Citations

Abstract Aims Despite improvements in cardiac haemodynamics and symptoms, long-term mortality remains increased in some patients after aortic valve replacement (AVR). Limited data exist on the prognostic role of left ventricular (LV) chamber stiffening in these patients. Methods and results We performed a retrospective analysis in 1893 patients with severe aortic stenosis (AS) referred for AVR. LV end-diastolic pressure–volume relations (EDPVR, P = αV^β) were reconstructed from echocardiographic measurements of end-diastolic volumes and estimates of end-diastolic pressure (EDP). The impact of EDPVR-derived LV chamber stiffness (CS30, at 30 mmHg EDP) on all-cause mortality after AVR was evaluated. Mean age was 76 ± 10 years, 39% were females, and ejection fraction (EF) was 61 ± 12%. The mean LV chamber stiffness (CS30) was 2.2 ± 1.3 mmHg/mL. A total of 877 (46%) patients had high LV stiffness (CS30 >2 mmHg/mL). In these patients, the EDPVR curves were steeper and shifted leftwards, indicating higher stiffness at all pressure levels. These patients were slightly older, more often female, and had more prevalent comorbidities compared to patients with low stiffness. At follow-up [median 4.2 (interquartile range 2.8–6.3) years; 675 deaths], a higher CS30 was associated with lower survival (hazard ratio: 2.7 for severe vs. mild LV stiffening; P < 0.0001), both in patients with normal or reduced EF. At multivariate analysis, CS30 remained an independent predictor, even after adjusting for age, sex, comorbidities, EF, LV remodelling, and diastolic dysfunction. Conclusion Higher preoperative LV chamber stiffening in patients with severe AS is associated with poorer outcome despite successful AVR.

AbstractBackgroundThe Surveillance, Epidemiology, and End Results (SEER) database and National Cancer Database (NCDB) show improved overall survival (OS) in patients with multiple myeloma (MM) over the last 15 years. This analysis evaluated the validity of the largely community‐based Connect MM Registry as a national reference for MM.MethodsBaseline disease characteristics and survival in US newly diagnosed MM patients were examined using the Connect MM Registry as well as SEER and NCDB databases. Baseline characteristics predictive of longer survival in Connect MM were also identified.ResultsAs of February 2017, 3011 patients were enrolled in the Connect MM Registry; 2912 were treated. Median age at time of MM diagnosis and age range were numerically similar from 2010 to 2015 across all 3 registries; SEER had a higher representation of nonwhite racial groups than that in the other 2 registries. OS rates suggest proportionate improvement with year of diagnosis among the 3 registries. A Cox proportional hazards model suggests that younger age (<65 years) is associated with longer survival (vs ≥75; HR, 0.39; 95% confidence interval, 0.34‐0.46) in the Connect MM Registry. However, sex (HR, 0.91; P = .15) and race (black vs white; HR, 0.88; P = .21) were not associated with longer OS.ConclusionsData from the Connect MM Registry appear to be largely representative of national trends, comprehensive, and reliable representations of the national MM population. Baseline characteristics were comparable, and survival similarly improved over time among the 3 registries.ClinicalTrials.gov, identifierNCT01081028.

Abstract Context Urine steroid metabolomics, combining mass spectrometry-based steroid profiling and machine learning, has been described as a novel diagnostic tool for detection of adrenocortical carcinoma (ACC). Objective, Design, Setting This proof-of-concept study evaluated the performance of urine steroid metabolomics as a tool for postoperative recurrence detection after microscopically complete (R0) resection of ACC. Patients and Methods 135 patients from 14 clinical centers provided postoperative urine samples, which were analyzed by gas chromatography–mass spectrometry. We assessed the utility of these urine steroid profiles in detecting ACC recurrence, either when interpreted by expert clinicians or when analyzed by random forest, a machine learning-based classifier. Radiological recurrence detection served as the reference standard. Results Imaging detected recurrent disease in 42 of 135 patients; 32 had provided pre- and post-recurrence urine samples. 39 patients remained disease-free for ≥3 years. The urine “steroid fingerprint” at recurrence resembled that observed before R0 resection in the majority of cases. Review of longitudinally collected urine steroid profiles by 3 blinded experts detected recurrence by the time of radiological diagnosis in 50% to 72% of cases, improving to 69% to 92%, if a preoperative urine steroid result was available. Recurrence detection by steroid profiling preceded detection by imaging by more than 2 months in 22% to 39% of patients. Specificities varied considerably, ranging from 61% to 97%. The computational classifier detected ACC recurrence with superior accuracy (sensitivity = specificity = 81%). Conclusion Urine steroid metabolomics is a promising tool for postoperative recurrence detection in ACC; availability of a preoperative urine considerably improves the ability to detect ACC recurrence.

Abstract Background Cardiac power output-to-mass (CPOM) ratio is a measure of myocardial performance that incorporates both pressure and flow output, normalized to left ventricular (LV) mass generating that cardiac work. Prior small studies have shown that CPOM predicts outcomes in patients with ischemic cardiomyopathy and reduced LV ejection fraction (EF). We sought to evaluate the prognostic significance of peak exercise CPOM and power reserve (increase from rest to peak exercise) in patients with normal EF. Methods and results Retrospective study in 24,783 patients (age 59±13 years, 45% females) with EF≥50% and no significant valve disease or right ventricular (RV) dysfunction, undergoing exercise stress echocardiography between 2004–2018. CPOM was calculated as previously described (0.222 x cardiac output x mean blood pressure / LV mass) and expressed in Watts/100g myocardium. Power reserve was calculated as difference in CPOM between peak stress and rest. All-cause mortality was the primary endpoint. Patients were divided into quartiles of power reserve. Patients with higher power reserve were younger, had higher blood pressure and heart rate, lower LV mass, and lower prevalence of prior myocardial infarction. (Table). During follow-up (median (IQR) 3.9 (0.6–8.3) years), 931 (3.8%) patients died. Progressively lower power reserve was associated with increasing mortality (Figure A). Compared to patients with abnormal stress test, patients with the lowest power reserve but otherwise normal stress test had the same survival as those with infarction/cardiomyopathy or ischemia on stress test (Figure B). Resting CPOM had lower predictive value. After adjusting for age, sex, METs achieved, ischemia/infarction on stress test results, and diastolic function grade, both peak exercise CPOM and power reserve were independent predictors of mortality (p<0.0001), incremental to conventional measures. Conclusion Cardiac power output and reserve measured during exercise stress echo provides independent prognostic information in patients with normal resting EF and no significant valve disease or RV dysfunction. The survival of patients with low power reserve but normal stress test was similar to patients with prior infarction/ cardiomyopathy or ischemia on stress test.

Abstract BRCA1 plays a key role in homologous recombination (HR) DNA repair. Accordingly, changes that downregulate BRCA1, including BRCA1 mutations and reduced BRCA1 transcription, due to promoter hypermethylation or loss of the BRCA1 transcriptional regulator CDK12, disrupt HR in multiple cancers. In addition, BRCA1 has also been implicated in the regulation of metabolism. Here, we show that reducing BRCA1 expression, either by CDK12 or BRCA1 depletion, led to metabolic reprogramming of ovarian cancer cells, causing decreased mitochondrial respiration and reduced ATP levels. BRCA1 depletion drove this reprogramming by upregulating nicotinamide N-methyltransferase (NNMT). Notably, the metabolic alterations caused by BRCA1 depletion and NNMT upregulation sensitized ovarian cancer cells to agents that inhibit mitochondrial metabolism (VLX600 and tigecycline) and to agents that inhibit glucose import (WZB117). These observations suggest that inhibition of energy metabolism may be a potential strategy to selectively target BRCA1-deficient high-grade serous ovarian cancer, which is characterized by frequent BRCA1 loss and NNMT overexpression. Significance: Loss of BRCA1 reprograms metabolism, creating a therapeutically targetable vulnerability in ovarian cancer.

Abstract Background: It has been known for approximately 19 years that germline mutations in RUNX1, lead to familial platelet disorder with predisposition to myeloid malignancy (FPD-MM, OMIM 601399). Since that time researchers have identified a broad range of different RUNX1 mutations, in over 100 families. In large families, the diagnosis of malignancy shows variable penetrance among family members with the same mutation; some carriers of RUNX1 mutations do not develop malignancy. The causes of this heterogeneity are currently not known, complicating counselling and risk analysis for individual carriers. Recent advances in genetic sequencing technology applied by many FPD-MM research groups around the world have highlighted their value in understanding the somatic genetic changes that are associated with development of malignancies in germline RUNX1 mutation carriers. Collectively this information could lead to powerful insights essential for more precise risk assessment, monitoring, and therapeutic intervention. Specifically, a growing catalogue of somatic mutations associated with germline RUNX1 malignancy offers the opportunity for informed monitoring of asymptomatic RUNX1 carriers for additional high-risk somatic mutations, in turn providing the possibility for early therapeutic intervention to arrest the leukemic process. The challenge in advancing these goals for FPD-MM is the relative rarity of the disorder in individual populations. Global data sharing in a highly interactive FPD-MM research community offers a solution to this problem that benefits all patients world-wide. Aims: To create a global RUNX1 network through identifying and contacting researchers and clinicians with known and novel germline RUNX1 families, seeking their collaboration to share genomics data. To create a RUNX1.db portal to collectively house and analyse genomics data from germline RUNX1 carriers, with associated phenotype and clinical information, such that researchers have an ongoing means by which to combine their data with those generated by other groups around the world. Methods: RUNX1 network : Through existing collaborative networks, a systematic review of the literature, and referrals from initial contacts, we have identified a global network of researchers managing FPD-MM cases and families. RUNX1.db: We have adapted a custom-built variant analysis platform, VariantGrid, that is a visual web application and database designed to help scientists manage and analyse DNA variants that can be used to aggregate and analyse multiple datasets. Results: Preliminary analysis of aggregated data from the literature suggests there are features of germline RUNX1 syndrome that can be ascertained. These include frequent somatic mutation of RUNX1 in malignancy development, as well as mutations in genes associated with clonal hematopoiesis that may precede development of overt leukemia. This analysis also suggests that different types of germline RUNX1 mutations may be associated with different combinations of somatic mutations in the tumour. To further this analysis, we have identified over 70 groups internationally that either manage RUNX1 families or have identified potential germline carriers through genomics initiatives. This represents a large and growing resource for both scientific studies and clinical programs to benefit individuals with FPD-MM. Many of these groups have generated NGS data sets from patient samples which will be available for analysis through this portal. Further details and activities of the network, and results from the genomics aggregation database will be presented. Conclusion: We have created a global RUNX1 network, aggregated their data, and generated a RUNX1.db genomics portal for the continuous curation of genomics data from germline RUNX1 carriers. A preliminary analysis has already identified specific features of germline RUNX1 mutated malignancies that have clinical importance. Ongoing scientific and clinical studies through the RUNX1 network will enhance the power of aggregated data analysis, with RUNX1.db providing a central link, driving new insights that benefit patients. Disclosures Natsoulis: Imago BioSciences, Inc.: Consultancy, Equity Ownership. Guzman:Cellectis: Research Funding. DiNardo:Bayer: Honoraria; Karyopharm: Honoraria; Celgene: Honoraria; Agios: Consultancy; Medimmune: Honoraria; Abbvie: Honoraria. Borate:Novartis: Consultancy; Agios: Consultancy. Wei:Amgen: Honoraria, Other: Advisory committee, Research Funding; Pfizer: Honoraria, Other: Advisory committee; Celgene: Honoraria, Other: Advisory committee, Research Funding; Abbvie: Honoraria, Other: Advisory board, Research Funding, Speakers Bureau; Servier: Consultancy, Honoraria, Other: Advisory committee, Research Funding; Novartis: Honoraria, Other: Advisory committee, Research Funding, Speakers Bureau. Dokal:MRC, Bloodwise, Telomerase Activator Sciences: Research Funding; The Gary Woodward Dyskeratosis Congenita Trust: Membership on an entity's Board of Directors or advisory committees; Action Medical Research, European School of Haematology: Membership on an entity's Board of Directors or advisory committees; Barts and The London School of Medicine and Dentistry, Queen Mary University of London,: Employment, Research Funding; Telomerase Activator Sciences: Research Funding; Barts and The London, Queen Mary University of London: Employment; Gary Woodward Dyskeratois Congenita Trust: Membership on an entity's Board of Directors or advisory committees. Hiwase:Novartis: Research Funding; Celgene: Research Funding. Branford:Cepheid: Honoraria; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Qiagen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Kramer:Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Bayer: Research Funding; Daiichi Sankyo: Consultancy. Owen:Merck: Honoraria; Teva: Honoraria; AbbVie: Research Funding; Pharmacyclics: Research Funding; Janssen: Honoraria, Research Funding; Celgene: Research Funding; AstraZeneca: Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Honoraria, Research Funding. Fitzgibbon:Epizyme: Consultancy, Research Funding; Gilead: Consultancy. Rienhoff:Imago BioSciences, Inc.: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Kurokawa:Astellas Pharma: Research Funding; Sumitomo Dainippon Pharma: Research Funding; Nippon Sinyaku: Honoraria, Research Funding; Kyowa Hakko Kirin: Honoraria, Research Funding; Eizai: Research Funding; MSD: Honoraria, Research Funding; Ono Pharmaceutical: Honoraria, Research Funding; Pfizer: Research Funding; Takeda Pharmaceutical: Research Funding; Otsuka Pharmaceutical: Research Funding; Teijin Pharma: Research Funding; Chugai Pharmaceutical: Research Funding.

Abstract Introduction: Topoisomerase I is a nuclear enzyme that relaxes torsional strain in DNA by nicking one DNA strand, allowing rotation, then resealing the DNA backbone. This is an important enzyme in replication and transcription, and therefore has been targeted by anti-cancer agents such as camptothecins. These agents intercalate into DNA at the topoisomerase I active site and inhibit the religation step catalyzed by the enzyme, causing increased topoisomerase I-DNA complexes that impede advancing replication forks or transcription complexes, leading to DNA damage and cell death. Platinating agents also stabilize topoisomerase I-DNA covalent complexes. The topotecan/carboplatin combination has recently shown promise in combination with the PARP inhibitor veliparib in aggressive and transformed myeloproliferative neoplasms (MPNs) and chronic myelomonocytic leukemia (K Pratz et al., Clin Cancer Res. 23:899, 2017). Given that both classes of agents have a narrow therapeutic window, it is important to try to predict the sensitivity/resistance of these agents in malignancies such as acute myeloid leukemia (AML) and transformed MPNs. Some of mechanisms of drug resistance that have been described are decreased numbers of drug-stabilized topoisomerase I-DNA complexes due to drug efflux, diminished topoisomerase I expression or topoisomerase I mutation. Thus, being able to detect and quantify these DNA-protein complexes may provide insight into drug sensitivity. Methods: Using a unique monoclonal antibody that detects topoisomerase I-DNA covalent complexes (A. Patel et al., Nucleic Acids Res. 44:2816, 2016), immunofluorescence techniques were used to quantify these topoisomerase I-DNA complexes in AML cell lines (SET2, HEL, K562, U937, ML2, MV-4-11, THP1, HL60, ML1, and Molm13) and clinical AML samples. To verify the fidelity of the anti-topoisomerase I-DNA covalent complex antibody (TopIcc), siRNA knockdown methods were utilized with confirmatory immunofluorescence and Western blotting. Slot blots were additionally used to assess the presence of these complexes in AML cell lines. Western blots were performed to assess topoisomerase I levels in AML cell lines. Topotecan drug sensitivity analysis was performed by using an MTS assay. Results: With treatment of the topoisomerase I inhibitor, topotecan, there was an increase in the percentage of leukemia cells positive for the topoisomerase I-DNA covalent complexes. The degree of increase in complexes varied across cell lines and patient samples. To ensure we were detecting TopIcc by immunofluorescence, we performed a topoisomerase-I siRNA knockdown to confirm the specificity of the antibody for TopIcc's. Slot blots on multiple AML cell lines confirmed the presence of topoisomerase-DNA covalent complexes. The Western blot of all the AML cell lines, ordered from low to high TopIcc revealed increasing amounts of topoisomerase I. The MTS assay revealed lower topotecan IC50 values in three of the cell lines with higher complex formation, including Molm13, ML1 and ML2 (IC50 6-8 nM compared to 13-46 nM in the other cell lines). Conclusions: Based on recent clinical results, there has been renewed interested in topoisomerase I inhibitors, especially for aggressive and transformed MPNs. Topoisomerase I-DNA complex repair/downregulation has been a hallmark of drug resistance to topoisomerase I inhibitors. Therefore, detecting and quantifying these complexes in treated samples has been hypothesized to provide insight into the drug sensitivity, which is particularly important in camptothecins and platinating agents given their narrow therapeutic windows. Immunodetection techniques using an anti-TopIcc antibody may help predict sensitivity of AML to topoisomerase I inhibitors and will be used as a correlative biomarker study in an upcoming phase II randomized study of topotecan/carboplatin with or without veliparib or placebo in advanced myeloproliferative disorders and chronic myelomonocytic leukemia (ClinicalTrials.gov NCT03289910). Disclosures Pratz: AbbVie: Consultancy, Research Funding; Agios: Research Funding; Astellas: Consultancy, Research Funding; Boston Scientific: Consultancy; Millenium/Takeda: Research Funding. Kaufmann:Mayo Clinic: Patents & Royalties: Co-inventor on a patent held by Mayo Clinic for the use of the anti-TOP1cc antibody as a diagnostic reagent.

Abstract Background : Treatment for relapsed multiple myeloma (MM) has evolved with the availability of many novel agents; outcomes in patients with newly diagnosed MM have improved with IMiD® agents (lenalidomide [R] or pomalidomide) and proteasome inhibitor (PI) use. Regardless of autologous stem cell transplant, many patients receive R maintenance therapy (Jagannath, Blood Adv 2018; Palumbo, N Engl J Med 2012). However, there is a lack of data describing the nature of relapse and treatment choices for patients progressing on R maintenance therapy. Recent phase III data do not evaluate these patients who are relapsed or refractory to R; current treatment guidelines do not specifically recommend second-line (2L) treatment options for these patients (Laubach, Leukemia 2016). However, phase III data show that pomalidomide in combination with bortezomib and dexamethasone improves progression-free survival (PFS) (HR 0.54; P = 0.0027) in R-exposed and refractory patients, including those with 1 prior line (Richardson, J Clin Oncol 2018). The Connect MM Registry is a US, multicenter, prospective observational cohort study designed to examine diagnostic and treatment patterns, clinical outcomes and quality of life in patients with MM. For patients who received R maintenance therapy, we describe patterns of relapse, 2L treatment choice, and outcomes. Methods : From 250 sites, transplant eligible and ineligible adult patients ≤ 60 days from MM diagnosis were enrolled (N = 3011). Patients were treated at physicians' discretion and followed up for treatment and outcomes until early discontinuation or study end. Patients who relapsed during R maintenance therapy (≤ 15 mg; assessed by treating physician), were analyzed for baseline (BL) characteristics, nature of relapse, and 2L treatment. Patients with symptoms at time of relapse were defined as the presence of ≥ 1 CRAB (hyperCalcemia, Renal failure, Anemia, and Bone disease) criterion ± 60 d from PD; absence of CRAB criteria at PD in this window was considered nonsymptomatic relapse. Primary endpoint was PFS from start of 2L; safety (serious adverse events; SAE) from start of 2L was also assessed. Logistic regression analyses on all BL factors and factors before start of 2L treatment were performed to determine covariates differentiating comparator groups. Survival outcomes were analyzed using a Cox regression after adjusting for covariates. Results : Data cutoff: 1/15/18. Of 2938 treated patients, 1102 entered 2L, 236 having received R maintenance therapy in 1L. Of those patients, 52% (n = 123) and 47% (n = 112) experienced symptoms at time of relapse and nonsymptomatic relapse, respectively (data not available for 1 patient). The top ten 2L regimens are presented in the Table. Median duration of prior maintenance therapy (367 d [IQR: 577] vs 489 d [IQR: 599]) and time from first progression to start of 2L treatment (0.3 vs 0.3 mo) did not notably differ between nature of relapse groups. Prolonged median PFS from start of 2L was observed for patients receiving triplet+ (≥ 3 agents) vs doublet (≤ 2 agents) regimens (HR: 0.72; Figure 1). PFS was better for IMiD agent + PI group compared with PI (without IMiD agents) group (HR, 0.68; Figure 2). Results of sensitivity analyses and overall survival will be presented. SAEs occurred similarly among treatment groups: 42.6% with IMiD agent + PI, 34.5% with IMiD agent (without PI), and 35.8% with PI. Conclusions: This is the first description of relapse patterns, 2L treatment choice and survival outcomes after PD on R maintenance therapy in community-based patients. Nearly equal numbers of patients had symptoms at time of relapse and nonsymptomatic relapse on R maintenance therapy. After PD on R maintenance, approximately 50% of patients switched to PI regimens without IMiD agents, 25% continued with IMiD agent + PI regimens, and 25% continued in the IMiD agents group. Our data show PFS benefit for triplet+ over doublet treatment in 2L. Patients in the IMiD agent + PI group gained survival benefits over patients in the PI group. Further characterization of the patients continuing with IMiD treatment in 2L after R maintenance therapy relapse (~ 25% of patients) are ongoing. Follow-up with recently approved agents (elotuzumab, daratumumab) and their use in 2L is limited in this analysis. These data may be used to better inform treatment choices after relapse on R maintenance therapy. Disclosures Jagannath: Celgene: Consultancy; Merck: Consultancy; Multiple Myeloma Research Foundation: Speakers Bureau; Medicom: Speakers Bureau; Bristol-Myers Squibb: Consultancy; Novartis: Consultancy. Narang:Janssen: Speakers Bureau; Celgene: Consultancy, Speakers Bureau. Ailawadhi:Takeda: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Research Funding; Celgene: Consultancy. Rifkin:Celgene: Consultancy; Boehringer Ingelheim: Consultancy; McKesson: Equity Ownership; EMD Serono: Consultancy; Amgen: Consultancy; Takeda: Consultancy; Sandoz: Consultancy. Terebelo:Celgene: Consultancy; Janssen: Speakers Bureau; Takeda: Speakers Bureau; Pharmacyclics: Speakers Bureau. Toomey:Celgene: Consultancy; Myriad Genetics: Speakers Bureau; Dava Oncology: Other: Travel. Durie:Takeda: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Amgen: Consultancy. Hardin:Celgene: Consultancy. Gasparetto:Janssen: Consultancy, Honoraria, Other: Travel; Bristol-Myers Squibb: Consultancy, Honoraria, Other: Travel; Takeda: Honoraria; Celgene: Consultancy, Honoraria, Other: Travel, Research Funding. Wagner:EveryFit: Consultancy; Gilead: Consultancy; Janssen: Consultancy. Omel:Takeda Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Srinivasan:Celgene: Employment. Kitali:Celgene: Employment. Agarwal:Celgene Corporation: Employment, Equity Ownership. Abonour:Prothena: Research Funding; Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.

Abstract Abstract 3150 Introduction. Affordability of health care in the United States (US), and the impact of patient insurance coverage on it have been shown to be associated with the delivery and timeliness of access to care. With increasing costs of novel therapies in hematology and oncology, this concern has been raised in hematologic cancers. This analysis evaluates whether the health-related quality of life (HRQOL) of patients with active, symptomatic multiple myeloma (MM) patients in the US varies by their insurance coverage as they initiate treatment. Methods. Baseline data were collected in Connect MM®, a prospective observational registry initiated in September 2009 involving centers in the US. Data on patient demographics and clinical characteristics were provided by clinicians. HRQOL was reported by patients in the clinic at enrollment, within two months of diagnosis. Patients completed 3 psychometrically validated instruments: the Brief Pain Inventory (BPI), EQ-5D, and Functional Assessment of Cancer Therapy-Multiple Myeloma (FACT-MM). Standard analyses were conducted of each instrument given clinical characteristics at that time. Patients were characterized as to the main source of their insurance coverage: Medicare, Medicaid or Commercial. The Medicare cohort included those with supplemental commercial coverage, and the Medicaid cohort included those with dual Medicare-Medicaid coverage. Reported mean BPI, EQ-5D and FACT-MM scores were analyzed by patient insurance coverage. Statistical significance of score differences among sub-cohorts was ascertained by ANOVA using SAS 9.1. Results. HRQOL data and insurance status were reported by 863 patients, enrolled from 189 centers. Patients were predominantly male (57%) and white (82%) with mean age at 67.0 (standard deviation [SD] 11.3) yrs. HRQOL scores by insurance status are presented: Overall FACT-MM results indicate that Medicaid insurance status is associated with greater decrement in baseline HRQOL compared to the other groups. Statistically significant differences are noted in the FACT-G general cancer HRQOL score, and its physical, social/family and emotional component scores. BPI data (on a scale of 0 [no pain] to 10 [worst pain] indicate that average pain may be worse among Medicaid patients compared to either Medicare or commercially insured patients. There are no statistically significant differences on EQ-5D scores (on a scale of 1 [no problem] to 2 [some problems] to 3 [incapacity] between cohorts based on insurance status. Conclusions. Initial results from the Connect MM® Registry indicate that HRQOL at baseline prior to initiation of treatment is worse among Medicaid patients compared to those with either Medicare or commercial coverage. This should be investigated to determine whether Medicaid patients are accessing care later in disease progression than others covered by Medicare or commercial insurance. Furthermore, future analyses should be conducted of patients by insurance coverage to determine whether status may be associated with access to medical care, subsequent clinical outcomes, and HRQOL over time. Results reported here should serve as a baseline reference. Disclosures: Pashos: Celgene: Membership on an entity's Board of Directors or advisory committees. Durie:Celgene: Membership on an entity's Board of Directors or advisory committees. Rifkin:Celgene: Membership on an entity's Board of Directors or advisory committees. Terebelo:Celgene: Membership on an entity's Board of Directors or advisory committees. Gasparetto:Celgene: Membership on an entity's Board of Directors or advisory committees. Mehta:Celgene: Membership on an entity's Board of Directors or advisory committees. Toomey:Celgene: Membership on an entity's Board of Directors or advisory committees. Abonour:Celgene: Membership on an entity's Board of Directors or advisory committees. Fonseca:Celgene: Membership on an entity's Board of Directors or advisory committees. Narang:Celgene: Membership on an entity's Board of Directors or advisory committees. Shah:Celgene: Membership on an entity's Board of Directors or advisory committees. Swern:Celgene Corporation: Employment, Equity Ownership. Sullivan:Celgene: Employment, Equity Ownership. Street:Celgene: Employment, Equity Ownership. Khan:Celgene: Employment, Equity Ownership.

Abstract Abstract 5070 Introduction. Studies in the United States (US) have identified variation in incidence and survival of multiple myeloma (MM) patients of different races, and noted that MM is the most common hematologic cancer among African Americans. This analysis was conducted to evaluate whether the health-related quality of life (HRQOL) of patients in the US as they initiate treatment with active, symptomatic MM varies by race. Methods. Data were collected in Connect MM®, a prospective observational registry begun in September 2009 involving centers in the US. Data on patient demographics and clinical characteristics were provided by clinicians. HRQOL was reported by patients in the clinic at enrollment, within two months of diagnosis. Patients completed 3 psychometrically validated instruments: the Brief Pain Inventory (BPI), EQ-5D, and Functional Assessment of Cancer Therapy-Multiple Myeloma (FACT-MM). Standard analyses were conducted of each instrument. Reported mean BPI, EQ-5D and FACT-MM scores were analyzed by patient race. Statistical significance of score differences was ascertained by ANOVA using SAS 9.1 in two ways: (1) among three different racial categories (White, Black and Other), and (2) between Blacks and non-Blacks. Hispanic/Latino patients and Asian patients comprise most of the Other cohort. Results. HRQOL data at baseline were reported by 916 pts, enrolled from 189 centers. Of these patients, 82% were White, 12% were Black, and 5% were of another race (Other). Among evaluable patients, the different race groups did not differ statistically by ECOG status or multiple myeloma stage (measured by either the International Staging System or the Durie and Salmon system). The three racial groups differed by age, with the mean (SD) age of Blacks (63 (11)) and Others (63 (13)) being less than that of Whites (68 (11), p<0.0001). Gender was trending, but not statistically significantly different, between races, with males comprising 58% of Whites, 52% of Blacks, and 46% of Others (p=0.1803). HRQOL scores by race are presented here: Overall FACT-MM results indicate that baseline HRQOL does not vary between races, as the main summary scores do not differ statistically, although the FACT-MM Total scores of Blacks and Whites are trending higher than those of Others. Only the emotional and social/family domain scores of the FACT-MM vary statistically, as Blacks show a worse mean score in the social/family domain and a better score in the emotional domain. BPI data (on a scale of 0 [no pain] to 10 [worst pain] do not show a statistically significant difference between races, and the same is true of the five EQ-5D domains (measured on a scale of 1 [no problem] to 2 [some problems] to 3 [incapacity]. Conclusions. Initial results from the Connect MM® Registry indicate that HRQOL at baseline prior to initiation of treatment does not vary by patient race. As such, these results may serve as a baseline reference for future analyses. In particular, as patients proceed through therapy, analyses should be conducted of patients by race, among other factors, to determine whether it may be associated with subsequent clinical outcomes and HRQOL over time. Disclosures: Pashos: Celgene: Membership on an entity's Board of Directors or advisory committees. Durie:Celgene: Membership on an entity's Board of Directors or advisory committees. Rifkin:Celgene: Membership on an entity's Board of Directors or advisory committees. Terebelo:Celgene: Membership on an entity's Board of Directors or advisory committees. Gasparetto:Celgene: Membership on an entity's Board of Directors or advisory committees. Mehta:Celgene: Membership on an entity's Board of Directors or advisory committees. Toomey:Celgene: Membership on an entity's Board of Directors or advisory committees. Abonour:Celgene: Membership on an entity's Board of Directors or advisory committees. Fonseca:Celgene: Membership on an entity's Board of Directors or advisory committees. Narang:Celgene: Membership on an entity's Board of Directors or advisory committees. Shah:Celgene: Membership on an entity's Board of Directors or advisory committees. Swern:Celgene Corporation: Employment, Equity Ownership. Sullivan:Celgene: Employment, Equity Ownership. Street:Celgene: Employment, Equity Ownership. Khan:Celgene: Employment, Equity Ownership.