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Background and Aims Interleukin‐22 has beneficial effects on inflammation and impaired hepatic regeneration that characterize alcohol‐associated hepatitis (AH). F‐652 is a recombinant fusion protein of human interleukin‐22 and immunoglobulin G2 fragment crystallizable. This study aims to assess the safety and efficacy signals of F‐652 in patients with moderate and severe AH. Approach and Results A phase‐2 dose‐escalating study was carried out. F‐652 (10 μg/kg, 30 μg/kg, or 45 μg/kg) administered on days 1 and 7 was tested in 3 patients each with moderate (Model for End‐Stage Liver Disease [MELD] scores: 11‐20) and severe AH (MELD scores: 21‐28). Safety was defined by absence of serious adverse events and efficacy was assessed by Lille score, changes in MELD score, and serum bilirubin and aminotransferases at days 28 and 42. Three independent propensity‐matched comparator patient cohorts were used. Plasma extracellular vesicles and multiplex serum cytokines were measured to assess inflammation and hepatic regeneration. Eighteen patients (9 moderate and 9 severe AH) were enrolled, 66% were male, and the mean age was 48 years. The half‐life of F‐652 following the first dose was 61‐85 hours. There were no serious adverse events leading to discontinuation. The MELD score and serum aminotransferases decreased significantly at days 28 and 42 from baseline (P < 0.05). Day‐7 Lille score was 0.45 or less in 83% patients as compared with 6%, 12%, and 56% among the comparator cohorts. Extracellular vesicle counts decreased significantly at day 28 (P < 0.013). Cytokine inflammatory markers were down‐regulated, and regeneration markers were up‐regulated at days 28 and 42. Conclusions F‐652 is safe in doses up to 45 μg/kg and associated with a high rate of improvement as determined by Lille and MELD scores, reductions in markers of inflammation and increases in markers of hepatic regeneration. This study supports the need for randomized placebo‐controlled trials to test the efficacy of F‐652 in AH.

AbstractOne of the hallmarks of aging is the progressive accumulation of senescent cells in organisms, which has been proposed to be a contributing factor to age‐dependent organ dysfunction. We recently reported that Bruton's tyrosine kinase (BTK) is an upstream component of the p53 responses to DNA damage. BTK binds to and phosphorylates p53 and MDM2, which results in increased p53 activity. Consistent with this, blocking BTK impairs p53‐induced senescence. This suggests that sustained BTK inhibition could have an effect on organismal aging by reducing the presence of senescent cells in tissues. Here, we show that ibrutinib, a clinically approved covalent inhibitor of BTK, prolonged the maximum lifespan of a Zmpste24−/− progeroid mice, which also showed a reduction in general age‐related fitness loss. Importantly, we found that certain brain functions were preserved, as seen by reduced anxiety‐like behaviour and better long‐term spatial memory. This was concomitant to a decrease in the expression of specific markers of senescence in the brain, which confirms a lower accumulation of senescent cells after BTK inhibition. Our data show that blocking BTK has a modest increase in lifespan in Zmpste24−/− mice and protects them from a decline in brain performance. This suggests that specific inhibitors could be used in humans to treat progeroid syndromes and prevent the age‐related degeneration of organs such as the brain.

Introduction: The phase 3 international, randomized, double-blind ROBUST clinical trial (NCT02285062) compared progression-free survival between patients with previously untreated ABC-type DLBCL treated with placebo plus rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (placebo-R-CHOP) versus lenalidomide + R-CHOP (R2-CHOP) for 6 21-day cycles. HRQoL, as measured by the Functional Assessment of Cancer Therapy-Lymphoma (FACT-Lym) and the EuroQoL 5-dimension 3-level (EQ-5D-3L) patient-reported questionnaires, was evaluated as a secondary endpoint for the 2 treatment arms. Methods: For each treatment group, FACT-Lym and EQ-5D-3L scores were measured at baseline (BL), mid-, end-of-treatment (EOT), and post-treatment, in 12-week intervals from Week 34 onward. Patients were evaluated if they had completed BL and ≥ 1 post-BL calculable FACT-Lym subscale measurements. Non-inferiority (NI) of R2-CHOP versus placebo-R-CHOP was measured for 4 key FACT-Lym subscales: Physical Well-Being (PWB), Additional Concerns (AC), Functional Well-Being (FWB), and Trial Outcome Index (TOI). NI was assessed at EOT (typically 3-4 weeks after completing Cycle 6) and at post-treatment follow-up at Week 34 by analysis of covariance (ANCOVA). The NI margins were prespecified as 1 less than the higher published minimal important difference (MID) for each subscale. Since a range of MIDs have been published, a more conservative value was also used as a sensitivity analysis. Time to improvement (TTI), using published responder definitions, was also assessed for the FACT-Lym subscales. EQ-5D-3L scores were summarized descriptively. Results: Demographic and baseline disease characteristics were balanced across the 2 treatment arms (N = 285 per arm). The percentage of patients who completed the FACT-Lym out of the expected population remained &gt; 85% at all time points with &gt; 50 patients still on the study in each treatment arm up to Week 142. Completion rates and reasons for missing assessments were balanced across the 2 treatment arms. FACT-Lym subscale scores were generally higher after EOT, similar for both treatment groups, and mean changes from BL were close to or above MID (where defined), except for the Social/Family Well-Being subscale. Mean differences in FACT-Lym TOI between treatment arms are shown in Table 1. As positive treatment differences favor R2-CHOP and -10 was the predefined NI margin, NI was demonstrated for the FACT-Lym TOI subscale at both EOT and Week 34 assessments. Superiority of R2-CHOP was demonstrated at EOT as the confidence interval (CI) lies completely above 0 (P &lt; 0.04); however, this difference was not clinically meaningful. Furthermore, NI was also demonstrated when using the sensitivity analysis margin of -4.5. ANCOVA models were also fitted for the other key subscales of PWB, AC and FWB (Table 2). NI was demonstrated for all NI margins at both time points for the PWB and AC subscales. The FACT-Lym FWB subscale demonstrated NI for both margins at EOT and Week 34 for the primary NI margin of -2 based on the MID minus 1, but did not demonstrate NI when an NI margin of -1, based on an alternative published MID, was used. The TTI curves and associated summary statistics were similar for the 2 treatment arms, with a median TTI for the FACT-Lym TOI of 21 weeks (95% CI 15-22) for patients treated with R2-CHOP and 18 weeks (95% CI 15-22) for patients treated with placebo-R-CHOP. Mean EQ-5D-3L visual analogue scale (VAS) and Utility Index (UK weights) change from baseline scores were higher in both treatment arms and the mean changes were above, or close to, the published MID (7 for VAS, 0.1 for Utility Index) at EOT assessments. Prespecified sensitivity and subgroup analyses supported the conclusions from the primary HRQoL analyses. Conclusions: The predefined NI levels were met for the 4 key FACT-Lym subscales. Similar results were observed across the other HRQoL assessments, sensitivity, and subgroup analyses. Adding lenalidomide to the R-CHOP regimen did not adversely affect the HRQoL of patients with DLBCL as measured by FACT-Lym and EQ-5D-3L. These data serve as a benchmark for future clinical trials combining next-generation immunomodulatory drugs with standard R-CHOP to improve clinical efficacy while maintaining HRQoL in patients with DLBCL. HRQoL analyses should become an integral part of future clinical trials of novel combination regimens in DLBCL. Disclosures Chiappella: Roche: Speakers Bureau; Teva: Speakers Bureau; Servier: Other: advisory board, Speakers Bureau; Janssen: Other: advisory board, Speakers Bureau; Celgene: Other: advisory board, Speakers Bureau. Cocks:Adelphi Values: Employment; Amgen: Consultancy; BMS: Consultancy; Celgene Corporation: Consultancy; Endomag Ltd.: Consultancy. Greenwood:Adelphi Values: Employment. Williams:Adelphi Values: Employment. Scott:Celgene: Consultancy; Roche/Genentech: Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding; Janssen: Consultancy, Research Funding. Yamamoto:SymBio: Research Funding; Ono: Consultancy, Honoraria, Research Funding; Otsuka: Honoraria; Sanofi: Honoraria; Astra-Zeneca: Consultancy, Research Funding; Sumitomo Dainippon: Honoraria; Chugai: Consultancy, Honoraria, Research Funding; Eisai: Consultancy, Honoraria, Research Funding; Janssen: Honoraria; Gilead Sciences: Research Funding; Solasia Pharma: Research Funding; Bayer: Research Funding; Celgene Corporation: Consultancy, Honoraria, Research Funding; ARIAD: Research Funding; Pfizer: Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Kyowa Kirin: Honoraria; MSD: Consultancy, Honoraria; Mundipharma: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Research Funding; Meiji Seika Pharma: Consultancy, Honoraria; HUYA/IQVIA Services Japan: Consultancy, Honoraria; Novartis: Honoraria, Research Funding; Incyte: Research Funding; Takeda: Consultancy, Honoraria, Research Funding. Jurczak:Bayer: Research Funding; Takeda: Research Funding; Gilead: Research Funding; Sandoz: Membership on an entity's Board of Directors or advisory committees, Research Funding; Morphosys: Research Funding; Incyte: Research Funding; Celgene Corporation: Research Funding; Loxo: 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; Roche: Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celtrion: Research Funding; Novo Nordisk: Research Funding; Servier: Research Funding; TG Therapeutics: Research Funding. Özcan:Sanofi: Other: Travel support; Abdi Ibrahim: Other: Travel support; BMS: Other: Travel support; Takeda: Honoraria, Other: Travel support, Research Funding; Archigen: Research Funding; Roche: Other: Travel support, Research Funding; Bayer: Research Funding; Janssen: Other: Travel support, Research Funding; Celgene Corporation: Research Funding, Travel support; AbbVie: Other: Travel support, Research Funding; MSD: Research Funding; Novartis: Research Funding; Jazz: Other: Travel support; Amgen: Honoraria, Other: Travel support. Belada:Roche: Consultancy; Gilead Sciences: Consultancy; Takeda: Consultancy. Margunato-Debay:Celgene Corporation: Employment, Equity Ownership. Czuczman:Celgene Corporation: Employment, Equity Ownership. Zhai:Celgene Corporation: Employment, Equity Ownership. Braverman:Celgene Corporation: Employment. Vitolo:Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; F. Hoffmann-La Roche: Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Nowakowski:Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding.

Background: Multiple myeloma (MM) is a heterogeneous disease with varying survival outcomes depending on the presence of certain genetic abnormalities. Common abnormalities include trisomies, translocations involving the chromosome 14, and amplifications or deletions of chromosomes 1, 13, and 17. t(11;14), occurring in 15% of patients with myeloma, had been considered a standard risk abnormality, but recent data suggest inferior outcome. This is important as new therapeutic options such as the BCL-2 inhibitor venetoclax has been shown to be particularly effective in t(11;14) patients. Methods: This was a multicenter study to identify the outcomes of patients with t(11;14), using a retrospectively assembled cohort. Patients with MM diagnosed between 2005 and 2015 with t(11;14) identified on FISH performed within six months of diagnosis, and with treatment details available and if alive, a minimum of 12 months of follow up, were enrolled. Results: The current analysis includes 1216 patients; median age of 62.56 years; 58.7% male. The median follow-up from diagnosis for the entire cohort was 51.9 months; 69.1% of the patients were alive at the last follow up. ISS stage distribution included: Stage I (35.7%), Stage II (34.0%) and Stage III (15.1%), data was missing for the rest. The distribution of concurrent FISH abnormalities included: trisomies (3.5%), del 13q (13.3%), 1q amp (8.8%), and del 17p or monosomy 17 (5.8%). Initial regimen included: 27.2% had an immunomodulatory (IMiD), 45.9% had a proteasome inhibitor (PI), 17.7% had both, and 9.0% had no novel agent. The drug classes by line of therapy are shown in Table 1. An early stem cell transplant (defined as within 12 months of start of first line treatment) was used in 49.4% of patients. The median time to next treatment (TTNT) after starting initial treatment was 26.6 (95% CI: 23.9 to 29.2) months. The median overall survival (OS) from diagnosis for the entire cohort was 95.1 (95% CI: 85.9 to 105.9) months; 4-year estimates for those diagnosed from January 2005 to December 2009, and from January 2010 to December 2014 were 77.5% and 78.6%, respectively. The median OS for those with any one high risk FISH lesion (del 17p/ 1q amp) was 67.5 (55.2, 97.1) versus 101.7 (89.7, 107.3) months. Patients with early SCT (within 12 months of diagnosis) had better OS: 108.3 (103.8, 133.0) vs. 69.8 (61.5, 80.3) months. Conclusion: Patients with t(11;14) without high risk FISH abnormalities have an excellent survival. Patients receiving a PI + IMiD combination and those receiving autologous SCT as part of initial therapy had best survival. Though numbers are limited, patients in the later lines receiving newer drugs such as venetoclax and daratumumab had high response rates and durable responses. Disclosures Kumar: Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Bittrich:Celgene: Other: Travel Funding, Research Funding; Else Kröner Fresenius Foundation: Research Funding; Otsuka Pharmaceuticals Europe: Other: N/A; SANOFI Aventis: Membership on an entity's Board of Directors or advisory committees, N/A, Research Funding; University Hospital Wuerzburg: Employment; Bristol Myers Squibb: Research Funding; Pfizer: Other: Travel Funding; AMGEN: Other: Travel Funding; JAZZ Pharmaceuticals: Other: Travel Funding; Wilhelm Sander Foundation: Research Funding; German Research Foundation (DFG): Other: N/A; University of Würzburg: Other: N/A. Goldschmidt:Mundipharma: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; John-Hopkins University: Research Funding; Dietmar-Hopp-Stiftung: Research Funding; Janssen: Consultancy, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Research Funding; Molecular Partners: Research Funding; John-Hopkins University: Research Funding; Amgen: Consultancy, Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Chugai: Honoraria, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding. Reece:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Otsuka: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; BMS: Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Merck: Research Funding. Mateos:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmamar: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria; EDO: Membership on an entity's Board of Directors or advisory committees. Ludwig:Celgene: Speakers Bureau; Amgen: Research Funding, Speakers Bureau; Takeda: Research Funding, Speakers Bureau; PharmaMar: Consultancy; Janssen: Speakers Bureau; BMS: Speakers Bureau. Mangiacavalli:celgene: Consultancy; Amgen: Consultancy; Janssen cilag: Consultancy. Dimopoulos:Sanofi Oncology: Research Funding. Kastritis:Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Honoraria; Prothena: Honoraria; Genesis: Honoraria. Yee:Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding; Karyopharm: Consultancy; Adaptive: Consultancy. Raje:Amgen Inc.: Consultancy; Bristol-Myers Squibb: Consultancy; Celgene Corporation: Consultancy; Takeda: Consultancy; Janssen: Consultancy; Merck: Consultancy. Rosta:Cornerstone Research Group: Employment. Haltner:Cornerstone Research Group: Employment. Cameron:Cornerstone Research Group: Employment, Equity Ownership. Durie:Amgen, Celgene, Johnson & Johnson, and Takeda: Consultancy.

Background: Early data from anti-CD19 chimeric antigen receptor (CAR) T-cell trials suggest that concurrent infection can lead to poor outcomes. 1,2 The relationship between CAR T-cell mediated inflammatory responses and infections is not well-established. With CAR T-cell therapies more readily available, practitioners must identify which patient, disease and CAR T-cell specific parameters are associated with an increased risk of infection to optimize outcomes. We provide a comprehensive analysis of infection risk within the first 30 days after CAR T-cell infusion across multiple types of CAR T-cell trials targeting distinct antigens. Methods: This was a single-center, retrospective study conducted at the National Cancer Institute analyzing infectious complications in subjects who underwent CAR T-cell therapy on one of four phase I clinical trials, targeting CD19, CD22, B-cell maturation antigen (BCMA) or disialoganglioside (GD2) from 2012 though 2018. Baseline characteristics are in Table 1. The primary objective was to establish the incidence of infections between initiation of lymphodepleting (LD) chemotherapy through day 30 after CAR T-cell infusion. The secondary objective was to identify risk factors for infection. Patients were censored at relapse and/or initiation of alternative therapy, including treatment for relapse or consolidative hematopoietic stem cell transplantation (HSCT). Univariate screening methods were used to identify parameters associated with increased risk of infection Results: Amongst 144 subjects, 52 (36.1%) received anti-CD19 CAR T-cells (CAR-T); 53 (36.8%) received anti-CD22 CAR-T, 26 (18.1%) received anti-BCMA CAR-T; and 13 (9%) received anti-GD2 CAR-T. The median age was 18 years (range: 4 to 66). Sixty-one (42.4%) had undergone at least one prior allogeneic hematopoietic stem cell transplant (HSCT) and 24 (16.7%) had at least one prior autologous HSCT. Sixty-eight (47.2%) had a history of a recent infection within 100 days of initiation of LD chemotherapy, of which 17 were a major chronic infection and 9 were considered severe. Fifty-eight (40.3%) subjects experienced a total of 103 infections from initiation of LD chemotherapy through day 30 post CAR T-cell infusion, with the median time to first infection being 6 days post-CAR infusion. Twenty-eight (19.4%) subjects had more than 1 infection; 20 (13.9%) subjects had C. difficile infection. The 103 infections consisted of 47 (45.6%) distinct episodes of focal bacterial infections (e.g., sinusitis, pneumonia, urinary tract infection), 25 (24.2%) episodes of bacteremia, 22 (21.4%) viral infections, and 9 (8.7%) invasive fungal infections. Fourteen infections (13.6%) occurred between initiation of LD chemotherapy and day 0 (prior to CAR T-cell infusion). Fever and neutropenia, without a source, was documented as a distinct entity in 85 patients (59.0%). Using univariate statistical screening methods, we identified 4 parameters that were individually associated with an increased risk of infection: increasing number of prior therapies (p=0.0034), prior history of recent infection within the past 100 days (p=0.0064), age > 18 (p =0.028), or enrollment on the CD22 CAR trial (p=0.0028). Eliminating the trial, since that is not generalizable, and combining these into a multivariable logistic regression model identified age > 18, prior history of infection and prior lines of therapies jointly associated with an increased risk of infection. Using these parameters, a predictive model was developed, which, when applied to the data set used to develop the model, can correctly predict 69 of 86 patients without an infection (80.3%; CI: 70.3-88.0%) as well as 32 of 58 patients with an infection (55.2%; 95% CI: 41.5- 68.3%). Conclusion: In this retrospective analysis, we provide the largest experience to date analyzing infection in the setting of CAR T-cell therapy across multiple CAR constructs. Our study demonstrates that adult age, prior history of infection, increased number of prior therapies and enrollment on a particular CAR T-cell trial, in this case the CD22 CAR-T trial, may lead to a higher risk of infection than in those without these risk factors. Further investigations are underway to evaluate clinical outcomes with infection which occur in the peri CAR T-cell setting and potential strategies to minimize infection risk. Generalizability of this model will be tested in an independent data set. Disclosures Lee: Kite, a Gilead Company: Research Funding; Harpoon Therapeutics: Consultancy; Juno Therapeutics: Other: External Advisory Board; ACI Clinical on behalf of Celgene:: Other: Independent Central Quality Review Committee. Mackall:Obsidian: Research Funding; Lyell: Consultancy, Equity Ownership, Other: Founder, Research Funding; Nektar: Other: Scientific Advisory Board; PACT: Other: Scientific Advisory Board; Bryologyx: Other: Scientific Advisory Board; Vor: Other: Scientific Advisory Board; Roche: Other: Scientific Advisory Board; Adaptimmune LLC: Other: Scientific Advisory Board; Glaxo-Smith-Kline: Other: Scientific Advisory Board; Allogene: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Apricity Health: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Unum Therapeutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Kochenderfer:Kite and Celgene: Research Funding; Bluebird and CRISPR Therapeutics: Other: received royalties on licensing of his inventions. OffLabel Disclosure: Conditioning chemotherapy for CAR T-cell therapy; this is a retrospective study that used different lymphodepletion regimens.

INTRODUCTION: EMZL is a heterogeneous disease with variable risk for relapse and progression. Based on age ≥70 years, stage III-IV and elevated LDH, Thieblemont et al (Blood. 2017) developed the MALT-IPI to identify high-risk patients. In this index, disease characteristics (stage and LDH) account for 66% while a disease nonspecific characteristic (age) for 33% of the index score. We reported (Am J Hematol. 2019) that EMZL with multiple mucosal sites (MMS) at diagnosis is characterized by shorter survival and increased incidence of higher grade transformation. To better recognize disease-attributable high-risk patients, we developed a new EMZL prognosis score chiefly based on patient's disease characteristics. METHODS: The revised (R)-MALT-IPI was developed using a retrospective data set of 405 EMZL patients treated at the University of Miami (UM) from 1995 to 2017. Cox proportional hazards regression analysis was conducted to evaluate the effect of the potential prognostic variables on progression-free survival (PFS) and overall survival (OS) and to develop the new index R-MALTI-IPI based on PFS. Model validation was performed in two independent cohorts of EMZL patients from the University of Iowa/Mayo Clinic Molecular Epidemiology Resource (MER) database (n=297) and the IELSG-19 study (n=400) used for the development of MALT-IPI. Performance of various prognostic indices was compared using AIC statistics, and concordance c-statistics by Harrell (CH) and by Gonen and Heller (CGH). RESULTS: Among the candidate variables tested in univariable analysis, the following were statistically significant predictors of shorter PFS: age >60, age ≥70, anemia (Hb<12g/dL), stage III-IV, ECOG PS ≥2, elevated serum LDH, number of extranodal sites >1, number of nodal sites >4, and presence of MMS at diagnosis, defined as EMZL with ≥2 different extranodal sites excluding spleen and bone marrow. A stepwise Cox regression analysis yielded a multivariable model with four independent predictors of shorter PFS: age >60 (HR=1.53, p=0.010), elevated LDH (HR=1.73, p=0.004), stage III-IV (HR=2.03, p=0.0003) and presence of MMS (HR=2.78, p<0.0001). Based on this, a new index R-MALT-IPI was developed with scores ranging from 0 to 5, calculated as a sum of 1 point for age >60, elevated LDH, stage III-IV, and 2 points for MMS. The R-MALT-IPI defined 4 risk groups: low-risk (score 0 (35%), reference group), low-medium risk (score 1 (39%), HR=1.91, p=0.005), medium-high risk (score 2 (13%), HR=3.77, p<0.0001), and high-risk (score 3+ (13%), HR=8.54, p<0.0001). When compared with MALT-IPI, R-MALT-IPI better stratifies and separates high risk patients (26%) into medium-high risk and high-risk patients with a median PFS of 5.8 years (2.9-9.1) and 1.8 years (1.3-2.6) respectively, compared to 2.6 years (1.8-4.7) in the high-risk MALT-IPI patients (16.8%). The R-MALT-IPI index also distinguished patients with different OS. For validation, we analyzed R-MALT-IPI index performance in independent Iowa/Mayo Clinic MER and IELSG-19 cohorts. Both R-MALT-IPI and MALT-IPI were useful in distinguishing PFS and OS in all the cohorts. In the UM training cohort, the concordance c-statistics' values for the two indices were similar: for PFS, CH=0.6893 and CGH=0.6611 for R-MALT-IPI, and CH=0.6551 and CGH=0.6367 for MALT-IPI; for OS, CH=0.7017 and CGH=0.6813 for R-MALT-IPI, and CH=0.7029 and CGH=0.67715 for MALT-IPI. In the validation cohorts, the concordance c-statistics' values for the two indices were also similar, but slightly lower than in the UM cohort for PFS. When comparing medium-high to high-risk R-MALT-IPI groups, there was a reduction of 4 years in median PFS in the UM cohort, and reduction in median EFS of 5.6 years in the MER cohort, an important difference between these risk groups identified by the R-MALT-IPI index. CONCLUSIONS: R-MALT-IPI is a new index for EMZL centered principally on disease characteristics. Overall, there is a similar prediction of PFS (EFS) by R-MALT-IPI and MALT-IPI indexes; however, R-MALT-IPI better recognizes a high-risk group accounting for 13% of EMZL patients with short median PFS and thus obviates the waiting period needed to recognize patients with shorter EFS24. Collaborative studies addressing best treatment approach for these high-risk EMZL patients are eagerly needed. Disclosures Alderuccio: Agios: Other: Immediate family member; Foundation Medicine: Other: Immediate family member; OncLive: Consultancy; Targeted Oncology: Honoraria; Puma Biotechnology: Other: Immediate family member; Inovio Pharmaceuticals: Other: Immediate family member. Thieblemont:Cellectis: Membership on an entity's Board of Directors or advisory committees; Kyte: Honoraria; Janssen: Honoraria; Celgene: Honoraria; Roche: Honoraria, Research Funding; Gilead: Honoraria; Novartis: Honoraria. Cerhan:Celgene: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding. Zucca:Kite, A Gilead Company: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees, Other: Travel Grant, Research Funding; AstraZenaca: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Research Funding; Merck: Research Funding; Celltrion Helathcare: Membership on an entity's Board of Directors or advisory committees; Abbvie: Other: Travel Grant. Lossos:NIH: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Janssen Scientific: Membership on an entity's Board of Directors or advisory committees.

Abstract Background: In contrast to the rapid increase in thyroid cancer (TC) incidence, thyroid cancer mortality rates have remained low and stable over the last decades. In Ecuador, however, TC mortality has increased and to determine possible drivers, a retrospective analysis of all patients attending a thyroid cancer referral center in Ecuador was conducted. Methods: From June 2014 to December 2017, a cross-sectional study was conducted at the Hospital de Especialidades Eugenio Espejo (HEEE), a regional reference public hospital for endocrine neoplasia in adults in Quito, Ecuador. We identified the mechanism of detection, histopathology and treatment modalities from a patient interview and review of clinical records. Results: Among 452 patients, 74.8% were young adults and 94.2% (426) of patients were female. 13.7% had a family history of thyroid cancer, and median of tumor size was 2 cm. The incidental finding was 54.2% whereas 45.8% was non-incidental. Thyroid cancer histology reported that 93.3% had papillary thyroid cancer (PTC), 2.7% follicular, 1.5% Hurtle cells, 1.6% medullary, 0.7% poor differentiated, and 0.2% anaplastic carcinoma. The mean MACIS (metastasis, age, completeness, invasion, and size) score was 4.95 (CI 4.15-5.95) with 76.2% of the thyroid cancer patients having MACIS score equal or less than 6. The very low and low risk of recurrence was 18.1% (79) and 62% (271) respectively. An analysis of 319 patients with non-metastatic thyroid cancer showed that 10.7% (34) of patients had surgical complications. Moreover, around 62.5% (80 from 128 patients with thyroglobulin laboratory results) of TC patients had a stimulated-thyroglobulin (sTg) value equal or higher than 2 ng/ml. Overall, a poor surgical outcome was present in 35.1% (112) patients. Out of 436 patients with differentiated thyroid carcinoma (DTC), 86% (n=375) received radioactive iodine (RAI). Conclusion: Thyroid cancer histological characteristics and method of diagnosis are like the ones described in other reports without any evidence of the high frequency of aggressive thyroid cancer histology. However, we observed evidence of overtreatment and poor surgical outcomes that demand additional studies to understand their association with thyroid cancer mortality in Ecuador.

Objective Cholangiocarcinoma (CCA) affects all ethnicities worldwide. The Hispanic population being the leading ethnic minority in the United States, its importance to the healthcare system cannot be understated. This study aims to assess the occurrence and outcomes of CCA in Hispanic patients in the United States. Methods This is a case-control study using the National Inpatient Sample 2014. All patients with ICD-9 CM codes for CCA were included. Hispanic patients were identified from the ethnic categories within the database. The primary outcomes were the occurrence and odds of CCA in the Hispanic population when compared with other ethnicities. Secondary outcomes were inpatient mortality, morbidity, ICU stay, multiorgan failure, and resource utilization. Results A total of 13 965 patients with CCA were identified, of which 2750 were propensity-matched to controls (1480 Hispanic). The inpatient occurrence of CCA in Hispanics relative to the national population was 2.73/100 000 persons, compared to 4.82/100 000 persons (39.9/100 000 relative to inpatient population) of all other ethnicities. After adjusting for confounders on multivariate analysis, Hispanic patients displayed adjusted propensity-matched odds of 1.28 (P < 0.01) of having CCA when compared with other ethnicities. Hispanics did not display different propensity-matched odds of inpatient mortality, morbidity, hospital length of stay, or resource utilization compared to non-Hispanic patients. Conclusion This study demonstrated that the odds of CCA in admitted patients are higher for the Hispanic population. This difference with the prevalence potentially suggests the presence of social factors such as disparities in cancer prevention or detection in this group.

Abstract Background Anthracyclines are one of the most effective chemotherapeutic agents but can lead to a decline in cardiac function. Two-dimensional (2D) speckle tracking echocardiography derived strain can predict cancer therapeutics-related cardiac dysfunction (CTRCD). However, little is known about the role of three-dimensional (3D) strain imaging in this setting. Purpose To evaluate different methods of Left Ventricular Ejection Fraction (LVEF) and strain, and to identify the best strain parameter for the prediction of CTRCD in this group of patients during treatment with anthracycline based chemotherapy. Methods Patients with Hodgkin's or non-Hodgkin's lymphoma receiving anthracycline based chemotherapy were enrolled. 2D-and 3D echocardiography was performed at 3 time points: baseline, at the completion of chemotherapy and at 1 year. 2D- and 3D LVEF (2D Modified Quinones, M-mode, 2D Biplane, 3D Philips, 3D GE and 3D TomTec), peak systolic left and right ventricular longitudinal, radial and circumferential strain and strain rate were measured. CTRCD was defined as a decrease in LVEF >10% to an absolute value of <53%. Lin's Concordance Correlation Coefficient (CCC) was calculated to compare LVEF methods. ANOVA, uni and multivariate analysis was performed. Results A total of 130 patients (79 males, mean age 57±16 years) were enrolled; 104 non-Hodgkin.3D Philips and GE (CCC 0.88 [0.84, 0.92]), 3D Philips and biplane (CCC 0.84 [0.79, 0.89]), 3D Philips and Modified Quinones (CCC 0.86 [0.82, 091]) as well as 3D Philips and M-mode (CCC 0.77 [0.70, 0.85]) showed strong correlation for LVEF. 15 patients (12%) developed CTRCD. Mean cumulative anthracycline dose was 263±65 mg/m2. 2D and 3D global longitudinal and circumferential peak systolic strain, 2D global longitudinal systolic and early diastolic strain rate, 2D global early diastolic strain rate, 2D right ventricular longitudinal peak systolic strain and systolic strain rate, 2D global radial peak systolic strain and systolic strain rate measured at the completion of chemotherapy were independent predictors of the development of CTRCD at 1 year post-chemotherapy. The strongest predictors of CTRCD were 3D global longitudinal and circumferential strain either individually (area under the curve, 0.90 and 0.95 respectively) or combined (area under the curve, 0.95) at the completion of chemotherapy; a cutoff value of <-18% in 3D global longitudinal strain had a sensitivity of 82% and specificity of 99%, while for 3D global circumferential peak systolic strain of <-24% had a sensitivity of 82% and specificity of 95%. Conclusions To our knowledge this is the first prospective trial that shows that 3D EF correlates well with other EF methods and 3D strain predicts cardiac toxicity in this group of patients with a very good sensitivity and specificity. Acknowledgement/Funding Department of Cardiovascular Medicine-Mayo Clinic Rochester MN