Zanwar, Saurabh

Abstract Introduction: Central nervous system (CNS) relapse is an uncommon but devastating complication occurring in about 2-10% of patients with diffuse large B-cell lymphoma (DLBCL). The CNS-IPI is a validated prognostic tool used to identify patients at high risk of CNS relapse. MYC and BCL2/BCL6 rearrangements (double-hit lymphoma- DHL) and non-GCB (NGCB) cell of origin may be at higher risk of CNS relapse. However, the ability of these molecular data to refine CNS-IPI risk prediction has not been assessed. In this study, we aimed to describe the impact of DHL and NGCB cell of origin in the incidence of CNS relapse in patients with newly diagnosed DLBCL. Methods: A retrospective review was conducted to identify patients with newly diagnosed DLBCL from 01/01/2002 - 06/30/2015 using the University of Iowa/Mayo Clinic Lymphoma Molecular Epidemiology Resource database. Patients with primary CNS lymphoma or with CNS involvement at diagnosis were excluded. All patients received chemoimmunotherapy. Clinical, biological, laboratory and radiological data were abstracted including the occurrence of CNS relapse. CNS IPI risk score categories were defined as low- (≤1) intermediate- (2-3) and high-risk (≥4) as originally described (Schmitz et al, JCO 2016). Cell of origin (COO) classification into GCB and non-GCB subtypes was performed using Hans algorithm and/or NanoString data. Characteristics between groups were compared using Kruskal-Wallis or Chi-squared test as appropriate. Survival analysis was performed using Cox proportional hazards model and the Kaplan Meier method. Statistical analysis was performed using SAS version 9.4M5 and R version 4.0.3. Results: We identified a total of 1,360 patients with newly diagnosed DLBCL. Patients had a median age of 62 years (range 18-93 years), were predominantly male (56%), had a performance status <2 (84%), had stage III/IV disease (61%) and an elevated LDH (56%) at diagnosis. Fluorescent in situ hybridization data was present for 65% of patients. Among patients with available data, DHL and NGCG COO represented 2.8% and 36% of the cohort, respectively. CNS IPI high- and intermediate-risk categories were present in 12.4% and 52% of the patients, respectively. R-CHOP was the most common upfront chemotherapy (n=980, 72%). The median follow-up for the entire cohort was 84.9 months (IQR: 58.9-120.9). Overall, 50 patients (3.6%) had a CNS relapse during the study period. Lymphoma relapsed in the CNS in 3.0% (95% CI:2.1-4.4), 4.7% (95% CI: 3.4-6.3) and 4.9% (95% CI: 3.7-6.6)% of patients with CNS-IPI score of intermediate/high risk at 1, 3 and 5 years following the diagnosis of DLBCL. In patients with low risk CNS-IPI, 1.1% (95% CI: 0.4-2.5), 1.7% (95% CI: 0.9-3.4) and 1.7% (95% CI: 0.9-3.4) had a CNS relapse at 1, 3 and 5 years following DLBC diagnosis. Patients with CNS relapse were more likely to have elevated LDH (76% vs 56%, p=0.008), advanced stage (78% vs 61%, p=0.01), adrenal involvement (8% vs 2.4%, p=0.014) and have a CNS IPI intermediate risk (68% vs 51%), and high risk (16% vs 12.3%, p=0.014) at the time of initial diagnosis compared to patients without CNS relapse. Patients with CNS relapse had similar rates of DHL (4% vs 2.7%, p=0.17) and NGCB cell of origin (42% vs 36.2%, p=0.52) compared to patients without CNS relapse. In the multivariable analysis, the strongest predictors for CNS relapse were CNS IPI high risk (Hazard Ratio [HR]= 3.6, 95%CI= 1.4-9.7) and CNS IPI intermediate risk (HR= 3.15, 95%CI= 1.46-6.81). DHL and NGCB cell of origin were not associated with a significantly higher risk of CNS relapse (HR= 1.79, [95%CI=0.42-7.59] and HR= 1.26, [95%CI=0.62-2.57], respectively). Conclusion: CNS relapse was an uncommon occurrence in patients with DLBCL who were treated with chemoimmunotherapy. CNS IPI intermediate- and high-risk scores remain the strongest predictors of CNS relapse in patients with DLBCL after adjusting to biological high-risk variables including DHL and NGCB cell of origin. Larger studies are required to validate our findings due to the low incidence of CNS relapse in our cohort. Figure 1 Figure 1. Disclosures Farooq: Kite, a Gilead Company: Honoraria. Maurer: Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Genentech: Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Witzig: Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding. Habermann: Tess Therapeutics: Other: Data Monitoring Committee; Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Novak: Celgene/BMS: Research Funding.

Abstract Background: Patients with multiple myeloma (MM) that are refractory to a proteasome inhibitors (PI), immunomodulatory drug (IMiDs) and CD38/SLAMF7 directed monoclonal antibodies are commonly referred to as triple class refractory (TCR). This is an increasingly common clinical problem and here we present the outcomes, prognostic markers and response to therapy for patients with TCR disease. Methods: Consecutive patients with MM diagnosed between 01/01/2013 and 12/31/2018 and seen at Mayo Clinic, Rochester, MN were included in this study after institutional review board approval. Refractoriness to therapy was defined as progression or non-responsiveness (failure to achieve at least a minimal response) to therapy within 60 days of discontinuation of therapy, based on the International Myeloma Workshop Consensus definition. Patients meeting the definition for refractory disease for at least 1 PI (bortezomib, carfilzomib or ixazomib), 1 IMiD (lenalidomide, pomalidomide or thalidomide) and 1 monoclonal antibody (daratumumab, isatuximab or elotuzumab) were considered to have TCR disease and included in the study population. The first date when patients satisfied the above-mentioned criteria for TCR was used to calculate the follow-up, progression free survival (PFS) and OS for TCR disease. The mSMART 3.0 (www.msmart.org) classification was used to characterize high-risk and standard-risk cytogenetics features in interphase fluorescence in situ hybridization (FISH). The currently prevalent international myeloma working group (IMWG) criteria were used for response assessment. The Kaplan-Meier method was used for estimation of time-to-event endpoints. Reverse censoring was used for estimation of follow-up time. Cox regression was used for multivariate analyses. Wilcoxon test was used for comparison of continuous variables and Chi square test or Fisher's exact test were used to compare categorical variables, respectively Results: In this retrospective study, 249 consecutive patients with TCR status were identified. The median follow-up from diagnosis of MM till date of last follow-up was 6.8 years (95% CI: 6.3-7.3 years) and 1.9 years (95% CI: 1.6-2.4) from TCR MM to last follow-up. The median age at diagnosis of MM was 61 years (range 31-89) and at TCR was 65 years (range 32-93). The median number of lines of therapy for the entire cohort were 8 (range 1-17); the patients were exposed to a median of 5 (range 1-12) lines of therapy prior to TCR status. Baseline characteristics for the cohort are depicted in Table 1. The median time to development of triple refractory disease was 2.9 years (95% CI: 2.6-3.2 years) from diagnosis of MM. The time to TCR disease was shorter for high-risk cytogenetics at 2.3 years (95% CI: 2-2.7) compared to 3.4 years (95% CI: 3.1-4.1) with a hazard ratio (HR) of 1.8 (95% CI: 1.4-2.4) p<0.0001], Figure 1A. The median overall survival (OS) from TCR was 1.01 (95% CI: 0.9-1.3) years. High-risk cytogenetics at diagnosis of MM were associated with an inferior OS from TCR disease even after adjustment for age, and ISS stage [median 1.05 years (95% CI: 0.8-1.5) for high-risk vs 1.3 years (95% CI: 0.9-2.9) for standard-risk cytogenetics; hazard ratio 1.44 (95% CI: 1.01-2.05); p=0.04]. Of 249 patients, 227 had data available for therapy post TCR (initial therapy details post TCR status are depicted in Table 2) with a median PFS of 4 months (95% CI: 3.5-5) for the salvage therapy post attainment of TCR. Patients achieving a deeper response [≥partial response (PR)] were noted to have a significantly improved PFS with the initial therapy post TCR disease [median PFS 8.2 months (95% CI: 7.5-12.7)] compared to patients not achieving a PR [median PFS 2 months (95% CI: 1.6-2.7); HR 0.2 (95% CI: 0.13-0.27); p<0.0001], Figure 1B. Deeper response (≥PR) to initial therapy at TCR disease was associated with an improved PFS [HR 0.23 (95% CI: 0.16-0.34); p <0.0001] after adjusting for age at TCR status, ISS stage and cytogenetic risk categories at diagnosis. Conclusion: Patients with triple refractory MM have a guarded prognosis and demonstrate an underwhelming median PFS of 4 months and median OS of 1 year. Achievement of a deeper response to therapy at triple refractory status is associated with a prolonged PFS. High-risk cytogenetic features at diagnosis confer a negative prognosis in TCR patients. Newer therapies are the needed to sustain the improvement in outcomes for this group of patients. Figure 1 Figure 1. Disclosures Kapoor: Cellectar: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; BeiGene: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Karyopharm: Consultancy; Regeneron Pharmaceuticals: Research Funding; AbbVie: Research Funding; Takeda: Research Funding; Sanofi: Research Funding; Karyopharm: Research Funding; Glaxo SmithKline: Research Funding. Dispenzieri: Pfizer: Research Funding; Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Alnylam: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Gertz: Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria. Dingli: Apellis: Consultancy; GSK: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Novartis: Research Funding; Alexion: Consultancy. Kumar: Sanofi: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; Tenebio: Research Funding; Novartis: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Merck: Research Funding; Carsgen: Research Funding; Antengene: Consultancy, Honoraria; Oncopeptides: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract INTRODUCTION Central nervous system (CNS) relapse is a challenging situation in diffuse large B-cell lymphoma (DLBCL). High CNS-International Prognostic Index (IPI), activated B-cell (ABC) subtype and MYD88 L265P mutation, features often found in transformed Waldenström macroglobulinemia (WM), are associated with a higher risk for developing CNS relapse. This study was aimed to describe CNS involvement in a large cohort of transformed WM. METHODS This international multicenter retrospective study included patients with a diagnosis of WM and a concurrent or sequential histological diagnosis of DLBCL. CNS disease was diagnosed by detection of DLBCL cells in the cerebrospinal fluid and/or by brain biopsy. Patients with CNS involvement by lymphoplasmacytic cells (Bing-Neel syndrome) were excluded. Of 254 identified patients with a diagnosis of histological transformation (HT) between 1988 and 2020, 19 were excluded due to lack of data on extranodal involvement. The first part of the analysis focused on baseline CNS involvement. Clinicobiological characteristics were compared between groups using Chi-square or Fisher's exact tests or Mann Whitney tests as appropriate. We analyzed CNS recurrence in the second part of the study. Forty-eight additional patients were excluded due to baseline CNS involvement (n = 25), absence of treatment at HT (n = 14) and lack of details on follow-up (n = 9). Cumulative incidence of CNS relapse was analyzed using competing-risk models that accounted for other events like systemic relapse or death from any cause, reporting sub-hazard ratio (SHR). RESULTS Baseline CNS involvement was present in 25 patients (11%) with transformed WM, including 10 (4%) with parenchymal disease, 10 with leptomeningeal, 4 (2%) with both, and 1 with unspecified CNS involvement. Characteristics associated with baseline CNS involvement were performance status 2-4 (P=0.03) and ≥2 extranodal sites (P=0.02). Median survival after HT was 1 year [0.7-2.5], comparable to the one of patients without CNS disease (1.8 year [1.2-2.6], P=0.74). We observed no difference in survival based on isolated CNS involvement (n = 10) compared to CNS and systemic involvement (n = 15) (P=0.94). Twenty-three CNS relapses occurred (12%). The 2-year and 3-year rates of CNS relapse were 9% (95% CI, 6-14) and 11% (95% CI, 7-16) (Figure 1). The median time to relapse in the CNS was 11 months (95% CI, 7-25). Thirteen CNS recurrences (57%) occurred during the first year of follow-up. Seventy percent were isolated CNS relapses. The location was leptomeningeal in 43% of cases, parenchymal in 35%, both in 17%, and unspecified in 4%. According to CNS-IPI risk groups (data available for 20 patients), 9 patients (45%) belonged to the high-risk group, 10 (50%) to the intermediate-risk group and 1 (5%) to the low-risk group. Prior to CNS relapse, 87% of patients had received rituximab, and 39% had received CNS prophylaxis (30% intrathecal chemotherapy, 4% high-dose methotrexate (HD-MTX), and 4% both). After CNS recurrence, 96% of patients received salvage treatment: combination of HD-MTX and HD-cytarabine (48%), HD-MTX alone (30%), or HD-cytarabine alone (9%). Four patients underwent consolidative autologous stem cell transplantation. The median survival after CNS relapse was 5.6 months. Factors associated with 3-year cumulative incidence of CNS recurrence in univariate analysis were involvement of kidney/adrenal glands (HR, 4.4; P=0.01) and MYD88 L265P mutation (P=0.01) (Figure 2A and B). Of note, among 74 patients (over 187, 40%) with data available for MYD88 mutation status, 11 CNS relapses occurred in patients with MYD88 L265P mutation (n = 54, 20%) whereas no relapse were observed in MYD88 WT cohort (n = 20). A trend toward higher risk of CNS relapse for ≥2 extranodal sites (HR, 2.3, 95% CI 0.98-5.3; P=0.06) was observed. Cumulative incidence according to CNS-IPI risk groups (0% in the low-risk, 9% in the intermediate-risk and 14% in the high-risk group) was not statistically significant (P=0.47). CONCLUSION CNS involvement occurs frequently in transformed WM. Rate of CNS relapse seems similar to DLBCL patients belonged to the CNS-IPI high-risk group. Special attention should be paid to patients with kidney/adrenal involvement and MYD88 L265P mutation. Figure 1 Figure 1. Disclosures Vos: Sanofi: Membership on an entity's Board of Directors or advisory committees; Celgene: Other: Travel reimbursement. Treon: X4: Research Funding; Janssen: Consultancy, Research Funding; Dana Farber Cancer Institute: Current Employment; BMS: Consultancy, Research Funding; Self: Patents & Royalties: Holder of multiple patents related to testing and treatment of MYD88 and CXCR4 mutated B-cell malignancies; AbbVie: Consultancy, Research Funding; BeiGene: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding. Dimopoulos: Janssen: Honoraria; Beigene: Honoraria; Amgen: Honoraria; BMS: Honoraria; Takeda: Honoraria. Kapoor: Cellectar: Consultancy; Karyopharm: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Castillo: Abbvie: Consultancy, Research Funding; BeiGene: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Janssen: Consultancy; Roche: Consultancy; TG Therapeutics: Research Funding.

SummaryPatients with asymptomatic/smouldering Waldenström macroglobulinaemia (SWM) have a variable risk of progression to active WM. Our study evaluated 143 patients with SWM consecutively seen between January 1996 and December 2013. With a median [95% confidence interval (CI)] follow‐up of 9·5 [8·1–11·5] years, the cumulative rate of progression was 11% at 1 year, 38% at 3 years and 55% at 5 years. On multivariate analysis, haemoglobin (Hb) ≤123 g/l [risk ratio (RR) 2·08; P = 0·009] and β2‐microglobulin (β2M) ≥2·7 µg/ml (RR 2·0; P = 0·01) were independent predictors of a shorter time‐to‐progression (TTP) to active WM. Patients with myeloid differentiation factor 88 wild type (MYD88WT) genotype (n = 11) demonstrated a trend toward shorter TTP [median (95% CI) 1·7 (0·7–8·7) vs. 4·7 (2·4–7·7) years for the MYD88L265P cohort, n = 42; P = 0·11]. The presence of C‐X‐C chemokine receptor type 4 (CXCR4) mutation (n = 29) did not impact the TTP (median: 3 years for CXCR4WT vs. 5·6 years for CXCR4MUT, P = 0·34). The overall survival (OS) for patients with SWM (median: 18·1 years) was comparable to an age‐, sex‐ and calendar year‐matched USA population (median: 20·3 years, P = 0·502). In conclusion, Hb and β2M at diagnosis represent independent predictors of progression to active WM. Comparable survival of SWM and a matched USA population argues against pre‐emptive intervention in this patient population.

Abstract Comparative data guiding initial therapy for Waldenström macroglobulinemia (WM), an infrequently encountered non‐Hodgkin lymphoma, are sparse. We evaluated three commonly used rituximab‐based frontline regimens: rituximab‐bendamustine (R‐Benda); dexamethasone, rituximab, cyclophosphamide (DRC); and bortezomib, dexamethasone, rituximab (BDR) in 220 treatment‐naïve patients with WM, seen at Mayo Clinic between November 1, 2000 and October 31, 2019. The median follow‐up was 4.5 (95%CI: 4–5) years. The R‐Benda cohort (n = 83) demonstrated superior overall response rate (ORR: 98%), in comparison to DRC (n = 92, ORR: 78%) or BDR (n = 45, ORR: 84%) cohorts, p = 0.003. Similarly, longer progression‐free survival (PFS) was evident with R‐Benda use [median 5.2 vs. 4.3 (DRC) and 1.8 years (BDR), p < 0.001]. The time‐to‐next therapy (TTNT) favored R‐Benda [median, not‐reached, 4.4 (DRC) and 2.6 years (BDR), p < 0.001). These endpoints were comparable between the DRC and BDR cohorts. Overall survival (OS) was similar across the three cohorts, p = 0.77. In a subset analysis of 142 patients genotyped for MYD88 L265P mutation, the ORR, PFS and TTNT were unaffected by the patients' MYD88 signature within each cohort. In conclusion, ORR, PFS and TTNT with R‐Benda are superior compared to DRC or BDR in treatment‐naïve patients with active WM. The patient outcomes with any one of these three regimens are unaffected by the MYD88 L265P mutation status.

SummaryIbrutinib is associated with durable responses in patients with Waldenström macroglobulinaemia (WM). We hypothesized that response depth is predictive of progression‐free survival (PFS) in WM patients treated with ibrutinib. Using landmark analyses, we evaluated response depth in two cohorts of WM patients treated with ibrutinib monotherapy. The learning cohort was composed of 93 participants from two clinical trials, and the validation cohort of 190 consecutive patients treated off clinical trial. Rates of partial response (PR) or better at six months in learning and validation cohorts were 64% and 71% respectively (P = 0·29). In the learning cohort, three‐year PFS rates for patients who attained PR or better at six monthsversusnot were 81% and 57% respectively (P = 0·009). In the validation cohort, three‐year PFS rates for patients who attained PR or better at six monthsversusnot were 83% and 54% respectively (P = 0·008). In multivariate analyses, attaining PR or better at six months was associated with superior PFS in the learning [hazard ratio (HR) 0·38;P = 0·01] and validation cohorts (HR 0·18;P = 0·004). Attaining PR at six months on ibrutinib emerges as an intermediate outcome of interest and should be validated as surrogate for PFS in clinical trials evaluating Bruton tyrosine kinase inhibitors in WM.

Introduction Due to the higher metabolic demand, malignant cells have an increased dependency on the nucleocytoplasmic trafficking of proteins, as compared to normal cells. Chromosome region maintenance protein 1 (CRM1), encoded by the XPO1 gene, is the main protein receptor which facilitates export of molecules, including tumor suppressor proteins, from the nucleus to the cytoplasm thereby making them inactive. Expression of CRM1 in tumor tissue has been shown to be an independent prognostic marker in several solid tumors and in acute myeloid leukemia; high CRM1 expression by immunohistochemistry (IHC) was associated with more aggressive disease and shorter survival. Importantly, selinexor, a first in class small molecule inhibitor of CRM1, was recently approved for the treatment of relapsed diffuse large B-cell lymphoma (DLBCL). The expression of CRM1 on tumor cells and the assessment of its prognostic impact have not been studied in patients (pts) with DLBCL or primary mediastinal B-cell lymphomas (PMBCL). Methods Paraffin embedded tumor tissue from pts with DLBCL or PMBCL treated with immunochemotherapy was assessed for CRM1 expression through IHC on tissue microarray (TMA). CRM1 anti-rabbit monoclonal antibody (Cell Signaling, catalog-no: 46249) was used at 1:100 dilution. Tumor cell grading was based on CRM1 staining in tumor cells compared to background non-malignant lymphocytes and non-malignant lymphocytes in spleen and tonsillar tissue controls. Renal cell carcinoma (RCC) was used as a positive control [known high levels of CRM1 staining (Inoue et al, J Urol, 2012)]. Two expert hematopathologists (RLK & AJW) independently scored CRM1 nuclear staining and assigned a grade of 0-3; 0 (no definitive nuclear staining, equal to background lymphocytes), 1 (dim nuclear staining), 2 (consistent nuclear staining, nuclear detail still visible behind the stain) and 3 (strong nuclear staining obscuring most nuclear detail, staining equivalent to RCC control). The average CRM1 score per case across all available cores on the TMA was calculated. Low CRM1 expression for a case was arbitrarily defined as a score of 0-2.0; high CRM1 expression was score 2.1-3.0. Scoring reliability between reviewers and between cores was assessed using intra-class correlation coefficient; score 0.75-0.90 was considered as a good scoring reliability. Event-free survival (EFS) was defined as time from diagnosis to progression, relapse, retreatment, or death. The association of CRM1 expression and risk of failing to achieve EFS at 24 months after diagnosis (EFS24) was estimated using odds ratios (OR) and 95% confidence intervals (CI) from logistic regression models, while the association of CRM1 expression with continuous EFS and overall survival (OS) was estimated using Kaplan-Meier curves and hazard ratios (HR) and 95% CI from Cox regression models. Results Tumor tissue from 282 pts was studied for CRM1 staining, including 275 pts with DLBCL and 7 pts with PMBCL. Median age of the study population was 61 years (range: 18-93) and 59% were male. The median follow-up for the entire cohort was 88.6 months. The first-line treatment regimens and baseline patient characteristics at diagnosis are outlined in Figure 1A. Of the 282 pts, 200 (71%) had high level of CRM1 expression and 82 (29%) had low CRM1 expression [only 4 (1.4%) had no or 0 staining]. Intra-class correlation coefficient to measure scoring reliability was 0.8. There was no difference in International Prognostic Index (IPI), ECOG performance score, lactate dehydrogenase or age at diagnosis among the groups with high CRM1 expression compared to low CRM1 expression (Figure 1A). The EFS24 failure was 29% for pts with low CRM1 expression while 26% in pts who had high CRM1 expression, OR=1.16, 95% CI 0.63-2.07; p=0.63. Null associations were also observed for EFS (HR=1.21, 95% CI 0.80-1.83; p=0.38) and OS (HR=1.02, 95% CI 0.61-1.69; p=0.95), (Figure 1B, C). Results were similar when adjusted for gender and IPI. Conclusion CRM1 expression by IHC on paraffin embedded tumor tissue is feasible in DLBCL and PMBCL. These data demonstrate that the CRM1 protein, the target for selinexor, is indeed expressed in the vast majority of these tumors; only 1.4% had no staining. However, CRM1 expression by IHC is not a prognostic marker for EFS24, EFS or OS. Whether CRM1 staining predicts selinexor response has not been studied but should be included in any new studies using CRM1 inhibitors. Disclosures Maurer: Nanostring: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Celgene / BMS: Research Funding. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding. Witzig:Acerta: Research Funding; Immune Design: Research Funding; Incyte: Consultancy; MorphSys: Consultancy; Celgene: Consultancy, Research Funding; Spectrum: Consultancy; Karyopharm Therapeutics: Research Funding; AbbVie: Consultancy.

Background: Patients with Waldenström Macroglobulinemia (WM) tend to present at an older age. Frailty, resulting from comorbidities and reduced organ function, poses unique challenges to the management of WM in the elderly. Age above 65 years, is an established unfavorable prognostic factor in WM. However, data specifically pertaining to the very elderly patient population are scant. The impact of advanced age (≥75 years at diagnosis) on the clinical features and outcomes of patients with symptomatic/active WM were studied. Methods: Patients with active WM, evaluated at Mayo Clinic, Rochester between January 1996 and December 2018 were included in the study. The characteristics and laboratory parameters at presentation of the cohort of patients with the age ≥75 years were compared to those of the younger (age &lt;75 years) cohort. The median follow-up and overall survival (OS) were assessed from active disease to last follow-up or death using the Kaplan Meier method. Because older age is a confounding factor for deaths from unrelated causes, the cause-specific survival (CSS) was calculated. Deaths were deemed WM-related if patients died from progressive disease, transformation with antecedent WM, concomitant light chain (AL) amyloidosis, infection associated with WM or anti-WM therapy related toxicity, while patients who died from other causes were considered to have a WM-unrelated death. The patients who died from causes unrelated to WM were censored at death for CSS analysis. The OS of the cohort of the very elderly patients was compared to that of a cohort of the general US population, matched for age, sex as well as follow-up from the calendar-year of diagnosis, to assess the degree to which WM impacts survival. Results: Among 949 consecutive patients, with a median follow-up of 8.4 years [95% Confidence Interval (CI): 7.7-9.3 years] from active disease, the median age at diagnosis was 65 years (range: 31-93 years). Of 177 patients (19%) who were ≥75 years of age at the onset of active WM, 173 (98%) received anti-WM therapy. The baseline characteristics of the 2 cohorts (patients ≥75 years of age versus &lt;75 years) are outlined in Table 1. The patients in the age ≥75 years cohort were noted to have lower IgM levels and serum albumin, and higher serum LDH and serum β-2 microglobulin compared to the age &lt;75 years cohort. A higher proportion of patients in the age &lt;75 years cohort had coexisting AL amyloidosis at diagnosis. The frequency of MYD88L265P mutation was similar between the 2 cohorts (p=0.2). During the 23-year period, there was an increase in the proportion of patients ≥75 years who were diagnosed with active WM (12% during the 1996-2003 period, 18% during 2004-2010, 25% during 2011-2018; P&lt;0.0001). In the elderly WM cohort, the most frequently used frontline treatment was rituximab monotherapy (36%), followed by rituximab-alkylating agent-based regimen (31%). Of 177 patients with age ≥75 years, 89 (50%) patients were deceased at the time of last follow-up and 58% (52/89) of all deaths in age ≥75 years were attributable to WM. By contrast, 303 (39%) out of the 772 patients in the age &lt;75 years cohort were deceased at last follow-up, with 73% (224/303) deaths attributable to WM. The CSS for patients with age ≥75 years was 10.9 years (95% CI: 7.3-11.7 years) versus 14.7 years (95% CI: 13.2-15.7 years) for age &lt;75 years [Risk ratio 2.1(95% CI: 1.5-2.8); p&lt;0.0001]. At the 1 and 2 year follow-up, WM-related mortality was 6.8% and 11.9%, respectively, for patients with age ≥75 years versus 2.6% and 4.9%, respectively, for the younger cohort. The median OS of patients with age ≥75 years from the diagnosis of active WM was 5.9 years (95% CI: 4.2-7.3 years) compared to the OS of 8.3 years for an age, sex and calendar-year-matched cohort, derived from the general US population (p&lt;0.001), Figure 1. Conclusion: Patients who are ≥75 years of age at the time of diagnosis of active WM present with certain poor prognostic features, including higher serum LDH and β-2 microglobulin and lower serum albumin compared to their younger counterparts. The impact of advanced age is underscored by a poorer WM-specific survival for the subset of patients with the age ≥75 years compared to the younger cohort. Furthermore, although active/symptomatic WM is typically an indolent malignancy, it adversely affects OS of the very elderly patients as suggested by the comparison with an age, sex and calendar-year matched cohort of the general US population. Disclosures Ansell: Bristol Myers Squibb: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; ADC Therapeutics: Research Funding; Seattle Genetics: Research Funding; AI Therapeutics: Research Funding; Takeda: Research Funding. Gertz:Ionis/Akcea: Other: personal fee; Alnylam: Other: personal fee; Prothena: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Annexon: Other: personal fee; Appellis: Other: personal fee; Amgen: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Physicians Education Resource: Other: personal fee; Abbvie: Other; Celgene: Other; Research to Practice: Other; Sanofi: Other; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Proclara: Other; Springer Publishing: Patents & Royalties; Aurora Bio: Other; Janssen: Other: personal fee. Nowakowski:NanoString: Research Funding; Seattle Genetics: Consultancy; Curis: Consultancy; Kymera: Consultancy; Kite: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees; MorphoSys: Consultancy, Research Funding; Celgene/BMS: Consultancy, Research Funding. Witzig:Spectrum: Consultancy; Immune Design: Research Funding; Karyopharm Therapeutics: Research Funding; Acerta: Research Funding; Incyte: Consultancy; MorphSys: Consultancy; AbbVie: Consultancy; Celgene: Consultancy, Research Funding. Dispenzieri:Pfizer: Research Funding; Janssen: Research Funding; Intellia: Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Dingli:Sanofi-Genzyme: Consultancy; Janssen: Consultancy; Bristol Myers Squibb: Research Funding; Rigel: Consultancy; Apellis: Consultancy; Karyopharm Therapeutics: Research Funding; Alexion: Consultancy; Millenium: Consultancy. Kumar:Sanofi: Research Funding; Kite Pharma: Consultancy, Research Funding; Cellectar: Other; Genecentrix: Consultancy; Novartis: Research Funding; Karyopharm: Consultancy; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Merck: Consultancy, Research Funding; MedImmune: Research Funding; Adaptive Biotechnologies: Consultancy; Tenebio: Other, Research Funding; Dr. Reddy's Laboratories: Honoraria; BMS: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments. Kapoor:Cellectar: Consultancy; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria.