy that penetrates the blood-brain barrier (BBB). The lower-intensity DA-EPOCH-R regimen has recently shown high survival rates in BL (Dunleavy, NEJM 2013), but it omits drugs traditionally used for CNS prophylaxis (like high-dose methotrexate [HDMTX]). The objective of this multi-institutional retrospective study was to examine treatments, risk factors, and CNS-related outcomes among patients (pts) with BL. Methods: We collected data from 26 US centers on adult BL pts diagnosed (dx) in 6/2009-6/2018. Using institutional expert pathology review and 2016 WHO criteria, we excluded other high-grade lymphomas (including BL-like/unclassifiable), or cases with inadequate clinicopathologic data. We studied factors associated with baseline CNS involvement (CNSinv) using logistic regression reporting odds ratios (OR). Progression-free (PFS), overall survival (OS), and cumulative incidence function of CNS recurrence (in a competing risk analysis) were examined in Cox or Fine-Gray models reporting hazard (HR) or subhazard ratios (SHR), respectively. All estimates report 95% confidence intervals (in square brackets). Results: Among 557 BL pts (median age, 47 years [yr], 24% women, 23% HIV+), 107 (19%) had CNSinv at dx, including 89 (16%) with leptomeningeal, and 15 (3%) with parenchymal CNS disease. In a multivariable model, factors significantly associated with CNSinv at dx included stage 3/4 (OR, 11.2 [1.47-85.9]), poor performance status (PS; OR, 2.12 [1.22-3.69]), ≥2 extranodal sites (OR, 3.77 [2.02-7.03]), or marrow involvement (OR, 2.44 [1.35-4.39]), whereas intestinal involvement conferred low risk of CNSinv (OR, 0.27 [0.11-0.65]). CNSinv at dx was not significantly associated with use of specific chemotherapy regimens (Fig. A,P=.75) or receipt of IT chemotherapy (91% vs 84%, P=.065). Pts with CNSinv were less likely to achieve a complete response (62% vs 76%, P=.005), had worse 3 yr PFS (47% vs 69%; P3x upper limit of normal [LDH>3x]; see Evens AM et al, ASH 2019 for further details). With median follow up of 3.6 yrs, 33 pts (6%) experienced a CNS recurrence (82% within 1 yr from dx; 79% purely in CNS, and 21% with concurrent systemic BL). The cumulative risk of CNS recurrence was 6% [4-8%] at 3y (Fig. D). Univariate significant predictors of CNS recurrence included baseline CNSinv, HIV+ status, stage 3/4, poor PS, LDH>3x, involvement of ≥2 extranodal sites, marrow, or testis. However, in a multivariate model only baseline CNSinv (SHR, 3.35 [1.53-7.31]) and poor PS (SHR, 2.24 [1.03-4.90]) retained significance. The 3 yr risk of CNS recurrence varied from 3% for pts with no risk factor, to 10% with one, and 17% with both factors (Fig. E). In addition, the risk of CNS recurrence differed according to chemotherapy regimen, and was significantly higher for pts treated with DA-EPOCH (12% at 3y [8-18%]; Fig. F) compared with CODOX-M/IVAC (4% [2-8%]) or hyperCVAD/MA (3% [1-6%]; SHR for DA-EPOCH vs. others, 3.50 [1.69-7.22]). All pts recurring after DA-EPOCH had received IT chemotherapy. Higher risk of CNS recurrence persisted with DA-EPOCH regardless of baseline CNSinv (Pinteraction=.70), poor PS (Pint=.14), or HIV status (Pint=.89). Baseline CNSinv was the strongest factor associated with CNS recurrence after DA-EPOCH (3 yr risk, 30% vs 8%, P Conclusions: In adult BL, baseline CNSinv and poor PS predicted subsequent CNS recurrence, an outcome that is associated with a dismal prognosis. Furthermore, treatment with DA-EPOCH was associated with a significantly increased risk of CNS recurrence in this real-world analysis. For BL pts with baseline CNSinv treated in routine clinical practice, regimens with highly BBB-penetrant drugs (e.g. CODOX-M/IVAC, hyperCVAD/MA) may be preferred. Studies should delineate ways to mitigate the risk of CNS recurrence with lower-intensity programs. Disclosures Evens: Seattle Genetics: Consultancy, Honoraria; Research to Practice: Honoraria; Verastem: Consultancy, Honoraria; Affimed: Consultancy, Honoraria; Pharmacyclics: Honoraria, Other: DMC; Bayer: Consultancy, Honoraria; Takeda: Research Funding; Merck: Research Funding. Smith:Incyte Corporation: Research Funding; Seattle Genetics: Research Funding; Portola Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding; Acerta Pharma BV: Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Ignyta (spouse): Research Funding; Merck Sharp & Dohme Corp: Consultancy, Research Funding; Denovo Biopharma: Research Funding; Bristol-Myers Squibb (spouse): Research Funding; Ayala (spouse): Research Funding. Naik:Celgene: Other: Advisory board. Reddy:KITE Pharma: Consultancy; Abbvie: Consultancy; Genentech: Research Funding; BMS: Consultancy, Research Funding; Celgene: Consultancy. Farooq:Celgene: Honoraria; Kite Pharma: Research Funding. Epperla:Verastem Oncology: Speakers Bureau; Pharmacyclics: Honoraria. Khan:Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Janssen: Other: Educational Content/Symposium; Abbvie: Membership on an entity's Board of Directors or advisory committees; Bristol Myers: Other: Research Funds. Alderuccio:Puma Biotechnology: Other: Immediate family member; Agios: Other: Immediate family member; Inovio Pharmaceuticals: Other: Immediate family member; Targeted Oncology: Honoraria; OncLive: Consultancy; Foundation Medicine: Other: Immediate family member. Yazdy:Bayer: Honoraria; Genentech: Research Funding; Octapharma: Consultancy; Abbvie: Consultancy. Diefenbach:Bristol-Myers Squibb: Consultancy, Research Funding; Denovo: Research Funding; Genentech: Consultancy, Research Funding; Incyte: Research Funding; LAM Therapeutics: Research Funding; MEI: Research Funding; Merck: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Millenium/Takeda: Research Funding; Trillium: Research Funding. Karmali:Astrazeneca: Speakers Bureau; Takeda, BMS: Other: Research Funding to Institution; Gilead/Kite; Juno/Celgene: Consultancy, Speakers Bureau. Martin:Celgene: Consultancy; Teneobio: Consultancy; Karyopharm: Consultancy; Janssen: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy. Magarelli:Tevan Oncology: Speakers Bureau. Kamdar:Seattle Genetics: Speakers Bureau; Pharmacyclics: Consultancy; AstraZeneca: Consultancy; Celgene: Consultancy; University of Colorado: Employment. Portell:Xencor: Research Funding; Roche/Genentech: Research Funding; Infinity: Research Funding; TG Therapeutics: Research Funding; AbbVie: Research Funding; Pharmacyclics: Consultancy; Janssen: Consultancy; Genentech: Consultancy, Research Funding; Amgen: Consultancy; Bayer: Consultancy; BeiGene: Consultancy, Research Funding; Kite: Consultancy, Research Funding; Acerta/AstraZeneca: Research Funding. Lossos:Janssen Scientific: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; NIH: Research Funding. Olszewski:Genentech: Research Funding; Adaptive Biotechnologies: Research Funding; TG Therapeutics: Research Funding; Spectrum Pharmaceuticals: Research Funding.

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 Among pts with PRF MCL, median PFS2 and OS were 1.2 [0.5-2.3] and 2.4 [0.7-4.5] yrs for BTKi (n=21), 0.5 [0.2-2.3] and 1.1 [0.5-NR] yrs for CIT (n=22), and 0.3 [0.1-0.6] and 1.9 [0.1-2] yrs for lenalidomide / bortezomib (n=8) as 2nd line therapy. Two pts with PRF MCL received no further therapy and both died within one month of POD. Conclusions: Time to relapse is predictive of outcome in pts with MCL and outcomes with current salvage therapies are poor for pts with relapse within 6 months of frontline therapy. Of currently available second line therapies, BTKi were associated with improved PFS2 in refractory pts. Outcomes are particularly poor for pts who receive intensive induction therapies yet still relapse early, representing a population at high risk for early mortality related to MCL. Novel treatment approaches should be evaluated in this population, including CAR-T cell therapy, and attempts to improve risk stratification at diagnosis and develop improved therapies for high-risk pts should continue. Disclosures Maddocks: Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding; Merck: Research Funding; Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Teva: Membership on an entity's Board of Directors or advisory committees. Kolla:Amgen: Equity Ownership. Bachanova:Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Gamida Cell: Research Funding; Novartis: Research Funding; Kite: Membership on an entity's Board of Directors or advisory committees; Incyte: Research Funding; Celgene: Research Funding; GT Biopharma: Research Funding. Gerson:Abbvie: Consultancy; Seattle Genetics: Consultancy; Pharmacyclics: Consultancy. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Merck: Research Funding; Mundipharma: Honoraria; Bayer: Consultancy, Research Funding; Seattle Genetics: Honoraria, Research Funding; Takeda: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Mundipharma: Honoraria. Hill:Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria; Celegene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Amgen: Research Funding; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; TG therapeutics: Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Research Funding. Martin:Karyopharm: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Teneobio: Consultancy. Danilov:Verastem Oncology: Consultancy, Other: Travel Reimbursement , Research Funding; Bristol-Meyers Squibb: Research Funding; Aptose Biosciences: Research Funding; Bayer Oncology: Consultancy, Research Funding; TG Therapeutics: Consultancy; Curis: Consultancy; Seattle Genetics: Consultancy; Celgene: Consultancy; MEI: Research Funding; Janssen: Consultancy; Abbvie: Consultancy; Pharmacyclics: Consultancy; Takeda Oncology: Research Funding; AstraZeneca: Consultancy, Research Funding; Gilead Sciences: Consultancy, Research Funding; Genentech: Consultancy, Research Funding. Grover:Seattle Genetics: Consultancy. Karmali:Takeda, BMS: Other: Research Funding to Institution; Astrazeneca: Speakers Bureau; Gilead/Kite; Juno/Celgene: Consultancy, Speakers Bureau. Ghosh:AstraZeneca: Honoraria, Speakers Bureau; Bristol-Myers Squibb: Honoraria, Speakers Bureau; Gilead: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Research Funding, Speakers Bureau; SGN: Consultancy, Honoraria, Research Funding, Speakers Bureau; TG Therapeutics: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Research Funding; Genentech: Research Funding; Forty Seven Inc: Research Funding. 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:Verastem Oncology: Speakers Bureau; Pharmacyclics: Honoraria. Hamadani:Pharmacyclics: Consultancy; Merck: Research Funding; Celgene: Consultancy; ADC Therapeutics: Consultancy, Research Funding; Sanofi Genzyme: Research Funding, Speakers Bureau; Janssen: Consultancy; Otsuka: Research Funding; Medimmune: Consultancy, Research Funding; Takeda: Research Funding. Kahl:BeiGene: Consultancy; TG Therapeutics: Consultancy; ADC Therapeutics: Consultancy, Research Funding; Seattle Genetics: Consultancy. Flowers:Gilead: Consultancy, Research Funding; BeiGene: Consultancy, Research Funding; AstraZeneca: Consultancy; Denovo Biopharma: Consultancy; National Cancer Institute: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Millenium/Takeda: Research Funding; Bayer: Consultancy; AbbVie: Consultancy, Research Funding; V Foundation: Research Funding; Optimum Rx: Consultancy; Eastern Cooperative Oncology Group: Research Funding; Karyopharm: Consultancy; Burroughs Wellcome Fund: Research Funding; TG Therapeutics: Research Funding; Acerta: Research Funding; Pharmacyclics/Janssen: Consultancy, Research Funding; Spectrum: Consultancy. Cohen:LAM Therapeutics: Research Funding; Takeda Pharmaceuticals North America, Inc.: Research Funding; Gilead/Kite: Consultancy; Astra Zeneca: Research Funding; Genentech, Inc.: Consultancy, Research Funding; Janssen Pharmaceuticals: Consultancy; Seattle Genetics, Inc.: Consultancy, Research Funding; Bristol-Meyers Squibb Company: Research Funding; ASH: Research Funding; Lymphoma Research Foundation: Research Funding; Hutchison: Research Funding; UNUM: Research Funding.