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We sought to determine risk factors for iv iron infusion-related reactions (IRR), and identify strategies for iron repletion after IRR.We conducted a retrospective chart review of patients treated in the classical hematology clinic at Yale Cancer Center (n = 330 consecutive patients) from 2016 to 2021, who received iv ferumoxytol (60.3%), iron sucrose (14.8%), or iron dextran (10.9%).The iv iron IRR was noted in 58 (17.6%) patients, 62.1% of whom had previously tolerated iv iron. The severity of IRR was mild in 22, moderate in 23, and severe in 11 patients. Most (72.4%) patients who experienced IRR tolerated a subsequent iv iron infusion. On multivariable analysis, a history of non-medication allergies was associated with greater odds of IRR (odds ratio [OR] 2.12, 95% confidence interval (CI): 1.16-3.87, p = .01). No patients with type AB blood, and few with type A blood (n = 6), had IRR; compared to type A or AB together, patients with type B (OR 5.00, 95% CI: 1.56-16.06, p = .007) or type O (OR 3.71, 95% CI: 1.44-9.55, p = .007) blood had greater odds of IRR.This study highlights a possible association of blood type with iv iron IRR; prospective studies with larger patient numbers are warranted to explore this association.

Tyrosine kinase inhibitor (TKI) use is critical to the care of patients with chronic myeloid leukemia (CML). Quantitative BCR-ABL1 polymerase chain reaction (qPCR) testing every 3 months during the first year of TKI treatment is recommended to assure achievement of milestone response goals. Real-world evidence for the patterns of qPCR monitoring and TKI adherence in the older patient population is lacking. Using the Surveillance, Epidemiology, and End Results-Medicare database we identified 1192 patients aged >66 years (median age of 74 years) with newly-diagnosed CML followed for ≥13 months from TKI initiation. Nine hundred sixty five patients (81.0%) had at ≥1 test with 425 (35.7%) and 540 (45.3%) of patients tested during 1-2 and ≥3 quarters (optimal monitoring) of the first year from TKI initiation, respectively. In multivariable analysis, diagnosis in later years (compared with 2007-2010, 2011-2014 odds ratio [OR]=1.97, 95% confidence interval [CI]: 1.43-2.7, p

Background The COVID-19 pandemic has led to delays in patients seeking care for life-threatening conditions; however, its impact on treatment patterns for patients with metastatic cancer is unknown. We assessed the COVID-19 pandemic’s impact on time to treatment initiation (TTI) and treatment selection for patients newly diagnosed with metastatic solid cancer. Methods We used an electronic health record–derived longitudinal database curated via technology-enabled abstraction to identify 14 136 US patients newly diagnosed with de novo or recurrent metastatic solid cancer between January 1 and July 31 in 2019 or 2020. Patients received care at approximately 280 predominantly community-based oncology practices. Controlled interrupted time series analyses assessed the impact of the COVID-19 pandemic period (April-July 2020) on TTI, defined as the number of days from metastatic diagnosis to receipt of first-line systemic therapy, and use of myelosuppressive therapy. Results The adjusted probability of treatment within 30 days of diagnosis was similar across periods (January-March 2019 = 41.7%, 95% confidence interval [CI] = 32.2% to 51.1%; April-July 2019 = 42.6%, 95% CI = 32.4% to 52.7%; January-March 2020 = 44.5%, 95% CI = 30.4% to 58.6%; April-July 2020 = 46.8%, 95% CI= 34.6% to 59.0%; adjusted percentage-point difference-in-differences = 1.4%, 95% CI = −2.7% to 5.5%). Among 5962 patients who received first-line systemic therapy, there was no association between the pandemic period and use of myelosuppressive therapy (adjusted percentage-point difference-in-differences = 1.6%, 95% CI = −2.6% to 5.8%). There was no meaningful effect modification by cancer type, race, or age. Conclusions Despite known pandemic-related delays in surveillance and diagnosis, the COVID-19 pandemic did not affect TTI or treatment selection for patients with metastatic solid cancers.

The hypomethylating agents (HMAs) azacitidine and decitabine have been the de facto standard of care for patients with acute myeloid leukemia (AML) who are unfit for intensive therapy. Using the Surveillance, Epidemiology, and End Results-Medicare linked database, we identified 2263 older adults (age ≥66 years) diagnosed with AML during 2005-2015 who received a first-line HMA; 1154 (51%) received azacitidine, and 1109 (49%) received decitabine. Median survival from diagnosis was 7.1 and 8.2 months (P < .01) for azacitidine- and decitabine-treated patients, respectively. Mortality risk was higher with azacitidine vs decitabine (hazard ratio [HR], 1.11; 95% confidence interval [CI], 1.01-1.21; P = .02). The findings were similar when evaluating only patients completing ≥4 cycles (42% of patients treated with either azacitidine or decitabine). These findings lost significance when evaluating those completing a standard 7-day schedule of azacitidine (34%) vs 5-day schedule for decitabine (66%) (HR, 0.95; 95% CI, 0.83-1.08; P = .43). Red blood cell (RBC) transfusion independence (TI) was achieved in one-third of patients with no difference between the 2 HMAs. In conclusion, the majority of older AML patients did not receive the minimum of 4 cycles of HMA often needed to elicit clinical benefit. We observed no clinically meaningful differences between azacitidine- and decitabine-treated patients in their achievement of RBC TI or survival.

Cytarabine-anthracycline based intensive induction chemotherapy (IC) remains the standard of care for remission induction among fit patients with newly diagnosed acute myeloid leukemia (AML) in the United States (US). However, the mortality rate outside of clinical IC trials, predictors of death, and resource utilization during admission for IC have not been thoroughly examined. We used the Premier Healthcare database to identify adult patients (aged 18-89 years) treated with cytarabine-anthracycline-based IC during their first recorded inpatient stay for AML during the contemporary period of 2010 to 2017. We identified factors associated with inpatient death or discharge to hospice, using multivariable logistic regression models. We also assessed the patterns of inpatient healthcare resource utilization. A total of 6442 patients with AML from 313 hospitals who were treated with IC were identified. Median age was 61 years (interquartile range [IQR], 50-68 years), and 56% were men. Median length of stay was 29 (IQR, 25-38) days, with rates of in-hospital death and discharge to hospice of 12.3% and 3.7% (17.9% and 6.3% among patients aged ≥65 years), respectively. Predictors of in-hospital death or discharge to hospice included older age, geographic region, and lower hospital volume. During admission, 28.0%, 12.6%, and 4.0% of patients required treatment in intensive care units, mechanical ventilation, and dialysis, respectively. Despite improvements in supportive care in the contemporary era, inpatient mortality during first hospitalization for adult patients with AML treated with IC in the US remains high particularly among older patients.

Background: Despite advances in chemoimmunotherapy and stem cell transplantation, mantle cell lymphoma (MCL) has historically been difficult to treat. Patients with advanced age and high-risk features (e.g. blastoid/pleomorphic features, high MIPI score, complex karyotype, TP53 mutation) face particularly poor outcomes with standard chemoimmunotherapy. Ibrutinib, a Bruton tyrosine kinase inhibitor (BTKi), was approved for second-line use in MCL in 2013. Other BTKis - acalabrutinib and zanubrutinib were approved in 2017 and 2019, respectively. BTKi provides a well-tolerated chemotherapy-free option for these hard-to-treat subgroups, especially the older patients. In this population-based study, we evaluated survival outcomes prior to and after the approval of ibrutinib, and hypothesized that survival benefit observed early after approval would be greatest in older patients not typically candidates for consolidative transplantation in the first-line setting. Methods: Using the Surveillance, Epidemiology, and End Results database, we included all adult patients diagnosed with MCL in the years 2007-2018 and followed them to the end of 2018 or death, whichever came first. The pre-BTKi era was defined by year of diagnosis 2007-2011, and the BTKi era was between 2014 and 2018. The years 2012-2013 were considered as a "washout" period to allow practice change related to the approval of ibrutinib. As age plays an important role in treatment decisions, including whether to use consolidative transplantation, patients were divided based on age at diagnosis: Results: We identified 7,625 individuals diagnosed with MCL during our study period (3,424 and 4,201 diagnosed during 2007-2011 and 2014-2018, respectively). The majority were male (71%) and white (90%), with 49% of patients 70 years or older. The median follow-up was 9.2 and 2.4 years for patients diagnosed during 2007-2011 and 2014-2018, respectively. The 3-year all-cause mortality and 3-year MFM rates were 39.8% and 27.3%, respectively, in the overall population. Both the 3-year all-cause mortality and MFM increased as age increased. The 3-year all-cause mortality was lower in the BTKi era among all age groups, except patients In the multivariable analyses, risk of death was significantly lower during the BTKi era in the 60-69 (HR:0.85, 95% CI: 0.72-1.00) and 70-79 (HR: 0.80, 95% CI: 0.70-0.92) age groups. MFM was also significantly lower during the BTKi era in these two age groups (60-69: sHR: 0.78, 95% CI: 0.64-0.94; 70-79: sHR: 0.76, 95% CI: 0.65-0.90, Table). The results were largely unchanged in sensitivity analyses (results not shown). Conclusion: In this large population-based cohort analysis of individuals diagnosed with MCL, overall and lymphoma-specific survival improved in the BTKi era. At a median follow up of 2.4 years in our BTKi cohort, significant survival benefits were observed in those older than 60 but less than 80 years of age, and the observed benefits were greatest in the 70-79 age group. Future real-world studies should examine the impact of novel agents on treatment patterns and outcomes of MCL over a longer follow up period. Figure 1 Figure 1. Disclosures Kothari: Incyte pharmaceuticals: Consultancy, Honoraria; Karyopharm pharmaceuticals: Consultancy, Honoraria. Zeidan: Amgen: Consultancy, Research Funding; Astellas: Consultancy; Jasper: Consultancy; BMS: Consultancy, Other: Clinical Trial Committees, Research Funding; Boehringer Ingelheim: Consultancy, Research Funding; BeyondSpring: Consultancy; Acceleron: Consultancy, Research Funding; BioCryst: Other: Clinical Trial Committees; Novartis: Consultancy, Other: Clinical Trial Committees, Travel support, Research Funding; AbbVie: Consultancy, Other: Clinical Trial Committees, Research Funding; Ionis: Consultancy; Loxo Oncology: Consultancy, Other: Clinical Trial Committees; Astex: Research Funding; AstraZeneca: Consultancy; Epizyme: Consultancy; Cardiff Oncology: Consultancy, Other: Travel support, Research Funding; Janssen: Consultancy; Agios: Consultancy; ADC Therapeutics: Research Funding; Jazz: Consultancy; Genentech: Consultancy; Gilead: Consultancy, Other: Clinical Trial Committees; Incyte: Consultancy, Research Funding; Geron: Other: Clinical Trial Committees; Pfizer: Other: Travel support, Research Funding; Daiichi Sankyo: Consultancy; Kura: Consultancy, Other: Clinical Trial Committees; Aprea: Consultancy, Research Funding. Podoltsev: PharmaEssentia: Honoraria; Incyte: Honoraria; Novartis: Honoraria; Bristol-Myers Squib: Honoraria; CTI BioPharma: Honoraria; Celgene: Honoraria; Blueprint Medicines: Honoraria; Pfizer: Honoraria. Neparidze: Janssen: Research Funding; Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Research Funding. Shallis: Curis: Divested equity in a private or publicly-traded company in the past 24 months. Ma: Celgene/Bristol Myers Squibb: Consultancy, Research Funding. Huntington: AbbVie: Consultancy; TG Therapeutics: Research Funding; SeaGen: Consultancy; DTRM Biopharm: Research Funding; Flatiron Health Inc.: Consultancy; Novartis: Consultancy; Bayer: Honoraria; Pharmacyclics: Consultancy, Honoraria; AstraZeneca: Consultancy, Honoraria; Genentech: Consultancy; Servier: Consultancy; Thyme Inc: Consultancy; Celgene: Consultancy, Research Funding.

BackgroundThe COVID-19 pandemic has led to delays in patients seeking care for life-threatening conditions; however, its impact on treatment patterns for patients with metastatic cancer is unknown. We assessed the COVID-19 pandemic’s impact on time to treatment initiation (TTI) and treatment selection for patients newly diagnosed with metastatic solid cancer.MethodsWe used an electronic health record-derived longitudinal database curated via technology-enabled abstraction to identify 14,136 US patients newly diagnosed with de novo or recurrent metastatic solid cancer between January 1 and July 31 in 2019 or 2020. Patients received care at ∼280 predominantly community-based oncology practices. Controlled interrupted time series analyses assessed the impact of the COVID-19 pandemic period (April-July 2020) on TTI, defined as the number of days from metastatic diagnosis to receipt of first-line systemic therapy, and use of myelosuppressive therapy.ResultsThe adjusted probability of treatment within 30 days of diagnosis [95% confidence interval] was similar across periods: January-March 2019 41.7% [32.2%, 51.1%]; April-July 2019 42.6% [32.4%, 52.7%]; January-March 2020 44.5% [30.4%, 58.6%]; April-July 2020 46.8% [34.6%, 59.0%]; adjusted percentage-point difference-in-differences 1.4% [-2.7%, 5.5%]. Among 5,962 patients who received first-line systemic therapy, there was no association between the pandemic period and use of myelosuppressive therapy (adjusted percentage-point difference-in-differences 1.6% [-2.6%, 5.8%]). There was no meaningful effect modification by cancer type, race, or age.ConclusionsDespite known pandemic-related delays in surveillance and diagnosis, the COVID-19 pandemic did not impact time to treatment initiation or treatment selection for patients with metastatic solid cancers.

Key Points 14% of newly diagnosed APL patients in the Vizient Clinical Data Base died during initial admission or were discharged to hospice.Adverse outcomes were lower with guideline-concordant treatment, low-risk disease, higher hospital AML volume, and younger age., Visual Abstract, Acute promyelocytic leukemia (APL) is associated with a favorable long-term prognosis if appropriate treatment is initiated promptly. Outcomes in clinical trials and population-based registries vary; potential explanations include a delay in treatment and lower adherence to guideline-recommended therapy in real-world practice. We used the Vizient Clinical Data Base to describe demographic characteristics, baseline clinical characteristics, and treatment patterns in patients newly diagnosed with APL during the study period of April 2017 to March 2020. Baseline white blood cell count was used to assign risk status and assess treatment concordance with National Comprehensive Cancer Network guidelines. Logistic regression models examined adjusted associations between patient, hospital, disease characteristics, and adverse outcomes (in-hospital death or discharge to hospice). Among 1464 patients with APL, 205 (14.0%) experienced an adverse outcome. A substantial subset (20.6%) of patients did not receive guideline-concordant regimens. Odds of adverse outcomes increased with failure to receive guideline-concordant treatment (odds ratio [OR], 2.31; 95% confidence interval [CI], 1.43-3.75; P = .001), high-risk disease (OR, 2.48; 95% CI, 1.53-4.00; P < .001), and increasing age (≥60 years: OR, 11.13; 95% CI, 4.55-27.22; P < .001). Higher hospital acute myeloid leukemia (AML) patient volume was associated with lower odds of adverse outcome (OR, 0.44; 95% CI, 0.20-0.99 [for ≤50 vs >200 AML patients per year]; P = .046). In conclusion, in this large database analysis, 14.0% of patients newly diagnosed with APL died or were discharged to hospice. A substantial proportion of patients did not receive guideline-concordant therapy, potentially contributing to adverse outcomes.

PURPOSE The MAIA trial found that addition of daratumumab to lenalidomide and dexamethasone (DRd) significantly prolonged progression-free survival in transplant-ineligible patients with newly diagnosed multiple myeloma, compared with lenalidomide and dexamethasone alone (Rd). However, daratumumab is a costly treatment and is administered indefinitely until disease progression. Therefore, it is unclear whether it is cost-effective to use daratumumab in the first-line setting compared with reserving its use until later lines of therapy. METHODS We created a Markov model to compare healthcare costs and clinical outcomes of transplant-ineligible patients treated with daratumumab in the first-line setting compared with a strategy of reserving daratumumab until the second-line. We estimated transition probabilities from randomized trials using parametric survival modeling. Lifetime direct healthcare costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs) were calculated for first-line daratumumab versus second-line daratumumab from a US payer perspective. RESULTS First-line daratumumab was associated with an improvement of 0.52 QALYs and 0.66 discounted life-years compared with second-line daratumumab. While both treatment strategies were associated with considerable lifetime expenditures ($1,434,937 v $1,112,101 in US dollars), an incremental cost of $322,836 for first-line daratumumab led to an ICER of $618,018 per QALY. The cost of daratumumab would need to be decreased by 67% for first-line daratumumab to be cost-effective at a willingness-to-pay threshold of $150,000 per QALY. CONCLUSION Using daratumumab in the first-line setting for transplant-ineligible patients may not be cost-effective under current pricing. Delaying daratumumab until subsequent lines of therapy may be a reasonable strategy to limit healthcare costs without significantly compromising clinical outcomes. Mature overall survival data are necessary to more fully evaluate cost-effectiveness in this setting.

BACKGROUND: PD-1 and PD-L1 have been studied interchangeably in the clinic as checkpoints to reinvigorate T cells in diverse tumor types. Data for biologic effects of checkpoint blockade in human premalignancy are limited. METHODS: We analyzed the immunologic effects of PD-L1 blockade in a clinical trial of atezolizumab in patients with asymptomatic multiple myeloma (AMM), a precursor to clinical malignancy. Genomic signatures of PD-L1 blockade in purified monocytes and T cells in vivo were also compared with those following PD-1 blockade in lung cancer patients. Effects of PD-L1 blockade on monocyte-derived DCs were analyzed to better understand its effects on myeloid antigen-presenting cells. RESULTS: In contrast to anti–PD-1 therapy, anti–PD-L1 therapy led to a distinct inflammatory signature in CD14(+) monocytes and increase in myeloid-derived cytokines (e.g., IL-18) in vivo. Treatment of AMM patients with atezolizumab led to rapid activation and expansion of circulating myeloid cells, which persisted in the BM. Blockade of PD-L1 on purified monocyte-derived DCs led to rapid inflammasome activation and synergized with CD40L-driven DC maturation, leading to greater antigen-specific T cell expansion. CONCLUSION: These data show that PD-L1 blockade leads to distinct systemic immunologic effects compared with PD-1 blockade in vivo in humans, particularly manifest as rapid myeloid activation. These findings also suggest an additional role for PD-L1 as a checkpoint for regulating inflammatory phenotype of myeloid cells and antigen presentation in DCs, which may be harnessed to improve PD-L1–based combination therapies. TRIAL REGISTRATION: NCT02784483. FUNDING: This work is supported, in part, by funds from NIH/NCI (NCI CA197603, CA238471, and CA208328).

Summary Background An important feature of severe acute respiratory syndrome coronavirus 2 pathogenesis is COVID-19-associated coagulopathy, characterised by increased thrombotic and microvascular complications. Previous studies have suggested a role for endothelial cell injury in COVID-19-associated coagulopathy. To determine whether endotheliopathy is involved in COVID-19-associated coagulopathy pathogenesis, we assessed markers of endothelial cell and platelet activation in critically and non-critically ill patients admitted to the hospital with COVID-19. Methods In this single-centre cross-sectional study, hospitalised adult (≥18 years) patients with laboratory-confirmed COVID-19 were identified in the medical intensive care unit (ICU) or a specialised non-ICU COVID-19 floor in our hospital. Asymptomatic, non-hospitalised controls were recruited as a comparator group for biomarkers that did not have a reference range. We assessed markers of endothelial cell and platelet activation, including von Willebrand Factor (VWF) antigen, soluble thrombomodulin, soluble P-selectin, and soluble CD40 ligand, as well as coagulation factors, endogenous anticoagulants, and fibrinolytic enzymes. We compared the level of each marker in ICU patients, non-ICU patients, and controls, where applicable. We assessed correlations between these laboratory results with clinical outcomes, including hospital discharge and mortality. Kaplan–Meier analysis was used to further explore the association between biochemical markers and survival. Findings 68 patients with COVID-19 were included in the study from April 13 to April 24, 2020, including 48 ICU and 20 non-ICU patients, as well as 13 non-hospitalised, asymptomatic controls. Markers of endothelial cell and platelet activation were significantly elevated in ICU patients compared with non-ICU patients, including VWF antigen (mean 565% [SD 199] in ICU patients vs 278% [133] in non-ICU patients; p

Background: Early during the COVID-19 pandemic patient and provider anxiety concerning in-person visits and travel restrictions may have delayed cancer diagnosis and altered treatment. We evaluated changes in clinical presentation and treatment patterns in multiple myeloma (MM) during the early COVID-19 period compared to historical pre-COVID periods. Methods: Using the nationwide Flatiron Health EHR-derived de-identified database, we compared clinical presentation and treatment patterns in the immediate post-COVID period (2020) to a comparable pre-COVID period (2018 and 2019). We focused on two separate clinical settings: 1) patients newly diagnosed with MM during February-June in the years of interest (NEWPT) with evidence of management within 90 days and follow-up for 7 months; and 2) patients diagnosed with MM during 2014-2019 receiving active treatment as of February (2018, 2019, 2020, ACTIVE) and follow-up for 11 months. Delayed clinical presentation was assessed using baseline (90 days before diagnosis/index date) measures of ISS stage, ECOG performance status, anemia, and kidney function. We examined treatment patterns (choice of regimen) of both cohorts in the two time periods. We compared clinical features of initial presentation in pre-COVID and COVID period using Pearson's χ 2 test. For NEWPT, we also utilized Kaplan-Meier curves and log-rank test to compare time to treatment initiation between the two periods. Multivariable Cox proportional hazards regression model with death as a competing risk was used to determine impact of COVID on treatment initiation by adjusting sex, age at diagnosis, race, insurance, stage, baseline ECOG, and hospital setting. All analyses were conducted in SAS (Version 9.4, SAS Institute, Cary, North Carolina) with 2 sided tests and a type I error of 5%. Results: Our study included 1319 NEWPT (964 pre-COVID and 355 COVID) and 2206 ACTIVE (1014 pre-COVID and 1192 COVID) patients. In the NEWPT cohort, we observed no differences between the pre-COVID and COVID periods in terms of baseline characteristics, including clinical features like stage, ECOG performance status, anemia or kidney function (Table A). Patients in the pre-COVID period were more likely to initiate any treatment (91.1% vs 86.2%, p In ACTIVE cohort, more patients in the pre-COVID period were anemic (Hemoglobin Conclusions: During early COVID-19 pandemic we did not observe evidence of delayed diagnosis or more advanced stage, anemia or kidney disease for NEWPT with MM. MM treatment patterns were notable for higher utilization of mAb, IMID-based therapies and decreased use of cyclophosphamide regimens, without significant change in time to treatment initiation. Reassuringly, changes in treatment-patterns during COVID pandemic were modest, some likely reflecting changes in MM treatment landscape (advances in mAb regimens) rather than direct impact of COVID. Further studies are needed to understand how these changes evolve and affect clinical outcomes over time beyond 2020. Figure 1 Figure 1. Disclosures Neparidze: GlaxoSmithKline: Research Funding; Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding. Zeidan: Jasper: Consultancy; AstraZeneca: Consultancy; Aprea: Consultancy, Research Funding; Gilead: Consultancy, Other: Clinical Trial Committees; Loxo Oncology: Consultancy, Other: Clinical Trial Committees; Astellas: Consultancy; Agios: Consultancy; Kura: Consultancy, Other: Clinical Trial Committees; Jazz: Consultancy; Pfizer: Other: Travel support, Research Funding; Genentech: Consultancy; Geron: Other: Clinical Trial Committees; BMS: Consultancy, Other: Clinical Trial Committees, Research Funding; ADC Therapeutics: Research Funding; Novartis: Consultancy, Other: Clinical Trial Committees, Travel support, Research Funding; Boehringer Ingelheim: Consultancy, Research Funding; Astex: Research Funding; BeyondSpring: Consultancy; Incyte: Consultancy, Research Funding; Daiichi Sankyo: Consultancy; Epizyme: Consultancy; BioCryst: Other: Clinical Trial Committees; Cardiff Oncology: Consultancy, Other: Travel support, Research Funding; Janssen: Consultancy; Ionis: Consultancy; Amgen: Consultancy, Research Funding; Acceleron: Consultancy, Research Funding; AbbVie: Consultancy, Other: Clinical Trial Committees, Research Funding. Podoltsev: Pfizer: Honoraria; PharmaEssentia: Honoraria; Blueprint Medicines: Honoraria; Incyte: Honoraria; Novartis: Honoraria; CTI BioPharma: Honoraria; Bristol-Myers Squib: Honoraria; Celgene: Honoraria. Shallis: Curis: Divested equity in a private or publicly-traded company in the past 24 months. Ma: Celgene/Bristol Myers Squibb: Consultancy, Research Funding. Davidoff: Amgen: Consultancy; AbbVie: Other: Family member consultancy. Huntington: AstraZeneca: Consultancy, Honoraria; TG Therapeutics: Research Funding; Thyme Inc: Consultancy; Flatiron Health Inc.: Consultancy; Genentech: Consultancy; SeaGen: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy, Honoraria; Servier: Consultancy; Bayer: Honoraria; DTRM Biopharm: Research Funding; AbbVie: Consultancy; Celgene: Consultancy, Research Funding.

Background/objectives: The COVID-19 pandemic led to a dramatic reduction of in-person medical care in the general population; however, impacts have not been well-characterized for patients with hematologic malignancies. This study assessed the impact of COVID-19 on healthcare delivery for patients with hematologic malignancies with documented active treatment. Methods: Patients from the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database with confirmed diagnosis of AML, DLBCL, FL, MCL, CLL or MM, and age ≥ 18 years at initial diagnosis were included. To be included in the study, documented receipt of at least one systemic, non-maintenance line of therapy between March 1, 2016 - February 28, 2021 was required. Patients were categorized into treatment types within lines of therapy: Oral therapy (OralTx); outpatient infusions (OutPtTx); and inpatient infusions, including hematopoietic transplants and CAR-T cell therapy (InPtTx). Monthly visit rates were calculated as the number of visits (telemedicine or in-person [in-clinic treatment administration, vitals, and/or labs]) per active patient per 30-day standardized month. Only visits occurring within a line of therapy were included (i.e. during active therapy, excluding surveillance). Telemedicine was only available for abstraction during the pandemic period. We used time-series forecasting methods on pre-pandemic monthly visit rate data (March 2016 - February 2020) to estimate projected counterfactual visit rates between March 2020 - February 2021 (expected in-person visit rates if the pandemic had not occurred) for all diseases combined, each disease, and each treatment type. Differences between projected and actual monthly visit rates during the pandemic period were considered statistically significant and related to the pandemic if the actual visit rate was outside of the 95% prediction interval (PI) surrounding the projected estimate. Results: A total of 22,559 patients were included in this analysis (6,241 OralTx, 14,501 OutPtTx, 7,675 InPtTx): 4,069 AML, 3,641 DLBCL, 2,004 FL, 1,899 MCL, 4,574 CLL and 6,701 MM. There was a gradual downward trend in in-person visit rates across all diseases over the study period (March 2016 - February 2021, Figure) and general visit frequencies were lower for OralTx and higher for OutPtTx and InPtTx overall. For all diseases combined, early pandemic months (March - May 2020) saw an 18% (95% PI 8.9% - 25%) reduction in in-person visit rates averaged across OralTx and OutPtTx, with the projected rate being 1.5 (95% PI 1.3 - 1.6) visits per patient per month, compared to an actual rate of 1.2. Reductions in the in-person visit rates were significant for all 3 treatment types for MM, for OralTx for CLL, and for OutPtTx for MCL and CLL. Telemedicine visit rates were greatest for patients who received OralTx, followed by OutPtTx, then InPtTx, with greater use in the early pandemic months and subsequent decrease in later months. All in-person visit rates increased close to predicted rates in the later half of the pandemic period. Conclusions: In treatment of hematologic malignancies, overall documented in-person visit rates for patients on OralTx and OutPtTx significantly decreased during early pandemic months, but returned close to the projected rates later in the pandemic. There were no significant reductions in the overall in-person visit rate for patients on InPtTx. Variability in these trends by disease type was observed, with significant reductions in in-person visits impacting MM, CLL, and MCL. Figure. Visit rates over time according to treatment category Figure 1 Figure 1. Disclosures Lau: Roche: Current equity holder in publicly-traded company; Flatiron Health Inc: Current Employment. Wang: Roche: Current equity holder in publicly-traded company; Flatiron Health: Current Employment. Davidoff: AbbVie: Other: Family member consultancy; Amgen: Consultancy. Huntington: Bayer: Honoraria; Thyme Inc: Consultancy; Novartis: Consultancy; Flatiron Health Inc.: Consultancy; Genentech: Consultancy; SeaGen: Consultancy; Servier: Consultancy; AstraZeneca: Consultancy, Honoraria; TG Therapeutics: Research Funding; DTRM Biopharm: Research Funding; AbbVie: Consultancy; Pharmacyclics: Consultancy, Honoraria; Celgene: Consultancy, Research Funding. Calip: Pfizer: Research Funding; Roche: Current equity holder in publicly-traded company; Flatiron Health Inc: Current Employment. Shah: AstraZeneca: Research Funding; Seattle Genetics: Research Funding; Epizyme: Research Funding. Stephens: CSL Behring: Consultancy; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Consultancy; Celgene: Consultancy; JUNO: Research Funding; Mingsight: Research Funding; Abbvie: Consultancy; Arqule: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; Epizyme: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; Innate Pharma: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding. Miksad: Flatiron Health Inc: Current Employment, Current holder of individual stocks in a privately-held company; Roche: Current equity holder in publicly-traded company. Parikh: GNS Healthcare: Current holder of individual stocks in a privately-held company; Onc.AI: Current holder of individual stocks in a privately-held company; Humana: Honoraria, Research Funding; Nanology: Honoraria; Thyme Care: Honoraria; Flatiron Health Inc: Honoraria. Takvorian: Pfizer: Research Funding; Genentech: Consultancy. Neparidze: GlaxoSmithKline: Research Funding; Janssen: Research Funding; Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees. Seymour: Flatiron Health Inc: Current Employment; Janssen: Membership on an entity's Board of Directors or advisory committees; Roche: Current equity holder in publicly-traded company; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees.

Background: The incidence of multiple myeloma (MM) and enrichment of cytogenetic abnormalities differ significantly between racial/ethnic groups in the US, and their significance in determining myeloma progression and survival is not well understood. Whole genome sequencing has identified unique mutational signatures in MM, including an age-related process common in hyperdiploid myeloma. Our purpose was to describe racial and age-related differences in the impact of high-risk cytogenetic abnormalities (HRCAs) on survival in MM. Methods: We conducted a retrospective cohort study of adult MM patients starting first-line therapy between January 2011 and May 2021 using the nationwide Flatiron Health electronic health record-derived de-identified database. Patient-level demographic and clinical characteristics were ascertained using structured and unstructured data, curated via technology-enabled abstraction. Patients who had documented fluorescence in situ hybridization testing within 30 days prior to or 90 days following the start of first-line treatment were included. HRCAs, including gain or amplification 1q21, deletion 17p, t(4;14), t(14;16) and t(14;20), were identified and categorized as 0, 1, or 2+ HRCAs. Our outcomes of interest were real world progression free survival (rwPFS) and overall survival (rwOS). Cox proportional hazards models were used to calculate adjusted hazard ratios (HR) and 95% confidence intervals (CI), adjusted for demographic and clinical characteristics and treatment including time-dependent receipt of autologous stem cell transplantation. Results: From a cohort of 4889 MM patients, there were 790 (16%) Black and 2995 (61%) White patients with median ages at diagnosis of 68 and 70 years, respectively. Compared to White patients, a higher proportion of Black patients had IgG M-protein (61% vs 55%) and a lower proportion had 1+ HRCAs identified (31% vs 34%). Among all racial groups, compared to patients aged Multivariable models showed evidence of significant statistical interaction between age and prevalence of HRCA for rwPFS (P-int: 0.02). Among White patients, having 2+ HRCAs ("double-hit MM") compared to no HRCAs was associated with worse rwPFS in both younger and older patients ( Similarly, we also found evidence of statistical interaction between age and prevalence of HRCA for rwOS (P-int: 0.02). Among White patients, double-hit MM was significantly associated with worse rwOS but the magnitude of increased risk differed for younger (HR 3.39, 95% CI 2.24-5.14, P Conclusions: In this cohort of newly diagnosed MM patients treated in routine practice, having double-hit MM was differentially predictive of poor survival across age groups. Double-hit MM was associated with worse rwPFS and rwOS among White patients, but these trends were less consistent among Black patients. Our current understanding of cytogenetic risk stratification of MM requires further study and additional data for identifying low- and high-risk subsets of patients across different ages and racial groups. Figure. Kaplan-Meier survivor functions for rwPFS in White (Panel A) and Black (Panel B) patients by age group and number of HRCAs Figure 1 Figure 1. Disclosures Calip: Flatiron Health: Current Employment; Roche: Current equity holder in publicly-traded company; Pfizer: Research Funding. Ascha: Flatiron Health: Current Employment; Roche: Current equity holder in publicly-traded company. Wang: Roche: Current equity holder in publicly-traded company; Flatiron Health: Current Employment. Pierre: Flatiron Health, Inc: Current Employment; Roche: Current holder of stock options in a privately-held company. Maignan: Flatiron Health: Current Employment; Roche: Current equity holder in publicly-traded company. Wadé: Roche: Current equity holder in publicly-traded company; Flatiron Health: Current Employment. Leng: Roche: Current equity holder in publicly-traded company; Flatiron Health: Current Employment. Seymour: Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Current equity holder in publicly-traded company; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Flatiron Health Inc: Current Employment. Patel: Janssen: Consultancy; Amgen: Consultancy; Celgene: Consultancy. Neparidze: Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Research Funding; Janssen: Research Funding.

Introduction: Monotherapy with hypomethylating agents (HMA) remains the standard of care for patients (pts) with myelodysplastic syndromes (MDS). Response in MDS is based on the modified International Working Group (IWG) 2006 criteria. Prior studies focusing on unselected MDS pts showed that achieving a complete remission (CR) was associated with favorable overall survival (OS). However, the association of other outcomes with OS was less clear and only 20% of HMA-treated MDS pts achieve a CR. For example, pts who achieved 11 g/dL). To avoid missing clinically meaningful benefits when studying new drugs in clinical trials, a clearly defined response criterion that is less stringent than CR but still captures clinically meaningful hematologic improvement (HI) is needed. Here we sought to evaluate the impact of current IWG 2006 response criteria as well as CRh on OS of pts with HR-MDS treated with frontline HMA monotherapy. Methods: We included all adult (≥18 years) MDS pts treated with frontline HMA (azacitidine [AZA], decitabine [DEC], or ASTX727) monotherapy between 1/1/2012 and 12/31/2020 at Yale University. We decided to use HMA monotherapy as it is the standard care for HR-MDS and to minimize the impact of therapy choice confounding the association of achieved response with OS. Pts were excluded if they received prior treatments for MDS aside from erythropoiesis-stimulating agents and if no baseline with at least one follow-up BM study were available for response assessment. We collected patient and disease characteristics (transfusion burden, IPSS/IPSS-R score, cytogenetics, molecular studies) at baseline. Best responses were assessed based on IWG 2006 criteria for MDS. We defined CRh as We performed Kaplan-Meier analysis to estimate the duration of overall survival and we used log rank test to test the difference in OS between subgroups of pts. Multiple comparisons were adjusted using the Bonferroni method. Results: A total of 100 pts was included in this analysis (Table 1). Median age was 68 years (yrs; range, 23 - 86), 60% were males, and 79% and 18% of pts received AZA and DEC, respectively. Median number of HMA cycles was 6 (interquartile range [IQR]: 4-10), and 33 pts (33%) underwent HCT. During follow-up, 46 pts (48%) progressed to AML. At a median follow-up of 1.5 yrs (IQR: 0.9 - 2.3 yrs), median OS for the entire pt cohort was 1.9 yrs (Figure 1). OS by response category is shown in Table 2. Median OS was not reached for patients who achieved a CR (95% CI: not reached [NR] - NR) as compared to 1.9 yrs (95% CI: 1.5 yrs - NR) and 2.0 yrs (95% CI: 1.2 yrs - NR) among pts with mCR + HI and mCR without HI, respectively. Median OS among patients with stable disease (SD) was similar (2.0 yrs [95% CI: 1.5 yrs - NR]). Finally, we explored the prognostic value of CRh and found a median OS of 1.9 yrs (95% CI: 1.5 yrs - NR), which appeared comparable to mCR +/- HI or SD. Similar results were found with censoring at time of HCT (Figure 2). Discussion: In this retrospective analysis of MDS pts treated with HMA monotherapy in the frontline setting, achieving CR as best response was associated with improved OS compared with mCR +/- HI and SD. However, as the numbers were small these results should be interpreted with caution, and other clinically relevant outcomes such as freedom of transfusion, infectious or bleeding complications, and patient-reported outcomes were not captured in the current analysis. Our results also apply only to MDS pts treated with HMA monotherapy in the frontline setting. The prognostic implications of CRh need to be evaluated in larger patient cohorts. To overcome these limitations, we are currently in the process of expanding the study to a much larger multi-center, international analysis. Figure 1 Figure 1. Disclosures Neparidze: Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Research Funding; Janssen: Research Funding. Shallis: Curis: Divested equity in a private or publicly-traded company in the past 24 months. Podoltsev: PharmaEssentia: Honoraria; Pfizer: Honoraria; CTI BioPharma: Honoraria; Blueprint Medicines: Honoraria; Incyte: Honoraria; Bristol-Myers Squib: Honoraria; Novartis: Honoraria; Celgene: Honoraria. Brunner: GSK: Research Funding; Aprea: Research Funding; Keros Therapeutics: Consultancy; Agios: Consultancy; AstraZeneca: Research Funding; Novartis: Consultancy, Research Funding; Acceleron: Consultancy; Takeda: Consultancy, Research Funding; BMS/Celgene: Consultancy, Research Funding; Janssen: Research Funding. Zeidan: AbbVie: Consultancy, Other: Clinical Trial Committees, Research Funding; Gilead: Consultancy, Other: Clinical Trial Committees; Epizyme: Consultancy; Amgen: Consultancy, Research Funding; BioCryst: Other: Clinical Trial Committees; Incyte: Consultancy, Research Funding; Boehringer Ingelheim: Consultancy, Research Funding; Cardiff Oncology: Consultancy, Other: Travel support, Research Funding; Acceleron: Consultancy, Research Funding; Agios: Consultancy; Novartis: Consultancy, Other: Clinical Trial Committees, Travel support, Research Funding; Genentech: Consultancy; Jasper: Consultancy; ADC Therapeutics: Research Funding; Jazz: Consultancy; Astex: Research Funding; Daiichi Sankyo: Consultancy; Kura: Consultancy, Other: Clinical Trial Committees; Aprea: Consultancy, Research Funding; BMS: Consultancy, Other: Clinical Trial Committees, Research Funding; Geron: Other: Clinical Trial Committees; AstraZeneca: Consultancy; Pfizer: Other: Travel support, Research Funding; BeyondSpring: Consultancy; Ionis: Consultancy; Loxo Oncology: Consultancy, Other: Clinical Trial Committees; Janssen: Consultancy; Astellas: Consultancy.

Introduction: Iron deficiency is the most frequent cause of anemia, which afflicts 32.9% of the global population and is a significant cause of morbidity worldwide. Oral iron is the first-line therapy for treating iron deficiency anemia; intravenous(IV) iron is used when oral iron is inappropriate, poorly tolerated or ineffective. The major adverse effect associated with IV iron is infusion-related reactions (IRR), ranging from mild reactions mediated by complement activation-related pseudo-allergy to anaphylaxis. In this study, we sought to determine rates and severity of iron IRR, identify patient characteristics associated with IRR and report strategies for subsequent iron repletion in patients who have IRR. Methods: We conducted a retrospective chart review of all patients older than 18 years who received IV iron from 1/1/2016 to 7/20/2021 in the outpatient Classical Hematology clinic at Yale New Haven Hospital. Demographics, risk factors, details of reactions and follow up were noted. The primary outcomes analyzed included rates and severity of IRR based on nursing and provider documentation and graded according to a previously-published IRR severity classification (Rampton D et al, Haematologica 2014;99:1671). Secondary outcomes included identification of patient characteristics associated with IRR utilizing Chi-square or Fisher's exact test for unadjusted analysis and logistic regression for multivariable analysis (IBM SPSS version 28). Results: A total of 330 patients, including 298 females, received IV iron. The common formulations used were ferumoxytol, iron sucrose and iron dextran with 199 (60.3%), 49(14.8%), and 36 (10.9%) patients, respectively, receiving each of these. Comorbid conditions were present in 317 (96.1%) patients, including 114 (34.5%) with cardiovascular disease (CVS) and 71 (21.5%) with asthma. Beta blocker or angiotensin-converting enzyme inhibitor (ACEI) use was noted in 90 (27.3%) patients. A history of allergies to medications was present in 167 (50.6%) patients while 139 (42.1%) had other non-drug allergies. The common indications for infusion were anemia due to heavy menstrual bleeding (27.6%), gastrointestinal bleeding (17.2%) and pregnancy (6.9%). Iron IRR was noted in 58 (17.6%) patients, of whom 36 (62.1%) had previously tolerated IV iron. Of the 58 patients with IRR, the median age was 40.32 ± 14.6 years; 30 (51.7%) had allergies to medications, 34 (58.6%) had non-drug allergies, and 13 (22.4%) each had a history of CVS or asthma. Beta blocker or ACEI use was found in 12 (20.7%) patients. The reaction manifestations included gastrointestinal in 16 (27.6%) patients, cardiovascular in 24 (41.4%), bronchopulmonary in 34(58.6%), mucocutaneous in 28(48.3%), neurological in 21(36.2%) and autonomic in 30 (51.7%). The severity of reaction was mild in 22 (37.9%) patients, moderate in 23 (39.7%), and severe in 11 (19%). After a reaction, 28 (48.3%) patients subsequently tolerated a different formulation of IV iron, while 14 (24.1%) patients tolerated the same formulation of IV iron at a slower rate with premedication; 5 (8.6%) patients had a subsequent reaction to a different IV iron formulation. Multivariable regression analysis was performed to examine associations of iron IRR with history of allergies to medications, non-drug allergies, asthma, CVS, use of beta blockers or ACEI and sex. In this analysis, a history of non-drug allergies was significantly and independently associated with greater odds of IRR (odds ratio (OR) 2.40, 95% confidence interval (CI): 1.32-4.37, p=0.004) while a history of CVS was associated with lower odds of IRR (OR 0.46, 95% CI: 0.22-0.988, p=0.047). None of the parameters were found to have an association with the severity of IRR. Conclusion: Iron IRR occurred in 17.6% of patients receiving IV iron, with severe reactions occurring in 3.3% of all patients; these rates are higher than those previously reported in literature. A history of non-drug allergies is independently associated with greater odds of IRR, and additional precautions may be indicated to prevent IRR in such patients. An association of CVS with lower odds of reaction may reflect anti-inflammatory effects of widespread aspirin use in these patients. The majority of patients with iron IRR can subsequently tolerate the same or a different formulation of IV iron with slower rates of infusion and premedication. Figure 1 Figure 1. Disclosures Neparidze: Janssen: Research Funding; GlaxoSmithKline: Research Funding; Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees.

Introduction: Skeletal-related events (SREs) can cause significant morbidity and adversely impact quality of life in patients with multiple myeloma (MM). The bisphosphonate zoledronic acid (ZOL) has historically been the most widely used agent to prevent and treat SREs in this population. In 2018, a landmark trial by Raje et al showed that denosumab (DEN), a monoclonal antibody against the receptor activator of nuclear factor-kappa B ligand (RANKL), was non-inferior to ZOL in time to SREs. The use of DEN has since been incorporated into official guidelines and there has been a significant uptake of DEN use in clinical practice, with some patients being switched from ZOL to DEN. Currently, there is a lack of data on the clinical and biological impact of the use of DEN following prior exposure to ZOL in patients with MM. Some have suggested that the use of DEN in patients extensively treated with ZOL may over-suppress bone turnover and recommend the use of bone resorption markers such as C-terminal telopeptide (CTX) to guide this treatment decision. In this observational study, we describe the reasons for the switch in use of these bone-modifying agents (BMAs) and evaluate the incidence of SREs in a selected population of MM patients who received both agents during their course of treatment. Methods: This retrospective study included all MM patients that were treated at Yale Cancer Center including Smilow Cancer Hospital and Smilow Care Centers between January 1, 2015 and August 1, 2019. Patient demographics, date of diagnosis, location of main treatment center, and dates and doses of receipt of all BMAs, including ZOL and DEN, were extracted from the electronic medical record. For patients who were switched from one class of BMA to another, we used manual chart review to extract the switch date, reason for switch, estimated glomerular filtration rate (eGFR), and dates and types of all SREs sustained thereafter. Results: We identified 658 patients who received BMAs for MM during the study period. Among these, 499 (75.8%) received ZOL only, 91 (13.8%) received DEN only, and 68 (10.3%) received ZOL and DEN during their treatment course. Of this last group, 63 were switched from ZOL to DEN. The most common reasons for switching from ZOL to DEN were as follows: change in eGFR (57.1%), physician preference (19%), ZOL intolerance (12.7%), and recalcitrant hypercalcemia (11.1%). Among patients switched due to change in eGFR, the median eGFR at time of switch was 34 mL/min/1.73m2 (range, 4->60). For switches made due to physician preference only, the date of switch was a median of 6 months (range, 2-16) following the FDA approval of DEN for MM indication in 2018. The median number of doses of ZOL (either 4mg, 3.5mg, 3.3mg, or 3mg) received before switch was 11 (IQR, 3.5-18) and the median number of doses of DEN (120mg) received after switch was 5 (2.5-9). Among patients who were switched from ZOL to DEN, 24/63 (38%) developed a new fracture at some time during treatment with either therapy, whereas 5/63 (7.9%) developed a new fracture after the switch to DEN. Time from ZOL initiation to new fracture was 16 months (range, 1-73) for any fracture and 38 months (range, 2-62) for long bone fractures. The median time to a new fracture after switch from ZOL to DEN was 5 months (range, 1-11). None of the patients who were switched from ZOL to DEN due to hypercalcemia developed new fractures during the study period. Out of all patients who received BMAs, 32/658 (4.9%) underwent serum CTX level testing to guide use of therapy. Conclusions: After the approval of DEN for MM as an alternative to ZOL, we observed that the most common reasons for switch of ZOL to DEN at our cancer center were due to changes in patient renal function or for bisphosphonate intolerance. The use of serum CTX to guide switch in therapy was uncommon in clinical practice and should be encouraged more. In a selected cohort of patients who were switched from ZOL to DEN, the time to new SRE was shorter than historically reported with DEN only. These data highlight the need for prospective studies on the efficacy of DEN in MM patients who have previously been exposed to ZOL. Figure 1 Figure 1. Disclosures Neparidze: Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Research Funding; Janssen: Research Funding.

Background/objectives: The COVID-19 pandemic impacted healthcare visit trends, propelling healthcare systems to reduce in-person visits and hospital admissions and increasingly rely on telemedicine; whether there are differences in these trends across racial groups is unknown. This study investigated potential racial disparities in visits during the pandemic for patients with documented active treatment for hematologic malignancies. Methods: We used the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database to select patients with confirmed diagnosis of AML, DLBCL, FL, MCL, CLL or MM, at least 18 years old at initial diagnosis, and documented race in the EHR as Black/African American or White were included. Patients were categorized into treatment types within lines of therapy: Orals (orals + outpatient infusions with orals) vs. Inpatient treatments (chemotherapy, hematopoietic transplants & CAR-T cell therapy). Monthly visit rates were calculated as the number of visits (telemedicine or in-person [in-clinic treatment administration, vitals, and/or labs]) per active patient per 30-day standardized month, except for months in which the patient was considered not active (e.g. no documented therapy, surveillance). We used time-series forecasting methods on pre-pandemic monthly visit rate data (March 2016 - February 2020) to estimate projected counterfactual monthly visit rates (expected rates if the pandemic did not occur) between March 2020 - February 2021 for all diseases combined, for each disease, each treatment type, and each race. Differences between projected and actual monthly visit rates during the pandemic period were considered significant and related due to the pandemic if the actual visit rate was outside of the 95% prediction interval (PI) surrounding the projected estimate. We used cross-correlation analysis to test for significant differences in visit rates between Black and White patients. Results: The analysis included 17,621 patients (2,225 Black, 15,396 White): 3,041 AML, 2,715 DLBCL, 1,558 FL, 1,511 MCL, 3,813 CLL and 5,244 MM (1,166 Black, 4078 White). Across all diseases and treatment categories, Black patients had no significant reductions in in-person visit rates throughout the pandemic period compared to the projected rates. There was, however, an 18% statistically significant reduction (95% PI 9.9% - 25%) in in-person visit rates for White patients on orals during early pandemic months (March - May 2020) from a projected visit rate of 2.0 (95% PI 1.8 - 2.2) visits per patient per month to an actual visit rate of 1.61. There was no significant reduction in in-person visit rates for White patients on inpatient treatments. Telemedicine uptake was significantly higher for White patients compared with Black patients for all diseases combined across all treatment categories (Figure A & B) (t = 9.5, p < 0.01), AML inpatient treatments (t = 2.4, p = 0.04), MM orals (Figure C) (t = 6.0, p < 0.01) and MM inpatient treatments (Figure D) (t = 2.3, p = 0.04). Conclusions: A tradeoff in reductions in in-person visits and uptake of telemedicine use was observed overall. White patients had significantly higher telemedicine uptake compared with Black patients for both oral and inpatient treatments. In-person visit rates for Black patients were unchanged regardless of treatment category. These in-person visit rates reflect documented telemedicine use disparities, which requires further study into possible compound causes, including economic and societal factors. Figure. Trends over time in telemedicine visit rates for White patients (blue line) and Black patients (black line) Figure 1 Figure 1. Disclosures Neparidze: Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Research Funding; Janssen: Research Funding. Lau: Flatiron Health Inc: Current Employment; Roche: Current equity holder in publicly-traded company. Wang: Flatiron Health: Current Employment; Roche: Current equity holder in publicly-traded company. Davidoff: Amgen: Consultancy; AbbVie: Other: Family member consultancy. Huntington: Bayer: Honoraria; Servier: Consultancy; Pharmacyclics: Consultancy, Honoraria; Thyme Inc: Consultancy; Genentech: Consultancy; AbbVie: Consultancy; SeaGen: Consultancy; Celgene: Consultancy, Research Funding; Flatiron Health Inc.: Consultancy; DTRM Biopharm: Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Consultancy, Honoraria; Novartis: Consultancy. Calip: Flatiron Health Inc: Current Employment; Roche: Current equity holder in publicly-traded company; Pfizer: Research Funding. Shah: AstraZeneca: Research Funding; Seattle Genetics: Research Funding; Epizyme: Research Funding. Stephens: Adaptive: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Abbvie: Consultancy; CSL Behring: Consultancy; Novartis: Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding; JUNO: Research Funding; Mingsight: Research Funding; AstraZeneca: Consultancy; Innate Pharma: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; Epizyme: Membership on an entity's Board of Directors or advisory committees; Arqule: Research Funding. Miksad: Flatiron Health Inc: Current Employment, Current holder of individual stocks in a privately-held company; Roche: Current equity holder in publicly-traded company. Parikh: Onc.AI: Current holder of individual stocks in a privately-held company; Humana: Honoraria, Research Funding; Flatiron Health Inc: Honoraria; Thyme Care: Honoraria; Nanology: Honoraria; GNS Healthcare: Current holder of individual stocks in a privately-held company. Takvorian: Genentech: Consultancy; Pfizer: Research Funding. Seymour: Janssen: Membership on an entity's Board of Directors or advisory committees; Roche: Current equity holder in publicly-traded company; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Flatiron Health Inc: Current Employment; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Introduction: Patients (pts) with chronic-phase chronic myeloid leukemia (CML) are recommended to have quantitative BCR-ABL1 polymerase chain reaction (qPCR) testing every 3 months (mo) during the 1 st year of tyrosine kinase inhibitor (TKI) treatment to assure achievement of milestone response goals. Adherence to TKI therapy is also critical to achieving responses and ultimately functional cure. Prior evaluations of qPCR testing/TKI adherence have only focused on imatinib-treated and/or younger pts. We sought to evaluate older CML pts in the United States using the Surveillance, Epidemiology, and End Results (SEER)-Medicare dataset. Methods: Using the SEER-Medicare database, we assembled a population-based cohort of CML pts diagnosed in 2007-17 who: 1) were age 66-99 years at diagnosis, 2) had continuous Medicare Parts A/B coverage from 1 year before diagnosis to end of follow-up, 3) Medicare Part D coverage from 3 mo before diagnosis to end of follow-up, 4) did not receive a TKI within 3 mo before diagnosis, and 5) received a TKI after diagnosis. To ensure adequate time to assess 1 st-year adherence/monitoring, we only included pts followed for ≥13 mo from TKI initiation. As suggested by guidelines, we assessed qPCR tests at 3, 6, 9, an 12 mo (all ±30 days) after TKI initiation. Optimal monitoring was defined as having a qPCR test at ≥3 milestones during the 1 st year of treatment. First-year TKI adherence was measured by the proportion of days covered (PDC); adherence was defined as a PDC >80%. Pearson's χ 2 tests and Wilcoxon rank tests were used to compare patient characteristics in a bivariate manner, and multivariable logistic regression was used to assess factors associated with optimal monitoring and its impact on TKI adherence. All statistical tests were two-sided and conducted with SAS (Version 9.4). Results: We identified 1188 newly-diagnosed CML pts with a median age at diagnosis of 74.5 (interquartile range [IQR]: 70-80) years. Median time from diagnosis to TKI initiation was 42 (IQR: 27-72) days with 970 pts (81.7%) initiating TKI within 90 days of diagnosis. Of 745 pts starting frontline imatinib, 17.9% switched to a 2 nd generation TKI; of 443 pts starting a frontline 2 nd generation TKI, 127 (30.9%) received a subsequent TKI with 89 (70.0%) switching to imatinib. In the 1 st year after TKI initiation, 962 pts (81.0%) had a qPCR test with a median of 3 (IQR: 2-4) tests. Among pts who had ≥2 tests, the median days between two consecutive tests was 89 (IQR: 63-105). Only 876 pts (73.7%) had at least one test around the 4 milestones with 329 (27.7%) and 547 (46.0%) of pts had tests at ≥3 and 1-2 milestones, respectively. The most recently diagnosed pts were more likely to receive a test at a milestone (Figure 1a), but even among pts diagnosed in the latest study period of 2015-17, only 126 (32.0%) had optimal monitoring. Compared with less frequently monitored pts, those with optimal monitoring were more likely to be non-Hispanic white (p=0.01), diagnosed in more recent years (p The median 1 st-year PDC was 90.3% (IQR: 70.6-98.3%) with 795 (66.9%) adherent pts. The median PDC among pts with qPCR tests at 0, 1-2 and ≥3 milestones was 86.4%, 90.1% and 93.1%, respectively (p Conclusions: We describe "real world" CML management patterns of 1 st-year molecular testing and TKI adherence using a large dataset. Our analyses showed that many older pts do not have recommended molecular monitoring, which was associated with decreased TKI adherence. This work was supported by the Frederick A. DeLuca Foundation. Figure 1 Figure 1. Disclosures Shallis: Curis: Divested equity in a private or publicly-traded company in the past 24 months. Zeidan: Novartis: Consultancy, Other: Clinical Trial Committees, Travel support, Research Funding; Agios: Consultancy; Astex: Research Funding; Pfizer: Other: Travel support, Research Funding; Jazz: Consultancy; Geron: Other: Clinical Trial Committees; Kura: Consultancy, Other: Clinical Trial Committees; AstraZeneca: Consultancy; BeyondSpring: Consultancy; Gilead: Consultancy, Other: Clinical Trial Committees; Aprea: Consultancy, Research Funding; ADC Therapeutics: Research Funding; Amgen: Consultancy, Research Funding; Ionis: Consultancy; Astellas: Consultancy; Acceleron: Consultancy, Research Funding; Boehringer Ingelheim: Consultancy, Research Funding; Incyte: Consultancy, Research Funding; Cardiff Oncology: Consultancy, Other: Travel support, Research Funding; Genentech: Consultancy; BioCryst: Other: Clinical Trial Committees; Loxo Oncology: Consultancy, Other: Clinical Trial Committees; Daiichi Sankyo: Consultancy; Epizyme: Consultancy; Janssen: Consultancy; BMS: Consultancy, Other: Clinical Trial Committees, Research Funding; Jasper: Consultancy; AbbVie: Consultancy, Other: Clinical Trial Committees, Research Funding. Huntington: Thyme Inc: Consultancy; Bayer: Honoraria; AstraZeneca: Consultancy, Honoraria; TG Therapeutics: Research Funding; DTRM Biopharm: Research Funding; SeaGen: Consultancy; Genentech: Consultancy; Flatiron Health Inc.: Consultancy; Novartis: Consultancy; Servier: Consultancy; AbbVie: Consultancy; Pharmacyclics: Consultancy, Honoraria; Celgene: Consultancy, Research Funding. Neparidze: Janssen: Research Funding; GlaxoSmithKline: Research Funding; Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees. Ma: Celgene/Bristol Myers Squibb: Consultancy, Research Funding. Podoltsev: Pfizer: Honoraria; Blueprint Medicines: Honoraria; Novartis: Honoraria; Incyte: Honoraria; PharmaEssentia: Honoraria; CTI BioPharma: Honoraria; Bristol-Myers Squib: Honoraria; Celgene: Honoraria.

Background: Despite a potential for cure, a large proportion of patients with acute promyelocytic leukemia (APL) succumb early to hemorrhagic and thrombotic complications. Prompt initiation of all-trans retinoic acid (ATRA) has been associated with improved outcomes. However, little is known about the patterns of care and clinical outcomes of patients with APL in the United States (US) outside of the controlled trial setting. Method s : We identified APL patients (pts) included in the Vizient Clinical Database/Resource Manager (CDB/RM™), which includes patient demographics, hospital characteristics, charge-level medication usage, procedures and mortality data from over 100 academic health centers and affiliated hospitals. Initial inpatient encounters of adult APL pts (≥18 years) during 2014-2015 (most recent years available) were identified by ICD-10 code (C92.40; C92.42) or ICD-9 codes for acute myeloid leukemia (AML; 250.00, 205.02) plus receipt of ATRA for ≥3 days as monotherapy, or in combination with arsenic trioxide (ATO) or an anthracycline. The 3-day minimum ATRA requirement is intended to exclude AML patients who may have therapy initiated while awaiting diagnostic confirmation. Pts were excluded if information on discharge disposition or medication administration were missing or if patients had an ICD-9/10 code consistent with relapsed AML/APL. Primary outcome was a composite of in-hospital death or discharge to hospice. Pearson's Chi-square test was used to compare categorical variables in bivariate analysis. Multivariable logistic regression was used to examine associations between patient, hospital, and treatment characteristics with the primary outcome. We lacked information on laboratory test results needed to assess the impact of treatment on clinical outcomes. Results: We identified 486 pts treated at 76 hospitals. Patient demographic, treatment and hospital characteristics are shown in Table 1. Median length of stay was 30 days (interquartile range [IQR]: 22-36 days). Pts received a median of 26 days of ATRA (IQR: 12-34 days). The majority of pts was treated with ATRA + ATO (240 pts; 49.4%) or ATRA + anthracycline (146 pts; 30.0%), which are the standard of care for lower- and higher-risk APL, respectively. Forty-two pts (9.3%) received ATRA monotherapy and 58 (11.9%) were treated with ATRA + ATO + anthracycline. Forty-eight pts (9.9%) required endotracheal intubation. Overall, 54 (11.1%) pts experienced our composite adverse outcome of in-hospital death or transfer to hospice (45 pts [9.3%] died in the hospital; 9 pts [1.9%] were discharged to hospice). Among 45 pts who died in the hospital, median time to death was 17 days (IQR: 5-24 days) with 31.1% of deaths occurring during the first 7 days of hospitalization. Half of the pts (n=18; 50%) who died in the ATRA monotherapy group died within 5 days of admission. In bivariate analyses, age ≥66 years (22.9% vs. 7.9%; p Discussion: A substantial proportion (11%) of adults treated for APL in this large inpatient dataset died or were discharged to hospice. This likely underestimates the full mortality rate of APL, because our APL case definition excluded pts who received Disclosures Wang: Celgene/BMS: Research Funding. Podoltsev:Kartos Therapeutics: Research Funding; Jazz Pharmaceuticals: Research Funding; Incyte: Consultancy, Honoraria; Sunesis Pharmaceuticals: Research Funding; Samus Therapeutics: Research Funding; Genentech: Research Funding; AI Therapeutics: Research Funding; Boehringer Ingelheim: Research Funding; CTI biopharma: Consultancy, Honoraria, Research Funding; Daiichi Sankyo: Research Funding; Bristol-Myers Squib: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Arog Pharmaceuticals: Research Funding; Blueprint Medicines: Consultancy, Honoraria; Alexion: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria, Research Funding; Agios Pharmaceuticals: Consultancy, Honoraria; Astex Pharmaceuticals: Research Funding; Astellas Pharma: Research Funding. Huntington:Genentech: Consultancy; DTRM: Research Funding; Astrazeneca: Honoraria; Bayer: Consultancy, Honoraria; Celgene: Consultancy, Research Funding; Novartis: Consultancy; AbbVie: Consultancy; Pharmacyclics: Honoraria; TG Therapeutics: Research Funding. Neparidze:Janssen: Research Funding; GlaxoSmithKline: Research Funding; Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other: Diagnostic committee member ; Sanofi: Membership on an entity's Board of Directors or advisory committees, Other: Advisory board. Ma:BMS: Consultancy; Celgene/BMS: Research Funding. Gore:Abbvie: Consultancy, Honoraria, Research Funding. Zeidan:Acceleron: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria; Cardinal Health: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Celgene / BMS: Consultancy, Honoraria, Research Funding; Cardiff Oncology: Consultancy, Honoraria, Other; Takeda: Consultancy, Honoraria, Research Funding; Ionis: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria, Research Funding; CCITLA: Other; Leukemia and Lymphoma Society: Other; Seattle Genetics: Consultancy, Honoraria; BeyondSpring: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Epizyme: Consultancy, Honoraria; Astex: Research Funding; MedImmune/Astrazeneca: Research Funding; Incyte: Consultancy, Honoraria, Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Research Funding; Agios: Consultancy, Honoraria; ADC Therapeutics: Research Funding; Taiho: Consultancy, Honoraria; Aprea: Research Funding; Trovagene: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria, Research Funding; Otsuka: Consultancy, Honoraria; Jazz: Consultancy, Honoraria. Davidoff:Celgene: Research Funding; Amgen: Consultancy; AbbVie: Consultancy.

Background: Cancer care delivered in an academic setting or by providers with higher volume has been associated with improved overall survival (OS) in selected surgical and medical scenarios, including the care of patients with multiple myeloma (MM). Most studies have limited their focus to OS, and have used a simple count of similar patients as a proxy measure for disease-specific expertise. Few studies have assessed whether treatment by an oncologist that specializes in a specific patient's cancer results in better quality care and outcomes. This latter focus may be particularly important for MM management, for which the approval of newer immunomodulatory drugs (IMiDs) and proteasome inhibitors (PIs), coupled with 1st-line PI-IMiD combinations, stem cell transplant (SCT) & maintenance therapy (MT) among fit patients, have expanded options, complexity and therapy lines. In this study, we constructed a measure reflecting oncologist sub-specialization in treatment of hematologic malignancies and examined associations between that dimension, academic care setting, and various aspects of active MM therapy as well as OS. Methods: We selected adults with a MM diagnosis between 07/07-12/15 from the SEER-Medicare linked database. We required continuous Medicare Parts A and B enrollment and no HMO/PPO coverage from 12 months prior to diagnosis (1 month prior for Part D) through death or end of study (12/16) and MM therapy initiation w/in 12 months post diagnosis. Outcomes including 1st treatment line PI-IMiD combination, SCT, MT, and 2nd, 3rd, and 4th treatment lines were constructed by applying a complex algorithm to claims-based indicators for oral and IV drugs and receipt dates. Provider setting was assigned as academic and/or NCI designated cancer center (NCI-CC), other hospital (other teaching or non-teaching), or community (non-hospital), based on claims from the most recent hematologist or oncologist evaluation and management visit prior to 1st line initiation. The percentage of each oncologist's patient panel diagnosed with a hematologic malignancy (HEME%) was calculated for each 3-year period, using a pooled sample of 11 major cancer sites (reported in SEER-Medicare) for the denominator; HEME% was linked back to each patient based on the oncologist of record at the visit prior to 1st line initiation. Bivariate analyses and multivariable regressions tested for associations with treatment (logistic regression) and OS (Cox proportional hazards models). Regressions controlled for demographics, health status, and diagnosis year. Results: The cohort (n=4932) was 14% Black, and 51% age ≥75 years [Table 1]. Care setting was 14.5% academic/NCI-CC, 22.4% other hospital, and 63.0% community; community setting decreased from 72.4 to 57.8% during the observation period (2007 to 2015). Mean HEME% (31% overall) was higher for academic/NCI-CC (51%), where there was a bimodal distribution with peaks at 25% and 85-90% (Figure 1). Mean HEME% was 27% at both other hospital and community practices, with a peak at 25%. 1st treatment line PI-IMiD combinations, MT after PI-IMiD, and SCT were received by 21%, 53%, and 4%, respectively. 2nd, 3rd, and 4th treatment lines were received by 55%, 31% and 18% respectively. After adjustment, higher HEME% was associated with increased likelihood of receiving a PI-IMiD combination and SCT during 1st line, receiving 3rd line (all at p Conclusion: Using a novel measure of oncologist sub-specialization in hematologic malignancies, we found strong positive associations with receipt of 1st line PI-IMiD combination therapy and ongoing treatment lines in a Medicare insured population with MM. In contrast to HEME%, care setting was less likely to be associated with treatment in our multivariable models. The bimodal distribution of HEME% within academic centers is consistent with academic acquisition of community oncology practices. Future research should consider the role of oncologist sub-specialization in other cancers and with additional outcomes, including patient care experience and cost of care. Disclosures Davidoff: Amgen: Consultancy; AbbVie: Consultancy; Celgene: Research Funding. Neparidze:Janssen: Research Funding; Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other: Diagnostic committee member ; Sanofi: Membership on an entity's Board of Directors or advisory committees, Other: Advisory board; GlaxoSmithKline: Research Funding. Podoltsev:Jazz Pharmaceuticals: Research Funding; Sunesis Pharmaceuticals: Research Funding; Astex Pharmaceuticals: Research Funding; Samus Therapeutics: Research Funding; AI Therapeutics: Research Funding; Genentech: Research Funding; Arog Pharmaceuticals: Research Funding; Kartos Therapeutics: Research Funding; Incyte: Consultancy, Honoraria; Blueprint Medicines: Consultancy, Honoraria; Agios Pharmaceuticals: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria, Research Funding; Alexion: Consultancy, Honoraria; Daiichi Sankyo: Research Funding; Astellas Pharma: Research Funding; Boehringer Ingelheim: Research Funding; CTI biopharma: Consultancy, Honoraria, Research Funding; Bristol-Myers Squib: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria. Wang:Celgene/BMS: Research Funding. Gore:Abbvie: Consultancy, Honoraria, Research Funding. Zeidan:Boehringer-Ingelheim: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Acceleron: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria; Cardinal Health: Consultancy, Honoraria; Taiho: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; BeyondSpring: Consultancy, Honoraria; Cardiff Oncology: Consultancy, Honoraria, Other; Takeda: Consultancy, Honoraria, Research Funding; Ionis: Consultancy, Honoraria; Epizyme: Consultancy, Honoraria; Leukemia and Lymphoma Society: Other; CCITLA: Other; Astex: Research Funding; MedImmune/Astrazeneca: Research Funding; Trovagene: Consultancy, Honoraria, Research Funding; Aprea: Research Funding; Agios: Consultancy, Honoraria; ADC Therapeutics: Research Funding; Incyte: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; Celgene / BMS: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Otsuka: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Research Funding. Huntington:DTRM: Research Funding; Novartis: Consultancy; AbbVie: Consultancy; Astrazeneca: Honoraria; Bayer: Consultancy, Honoraria; Celgene: Consultancy, Research Funding; Genentech: Consultancy; Pharmacyclics: Honoraria; TG Therapeutics: Research Funding.

Background: Isatuximab (SAR650984) is an IgG1k monoclonal antibody that binds with high affinity to CD38 expressed on plasma cells in AL amyloidosis. It has been shown to be efficacious and well tolerated in relapsed and refractory multiple myeloma as a single agent and in combination. Here we report on the preliminary results of a prospective multi-center, phase II study of isatuximab in previously treated patients with AL amyloidosis (NCT03499808). Methods: Eligibility included age ≥ 18 years, relapsed or refractory systemic AL amyloidosis, ≥ 1 prior line of therapy, measurable disease (defined as a positive monoclonal serum immunofixation electrophoresis (IFE) or urine IFE, a serum free light chain ratio outside of the normal range (0.25-1.65), and a difference in the involved versus the uninvolved serum free light chain of ≥ 4.5 mg/dL), at least one organ involved, not refractory to daratumumab, ECOG performance status 0-2, creatinine clearance ≥25 mL/min as measured by 24-hour urine collection or as estimated by Cockcroft and Gault formula, and NT-proBNP ≤8500 pg/mL. Patients received isatuximab intravenously 20 mg/kg weekly during the first 28 day cycle and every other week during cycles 2 through 24 for a maximum of 24 cycles. The primary objective was hematologic response with secondary objectives of organ response, safety, progression free survival, and overall survival. Results: At data cut-off (July 24, 2020), 43 patients were registered from March 2018 to September 2019 at 14 institutions. Thirty six patients were eligible with 35 patients receiving at least one dose of isatuximab. Of the eligible patients, the median age was 70 (range 40-81). Prior therapies included proteasome inhibitors in 32 patients (89%), high dose therapy followed by autologous stem cell transplant in 17 patients (47%), immunomodulatory therapy in 9 patients (25%), and anti-CD38 monoclonal antibody therapy in 2 patients (6%). Single organ system involvement was seen in 19 patients (53%), ≥ 2 organ systems in 17 patients (47%), 16 patients (44%) had renal involvement, and 24 (67%) had cardiac involvement. For those with cardiac involvement, 7 patients (29%) had cardiac biomarker stage II and 9 patients (38%) had stage III disease using the Revised Mayo Staging (Kumar S et al., J Clin Oncol, 2012). A total of 17 patients remain on therapy. The median duration on treatment for eligible patients is currently 11.8 months (current range, 0.3-22.1). Of the 19 patients who discontinued treatment, the most common reasons included adverse events in 5 patients (26%), disease progression in 4 patients (21%), sub-optimal response in 2 patients (11%), and concerns related to COVID-19 in 2 patients (11%). The current median follow up is 16.3 months. The most common drug-related AEs were infusion related reactions in 18 patients (50%) with the majority (16/18) being grade I or II, anemia in 9 patients (25%) with the majority (8/9) being grade I, and lymphopenia in 8 patients (22%). Patient characteristics and preliminary safety data were previously presented at the International Symposium on Amyloidosis. The overall hematologic response rate was 77%. Hematological complete response (CR) was observed in 1 of 35 evaluable (completing at least 1 dose) patients (3%), very-good-partial response (VGPR) in 19 patients (54%), and partial response (PR) in 7 patients (20%). Conclusions: Isatuximab demonstrates encouraging efficacy in previously treated patients with AL amyloidosis. The administration of isatuximab in these patients is associated with a good safety profile similar to other monoclonal antibodies against CD38. The data will be updated at the meeting. Disclosures Sanchorawala: Prothena: Research Funding; Caelum: Research Funding; Oncopeptide: Research Funding; Janssen: Research Funding; Regeneron: Other: advisory board; Caleum: Other: advisory board; Proclara: Other: advisory board; Abbvie: Other: advisory board; UpToDate: Patents & Royalties; Takeda: Research Funding; Celgene: Research Funding. Kapoor:Sanofi: Consultancy, Research Funding; Celgene: Honoraria; Cellectar: Consultancy; Janssen: Research Funding; Amgen: Research Funding; GlaxoSmithKline: Research Funding; Takeda: Honoraria, Research Funding. Neparidze:GlaxoSmithKline: Research Funding; Janssen: Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees, Other: Advisory board; Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other: Diagnostic committee member . Sarosiek:Spectrum: Research Funding. Durie:Amgen, Celgene, Johnson & Johnson, and Takeda: Consultancy. Usmani:Incyte: Research Funding; Takeda: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Sanofi: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; SkylineDX: Consultancy, Research Funding; Merck: Consultancy, Research Funding; Array Biopharma: Research Funding; Pharmacyclics: Research Funding; Celgene: Other; Seattle Genetics: Consultancy, Research Funding; GSK: Consultancy, Research Funding; BMS, Celgene: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Amgen: Consultancy, Honoraria, Other: Speaking Fees, Research Funding; Abbvie: Consultancy. Orlowski:Laboratory research funding from BioTheryX, and clinical research funding from CARsgen Therapeutics, Celgene, Exelixis, Janssen Biotech, Sanofi-Aventis, Takeda Pharmaceuticals North America, Inc.: Research Funding; STATinMED Research: Consultancy; Founder of Asylia Therapeutics, Inc., with associated patents and an equity interest, though this technology does not bear on the current submission.: Current equity holder in private company, Patents & Royalties; Sanofi-Aventis, Servier, Takeda Pharmaceuticals North America, Inc.: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen, Inc., AstraZeneca, BMS, Celgene, EcoR1 Capital LLC, Forma Therapeutics, Genzyme, GSK Biologicals, Ionis Pharmaceuticals, Inc., Janssen Biotech, Juno Therapeutics, Kite Pharma, Legend Biotech USA, Molecular Partners, Regeneron Pharmaceuticals, Inc.,: Honoraria, Membership on an entity's Board of Directors or advisory committees. OffLabel Disclosure: Isatuximab is FDA approved for relapsed refractory myeloma in combination with pomalidomide and dexamethasone. Isatuximab is not FDA approved for AL amyloidosis.

Key Clinical Message Asymptomatic hyperbilirubinemia in a patient with no underlying liver disease or renal impairment while on lenalidomide therapy may be attributable to the unmasking of previously undiagnosed Gilbert's syndrome, as previously shown in the literature. The hyperbilirubinemia should resolve after discontinuation of the drug.

Chromosome 1 abnormalities (C1As) are common genetic aberrations among patients with multiple myeloma (MM). We aimed to evaluate the significance of C1As among a contemporary cohort of patients with MM in the United States. We used electronic health records from the Flatiron Health database to select patients newly diagnosed with MM from January 2011 to March 2018 who were tested using fluorescence in situ hybridization within 90 days of diagnosis. We characterized patients as having documented C1As or other high-risk chromosomal abnormalities (HRCAs) as defined by the Revised-International Staging System (R-ISS) such as del(17p), t(14;16), and t(4;14). We used Kaplan-Meier methods to compare overall survival (OS) of patients with or without C1As and stratified log-rank tests (with the presence of HRCAs as a stratifying variable). We used Cox proportional hazards regression models to compare OS, adjusting for age, sex, stage, HRCAs, and type of first-line therapy. Of 3578 eligible patients, 844 (24%) had documented C1As. Compared with patients without C1As, patients with C1As were more likely to have higher stage (R-ISS stage III; 18% vs 12%), to have HRCAs (27% vs 14%), and to receive combinations of proteasome inhibitors and immunomodulatory agents (41% vs 34%). Median OS was lower for patients with C1As (46.6 vs 70.1 months; log-rank P < .001). C1As were independently associated with worse OS (adjusted hazard ratio, 1.42; 95% confidence interval, 1.19-2.69; P < .001), as were older age, higher R-ISS stage, HRCAs, and immunoglobulin A isotype. C1As were associated with inferior OS, independent of other HRCAs, despite greater use of novel therapies. Clinical trials testing newer therapies for high-risk MM should incorporate patients with C1As.

Preneoplastic lesions carry many of the antigenic targets found in cancer cells but often exhibit prolonged dormancy. Understanding how the host response to premalignancy is maintained and altered during malignant transformation is needed to prevent cancer. To understand the immune microenvironment in precursor monoclonal gammopathy of undetermined significance (MGUS) and myeloma, we analyzed bone marrow immune cells from 12 healthy donors and 26 patients with MGUS/myeloma by mass cytometry and concurrently profiled transcriptomes of 42,606 single immune cells from these bone marrow samples. Compared with age-matched healthy donors, memory T cells from both MGUS and myeloma patients exhibited greater terminal effector differentiation. However, memory T cells in MGUS show greater enrichment of stem-like TCF1/7(hi) cells. Clusters of T cells with stem-like and tissue residence genes were also found to be enriched in MGUS by single-cell transcriptome analysis. Early changes in both NK and myeloid cells were also observed in MGUS. Enrichment of stem-like T cells correlated with a distinct genomic profile of myeloid cells and levels of Dickkopf-1 in bone marrow plasma. These data describe the landscape of changes in both innate and adaptive immunity in premalignancy and suggest that attrition of the bone marrow–resident T cell compartment because of loss of stem-like cells may underlie loss of immune surveillance in myeloma.

Background With improving survival for patients with multiple myeloma (MM), supportive care that is focused on optimizing quality of life and minimizing treatment-related toxicities is increasingly important. The extent to which patients with MM are receiving recommended supportive care is unknown. Methods This study used the Surveillance, Epidemiology, and End Results-Medicare database to identify older adults (age ≥66 years) diagnosed with MM in 2008-2013 who had received active treatment and survived 1 year or longer after their diagnosis. Outcomes of interest included guideline-recommended supportive care, which was defined as 1) bone-modifying drugs (BMDs) within the 12 months after the diagnosis, 2) influenza vaccination in the first season after the diagnosis, and 3) concomitant use of prophylactic antivirals with proteasome inhibitors. Multivariable logistic regression models were used to evaluate associations between patient/facility-level characteristics and supportive care use. Results Among 1996 patients receiving MM-directed therapy, 64%, 52%, and 49% received BMDs, an influenza vaccination, and antiviral prophylaxis, respectively. Non-Hispanic black patients (odds ratio [OR] vs white patients, 0.63; 95% confidence interval [CI], 0.46-0.88) and patients with baseline renal impairment (OR, 0.43; 95% CI, 0.34-0.54) had lower odds of BMDs. Non-Hispanic blacks (OR, 0.52; 95% CI, 0.37-0.73) and those with dual Medicaid enrollment (OR, 0.76; 95% CI, 0.58-0.99) had lower odds of influenza vaccination. Treatment in a community-based setting was associated with reduced odds of antiviral prophylaxis (OR, 0.58; 95% CI, 0.46-0.72). Conclusions Substantial underutilization of guideline-recommended supportive care was observed among older adults with MM in the United States, and this was associated with both patient and facility characteristics. Targeted interventions are needed to improve supportive care for patients with MM.

e19057 Background: Approval of MM therapies including immunomodulatory agents (IMiDs), and proteasome inhibitors (PIs), coupled with increasing evidence supporting PI-IMiD combinations, maintenance (MT), and autologous stem cell transplant (ASCT) among fit patients, have expanded options, complexity and duration of active therapy. Prior research reported race disparities in initial therapy receipt and survival differences based on provider characteristics. It is unknown whether these effects extend to longer-term management. Methods: We selected adults with MM diagnosis (dx) between 07/07-12/15 from the SEER-Medicare linked database. We required continuous Medicare Parts A, B, and D enrollment and no HMO/PPO coverage from 12 months prior to dx through death or end of study (12/16) and MM therapy initiation w/in 12 months post dx. Outcomes including line of therapy (LOT) 1 PI-IMiD combination, LOT1 length, ASCT, MT, any LOT2, and any LOT4, were constructed using claims indicators for oral and IV drugs and receipt dates. Initial provider setting was assigned as academic &/or NCI cancer center, non-teaching hospital, or community (non-hospital) based on 1st oncologist E & M visit w/in 2 months pre- or post-MM dx. We also examined race (white, black, other), Hispanic ethnicity, Part D Low Income Subsidy (LIS) receipt and linked area poverty rate. Multivariable logistic and Cox proportional hazard regressions controlled for demographics, health status, and diagnosis year. Results: The cohort (n = 5678) was 51% male, 14% Black, and 51% age ≥75 years. Initial care setting was 50% academic/NCI, 32% non-teaching hospital, and 19% community; 22%, 53%, and 19% received LOT1 PI-IMiD, LOT 2, and LOT 4, respectively. Median LOT1 length was 165 days. Relative to academic/NCI, community care was associated with lower adjusted odds of all outcomes (e.g. LOT2, aOR: .56, 95% confidence interval (CI) .48 -.65, p < .001; LOT4, aOR: .74, 95% CI .58-.95, p = .02) except LOT1 PI-IMiD. Care at non-teaching hospitals was associated with reduced odds of LOT2. Part D LIS was associated with lower odds of LOT1 PI-IMiD, while increasing % poverty was associated with lower odds of LOT1 PI-IMiD combinations, LOT1 ASCT, LOT2 and LOT4. No associations were observed with race or ethnicity and any outcome. Conclusions: In Medicare insured adults treated for MM, initial care in a community setting was associated with shorter and less complex therapy. Socioeconomic status (Part D LIS, area poverty rates), but not race or ethnicity, was a consistent predictor of MM treatment.

Comprehensive preclinical studies of Myelodysplastic Syndromes (MDS) have been elusive due to limited ability of MDS stem cells to engraft current immunodeficient murine hosts. Here we report a MDS patient-derived xenotransplantation model in cytokine-humanized immunodeficient “MISTRG” mice that provides efficient and faithful disease representation across all MDS subtypes. MISTRG MDS patient-derived xenografts (PDX) reproduce patients’ dysplastic morphology with multi-lineage representation, including erythro- and megakaryopoiesis. MISTRG MDS-PDX replicate the original sample’s genetic complexity and can be propagated via serial transplantation. MISTRG MDS-PDX demonstrate the cytotoxic and differentiation potential of targeted therapeutics providing superior readouts of drug mechanism of action and therapeutic efficacy. Physiologic humanization of the hematopoietic stem cell niche proves critical to MDS stem cell propagation and function in vivo. The MISTRG MDS-PDX model opens novel avenues of research and long-awaited opportunities in MDS research., Myelodyplastic hematopoietic stem cells (MDS HSC) have eluded in vivo modeling. Here the authors present a highly efficient MDS patient-derived xenotransplantation model in cytokine-humanized mice with replication of the donors’ genetic complexity and myeloid, erythroid, and megakaryocytic lineage dysplasia.

Comprehensive preclinical studies of Myelodysplastic Syndromes (MDS) have been elusive due to limited ability of MDS stem cells to engraft current immunodeficient murine hosts. We developed a novel MDS patient-derived xenotransplantation model in cytokine-humanized immunodeficient "MISTRG" mice that for the first time provides efficient and faithful disease representation across all MDS subtypes. MISTRG MDS patient-derived xenografts (PDX) reproduce patients' dysplastic morphology with multi-lineage representation, including erythro- and megakaryopoiesis. MISTRG MDS-PDX replicate the original sample's genetic complexity and can be propagated via serial transplantation. MISTRG MDS-PDX demonstrate the cytotoxic and differentiation potential of targeted therapeutics providing superior readouts of drug mechanism of action and therapeutic efficacy. Physiologic humanization of the hematopoietic stem cell niche proves critical to MDS stem cell propagation and functionin vivo. The MISTRG MDS-PDX model opens novel avenues of research and long-awaited opportunities in MDS research.

A role for antigen-driven stimulation has been proposed in the pathogenesis of monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma (MM) based largely on the binding properties of monoclonal Ig. However, insights into antigen binding to clonal B cell receptors and in vivo responsiveness of the malignant clone to antigen-mediated stimulation are needed to understand the role of antigenic stimulation in tumor growth. Lysolipid-reactive clonal Ig were detected in Gaucher disease (GD) and some sporadic gammopathies. Here, we show that recombinant Ig (rIg) cloned from sort-purified single tumor cells from lipid-reactive sporadic and GD-associated gammopathy specifically bound lysolipids. Liposome sedimentation and binding assays confirmed specific interaction of lipid-reactive monoclonal Ig with lysolipids. The clonal nature of lysolipid-binding Ig was validated by protein sequencing. Gene expression profiling and cytogenetic analyses from 2 patient cohorts showed enrichment of nonhyperdiploid tumors in lipid-reactive patients. In vivo antigen-mediated stimulation led to an increase in clonal Ig and plasma cells (PCs) in GD gammopathy and also reactivated previously suppressed antigenically related nonclonal PCs. These data support a model wherein antigenic stimulation mediates an initial polyclonal phase, followed by evolution of monoclonal tumors enriched in nonhyperdiploid genomes, responsive to underlying antigen. Targeting underlying antigens may therefore prevent clinical MM.

Background: c-MYC activation is an early event of myeloma pathogenesis. It upregulates the expression of the glutaminase 1 (GLS1) enzyme which converts glutamine to glutamate in the mitochondria. Glutamate is required for the biosynthesis of various molecules in the tricarboxylic acid (TCA) cycle (i.e., glutamine anaplerosis). CB-839 HCl is a first-in-class, orally available, selective, noncompetitive inhibitor of GLS1. This inactivation of GLS1 results in an increase of glutamine and a decrease of glutamate and several TCA cycle intermediates within cancer cells, leading to a decrease in their proliferation and/or an increase in cell death. In the phase 1 study, CX-839-002, the safety and tolerability of CB-839 HCl was evaluated in patients with hematological tumors (multiple myeloma (MM) and non-Hodgkin's lymphoma), either as monotherapy or in combination with pomalidomide and dexamethasone or with dexamethasone alone. It was determined to be well tolerated and the maximal tolerated dose (MTD) was not reached. Proteasome inhibitors (PI) are the cornerstone agents in the treatment of myeloma. They disrupt normal protein homeostasis causing an induction of cellular proteotoxic stress, thus, making it an effective strategy against myeloma plasma cells, which naturally mass-produce large quantities of immunoglobulin proteins. PI-resistant MM cells are associated with changes in cellular bioenergetics that favor the increased use of mitochondrial respiration for energy production. Given the increased reliance of PI-resistant MM cells on mitochondrial respiration, and the critical role of glutamine for cellular respiration, inhibition of glutamine metabolism is a rational molecular strategy for the treatment of PI-resistant MM. Furthermore, pre-clinical studies demonstrate the in vitro and ex vivo synergism of CB-839 HCl with carfilzomib (CFZ) in terms of its cytotoxicity and anti-proliferation capacity in various primary human myeloma cell lines and primary patient myeloma cells respectively. As a result, this novel combination of glutaminase inhibition with proteasome inhibition appears promising as a therapeutic combination in MM and warrants further clinical investigation. Methods: This study is a phase 1, multicenter clinical trial of CB-839 HCl in combination with carfilzomib and dexamethasone for patients with relapsed and/or refractory myeloma. Part A of this trial is a 3+3 dose escalation design and Part B is a dose expansion cohort at the RP2D determined in Part A. Up to a maximum of 42 patients will be enrolled at participating ETCTN sites. CFZ will be administered in its usual weekly dosing schedule of days 1, 8 and 15 of a 28 day schedule along with dexamethasone on days 1, 8, 15 and 22. CB-839 will be started at a dose level of 400 mg twice daily and will be investigated to a maximum dose of 800 mg twice daily. Prior to day 1 of Cycle 1, we will administer a 7 day lead in of CB-839 monotherapy before combining it with CFZ. Key inclusion criteria are having relapsed/refractory myeloma with at least 2 prior lines of therapy and prior exposure to PIs, immunomodulators and Anti-CD38 monoclonal antibodies, having measurable disease, adequate hematologic reserve, kidney function and liver function. Key exclusion criteria are being refractory or intolerant to CFZ, adverse cardiac history, central nervous system disease and AL amyloidosis. The primary objective of this trial is to determine the MTD or recommended phase II dosing (RP2D) of CB-839 HCl in combination with carfilzomib and dexamethasone. The secondary objective is to evaluate the safety and tolerability as well as the overall response rate (ORR) associated of CB-839 HCl in combination with carfilzomib and dexamethasone. Correlative objectives will evaluate plasma pharmacokinetic profiles of CB-839 HCl and carfilzomib when used in combination. They will also evaluate potential predictive and prognostic biomarkers as well as resistance mechanisms using genomic DNA, RNA, flow cytometry, immunohistochemistry and metabolomics-based assessment platforms. Recruitment is ongoing and this trial is registered on clinicaltrials.gov: NCT03798678. Disclosures Baz: Bristol-Myers Squibb: Research Funding; Sanofi: Research Funding; Karyopharm: 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; AbbVie: Research Funding; Merck: Research Funding. Neparidze:Janssen Scientific Affairs, LLC: Research Funding; Eidos Therapeutics: Other: Member of Independent Diagnostic Committee; MMRF/Synteract: Membership on an entity's Board of Directors or advisory committees. Kumar:Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Takeda: Research Funding.

AMZ and NAP contributed equally to this work Introduction: Anthracycline- and cytarabine-based induction chemotherapy (IC), known as "7+3", has been the standard of care for fit patients (pts) with AML for over 45 years. While various aspects of IC admissions, such as use of mechanical ventilation and dialysis, admission to intensive care units (ICU), and IC-related mortality have been reported in clinical trial setting, little is known about experience and outcomes with 7+3 therapy in real-world settings. We conducted a large population-based retrospective cohort study to assess inpatient care delivered in the US for AML pts receiving 7+3 including IC-related death rates and their predictors. Methods: We used the Premier Healthcare Database, which includes data from geographically diverse, non-profit, nongovernmental, community and teaching hospitals in the US. Premier captures information from 25% of all inpatient admissions across all ages and payor groups. The database includes demographics, diagnoses, and detailed information on diagnostic tests and the use of drugs, procedures, and other inpatient resources, with dates relative to admission. We selected adult (age ≥18 years) AML pts who received 7+3 during their first recorded inpatient stay between 2010 and 2017. Pts were excluded if they 1) were diagnosed with acute promyelocytic leukemia; 2) received "non-7+3" chemotherapy; or 3) had an inpatient length of stay exceeding one year. We defined antifungal prophylaxis (px) as receipt of non-topical agents within the first 14 days after 7+3 initiation and stratified as mold-directed vs not (fluconazole only). Hospitals were categorized based on the mean number of AML pts included in the study per year as low- ( Results: A total of 6,442 AML pts from 313 hospitals who received 7+3 were included. Median age was 61 years (interquartile range [IQR]: 50-68 years; 53.1% age ≥ 60 years); 56% of pts were male (Table 1). Median length of stay was 29 (IQR: 25-38) days with percentages of in-hospital death and discharge to hospice of 12.3% and 3.7%, respectively (total 16.0%). In-hospital death or discharge to hospice were lower in high-volume hospitals (14.0%) compared to low- (17.1%, p During their inpatient stay, 12.6% and 4.0% of pts required ICU admissions with mechanical ventilation and dialysis, respectively, with no difference by hospital volume (Table 2). Only 59.2% of pts had claims for bone marrow aspirate/biopsy (BMA) during their inpatient stay. 99.1% received anti-infective medications, and 76.7% received anti-viral medications. Pts in high-volume hospitals were more likely to undergo BMA (p=.02), anti-infective medications (p Conclusions: To our knowledge, this is the largest population-based study to examine practice patterns and induction mortality for AML pts receiving "7+3" in the US. One of seven pts receiving 7+3 died in the hospital during induction or was discharged to hospice. We observed high use of intensive resources. IC-related mortality, use of any antifungal px, and use of mold-directed antifungal px were significantly better in high-volume hospitals compared to low- and medium-volume hospitals. Further analyses are ongoing to examine other predictors of IC-related deaths. Improved understanding of factors that predict induction-related mortality with 7+3 is vital to develop strategies that improve patient outcomes. Disclosures Zeidan: Boehringer-Ingelheim: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Ariad: Honoraria; Jazz: Honoraria; Medimmune/AstraZeneca: Research Funding; ADC Therapeutics: Research Funding; Acceleron Pharma: Consultancy, Honoraria, Research Funding; Celgene Corporation: Consultancy, Honoraria, Research Funding; Incyte: Consultancy, Honoraria, Research Funding; Trovagene: Consultancy, Honoraria, Research Funding; BeyondSpring: Honoraria; Abbvie: Consultancy, Honoraria, Research Funding; Novartis: Honoraria; Cardinal Health: Honoraria; Seattle Genetics: Honoraria; Daiichi Sankyo: Honoraria; Astellas: Honoraria; Otsuka: Consultancy, Honoraria, Research Funding; Agios: Honoraria. Podoltsev:Blueprint Medicines: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Alexion: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Agios Pharmaceuticals: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding; Astellas Pharma: Research Funding; Daiichi Sankyo: Research Funding; Sunesis Pharmaceuticals: Research Funding; Kartos Therapeutics: Research Funding; Jazz Pharmaceuticals: Research Funding; Pfizer: Research Funding; Astex Pharmaceuticals: Research Funding; CTI Biopharma: Research Funding; Celgene: Other: Grant funding, Research Funding; Genentech: Research Funding; AI Therapeutics: Research Funding; Samus Therapeutics: Research Funding; Arog Pharmaceuticals: Research Funding. Huntington:Celgene: Consultancy, Research Funding. Neparidze:Janssen Scientific Affairs, LLC: Research Funding; Eidos Therapeutics: Other: Member of Independent Diagnostic Committee; MMRF/Synteract: Membership on an entity's Board of Directors or advisory committees. Gore:Celgene Corporation: Consultancy, Research Funding. Ma:Celgene Corporation: Research Funding. Davidoff:Celgene Corporation: Consultancy, Research Funding. Wang:Celgene Corporation: Research Funding.