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Background: Central nervous system (CNS) involvement by peripheral T cell lymphoma (PTCL) is a rare condition. Among primary CNS lymphomas, only 2% are secondary to PTCL, while the risk of CNS relapse in all cases of PTCL is estimated at 2% to 6%. Little is known about the presentation and outcomes of PTCL patients with CNS involvement given the rarity of this entity. In this study, we describe patient characteristics, histology, and clinical course of patients with CNS involvement by PTCL. Methods: The Mayo Clinic Lymphoma Database was used to identify PTCL patients with primary or secondary CNS involvement seen at our institution between 2000 and 2018. A total of 12 patients were identified and their medical records were reviewed for patient and disease characteristics, CNS-directed treatment modality, and outcomes. The Kaplan-Meier method was used for time-to-event analysis. Results: The median age at CNS diagnosis was 63 years (range 41 to 76) and 11 (93%) patients were male. The histological diagnoses were PTCL, NOS in 9 (75%) patients, enteropathy-associated T-cell lymphoma in 2 (17%) patients, and angioimmunoblastic T-cell lymphoma in 1 (8%) patient. Five patients presented with primary T-cell CNS lymphoma (all with a PTCL, NOS histology), while the remaining 7 (58%) patients also had systemic involvement. All patients presented with neurologic symptoms at the time of CNS involvement diagnosis including: focal motor deficits in 6 patients (unilateral upper extremity weakness, gait impairments, and hemiparesis), cognitive decline in 5 patients (memory impairments, reduced attention, and confusion), headache in 4 patients, and seizure in 3 patients. The CNS disease location included the brain parenchyma in 9 (75%) patients, leptomeninges in 1 (8%) patient, and lumbar plexus in 1 (8%) patient. One patient (8%) had positive CSF finding only without radiologic evidence of involvement. CSF analysis was performed in 11 patients. Elevated protein levels were noted in 3 (27%) patients, malignant cells in 2 (18%), and no clear abnormalities in the remaining 6 (55%) patients. Concomitant bone marrow involvement was seen in only 1 patient. Elevated LDH was seen in 2 patients. The a median LDH was 195 U/L (range 139 to 4,360) The most common CNS-directed therapies were: high-dose methotrexate (MTX)-based regimens in 8 (67%) patients, including high-dose MTX in combination with temozolomide (n=2), or cytarabine and thiotepa (n=2). Intrathecal MTX, temozolomide and dexamethasone, lenalidomide, high-dose steroids, and surgical resection were the treatment modality used for one patient each. At a median follow up of 18 months, eight (75%) out of 12 patients were not alive at the time of last follow up. The median overall survival (OS) from diagnosis was 16 months (95% CI: 2.8-173). The median progression free survival (PFS) from initiation of CNS-directed therapy was 9 months (95% CI: 1.6-33) (figure). Four patients had a PFS longer than 12 months. These 4 patients were treated with: temozolomide/dexamethasone, high-dose MTX, lenalidomide, and high-dose MTX followed by cytarabine/thiothepa. Conclusion: CNS involvement by T-cell lymphoma is a rare complication that carries a poor prognosis. Early onset of neurologic symptoms should trigger prompt investigation of CNS involvement. Despite the short OS and PFS, some patients may achieve a relatively longer disease free interval. Disclosures Bennani: Adicet Bio: Other: Advisory board; Seattle Genetics: Other: Advisory board; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Adicet Bio: Other: Advisory board; Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Kite Pharma: Other: Advisory board. Cerhan:Celgene: Research Funding; NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees. Nowakowski:Celgene: Consultancy, Research Funding; Bayer: Consultancy, Research Funding; Curis: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding; NanoString: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees. Ansell:Mayo Clinic Rochester: Employment; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding. Paludo:Celgene: Research Funding; Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding; Celgene: Research Funding.

Introduction Neutropenic fever following high-dose chemotherapy and autologous stem cell transplantation (ASCT) is a common (incidence 63-100%) and potentially life-threatening complication. Recommended time to antibiotic (TTA) administration is within 1 hr of fever onset with delays associated with significant morbidity, prolonged hospitalization, and mortality. Standard of care guidelines emphasize patient self-monitoring for fever, with instructions to seek immediate medical attention if body temperature (temp) reaches 100.4°F or higher. In this study, we evaluated if a novel wearable, continuous temp monitor, tPatch, could reliably estimate core body temp and detect fever in an outpatient setting following ASCT. Additionally, we gathered preliminary data to explore early detection and prediction of clinically relevant temp rise in this clinical setting. Methods Patients (N = 86) with hematologic malignancies (62% multiple myeloma) who underwent high-dose chemotherapy followed by ASCT at Mayo Clinic, MN were prospectively enrolled between June 2018 and March 2019. Patients (82% male) wore an axilla-placed tPatch continuously for 7 days in an outpatient setting during the post ASCT period and were asked to record self-measured oral temp in 3-4 hr intervals daily using a standardized thermometer after appropriate training . Patients followed standard of care procedures with daily clinic assessment of temp, blood counts, and vital signs. An optional patient questionnaire was given at end-of-study. A model was trained using both patient- and clinic-assessed oral temp measures to estimate core temp from 2 sensors on the tPatch device. Core temp estimates and trends were then compared to patient- and clinic-assessed measurements. Fever was defined as a temperature ≥100.4°F for at least 1 hr. Results When compared to all oral temp reads, the tPatch estimated core temp within 0.03 ± 0.7℉. Among the 86 patients, clinic-assessed fever incidence was 29.4% while tPatch-assessed incidence was 58.8%. Using all clinic-recorded temp readings as "ground truth," the sensitivity and specificity of the tPatch algorithm in detecting fevers were 88% and 86%, respectively, while patient self fever detection sensitivity was 62% and specificity 93%. With "fever episode" defined as a temp ≥100.4°F for at least 1 hr, tPatch detected 9.6 times the number of fever episodes vs. clinic reads. The average lead time of tPatch detection of clinic-recorded fevers was 3.7 hours. In 25% of all intervals between clinic temp readings, either tPatch or patients detected at least 1 fever episode. The tPatch was well-tolerated, the only adverse events reported were grade 1 skin irritation and discomfort in 4 (5%) patients. Of 65 patients who completed the survey, 95% reported the tPatch as "quite" or "somewhat" comfortable and 94% stated no difficulty in using the tPatch. Exploration of tPatch temp trends over various time intervals for use in fever prediction is ongoing. Conclusions Patient self-monitoring of temp has low sensitivity and is not feasible for long intervals of time (e.g., overnight). Continuous temperature monitoring by a wearable device overcomes these challenges and has the potential to improve early detection and consequently shorten time to antibiotic initiation. A follow-up randomized study is planned to assess the clinical benefits of continuous temp monitoring through patient and clinician alerts triggering early clinical intervention for febrile neutropenia. Figure Disclosures Vera-Aguilera: Verily Life Sciences: Research Funding. Haji-Abolhassani:Verily Life Sciences: Employment. Kulig:Verily Life Sciences: Employment. Heitz:Verily Life Sciences: Employment. Paludo:Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding; Celgene: Research Funding; Celgene: Research Funding. Ghoreyshi:Verily Life Sciences: Employment. Scheevel:Verily Life Sciences: Research Funding. Schimke:Verily Life Sciences: Research Funding. Markovic:Verily Life Sciences: Research Funding.

Introduction Waldenstrom macroglobulinemia (WM) is a rare, incurable, indolent non-Hodgkin lymphoma that is preceded by an IgM monoclonal gammopathy of undetermined significance (IgM MGUS). In recent years, better understanding of the pathobiology of WM and IgM MGUS has strengthened the hypothesis that they may represent different stages of the same disease. Studying the relationship between these two conditions is the essential first step to understanding the mechanisms driving the malignant transformation from IgM MGUS to WM. Recently long non-coding RNAs (lncRNAs) have garnered significant recognition for their roles in the regulation of gene expression and cellular function. lncRNA can regulate gene expression of neighboring protein-coding genes through multiple mechanisms such as by recruiting chromatin modifiers and increasing accessibility of genes to transcription proteins, or by directly binding to enhancers or promoters. Here we present the first analysis of the lncRNA expression profile in patients with WM compared to IgM MGUS. Methods Twenty-one patients with untreated WM (n=14) and IgM MGUS (n=7) seen at Mayo Clinic were included in this analysis. Malignant cells were isolated from bone marrow samples using CD19 and CD38 positive selection. Total RNA was extracted and sequencing was performed using the Illumina HiSeq4000 NGS platform. Differentially expressed lncRNAs in WM compared to IgM MGUS were defined as log2 fold change (FC) > 1.0 (upregulated) or < -1.0 (downregulated) and a false discovery rate (FDR) < 0.05. The nearest gene to each lncRNA was also identified and their gene expression was detected. Using the Ingenuity Pathway Analysis software and taking into account the transcriptional expression and known function of these genes, a correlation between cell function and disease analysis was performed. Results A total of 119 lncRNAs were differently expressed between WM and IgM MGUS (17 transcripts were upregulated in WM, while 102 were downregulated in WM). Sixteen unique genes were identified as the nearest gene to 17 upregulated lncRNAs, while 18 genes were identified as the nearest genes to the top 18 downregulated lncRNAs in WM compared to IgM MGUS. Several of the upregulated lncRNA in WM were in proximity to known oncogenes. The well-known oncogenic lncRNA PVT1 was found to be upregulated in WM compared to IgM MGUS (log2 FC 1.35, FRD 0.04). PVT1 is overexpressed in several malignancies and associated with inhibition of apoptosis and increased cell proliferation. PVT1 is in close proximity to MYC and co-expression of PVT1-MYC has been described in multiple cancers. PVT1 also potentiate MYC amplification by increasing MYC protein stability, therefore promoting malignant cell growth. The lncRNA TCB1D27, also upregulated in WM compared to IgM MGUS, is located in close proximity to the oncogene TNFRSF13B (TACI), which was found to be overexpressed in WM patients (log2 FC 1.61, FDR <0.001). TACI is a receptor for BLyS/BAFF, which modulates the development of normal B-cells and plays a role in various B-cell malignancies. In fact, BLyS/BAFF level is known to be increased in WM and to promote survival and proliferation of WM B cells. The upregulated lncRNA RP11-25K21.1 in WM is located in close proximity to the oncogene FCGR2B (CD32B), which was also upregulated in WM compared to IgM MGUS (log2 FC 1.59, FDR 0.001). Overexpression of CD32B was previously shown to be associated with inferior outcomes in DLBCL and FL patients, presumably secondary to an increased internalization and clearance of rituximab due to increased CD32B expression on malignant cells. Several other upregulated lncRNAs in WM compared to IgM MGUS are also in proximity of other oncogenes such as PCED1B, POLD3, CLLU1, and SMAD7. Finally, we considered the expression of the nearest genes and their reported cell function and association with diseases. Several genes that are known to have a role in the cell proliferation and/or neoplasm development were noted to be upregulated in WM (figure 1). Conclusion We present the first report of lncRNAs expression in WM and IgM MGUS in addition to a concurrent analysis of the gene expression of the nearest protein-coding genes. Several known oncogenes are in proximity of overexpressed lncRNAs in WM compared to IgM MGUS that could indicate potential implications in the pathobiology of these diseases and the mechanism driving the malignant transformation to WM. Disclosures Paludo: Celgene: Research Funding; Celgene: Research Funding; Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding. Dasari:The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Kapoor:Celgene: Honoraria; Cellectar: Consultancy; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding. Ailawadhi:Amgen: Consultancy, Research Funding; Pharmacyclics: Research Funding; Takeda: Consultancy; Janssen: Consultancy, Research Funding; Cellectar: Research Funding; Celgene: Consultancy. Gertz:Amyloidosis Foundation: Research Funding; i3Health: Other: Development of educational programs and materials; Medscape: Consultancy, Speakers Bureau; Ionis/Akcea: Consultancy; Celgene: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Teva: Speakers Bureau; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Research to Practice: Consultancy; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Springer Publishing: Patents & Royalties; International Waldenstrom Foundation: Research Funding. Novak:Celgene Coorperation: Research Funding. Ansell:Affimed: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding.

Background: Two-year follow-up from ZUMA-1 trial for axicabtagene ciloleucel (axi-cel) CD19 chimeric antigen receptor T-cell (CART) in aggressive non-Hodgkin lymphoma (NHL) demonstrated that patients (pts) achieving complete remission (CR) as their best response have the longest progression free survival (PFS), while PFS remained poor for others. Majority of the best response are achieved by month 3 post-infusion. Moreover, a subset of pts who do not achieve CR by month 1 may still achieve CR while others will progress within months. Having a clinically available test to predict for durable response can assist clinicians in selecting pts who can be observed for continued response vs. those who may need intervention earlier. Peak CAR-T expansion has been correlated with best clinical response to axi-cel. However there is no clinically available test to quantify CART cells post treatment. Given the prolonged lymphotoxic effect of the lymphodepletion (LD) chemotherapy administered before CART infusion, we hypothesize that the peak expansion of absolute lymphocyte count (ALC, ALCpeak) after infusion likely corresponds to CART expansion. We examined for correlation between ALCpeak and clinical response at month 3 post-infusion for pts who received axi-cel. Methods: Data was collected from pts who received axi-cel between June 2016 and March 2019 at Mayo Clinic Rochester (NCT02348216, NCT03153462, and standard of care). All infused pts were included in the intention to treat analysis for response and event-free survival (EFS). Lugano 2014 criteria were used for clinical response. EFS was defined as the date of infusion until progression or death due to any cause and evaluated using Kaplan Meier curves with log-rank test. Comparison between subgroups was investigated using Fisher's exact test and Wilcoxon test for categorical and continuous variables, respectively. Statistical analysis performed using JMP Pro 14.1. Results: Of the thirty-six NHL pts treated with axi-cel, the median age was 56 yrs (range 26-65); 78% (28) were male; 44% (16) had DLBCL; the median number of prior therapies was 3 (2-6), 47% (17) had stem cell transplant. Nineteen (53%) pts received bridging therapy after leukapheresis. All pts received fludarabine and cyclophosphamide for LD chemotherapy and achieved ALC nadir by the day of CART infusion (median 0.03 x 10^9/L, range 0.01-0.11). As CART expansion were found to peak within the first two weeks in ZUMA-1 trial, we examined ALC trend over 15 days post infusion and found that ALCpeak generally happened within the same timeframe (median ALCpeak day: 9, range 6-15). At 3 months post infusion, 33.3% (12/36) of pts achieved CR, 8.3% (3/36) pts were in partial remission (PR). No correlation was found between CR response and clinical characteristics: age >60 years, stage III/IV, B symptoms, elevated LDH, IPI score 3-4, number of previous treatments, use of bridging therapy, peak CRP and ferritin. However, the ALCpeak was significantly different between CR and non-CR pts (median, range: 1.09, 0.35-2.55; 0.67, 0.15-1.03; p=0.04). Using receiver operator curve (ROC)-derived area under the curve (AUC) estimates, ALCpeak 1.08 x 10^9/L was identified as the best threshold to discriminate patients at different likelihood to achieve CR at month 3. Pts achieving ALCpeak ≥ 1.08 showed a strong increased likelihood of achieving CR at month 3 (OR 2.8; 95% CI, 1.12-6.99; P=0.02). There was no statistical difference between the ALCpeak high and low groups in terms of use of bridging therapy, occurrence of any grade or higher grade cytokine release syndrome or neurotoxicity, or the use of tocilizumab or steroid. Interestingly, for pts who had changes in clinical response from month 1 to month 3, all 3 pts who converted to CR by month 3 had ALCpeak≥1.08, while the 13 of the 15 pts who had progressed by month 3 had ALCpeak<1.08. In addition, EFS was significantly different between pts who had ALCpeak above and below 1.08 (6 months EFS rate 75% vs. 25%, respectively, Figure 1). Conclusions: We found that the ALC expansion occurred in the first 15 days post axi-cel infusion, consistent with the known time frame for CART expansion. Higher ALCpeak level in this timeframe correlated with higher likelihood of achieving CR, and is associated with conversion to CR. This study is limited by the small sample size and limited follow-up, but the results are promising for further prospective investigation in a larger cohort of patients. Disclosures Paludo: Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding; Celgene: Research Funding; Celgene: Research Funding. Ansell:Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding. Bennani:Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Adicet Bio: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Kite Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Seattle Genetics: Other: Advisory board; Adicet Bio: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Other: Advisory board; Purdue Pharma: Other: Advisory board. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Karyopharm: Research Funding; Rigel: Consultancy. Kapoor:Celgene: Honoraria; Janssen: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding. Kenderian:Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding. Kumar:Takeda: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.

Abstract Introduction Waldenstrom macroglobulinemia (WM) is a rare disease accounting for only 1-2% of all hematologic malignancies and with an overall annual, age-adjusted incidence of approximately 3.5 to 5.5 cases per million-person years. With approximately 13,000 active hematologist/oncologists in the US, most of who are in the community oncology setting, it's estimated that a hematologist/oncologist will only diagnose a WM case approximately every 8 years. Therefore, the clinical experience of a general hematologist/oncologist in the management of WM is likely very limited compared to more prevalent malignances. Previous studies in the setting of rare cancers suggest a correlation between higher volume of care and improved outcomes. Therefore, we explored the volume-outcome relationship in WM using the National Cancer Data Base (NCDB). Methods Patient-level data from the NCDB, a nationwide, facility-based, database covering approximately 70% of all newly diagnosed cancer cases in the US, was queried for all new WM cases diagnosed between 2004 and 2014. Only patients requiring treatment were included. Treatment facilities were divided into quartiles based on the average annual volume of newly diagnosed cases of WM seen. Cox regression was used to analyze the association between facility WM volume and survival, adjusted by demographics (sex, age, race), socioeconomic status (income, education, insurance type), geography (area of residence, treatment facility type, travel distance), comorbidity factors (Charlson-Deyo score), and year of diagnosis. Time-to-event analysis was calculated from frontline therapy initiation date using the Kaplan-Meier method and the log-rank test. Results A total of 3,732 patients with WM treated in 831 facilities were included. The median age at diagnosis was 70 years and 75% of the patients were treated within 20 miles from their residency zip code. Patient characteristics per treatment facility volume quartile are shown in table 1. The median annual facility volume was 1 new WM patient/year (range 0.1 to 21). The median follow-up from frontline treatment was 5 years. The unadjusted median OS by facility volume was: Q1: 6.5 years (95% CI: 5.7-7.4), Q2: 7 years (95% CI: 6.3-8.2), Q3: 8.2 years (95% CI: 7.1-8.9), and Q4: NR (95% CI: 8.5-NR), p<0.0001 (figure 1). The estimated 5-year OS by facility volume was: Q1: 56%, Q2: 61%, Q3: 64%, Q4: 71%, p<0.0001. Multivariate analysis including all variables showed in Table 1 demonstrated that facility volume was independently associated with all-cause mortality. Compared to patients treated at Q4 facilities, patients treated at lower-quartiles facilities had a higher incremental risk of death (Q3 hazard ratio [HR], 1.07 [95% CI: 0.88 to 1.29] p=0.46; Q2 HR, 1.34 [95% CI: 1.11 to 1.63] p=0.002; Q1 HR, 1.52 [95% CI: 1.23 to 1.88] p=<0.0001). Conclusion Our results suggest that a volume-outcome relationship exits in WM as patients treated initially at higher-volume facilities had a lower risk of mortality. Although differences in the underlying disease biology, referral patterns after initial therapy, or cumulative treating-physician experience could not be assessed, these potential biases would only underestimate the magnitude of the volume-outcome relationship reported. Disclosures Ansell: Celldex: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Pfizer: Research Funding; Affimed: Research Funding; Merck & Co: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding. Gertz:Medscape: Consultancy; janssen: Consultancy; Alnylam: Honoraria; Ionis: Honoraria; Physicians Education Resource: Consultancy; Prothena: Honoraria; Teva: Consultancy; Research to Practice: Consultancy; spectrum: Consultancy, Honoraria; celgene: Consultancy; Amgen: Consultancy; Abbvie: Consultancy; annexon: Consultancy; Apellis: Consultancy. Kapoor:Takeda: Research Funding; Celgene: Research Funding. Ailawadhi:Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Research Funding; Celgene: Consultancy; Takeda: Consultancy. Reeder:Affimed: Research Funding. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Lacy:Celgene: Research Funding. Kumar:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Background Limited data exist with respect to outcome and optimal therapeutic strategies in patients with central nervous system (CNS) involvement in multiple myeloma (MM). We present a single center experience of patients with myelomatous CNS involvement in newly diagnosed and relapsed / refractory MM. Methods Of 4060 patients with MM seen at Mayo Clinic, Rochester, MN between January, 1st 1998 and December, 31st 2012, 26 patients had identifiable CNS involvement confirmed by biopsy / presence of plasma cells in the cerebrospinal fluid (CSF) and/or identification of intraparenchymal or meningeal involvement by imaging (MRI/CT). Patients were risk stratified by mSMART (Mayo Stratification for Myeloma And Risk-adapted Therapy) criteria. Overall survival (OS) from diagnosis and the time of CNS involvement was calculated using the Kaplan-Meier method. Results Myelomatous CNS involvement occurred in 26 (0.6%) patients with MM of whom 3 were newly diagnosed. The median time to detection of CNS involvement was 24 months (range: 0-125) from diagnosis of MM. Median age at CNS myeloma diagnosis was 58 years (range 37-80) and 73% were male. Abnormally high LDH was observed in 11 out of 22 patients at the time of CNS involvement. Lumbar puncture was performed on 16 patients, 13 (81%) of whom had plasma cells in the CSF detected by cytology/flow-cytometry. Two patients, without evidence of plasma cells, had abnormally high CSF protein and 1 had normal CSF analysis. Of the 25 patients who underwent MRI, 16 (64%) had at least one of the following significant abnormalities; intraparenchymal disease (37%), leptomeningeal enhancement (68%) or direct extension of MM (31%). The neurological symptoms at or after diagnosis of CNS myeloma included headache (38%), cranial nerve palsy (38%), visual disturbance (38%), gait disturbance (35%), paresthesias (35%), limb weakness (31%), confusion (30%), nausea/vomiting (15%), dysarthria (12%), seizures (8%) and urinary incontinence (4%). Fluorescent in-situ hybridization (FISH n=7), cytogenetics (n=8) and/or plasma cell labeling index (PCLI n=12) were available in 18 patients prior to the diagnosis of CNS disease. Ten (56%) out of those 18 patients had high-risk features at least by one criterion. At the time of CNS involvement, six additional patients demonstrated high risk features [5 by PCLI (≥ 3%) and 1 by FISH]. Overall, 16 out of 26 (62%) patients were classified as high risk by mSMART criteria prior to or at the time of CNS involvement. Four (27%) out of 15 had a deletion p53 or monosomy 17 chromosomal abnormality. Median OS was 42 (95% CI, 19-55) months from the diagnosis of MM and 3 months (95% CI: 1-7.9) from the time of CNS involvement (Figure). OS of patients with high risk features was significantly worse (27 months) compared to standard risk disease (67 months, p=0.02) from diagnosis of MM. Eighteen patients received radiation therapy for CNS myeloma. Five of those patients also received intrathecal (MTX and ARA-C) therapy. One patient received intrathecal and systemic chemotherapy. Four patients did not receive any treatment. Novel agents, including bortezomib (23%), thalidomide (15%), and pomalidomide (4%) were administered to the patients post diagnosis of CNS disease. Six (23%) patients underwent autologous stem cell transplant post diagnosis of CNS disease with a median OS of 19 months (95% CI: 10-122 months) from the time of CNS involvement. Conclusion CNS involvement is a rare complication of MM that portends a poor survival outcome. It is likely that the rates in this study are an underestimate of the true incidence due the perceived futility of CNS directed therapy in this disease. Among those recognized, high-risk genetic and markers of increased proliferative activity, including deletion p53 / monosomy 17 and elevated PCLI (≥ 3%) appear to cluster in this cohort. Current therapeutic approaches are largely ineffective in managing this aggressive subset of myeloma patients. Disclosures: No relevant conflicts of interest to declare.

Abstract Introduction Recent advances in the understanding of the WM pathobiology led to the expansion of our therapeutic options in this disease. A number of targeted drugs are either available or under investigation and are poised to change the chemo-immunotherapy paradigm in the treatment of WM. Now more than ever, an individualized treatment approach for patients with WM is possible, where patient characteristics and preferences can be matched by different treatment goals and side effect profiles. While deep responses have been associated with longer disease-free survival in other hematologic malignancies, data on patients with WM are sparse. We report the impact of depth of response in disease-free and overall survival (OS) in WM. Methods WM patients consecutively seen at Mayo Clinic between 01/1998 and 12/2016 were reviewed for response to therapy and disease burden. The best response achieved after the treatment of interest (TOI) was classified using the IWWM-7 Response Criteria. The included TOI were: BR, DRC, BDR and high-dose chemotherapy followed by ASCT. All time-to-event analyses were performed from the TOI initiation date using the Kaplan-Meier method and the log-rank test. A landmark analysis from the date-of-best response was also performed for OS to prevent immortal-time bias. Univariate and multivariate analyses of progression-free survival (PFS) and time-to-next therapy (TTNT) were performed using the Cox regression method. Results A total of 181 patients had disease response assessed after the TOI. Baseline characteristics at time of diagnosis are summarized in table 1. The median follow up from TOI was 3.8 years (95% CI: 3-4), the majority of patients received TOI as salvage therapy [n=112 (63%); median 2nd line (rage 1-11)]. Best response rates with the corresponding 5-year PFS and TTNT are summarized in table 2. The median OS from TOI was longer in patients who achieved at least a PR [median 7.2 years (95% CI: 5-NR) vs 3.7 years (95% CI: 1.6-NR), p=0.01]. A trend towards a longer OS was also seen with deeper responses (PR or better) achieved with frontline therapy [median 5.8 years (95% CI: 5.8-NR) vs 3.4 years (95% CI: 1.6-NR), p=0.24]. Figure 1 shows the correlation between deeper responses with PFS and TTNT. Among patients achieving a PR or VGPR, those with a normal FLC ratio post TOI demonstrated a longer PFS and TTNT [PFS: median NR (95% CI: 3.4-NR) vs 4.9 years (95% CI: 2.8-8.7), p=0.01; TTNT: median NR (95% CI: 3.5-NR) vs 5.2 years (95% CI: 4.2-9.4), p=0.04], figure 2. In a multivariate analysis including normal FLC ratio, normal IgM level and minimal BM involvement (<5%) post TOI, normal FLC ratio remained an independent prognostic factor for longer PFS and TTNT. Similar trends were seen when considering treatment naïve and relapsed/refractory patients independently (data not shown). Discussion Our results not only suggest an association between depth of response with PFS and TTNT, but also with OS in patients with WM. A normal FLC ratio (not part of the IWWM-7 response criteria) seems to predict a longer disease-free interval in patients achieving a PR or VGPR. Disclosures Gertz: Ionis: Honoraria; Apellis: Consultancy; annexon: Consultancy; Prothena: Honoraria; janssen: Consultancy; Physicians Education Resource: Consultancy; Alnylam: Honoraria; Teva: Consultancy; spectrum: Consultancy, Honoraria; Medscape: Consultancy; celgene: Consultancy; Research to Practice: Consultancy; Amgen: Consultancy; Abbvie: Consultancy. Kapoor:Takeda: Research Funding; Celgene: Research Funding. Ailawadhi:Amgen: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Pharmacyclics: Research Funding; Celgene: Consultancy. Reeder:Affimed: Research Funding. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Lacy:Celgene: Research Funding. Kumar:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Ansell:Seattle Genetics: Research Funding; Celldex: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Merck & Co: Research Funding; Affimed: Research Funding; Regeneron: Research Funding.

Abstract Introduction Immunoglobulin M monoclonal gammopathy of undetermined significance (IgM MGUS) is a relatively common pre-malignant condition that may progress to Waldenstrom macroglobulinemia (WM), an incurable low-grade non-Hodgkin lymphoma. The acquisition of genomic alterations in a multistep process of progression is likely a central mechanism responsible for the progression of IgM MGUS to WM, leading to increased tumor burden and end-organ damage. The exact role of the immune system in this process is still poorly characterized. The modulation of the immune system by malignant cells leading to anti-lymphoma immunity or immune evasion is a well-stablished principle associated with lymphoma survival and progression, respectively. The understanding of the pathobiology of IgM MGUS and WM has grown significantly over the last few years; however, most of the past research has focused on genetics and flow cytometric analysis of malignant cells. The introduction of CyTOF, a novel platform coupling mass spectometry with single-cell flow cytometry using antibody-metal isotope pairs, has allowed a broader single-cell analysis and the study of functional profiles. We here report the use of CyTOF technology to comprehensively profile the immune system of patients with IgM MGUS and WM. Methods Viably-cryopreserved (DMSO 10%) single-cell suspensions containing peripheral blood mononuclear cells from 15 patients (WM n=9 and IgM MGUS n=6) were used in this study. Recovered cells (1-3 x 106 per sample) were stained with a 30-parameter surface protein CyTOF panel designed to characterize multiple cell types and profile the immune system. Nucleated cellular events were identified using a DNA intercalator conjugated to natural abundance iridium (191Ir and 193Ir). Cisplatin (195Pt) was used for dead-live cell discrimination and calibration beads containing natural abundance cerium (140/142Ce), europium (151/153Eu), holmium (165Ho), and lutetium (175/176Lu) were used for normalization of the instrument signal. CyTOF analysis of normalized files was carried out using the Astrolabe Diagnostics platform. Cell clusters were assigned using the FlowSOM package and differential abundance analysis was performed using the edgeR package. Analysis is adjusted for multiple comparisons. Results The median live single-cell count for the entire cohort was 573,300 (range 50,681 to 869,727), representing a median of 81% (range 39% to 87%) of the total event counts [median 820,800 (range 130,452 to 1,000,000]. The cell count and the proportion of event count was similar in patients with WM or IgM MGUS. T cells represented 45.8% of the total events; granulocytes represented 31.3%; NK cells represented 8.6%; monocytes represented 8.1%; B cells represented 2.4% of the total events for the entire cohort. Figure 1 shows a heat map of different immune cell sub-types proportion per patient sample. A difference was noted in the proportion of monocytes (CD14+, CD16+) and B-cells when comparing patients with IgM MGUS and WM (figure 2). Patients with WM had a higher proportion of monocytes compared to IgM MGUS patients (p=0.05). A higher proportion of B-cells was noted in patients with IgM MGUS when compared to WM (4.2% vs 0.6%, p=0.01). When B-cells were sub-classified as naïve, transitional, non-switched memory, switched memory, and plasmablasts, the proportion of non-switched memory B-cells was higher in IgM MGUS compared to WM (p=0.05). While the results of this pilot study suggest important differences between IgM MGUS and WM as regards the immune repertoire, confirmatory studies are in progress in a larger cohort of patients. Conclusion To our knowledge, this is the first study of mass cytometry in patients with WM and IgM MGUS patients. A higher proportion of monocytes and lower proportion of memory B-cells was noted in patients with WM compared to IgM MGUS. CyTOF study of the immune profile in these patients is feasible and can potentially uncover relationships between cell types not typically associated with the disease progression continuum (IgM MGUS to WM). While definitive conclusion cannot be made using this dataset due to the small sample size, CyTOF is a powerful tool in the study of the immune profile of WM patients. Disclosures Gertz: Amgen: Consultancy; Abbvie: Consultancy; Apellis: Consultancy; annexon: Consultancy; spectrum: Consultancy, Honoraria; Teva: Consultancy; Alnylam: Honoraria; Physicians Education Resource: Consultancy; Ionis: Honoraria; janssen: Consultancy; celgene: Consultancy; Prothena: Honoraria; Research to Practice: Consultancy; Medscape: Consultancy. Kapoor:Celgene: Research Funding; Takeda: Research Funding. Ailawadhi:Takeda: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Pharmacyclics: Research Funding. Reeder:Affimed: Research Funding. Ansell:Seattle Genetics: Research Funding; Regeneron: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Merck & Co: Research Funding; Trillium: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Celldex: Research Funding; Bristol-Myers Squibb: Research Funding.

Abstract Background: The oral BTK inhibitor ibrutinib is the only approved therapy for patients with symptomatic Waldenström macroglobulinemia (WM). Bing-Neel syndrome (BNS) is a rare complication of WM that results from infiltration of malignant lymphoplasmacytic cells into the central nervous system (CNS) causing neurological deficits. Treatment options in patients with BNS are limited to agents with CNS penetration. Ibrutinib can penetrate into the CNS, but data on its efficacy in BNS is lacking outside case reports. Methods: We performed a multicenter retrospective study evaluating the efficacy of ibrutinib in patients with BNS. The diagnosis of BNS was established in patients with a clinicopathological diagnosis of WM by radiological and/or cytological evidence of CNS involvement by WM, and response was assessed based on recently published criteria. Ibrutinib was given orally at doses of 420-560 mg PO once daily until disease progression or intolerable toxicity. Response was assessed using criteria from the 8th International Workshop for WM (Minnema et al. Haematologica 2017). Events were defined as death from any cause, progression of disease and stopping ibrutinib from any reason. Time to events was estimated using the Kaplan-Meier method. Results: We present data on 24 patients with BNS treated with ibrutinib. The median age at diagnosis of WM was 60 years (range 38-76 years) and 14 patients (58%) were men. The median lines of therapy for WM prior to BNS diagnosis was 1 (range 0-7 lines), and 9 patients (38%) were untreated for WM at the time of BNS diagnosis. Previous WM therapies included anti-CD20 antibodies (n=15), alkylators (n=13), nucleoside analogues (n=8), proteasome inhibitors (n=3), immunomodulators (n=2), and autologous transplant (n=1). The median age at BNS diagnosis was 65 years (range 38-80). The median time from WM to BNS diagnosis was 4 years (range 0-27 years). In 2 patients, the diagnosis of BNS was made concurrently with WM diagnosis. The median number of BNS lines prior to ibrutinib was 1 (range 0-5 lines). Previous BNS therapies included intrathecal chemotherapy (n=9), high-dose methotrexate (n=6), bendamustine (n=3) and radiation therapy (n=3). In 7 patients (29%), ibrutinib was the first line of treatment for BNS. The most common symptoms at BNS presentation were cognitive deficits (n=10), sensory deficits (n=8), ataxia/falls (n=8), motor deficits (n=6), headache (n=5) and seizures (n=5). MRI findings included leptomeningeal enhancement (n=16) and brain masses (n=5). Cerebrospinal fluid (CSF) flow cytometry confirmed the presence of clonal CD19+ in 19 patients (79%). Biopsies were performed in 5 patients (21%) and confirmed presence of WM cells. 4 patients had normal MRI but had abnormal CSF cytology and/or flow cytometry. Tissue was not obtained in 1 patient in whom MRI showed leptomeningeal enhancement. Interestingly, 2 patients were diagnosed with lymphoplasmacytic lymphoma secreting IgG paraprotein. The median serum IgM (n=20) prior to ibrutinib initiation was 1,294 mg/dl (range 125-5,938 mg/dl), and the median hemoglobin level was 11.9 g/dl (7.7-15.2 g/dl). Ten patients (42%) received ibrutinib 560 mg PO once daily, and 14 (58%) received ibrutinib 420 mg PO once daily. At best response, median serum IgM and hemoglobin levels were 340 mg/dl (82-3,330 mg/dl) and 14.6 g/dl (range 9.2-16.0 g/dl). Based on consensus BNS response criteria, complete response was attained in 2 patients (8%), partial response in 14 (58%) and clinical improvement in 3 patients (13%). With a median follow-up time of 13 months (95% CI 8-21 months), 5 patients have stopped ibrutinib, 3 due to BNS progression, 1 due to grade 3 muscle cramps and 1 due to arrhythmia, and 3 patients have died, 2 from infection and 1 from BNS progression. The median event-free survival (EFS) from ibrutinib initiation was not yet reached. The 1-year and 2-year EFS rates were 71% (95% CI 46-86%) and 52% (23-75%), respectively. Conclusion: Ibrutinib is a safe and effective treatment option for patients with BNS. Disclosures Palomba: Pharmacyclics: Consultancy; Celgene: Consultancy. Talaulikar:Amgen: Consultancy, Honoraria; Takeda: Research Funding; Janssen: Honoraria, Speakers Bureau; Roche: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau. Buske:Janssen: Honoraria, Research Funding; Bayer: Research Funding; Roche: Honoraria, Research Funding. Tedeschi:Gilead: Consultancy; AbbVie: Consultancy; Janssen: Consultancy, Speakers Bureau. Simpson:Pharmacyclics LLC, an AbbVie Company: Research Funding; Acerta: Research Funding; Merck: Honoraria, Research Funding; BeiGene: Research Funding; Sanofi: Research Funding; Bristol-Myers Squibb: Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Celgene: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Novartis: Other: TRAVEL, ACCOMMODATIONS, EXPENSES; MSD: Honoraria; Roche: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; Amgen: Research Funding, TRAVEL, ACCOMMODATIONS, EXPENSES; Janssen: Honoraria, Research Funding. Tam:Janssen: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BeiGene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Ansell:Affimed: Research Funding; Takeda: Research Funding; Merck & Co: Research Funding; Pfizer: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Celldex: Research Funding; LAM Therapeutics: Research Funding. Treon:Johnson & Johnson: Consultancy; BMS: Research Funding; Pharmacyclics: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding; Janssen: Consultancy, Other: Travel, Accommodations, Expenses. Castillo:Millennium: Research Funding; Genentech: Consultancy; Abbvie: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Beigene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Abstract Background Waldenström macroglobulinemia (WM) is a rare, indolent immunoglobulin M- associated lymphoplasmacytic lymphoma characterized by the alternation in the MYD88 locus in 90-95% of the cases. MYD88L265P is the most common alteration in WM patients and is considered a key molecular signature with a pathophysiological role in WM. Because of extremely low prevalence of WM with MYD88 wild type (WT) genotype there is a paucity of clinical and outcome data in this unique patient population. A recent study (Treon et al, Blood May, 2014), in an analysis based on the patients' MYD88 status, reported on the clinical features including older age at presentation and an unexpectedly higher mortality (38%) in the MYD88WTcohort compared to MYD88L265P patients (mortality 6%, P < .0001). However, the sample size of the MYD88WT WM cohort was small (n=15), with a few events during the short follow-up (median 4.84 years). Herein, we report on larger cohort of WM patients with this rare genotype. Methods This study included patients evaluated at Mayo Clinic, Rochester in whom the diagnosis of WM was established based on their clinicopathologic features and the MYD88 mutation status was determined through AS-PCR (assay sensitivity 1% mutant allele) performed on archived bone marrow samples obtained between 2007-2014. Patients with MYD88WT status were the focus of this study. Clinical data were collected from the patients' medical records. The Kaplan-Meir method was utilized for the survival analysis calculated from the time of diagnosis of WM. Outcomes of MYD88WT patients were compared with those harboring the MYD88L265Pmutation. Results Our cohort of 171 patients with an established diagnosis of WM and known MYD88 mutation status was found to be enriched for MYD88WT (n=40) patients. All patients required therapy. At diagnosis, the median age of the patients with MYD88 WT was 63 years (range 37.5-83.5 years; comparable to that of the MYD88L265P cohort, median 65 years, range: 32-92 years, p=0.16). Familial WM was identified in 10% of patients. Sixty four percent of patients presented with constitutional symptoms at diagnosis. These symptoms included fatigue (45%), weight loss (17%), night sweats (8%) dizziness (10%), dyspnea (23%), bleeding (10%), headache (10%) and hyper viscosity syndrome (5%). Splenomegaly and lymphadenopathy was observed in 20% and 27% of patients, respectively. Thirteen percent of patients had concomitant AL amyloidosis. Additional baseline characteristics are reported in Table 1. Transformation to a higher grade lymphoma was noted in 9 (23%) of patients, four of whom had received a purine analog and /or chlorambucil previously. The estimated median follow of MYD88WT patients was 8.1years (95% CI: 6.4-8.9) and their median overall survival (OS) was 8.5 years (95% CI: 6.4-29.4). No OS difference was evident between this cohort and the remainder of the patients with the MYD88L265Pmutation (n=131, median OS 11.7 years, 95% CI: 10-18, p=0.7; median follow-up 7.7 years 95% CI: 6.4-9.1, Figure 1). Conclusion In this relatively large cohort of WM MYD88WT patients with a prolonged follow-up, the MYD88mutation status was not found to be a determinant of patients' outcomes. Our findings contradict the results of a seminal previous study and require external validation, preferably through prospective studies. Disclosures Kapoor: Amgen: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Ansell:BMS, Seattle Genetics, Merck, Celldex and Affimed: Research Funding. Kumar:Sanofi: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Glycomimetics: Consultancy; Onyx: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy; Millennium: Consultancy, Research Funding; AbbVie: Research Funding; Kesios: Consultancy.