Lust, John A.

Abstract Background: Renal impairment is a common feature of multiple myeloma (MM) seen in over a quarter of newly diagnosed patients (pts). Studies have confirmed the presence of renal impairment (RI) as a strong predictor of inferior survival in MM. Some studies have also indicated that reversibility of RI is associated with improved survival. However, it is not clear if normalization of renal function improves the outcome to that expected for MM pts without RI at diagnosis. Methods: We evaluated 1,135 consecutive pts with newly diagnosed MM seen at the Mayo Clinic, Rochester between December 2002 and January 2011. Renal function was assessed by the estimated creatinine clearance (CrCl) which was calculated by the modified MDRD formula. We examined these pts for improvement in renal function based on their CrCl at diagnosis and their highest CrCl during their disease course. RI was defined as having a CrCl of < 60. Pts were categorized based on their renal function at diagnosis and response to therapy: Group 1- CrCl >60 at diagnosis, Group 2- CrCl <60 at diagnosis but improved to >60 after therapy and Group 3- CrCl <60 at diagnosis and remained <60 after therapy. The degree of restoration of renal function was evaluated according to the IMWG criteria. Survival analysis was performed by the Kaplan-Meier method and differences assessed using the log rank test. Results: The median age at diagnosis was 65 years (range; 22 - 93) and 682 (60%) were male. The median follow up for the entire group from diagnosis was 73 mos (95% CI; 69 - 77). At diagnosis, 123 (11%) pts had a CrCl < 30, 322 (28%) had a CrCl of 30-59 and 690 (61%) had a CrCl >60. Most pts (N=754, 67%) received novel agent induction (NAI) therapy. The median PCLI was 0.7 (range: 0 – 22) and 91 (21%) pts had high-risk cytogenetics by FISH. The median OS for the pts with CrCl at diagnosis of < 30, 30-59 and >60 were 41 mos, 60 mos and not reached respectively (P < 0.001). Of the 445 patients with RI, the median absolute creatinine and CrCl at diagnosis were 1.6 mg/dL (range: 1 – 11) and 44 (range: 4 – 59) respectively. Among pts with RI, any improvement in CrCl was seen in 295 (66%) with median time to highest CrCl of 5 months and 228 (51%) had complete reversal of their RI. The median OS for pts with RI at diagnosis receiving and not receiving NAI therapy was not reached (NR) vs. 46 mos (P < 0.001). The median OS for Groups 1, 2 and 3 were NR, 60 and 49 mos respectively (Figure 1, P < 0.001). At a 6 month landmark analysis, the median OS for Groups 1, 2 and 3 were NR, 67 and 62 mos respectively (P < 0.001). The complete renal response and no renal response rates for pts with RI at diagnosis receiving and not receiving NAI induction therapy was (57% vs. 44%, P=0.004) and (29% vs. 39%, P=0.04) respectively. In a univariable analysis, presence of RI at diagnosis, no NAI therapy, older age, ISS stage 3, high-risk FISH, elevated PCLI, diagnosis prior to 2007 and increased LDH were found to predict for worse OS; however only older age (P<0.001), high-risk FISH (P=0.037) and lack of NAI therapy (P=0.023) retained their negative prognostic significance in a multivariable analysis. Conclusion: MM pts with RI treated with novel agent induction therapy demonstrate improved responses in their renal function and OS. The results also demonstrate improved outcome for pts with improvement in renal function, but it remains inferior to pts with normal renal function at diagnosis. These results have implications for early treatment strategies for pts at risk of developing renal insufficiency. Figure 1: OS based on improvement in CrCl upon receiving treatment Figure 1:. OS based on improvement in CrCl upon receiving treatment Figure 2 Figure 2. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Prior studies suggest that the presence of >5% polyclonal plasma cells (pPCs) among total plasma cells (PCs) within the bone marrow (BM) is associated with a longer progression-free survival, higher response rates, and lower frequency of high-risk cytogenetic abnormalities in patients with newly diagnosed multiple myeloma (MM). However, the incidence and prognostic utility of this factor in patients with relapsed and/or refractory MM has not been previously evaluated. Thus, we evaluated the prognostic value of quantifying the percentage of pPCs among the total PCs in the BM of patients with actively relapsing MM. Methods: We evaluated all MM patients with actively relapsing disease (biochemical and/or symptomatic) seen at the Mayo Clinic, Rochester, from 2012 to 2013, who had BM samples evaluated by seven-color multiparametric flow cytometry. All patients had at least 24 months of follow-up from the date of flow evaluation. Cell surface antigens were assessed by direct immunofluorescence antibodies for CD45, CD19, CD38, CD138, cytoplasmic Kappa and Lambda Ig light chains, and DAPI nuclear stain. The flow cytometry data was collected using the Becton Dickinson FACSCanto II instruments that analyzed 150,000 events (cells); this data was then analyzed by multi-parameter analysis using the BD FACS DIVA Software. PCs were selectively analyzed through combinatorial gating using light scatter properties and CD38, CD138, CD19, and CD45. Clonal PCs were separated from pPCs based on the differential expression of CD45, CD19, DAPI (in non-diploid cases), and immunoglobulin light chains. The percentage of pPCs was calculated in total PCs detected. Survival analysis was performed by the Kaplan-Meier method and differences were assessed using the log rank test. Results: There were 180 consecutive patients with actively relapsing MM who had BM biopsies analyzed via flow cytometry as part of their routine clinical evaluation. The median age of this group was 65 years (range: 40 - 87); 52% were male. At the time of this analysis, 104 patients had died, and the 2-year overall survival (OS) rate for the cohort was 58%. The median number of therapies received was 4 (range: 1 - 15). Of these patients, 61% received a prior ASCT, and almost all (99%) received prior regimens containing either immunomodulators or proteasome inhibitors. There were 55 (30%) patients with >5% pPCs among the total PCs in their BM. The median percentage of pPCs among total PCs in these 55 patients was 33% (range: 5 - 99). The median OS for those with >5% pPCs was not reached compared with 22 months for those with <5% pPCs (P = 0.028; Figure 1). Patients with <5% pPCs PCs had a higher likelihood of high-risk FISH cytogenetics compared with the rest of the patients. In a univariate analysis, increasing number of pPCs was associated with an improved OS, while higher labeling index, number of prior therapies, and the presence of high-risk FISH cytogenetics were associated with a worse OS. In a multivariate analysis, only the increasing number of pPCs (P = 0.006), higher labeling index (P = 0.0002) and number of prior therapies (P = 0.003) retained statistical significance. Conclusion: Quantitative estimation of the percentage of pPCs among the total PCs in the BM of patients with actively relapsing MM was determined to be a predictor of worse OS. As such, this parameter is able to identify a group of patients with MM with actively relapsing disease who have a particularly poor outcome. Further studies evaluating its biological significance are warranted. Figure 1 Kaplan-Meier curve comparing OS between patients with ≥5% pPCs and <5% pPCs among the total PCs in their BM. Figure 1. Kaplan-Meier curve comparing OS between patients with ≥5% pPCs and <5% pPCs among the total PCs in their BM. Disclosures Kapoor: Celgene: Research Funding; Amgen: Research Funding; Takeda: Research Funding. Gertz:Prothena Therapeutics: Research Funding; Novartis: Research Funding; Alnylam Pharmaceuticals: Research Funding; Research to Practice: Honoraria, Speakers Bureau; Med Learning Group: Honoraria, Speakers Bureau; Celgene: Honoraria; NCI Frederick: Honoraria; Sandoz Inc: Honoraria; GSK: Honoraria; Ionis: Research Funding; Annexon Biosciences: Research Funding. Kumar:AbbVie: Research Funding; Noxxon Pharma: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Millennium: Consultancy, Research Funding; Kesios: Consultancy; Glycomimetics: Consultancy; BMS: Consultancy.

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: 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: 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 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 Eukaryotic translation initiation factor 5A (eIF5A) has been implicated in the regulation of cell proliferation, apoptosis, and inflammation. SNS01-T is a novel therapeutic with a dual mechanism of eIF5A modulation: inducing cell death via siRNA-mediated inhibition of hypusinated eIF5A while simultaneously causing over-expression of pro-apoptotic eIF5AK50R via a DNA plasmid with a B-cell promoter to induce tumor cell death, using a PEI vector. SNS01-T significantly inhibits tumor growth and increases survival in mouse models of myeloma (MM), mantle cell and diffuse large B-cell lymphoma. Methods This is an open label, phase 1-2 dose escalation study in pts with refractory B-cell cancers, comprising 4 SNS01-T dose cohorts: 0.0125, 0.05, 0.2 and 0.375 mg/kg twice weekly IV for 6 weeks. Key inclusion criteria are: MM per IMWG criteria or lymphomas or plasma cell leukemia with histologic confirmation; measurable disease, relapsed or refractory after ≥2 prior regimens; not eligible for standard therapy known to extend life expectancy. Primary endpoints are safety and tolerability of SNS01-T. Secondary endpoints include pharmacokinetics, tumor response (M protein, % plasma cells, radiologic response) and time to relapse or progression. Efficacy assessments were performed at baseline and after 12 infusions in all pts (week 6); myeloma pts were also assessed at week 3. Results All cohorts will have completed enrollment in August 2014 and dosing in cohort 4 will be complete by September. A total of 21 pts have been treated, of whom 18 currently have data available. Demographics are provided in Table 1. Abstract 4464. Table 1:DemographicsSNS01-T DoseOverall(n=18)0.0125 mg/kg(n=6)0.05 mg/kg(n=4)0.2 mg/kg(n=4)0.375 mg/kg(n=4)Median age (range)63 (55-77)61.5 (57-66)63 (60-77)68 (66-74)58 (55-71)Male, n (%)12 (67)5 (83)03 (75)4 (100)Caucasian, n (%)17 (94)6 (100)3 (75)4 (100)4 (100)Median weight in kg (range)84 (53-117)81 (69-103)58 (53-87)86 (77-92)97 (81-117)Median performance status (range)1 (0-2)1 (0-1)1 (0-2)0 (0-2)1 (0-1)Cancer type, n (%) Multiple myeloma DLBCL15 (83) 3 (17)6 (100) 03 (75) 1 (25)2 (50) 2 (50)4 (100) 0Median prior therapies (range)5 (2-17)4.5 (3-12)6.5 (2-13)7.5 (2-17)7 (5-14) Treatment-emergent adverse events (TEAE) were reported for all pts. The most frequently reported System Organ Classes were General Disorders and Administration Site Conditions (72%) and Gastrointestinal Disorders (56%), with somewhat higher reporting frequency in dose cohorts 3 and 4. The most commonly reported AEs were fatigue (50%), nausea (33%), infusion-related reaction (33%), chills (28%), thrombocytopenia (22%) and pyrexia (17%). Thrombocytopenia, nausea, fatigue, infusion reaction appeared to show some degree of dose relationship. Grade ≥3 TEAEs occurred in 50% of pts with no obvious dose relationship. The only grade ≥3 TEAE reported in >1 pt was thrombocytopenia (17%). There have been no treatment-related deaths. There was 1 DLT at dose level 4 (0.375 mg/kg). Pt 51-001 did not receive premedication prior to the third infusion of SNS01-T and consequently experienced a grade 4 infusion reaction, from which all symptoms resolved within 24 hours. Study treatment was discontinued and the protocol was amended to require the following premedication at each SNS01-T infusion: a corticosteroid, antihistamine and acetaminophen are obligatory, plus an opioid as clinically indicated. Preliminary efficacy was explored. To date, 2 pts have shown stable disease of myeloma at week 3 with some decrease in serum and urine disease markers and one pt with DLBCL had a 15% decrease in small lymph node disease with approximately a 5 month duration. These patients were in cohorts 3 and 4. Conclusions SNS01-T administration was feasible in all 4 dose cohorts with prophylaxis for infusion reactions. Early signs of potential efficacy are encouraging. Expansion of efficacy testing to more patients and combination studies are planned. Disclosures Siegel: Senesco: PI Other. McDonald:Senesco: PI Other. Novitzky:Senesco: PI Other. Bensinger:Senesco: PI Other. Craig:Senesco: PI Other. van Rhee:Senesco: PI Other. Gutierrez:Senesco: PI Other. Libby:Senesco: PI Other. Thompson:Senesco: Consultancy, Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding. Bexon:Senesco: Consultancy. Barranco:Senesco: Consultancy. Taylor:Senesco: Research Funding. Dondero:Senesco: Employment. Browne:Senesco: Employment. Kurman:Senesco: Consultancy. Lust:Senesco: PI Other.

Abstract Background: Pomalidomide is an immunomodulatory agent (IMiD®) that has been approved for treatment of relapsed and refractory multiple myeloma (MM). Combinations of IMiDs and proteasome inhibitors offer the potential for deeper and more durable responses due to enhanced efficacy. Preliminary results of a phase 1 study of twice weekly bortezomib with pomalidomide have been reported with promising results (Richardson, ASH 2012). This phase I/II trial was designed to evaluate the maximum tolerated doses (MTD) as well as safety and efficacy of the combination of pomalidomide, once weekly bortezomib and dexamethasone (PVD) in patients with relapsed, lenalidomide refractory, MM. Patients and methods: We included patients with relapsed MM who had 1-4 prior lines of therapy and were resistant or refractory to lenalidomide. In the phase I portion of the trial, dose level 1 consisted of pomalidomide 4 mg days 1-21 PO, bortezomib 1.0mg/m2 days 1,8,15, and 22 IV or SQ and dexamethasone 40 mg days 1,8,15, and 22 PO, given every 28 days. Bortezomib was increased to 1.3mg/m2 for dose level 2 and and was adopted for the phase 2 portion. The primary aim of the phase I cohort was to determine the MTD of the combination, and for the phase II cohort was to evaluate the confirmed response rate (PR, VGPR, or CR) in relapsed refractory MM. Response was assessed by the IMWG criteria and toxicity was graded using the CTCAE v4.0. Results: 50 patients were accrued between March 2012 and July 2014 (dose level (DL)1: 3, DL 2: 6, Phase II: 41). We describe results in 47 patients treated at MTD and phase II. Median age was 66, 51% were female and median time from diagnosis to study was 46 months (15-142). Twenty five percent had mSMART defined high-risk status. Median number of prior regimens was 3. All patients had prior lenalidomide, 68% had stem cell transplant, 17% received thalidomide, 56% had alkylators and 57% had bortezomib. With median follow up of 9 months, 72% remain progression free, 96% are alive and 66% remain on treatment. The most common AEs at least possibly attributable to the combination were anemia, fatigue, leukopenia and thrombocytopenia; however, the majority of these were grade 1-2. Grade ≥3 AEs (regardless of attribution) that occurred in at least 3 patients included neutropenia (29), leukopenia (15), lung infection (6), lymphopenia (8) dyspnea (3) and syncope (3). DVT/PE occurred in one patient. Among the 42 patients who were evaluable, confirmed responses (PR, VGPR, or CR) were seen in 34 (81%) including sCR (3), CR (5), VGPR (8), PR (18). Confirmed responses were seen in 9 of 11( 82%) high risk patients. Median progression free survival was 17.7 months (95%CI: 9.5-NA). Conclusions: PVD is a highly effective combination in patients refractory to lenalidomide with confirmed responses in over 80%. Weekly administration of bortezomib enhanced the tolerability and convenience of this regimen. Toxicities are manageable, mostly consisting of mild cytopenias with no significant neuropathy or DVT. PVD is a highly attractive option in patients with relapsed and refractory MM. Disclosures Lacy: Celgene: Research Funding. Lust:Senesco: PI Other. 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. Stewart:Celgene: Consultancy; Novartis: Consultancy; Array BioPharma: Consultancy; BMS: Consultancy; Millenium: Research Funding. Reeder:Millennium, Celgene, Novartis: Research Funding. Mikhael:Onyx: Research Funding; Celgene: Research Funding; Sanofi: Research Funding; Novartis: Research Funding.