Go, Ronald S.

Abstract The impact of fluorescence in-situ hybridization (FISH) on outcome in AL amyloidosis remains uncertain. We analyzed the response and overall survival (OS) of 692 AL amyloidosis patients with available FISH testing at diagnosis. First line treatment was categorized as autologous stem cell transplant or three non-transplant regimens (melphalan-based; bortezomib-based, and immunomodulatory drug (IMiD)-based). Forty-nine percent of patients had t(11;14), 37% del 13q/monosomy 13 and 19% had trisomy/tetrasomy. Analysis by abnormality type was restricted to t(11;14) and trisomy/tetrasomy sub-groups as chromosome 13 abnormalities were commonly associated with the other abnormalities. Patients with t(11;14) had lower rate of very good partial response or better (≥VGPR) compared to those lacking t(11;14) (56% vs 70%, P=0.001). By regimen stratification, this difference was maintained for bortezomib-based (52% vs 77%; P=0.004) and IMiD-based therapy (13% vs 54%; P=0.04) (Figure 1). Patients with trisomy/tetrasomy had no difference in the rate of ≥VGPR compared to those who did not (66% vs 63%, P=0.62), with no difference within regimen types. OS was similar between t(11;14)-positive and negative patients (median 43 vs 57 months; P=0.58). However, sub-analysis by regimen type showed a significantly inferior OS among t(11;14)-positive bortezomib-treated patients (median 15 vs 27 months; P=0.05) and t(11;14)-positive IMiD-treated patients (median 12 vs 32 months; P=0.05) (Figure 2). Among t(11;14)-positive bortezomib-treated patients, the OS difference was maintained among favorable-prognosis patients, but was absent for poor-prognosis sub-groups (Table). Trisomy/tetrasomy was associated with inferior OS (median 29 vs 69 months; P=0.001), a difference that was maintained for melphalan (median 15 vs 32 months; P=0.01) and borderline significance for bortezomib (median 14 vs 38 months; P=0.09). Multivariate analysis confirmed an independent effect on OS for trisomy/tetrasomy in the study cohort and for t(11;14) among bortezomib-treated patients. FISH analysis is essential in newly diagnosed AL amyloidosis, as it provides prognostic information among treatment groups and may influence the selection of induction treatment. Patients with t(11;14) should be considered for ASCT at diagnosis. Disclosures Dispenzieri: Celgene: Research Funding; Alnylam: Research Funding; pfizer: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jannsen: Research Funding. Kumar:Glycomimetics: Consultancy; AbbVie: Research Funding; Array BioPharma: Consultancy, Research Funding; Kesios: Consultancy; Onyx: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; BMS: Consultancy; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Kapoor:Amgen: Research Funding; Takeda: Research Funding; Celgene: Research Funding.

Abstract Background: A recent preclinical study revealed an antiproliferative and apoptotic effect of propranolol on MM cell lines. This study was to investigate if propranolol and other beta blocker intake improved survival in MM patients. Methods: Among patients seen at Mayo Clinic, Rochester from 1993 to 2010, we identified those taking propranolol. Age, year of diagnosis, International Staging System (ISS), Mayo Stratification of Myeloma and Risk-Adapted Therapy (mSMART) were used as case-match variables to match propranolol users to two control populations: no beta blocker and other beta-blocker. Cox proportional hazard modeling was utilized to analyze the effect of propranolol and other beta blockers intake on overall survival (OS) and disease-specific survival (DSS). Results: In 3 groups: propranolol (n=52), no beta blocker (n= 136), or other beta blocker (n=84), transplant eligibility was 63.5%, 66.9%, 66.7% respectively (p=0.90). Median age was 63 years. Median follow-up was 86 months. No statistically differences were seen in age, ISS, mSMART or year of diagnosis in 3 groups (p=0.46).In univariate analysis comparing propranolol vs no beta blocker or other beta blocker cohort, 5-year OS rate was 60.2% vs 47% or 64% (p=0.039), and 5-year DSS rate was 71.7% vs 50.3% or 69.1% (p=0.0029). In multivariate analysis adjusted for age, ISS, transplant eligibility, mSMART and year of diagnosis, compared to propranolol intake, no beta blocker group had poorer OS [HR= 2.081; 95% CI (1.353- 3.200); p=0.0008], and DSS [HR=2.833 (1.709-4.697); p<0.0001], but other beta blocker users had no difference in OS [HR =1.145 (0.728-1.803);p=0.56],and DSS [HR= 1.276 (0.745-2.185); p=0.38]. Conclusion: Propranolol and other beta-blocker intake among MM patients were equally associated with a more favorable OS and DSS. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures Lust: Senesco: PI Other.

Abstract Background Suppression of uninvolved immunoglobulins is a common finding in multiple myeloma and the preservation of uninvolved immunoglobulins at diagnosis is associated with improved progression-free and overall survival. However, little is known about the impact of myeloma treatment on levels of uninvolved immunoglobulins, and the link between changes in uninvolved immunoglobulins during therapy and treatment response, disease progression and survival. Methods We identified patients who received therapy for newly diagnosed multiple myeloma at our institution between 2001 and 2014, and who had data available on absolute lymphocyte count (ALC) and quantitative uninvolved immunoglobulins (Ig) before commencing treatment. The ALC and levels of uninvolved Ig after 4 cycles of therapy were abstracted from the electronic medical record; patients who switched or stopped treatment, or died, before this time point were excluded. To assess change in ALC, the percentage difference in ALC between baseline and 4 cycles was calculated; for uninvolved Ig, the average of the percentage difference between baseline and 4 cycles for each uninvolved Ig (IgA and IgM for IgG myeloma, IgG and IgM for IgA myeloma, IgG and IgA for IgM and IgD myeloma, and IgG, IgM and IgA for light-chain only myeloma) was calculated. Treatment response at 4 cycles was retrospectively assigned according to International Myeloma Working Group criteria. Time to treatment failure (TTF) was defined as time from start of initial therapy to start of next line of therapy or death (if no additional treatment was received). A landmark analysis was used to calculate overall survival (OS) from the date of follow-up after 4 cycles of therapy. The Kruskal-Wallis, Chi-Square, and log rank tests were used to detect differences in medians, proportions, and survival times respectively. Results A total of 421 patients were included in this analysis. The median age was 63 years (range 33-91), 254 patients (60.3%) were male and median follow-up was 6.5 years (95% CI 5.6-7.3); the vast majority of patients had IgG (n=247 [58.7%]), IgA (n=98 [23.3%]) or light-chain only myeloma (n=68 [16.2%]). First line therapy comprised of pulse-dose dexamethasone (DEX, n=92 [21.9%]), lenalidomide-dexamethasone (RD, n=176 [41.8%]), bortezomib-dexamethasone (VD, n=22 [5.2%]), bortezomib-cyclophosphamide-dexamethasone (VCD, n=84 [20.0%]), and bortezomib-lenalidomide-dexamethasone (VRD, n=47 [11.2%]). Across the entire cohort, the median change in ALC and uninvolved Ig after 4 cycles of treatment was -11.0% (range: -92.7 to +718.8) and +9.0% (-77.7 to +1094.4) respectively; treatment with VCD was associated with the greatest median declines in ALC (DEX: -0.1%; RD: -9.9%; VD: -20.8%; VCD: -40.9%; VRD: -15.3%) and uninvolved Ig (DEX: -0.5%; RD: +15.5%; VD: +44.0%; VCD: -14.0%; VRD: +76.0%, both p<0.001). Conversion from suppression to normalization of the primary uninvolved Ig (IgA in IgG myeloma, and IgG in all other myeloma types) after 4 cycles was seen more frequently with the use of RD (13.1%) and VRD (12.8%) compared to DEX (4.7%), VCD (1.3%), or VD (4.8%), χ2=21.8, p=0.040. When considering only patients in whom the primary uninvolved Ig remained suppressed between baseline and 4 cycles, a ≥25% reduction in the primary uninvolved Ig occurred more frequently with the use of DEX (51.5%) and VCD (34.5%) compared to RD (24.8%), VD (23.5%) or VRD (25.7%), χ2=15.1, p=0.005 (Table 1). Although an average reduction in uninvolved Ig between baseline and 4 cycles (ΔIg<0) was independently associated with a lower likelihood of achieving very good partial response (VGPR) of better on multivariate analysis adjusting for age, sex and treatment regimen (OR=0.40 [0.24-0.63], p<0.001), there were no differences in TTF (2.0yrs vs. 2.0yrs, p=0.783) or OS (8.0yrs vs. 8.0yrs, p=0.721) between patients with ΔIg<0 (n=169) and those with ΔIg≥0 (n=222). Conclusions Myeloma treatments produce differential impacts on immune parameters, with VCD causing the greatest reduction in lymphocytes and uninvolved Ig, implying general targeting of plasma cells, in comparison to lenalidomide, which appeared to be more tumor-specific with relative sparing of lymphocytes and uninvolved Ig. While an average decrease in uninvolved Ig was an independent predictor of a lower likelihood of achieving VGPR or better after 4 cycles of therapy, it was not associated with a shorter TTF or poorer OS. Disclosures Kumar: BMS: Consultancy; Glycomimetics: Consultancy; Onyx: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Kesios: Consultancy; Millennium: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; AbbVie: Research Funding. Dispenzieri:GSK: Membership on an entity's Board of Directors or advisory committees; Prothena: Membership on an entity's Board of Directors or advisory committees; pfizer: Research Funding; Jannsen: Research Funding; Alnylam: Research Funding; Celgene: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kapoor:Amgen: Research Funding; Celgene: Research Funding; Takeda: Research Funding. Bergsagel:Amgen, BMS, Novartis, Incyte: Consultancy; Novartis: Research Funding.

Abstract Background We performed a population-based study to determine the natural history of monoclonal gammopathy-associated malignancies (MGAM) including multiple myeloma, lymphoplasmacytic lymphoma, and Waldenstrom's macroglobulinemia that were considered smoldering at the time of cancer diagnosis. We compared the clinical outcomes among those with and without a prior monoclonal gammopathy of undetermined significance (MGUS) follow-up. Methods Data were obtained from the Surveillance Epidemiology and End Results (SEER) database linked to Medicare claims. We considered patients age ≥ 67 years with MGAM diagnosed from 1994-2005. We excluded those who were diagnosed by autopsy or death certificate only, had invasive cancers within 5 years prior to MGAM diagnosis, prior diagnosis of MGAM, lacked date of either diagnosis or death, lacked complete Medicare parts A/B coverage 15 months prior to or 3 months after MGAM diagnosis (or to date of death, if death was within 3 months), and receiving dialysis more than 3 months before MGAM diagnosis. Major complications including acute kidney injury, cord compression, dialysis-requirement, fracture, and hypercalcemia at time of disease progression were obtained from diagnosis and procedure claims. MGUS follow-up was defined as having a diagnosis claim 4-15 months prior to smoldering MGAM diagnosis. Smoldering MGAM was defined as absence of all of the following criteria: any major complication claims, any treatment claims, and death because of MGAM within 12 months of MGAM diagnosis, while progression to active MGAM was defined by the presence of any of these criteria. Results At the time of MGAM diagnosis 2,189 had smoldering disease. Of these, 1,753 (80.1%) progressed to active MGAM with a median time-to-progression of 17 months. Progression to active MGAM were identified by claims reflecting the development of major cancer complications (34.9%), administration of cancer therapy (59.5%), both (0.7%), or report of death from MGAM without major complication or treatment claims (4.9%). The cumulative probability of progression by Kaplan-Meier analysis was 40.2%, 72.9%, 85.7%, and 96.1%, at years 1, 3, 5, and 10, respectively. Among those who progressed, 35.6% developed one or more major complications including acute kidney injury (13.0%), cord compression (1.8%), dialysis-requirement (2.0%), fracture (15.6%), and hypercalcemia (5.6%). A prior MGUS follow-up occurred in 199 (9.1%) smoldering MGAM patients. The time to progression for smoldering MGAM patients with a prior MGUS follow-up was similar to those without MGUS follow-up (P = 0.52). Multivariable analysis factoring in year of smoldering MGAM diagnosis, type of cancer, age, sex, race, place of residence, SEER site, median annual household income, Charlson co-morbidity index, and prior MGUS follow-up showed that older age, higher Charlson co-morbidity scores, and diagnosis of multiple myeloma as independent predictors of progression (Table). Conclusions Our population-based study shows that most patients with smoldering MGAM diagnosed at age ≥ 67 years progress to active disease within the first three years. Those with a prior history of MGUS follow-up progress at a similar rate compared to those without such a history. The determinants of progression at diagnosis are age, number of co-morbidities, and type of MGAM. Disclosures: No relevant conflicts of interest to declare.

Abstract Background: Pomalidomide has demonstrated excellent activity in patients with relapsed, lenalidomide refractory, multiple myeloma (MM). Between November 2007 and March 2012, we enrolled 285 patients with relapsed MM on 5 sequential phase 2 trials; patients received pomalidomide at 2mg or 4 mg daily with weekly dexamethasone (Pom/dex). The approved dose of pomalidomide is 4 mg for 21 of 28 days. We wished to compare efficacy, tolerability and long-term outcomes between cohorts treated with 2 mg or 4mg daily continuously and 4mg daily for 21/28 days. Methods: After excluding two ineligible patients, 283 patients with lenalidomide refractory, relapsed MM from 5 sequential cohorts were analyzed. These patients were divided into 3 groups: Group1 received Pom 2mg for 28/28 day cycle (N= 69), Group 2 received Pom 4 mg for 28/28 day cycle (N= 95) and Group 3 received Pom 4mg for 21/28 day cycle (N= 119). All patients received oral dexamethasone given 40 mg daily on days 1, 8, 15, and 22. Response was assessed by the IMWG Uniform Response criteria. All patients received aspirin 325 mg daily for DVT prophylaxis or full dose anticoagulation. Results: The median age was 63 years (32-85); 35% were female. The median time from diagnosis was 53 months and the median number of prior regimens was 4. 127 (46%) had high-risk molecular markers. Prior therapies (% received) included lenalidomide (100%), thalidomide (46%), bortezomib (78%), autologous stem cell transplant (71%), and allogeneic transplant (4%). The median follow-up is 16.4 months (3.2-64.4). Forty eight percent are alive and 26% remain progression free; 15 patients are continuing to receive treatment. Frequency of AEs by groups are shown in Table 1. The most notable difference is grade 3+ neutropenia seen in 39% of group 1 and 56% and 57% of groups 2 and 3. Confirmed responses of PR or better were seen in 29% (group1), 35% (group2) and 24% (group3). Median duration of response (DOR) was 14.1 months (group1), 14.5 months (group2) and 10.2 months (group3). Median PFS was 5.5 months (group1), 6.9 months (group2) and 4.3 months (group3). Although the dose level cohorts were sequential rather than randomized, we compared OS between the dose levels in an exploratory manner. There was no significant difference in OS between dose levels (p=0.26). Median overall survival (OS) was 16.6 months (group1), 21.9 months (group2) and 16.0 months (group3). Conclusions: Pom/dex is active and well tolerated even in heavily pretreated patients Responses are durable. Response rates and overall toxicity are similar between the 2 mg and 4 mg doses. Neutropenia is more common in those receiving doses of 4mg daily or for 21/28 days compared to those receiving 2 mg daily. Table 1. All Grades Grade 3+ 2mg 28 Day 4mg 28 Day 4mg 21 Day 2mg 28 Day 4mg 28 Day 4mg 21 Day Anemia 68% 58% 74% 14% 15% 27% Lymphopenia 22% 51% 11% 16% 32% 8% Neutropenia 71% 82% 77% 39% 57% 56% Thrombocytopenia 51% 61% 63% 10% 9% 23% Leukopenia 59% 77% 72% 26% 38% 39% Pneumonia 7% 11% 12% 6% 7% 11% Fatigue 51% 65% 60% 9% 5% 8% Neuropathy 28% 32% 28% 0% 3% 0% Elevated Blood Glucose 10% 21% 8% 4% 6% 3% Pneumonitis 3% 2% 3% 3% 1% 1% VTE (Thrombosis) 3% 3% 3% 1% 3% 3% Secondary Malignancy 0% 2% 1% 0% 2% 1% Figure1. Kaplan Meier Overall Survival Curves Figure1. Kaplan Meier Overall Survival Curves Disclosures Lacy: Celgene: Research Funding. Fonseca:Medtronic, Otsuka, Celgene, Genzyme, BMS, Lilly, Onyx, Binding Site, Millennium, AMGEN: Consultancy, patent for the prognostication of MM based on genetic categorization of the disease. He also has sponsored research from Cylene and Onyx Other, Research Funding. Bergsagel:Novartis: Research Funding; Constellation Pharmaceutical: Research Funding; OncoEthix: Research Funding; MundiPharma: Research Funding. Stewart:Novartis: Consultancy; Celgene: Consultancy; Bristol Myers Squibb: Consultancy; Array BioPharma: Consultancy; Sanofi: Consultancy; Takeda Pharmaceuticals International Co.: Research Funding. Reeder:Millennium, Celgene, Novartis: Research Funding. Mikhael:Onyx: Research Funding; Celgene: Research Funding; Sanofi: Research Funding; Novartis: Research Funding.

Abstract Background: Approximately 1,000 acute promyelocytic leukemia (APL) patients are diagnosed in the US annually. APL has the highest cure and early mortality rates of all acute leukemias. The availability of all trans-retinoic acid (ATRA) in 1995 and arsenic trioxide in 2000 has further improved the overall survival (OS). However, whether there is uniform improvement in OS across demographic subgroups and if sooner time-to-treatment (TTT) reduces early mortality are unknown. We used the National Cancer Data Base (NCDB), a nationwide oncology registry covering 70% of the US cancer population to answer these questions. Methods: We identified patients with APL diagnosed from 1998-2011 using ICD-O-3 code 9866. Survival functions were estimated using the Kaplan-Meier method and 30-day mortality was estimated as 1-survival at 30 days. We compared OS according to demographic subgroups (gender, age [18-40, 41-64, and >65 years], race [White, Black, Native American, Asian/Pacific Islander, and other], and ethnicity) across years of diagnosis (Period [P] 1: 1998-2001, P2: 2002-2006, and P3: 2007-2011). For 30-day mortality, we compared the rates according to demographic subgroups and time periods and determined the effect of TTT (days from APL diagnosis to ATRA and/or chemotherapy). For this analysis we included only patients treated within 30 days of diagnosis and those diagnosed from 2003 to 2011. TTT was grouped as 0, 1, 2, or >3 days. We used mixed-effects logistic regression model to obtain odds ratio comparing treatment delays. Our model accounted for multiple subjects per facility with a random intercept and was adjusted for gender, Charlson-Deyo score, and year of diagnosis. Results: Characteristics: There were 8,084 APL patients in our study. The median age at diagnosis was 51 (24% were older than 65) years and 50% were females. White race (85%) was the most common, followed by black (11%) and Asian (3%). Twelve percent were Hispanic in origin. Slightly more patients (54.8%) were treated in academic centers. Thirty seven percent had either Medicaid or Medicare insurance. OS: Race had no impact on OS, although Asians had a trend towards improved OS (P=0.06). Both females and young age affected OS favorably (P <0.0001). In general, OS improved over the three time periods (P=0.002). Across Periods 1-3, we observed significant improvement in OS among the males (P=0.03), 18-40 (P=0.035) and 41-64 (P=0.005) age groups, Whites (P=0.012), and non-Spanish/Hispanics (P=0.002), but not among their counterparts. 30-day mortality rate: Age above 65 years was associated with highest 30-day mortality (33%). Similarly male gender had statistically significant higher 30-day mortality (shown in the Figure). There was no statistically significant difference among Periods 1-3. As expected, untreated patients had an increased risk of death versus treated (HR=1.9, confidence interval 1.7-2.1). TTT: A third (33.5%) of the patients was treated within two days of APL diagnosis. TTT was not independently associated with lower 30-day mortality rate (shown in the Table). Presence of disseminated intravascular coagulopathy (DIC) data was not available to analyze. Conclusions: From 1998-2011, the OS of APL continued to improve but not uniformly across demographic subgroups. In contrast, the 30-day mortality did not improve in the same time period. Both Age above 65 and male gender predicted worse 30-day mortality and OS. Our study did not find a favorable association between shorter TTT and lower 30-day mortality rate. Our study was not able to study these findings among different risk groups. Disclosures Al-Kali: Celgene: Research Funding. Tibes:TetraLogic Pharmaceuticals: Research Funding.

Abstract Background: Cytogenetic evaluation using fluorescence in situ hybridization (FISH) at the time of diagnosis is essential for initial risk stratification in multiple myeloma. Despite the absence of cytogenetic high-risk abnormalities a subset of patients does experience poor overall survival comparable high-risk disease (i.e. median overall survival less than three years after diagnosis). We aimed to identify demographic, clinical, and cytogenetic characteristics predicting poor three-year overall survival in patients with standard-risk cytogenetics. Methods: We studied 428 patients who were diagnosed with multiple myeloma between July 2004 and July 2014 at Mayo Clinic Rochester, underwent FISH evaluation within six months of diagnosis, and received treatment with novel agents (immunomodulator, proteasome-inhibitor, or a combination thereof). Patients with high- and intermediate-risk cytogenetics as well as patients lost to follow-up within three years were excluded. High-risk cytogenetics were defined as del(17p), t(14;16), and t(14;20). Intermediate-risk cytogenetics were defined as t(4;14) and gain(1q). Bone marrow aspirates were evaluated for deletions, monosomies, trisomies, and tetrasomies using chromosome- or centromere-specific FISH probes. IGH rearrangements were evaluated using an IGH break-apart probe and evaluating up to five potential partners (FGFR3, CCND1, CCND3, MAF, and MAFB). A multivariable-adjusted logistic regression model was used to assess the associations between the parameters of interest and three-year overall survival. Discrimination and calibration of the model were evaluated using the c-statistic and the Hosmer-Lemeshow test, respectively. The odds ratios of the identified predictors were rounded up to the next integer and assigned as points in a scoring system. Receiver operating characteristic analysis was used to determine the optimal cut-point and associated test performance characteristics. P-values below 0.05 were considered statistically significant. Results: The median age at diagnosis was 65 years (31 - 95), 259 (61%) of the patients were male. The median overall survival was 7.4 years (6.1 - 8.6) for the entire cohort (n = 428), 10.5 years (8.3 - NR) for those who survived at least three years (n = 327, 76%), and 1.6 years (1.2 - 1.7) for those who did not survive three years after diagnosis (n = 101, 24%). The factors associated with poor three-year overall survival and the derived scoring system are summarized in Table 1. Conclusions: Patients with multiple myeloma and standard-risk cytogenetics are a heterogeneous group. One fourth of the patients are experiencing less than three years of overall survival after diagnosis. Stage, age, extent of bone marrow involvement, karyotype, and platelet count at the time of diagnosis were helpful in identifying patients at risk for poor three-year overall survival. These findings emphasize the importance of further risk stratification in this patient population and warrant external validation. Disclosures Dispenzieri: Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jannsen: Research Funding; pfizer: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Alnylam: Research Funding. Kapoor:Takeda: Research Funding; Amgen: Research Funding; Celgene: Research Funding. Kumar:AbbVie: Research Funding; BMS: Consultancy; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Noxxon: Consultancy, Honoraria; Janssen: Research Funding; Skyline: Consultancy, Honoraria.

Abstract Background: Prior studies on the risk of progression of monoclonal gammopathy of undetermined significance (MGUS) into lymphoplasmacytic malignancies (LPMs) were almost exclusively in the White populations, comprised of limited number of patients residing in relatively small geographic areas, or included patients mostly detected by serologic screening as part of clinical study (as opposed to detected clinically during evaluation of symptoms suspicious for LPMs). Similar epidemiologic studies in a large, racially diverse population are lacking. Methods: We conducted a retrospective analysis of incident MGUS patients diagnosed from 2006-2013 using theOptum Labs Data Warehouse, a large database including administrative claims information on >110 million privately insured and Medicare Advantage enrollees throughout the United States. We identified patients with a diagnosis of MGUS (ICD9: 273.1) with 1-5 years of continuous enrollment. Each enrollment cohort based on the duration of follow-up (1-, 2-, 3-, 4-, or 5-year) was analyzed individually to help estimate the progression to cancer. We excluded patients who were diagnosed with LPMs within three months of MGUS diagnosis. We calculated the rate of progression into LPMs (chronic lymphocytic leukemia [CLL], light chain amyloidosis [AL], multiple myeloma [MM], non-Hodgkin lymphoma [NHL], and Waldenström macroglobulinemia [WM]) expressed as number per 100 person-years. Results: There were 14,728 MGUS patients for a total of 21,288 person-years of follow-up. The distributions of the number of patients and events according to the cohorts classified by duration of follow-up were: 1-year (14,728 patients; 243 events), 2-year (10,644 patients; 307 events), 3-year (7,333 patients; 299 events), 4-year (4,497 patients; 237 events), and 5-year (2,960 patients; 191 events). The rates of progression to LPMs were consistently highest during the first year after MGUS diagnosis (~2.00), generally declined by half during the second year and remained fairly stable thereafter (~1.00; Table 1). The rates of progression into LPMs overall as well as by demographics are shown in Table 2. The risk of progression was significantly higher among men (P < 0.01) and older patients (>50 years; P = 0.03) compared to their counterparts but similar among races (P = 0.15). Of the 243 patients who progressed, the distribution of LPMs was MM (70.0%), NHL (13.2%), WM (12.3%), AL (4.1%), and CLL (0.4%). Conclusions: Among patients withMGUS, the risk of transformation into LPMs is continuous although twice as high during the first year after MGUS diagnosis compared to subsequent years. The risk of transformation was higher among men and those who were older but did not differ among the racial subgroups. Our findings can be used to develop an optimal risk-based MGUS follow-up strategy that incorporates not only serum biomarkers but also demographic factors. Disclosures No relevant conflicts of interest to declare.

Abstract Introduction: A recent study revealed an antiproliferative and apoptotic effect of propranolol on multiple myeloma (MM) cells. Our previous small matched case-control study showed longer survival in patients with propranolol and other beta-blockers (BB) intake than those without. This larger scale study was conducted to confirm the positive association of BB and MM survival. Methods: We identified 1971 newly diagnosed pts seen at Mayo Clinic between 1995 and 2010. Cardiac medication usage after diagnosis of MM was extracted from patient records and categorized based on BB intake. Cause of death was collected with death due to MM as the primary interest event and death due to cardiac disease or other reasons as competing risk events. The primary outcomes were MM disease-specific survival (DSS) and overall survival (OS). Cumulative incidence functions and Kaplan-Meier method were used to estimate the 5-year cumulative incidence rate (CIR) of MM death and OS rate, respectively. DSS and OS were compared by Gray's test and log-rank test, respectively. Multivarable Cox proportional hazard models were used to estimate the adjusted cause-specific HR (HRCSadj.) and hazard ratio (HRadj.) for DSS and OS, respectively, adjusting for demographics, disease characteristics, diagnosis year, and various chemotherapies. Results: 930 (47.2%) of MM patients had no intake of any cardiac medications; 260 (13.2%) had BB only; 343 (17.4%) used both BB / non-BB cardiac medications; and 438 patients (22.2%) had non-BB cardiac drugs. Five-year CIR of MM death and OS rate were shown in table. Superior MM DSS was observed for BB only users, compared to patients without any cardiac drugs (HRCSadj., .53, 95% confidence interval [CI], .42-.67, padj.<.0001) and non-BB cardiac drugs users (HRCSadj., .49, 95% CI, .38-.63, padj.<.0001). Patients received both BB and other cardiac drugs also showed superior MM DSS than non-cardiac drugs users (HRCSadj.., .54, 95% CI, .44-.67, padj.<.0001) and non-BB cardiac drug users. (HRCSadj., .50, 95% CI, .40-.62, padj.<.0001). MM DSS does not differ between BB users with and without other cardiac drugs (padj.=0.90). Multivariable analysis showed the same pattern for OS. None of the MM therapies impacted the differences in DSS and OS among BB intake groups (interaction padj.>.60). Conclusion: MM patients with BB intake showed reduced risk of death due to MM and overall mortality compared to patients who used non-BB cardiac or never used cardiac drugs. The result warrants further investigation for anti-cancer effect of BB in MM. Disclosures Shi: Mayo Clinic: Employment. Kumar:Onyx: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Research Funding; Glycomimetics: Consultancy; Janssen: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; BMS: Consultancy; Kesios: Consultancy. Gertz:NCI Frederick: Honoraria; Celgene: Honoraria; Med Learning Group: Honoraria, Speakers Bureau; Research to Practice: Honoraria, Speakers Bureau; Alnylam Pharmaceuticals: Research Funding; Novartis: Research Funding; Prothena Therapeutics: Research Funding; Ionis: Research Funding; Annexon Biosciences: Research Funding; GSK: Honoraria; Sandoz Inc: Honoraria. Kapoor:Celgene: Research Funding; Amgen: Research Funding; Takeda: Research Funding. Dispenzieri:pfizer: Research Funding; Celgene: Research Funding; Alnylam: Research Funding; Jannsen: Research Funding; GSK: Membership on an entity's Board of Directors or advisory committees; Prothena: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Background: The incidence for acute myelogenous leukemia (AML) is on the rise in the United States (US). Roughly 20,000 new AML patients are expected to occur in 2016 in the US (data from Surveillance Epidemiology and End Results Program). It is mainly a disease of older individuals with median age of 67 years. Unfortunately, most patients are not cured. Recent data suggest that early referral for hematopoietic stem cell transplant (HSCT) leads to more favorable outcomes, particularly those with non-good risk cytogenetics compared to alternate therapies. The objective of our study was to assess the use of upfront HSCT among AML patients with a focus on patients with non-good risk cytogenetics and determine disparity in its access based on sociodemographic and regional considerations. Methods: We analyzed data obtained from National Cancer Data Base (NCDB) Participant User Files for patients diagnosed with AML between 2004 and 2013 using the International Classification of Diseases for Oncology version 3 (ICD-O-3) codes 9840-9861, 9865-9874, 9891-9931. The data is collected prospectively by joint program of Commission on Cancer (CoC) and American Cancer Society. It covers nationwide oncology outcome from more than 1,500 CoC-accredited hospitals. Over 70% of all newly diagnosed cancer cases in the US are captured by NCDB. Since unique ICD-O-3 codes exist for the good-risk but not for intermediate- or poor-risk AML, we categorized the AML subtypes as good risk or non-good risk for analytic purposes. We considered patients with t(15;17), inv(16) and t(8;21) with corresponding ICD-O codes of 9871, 9896, and 9866, as good-risk patients. All others were considered non-good risk. Proportion of HSCT usage was estimated in various subgroups with 95% confidence intervals calculated using robust estimates of standard error. Results: We identified 80,087 patients who were diagnosed with AML between 2004 and 2013. Majority of these patients were Whites (85.9%), males (53.8%) and between the ages of 40 and 79 years (71.5%). The overall use of upfront HSCT increased consistently over time. This occurred predominantly among the non-good risk AML from a rate of 6.5% in 2004 to 12.5% in 2013 (Figure). Non-good risk patients who were Black, had Medicare insurance, with lower annual household income, and treated at facilities located in the East, South and Central parts of US ( AL, KY, MS, TN) had less access to HSCT (Table). Conclusion: The use of upfront HSCT in AML has almost doubled in the past decade, predominantly among those with non-good risk cytogenetics. Nevertheless, we found substantial disparity among sociodemographic and geographic subgroups. Future studies should try to understand and address how to bridge this gap. Disclosures No relevant conflicts of interest to declare.