Lin, Yi

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. Diffuse large B-cell lymphoma (DLBCL) is curable for the majority of patients treated with anthracycline based immunochemotherapy (IC). While most patients achieve response to initial therapy, a subset of patients are refractory to initial IC or become refractory to subsequent salvage therapies. Prognosis in this setting is very poor. Here we determine the incidence of refractory disease from a large cohort of DLBCL prospectively followed from diagnosis in the IC era and assess outcomes in these patients. Methods. Patients were prospectively enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE Molecular Epidemiology Resource (MER) within 9 months of diagnosis. Patients were followed for relapse, retreatment, and death; all events were validated by medical record. This analysis includes patients with DLBCL or primary mediastinal B-cell lymphoma (PMBCL) who received initial treatment of anthracycline based immunochemotherapy; patients with primary CNS lymphoma or post-transplant lymphoproliferative disorders were excluded. Response to therapy was retrospectively classified per 2007 Revised Response Criteria for Malignant Lymphoma from available clinical and radiology records. Refractory disease was defined as having a best response to any systemic therapy of stable disease (SD), progressive disease (PD), or relapse within 12 months of autologous stem cell transplantation (SCT). We also examined patients with transient response to IC as defined by achieving an interim response (CR or PR) but having progressive disease at or prior to the end of the planned number of cycles of IC. Results. 1039 patients with DLBCL or PMBCL lymphoma were enrolled in the MER from 2002-2012 and treated with R-CHOP or comparable IC. Median age at diagnosis was 62 years (range 18-91) and 577 (56%) were male. At a median FU of 60 months (range 1-148), 136 patients developed refractory disease. The median age at diagnosis of patients with refractory disease was 62 years (range 19-87). The cumulative incidence of refractory DLBCL was 11.3% at 2 years (95%: CI: 9.5-13.4) and 13.1% at 5 years (95% CI: 11.2-15.4). The median overall survival after becoming refractory was 4.7 months (95% CI: 4.1-5.5) with a 1 year survival rate of 21% (95% CI: 15%-30%). The median number of therapies before becoming refractory was 2 with 35 patients becoming refractory following their first therapy (i.e. IC), 83 patients becoming refractory after their 2nd therapy, and 23 patients becoming refractory after their 3rd or later therapy; 27 patients had received stem cell transplant prior to becoming refractory. Outcomes were poor regardless of when patients became refractory (figure). Patients received a median (range) of 2 (0-8) treatments after becoming refractory with 40% (N=54) attempting subsequent platinum based salvage therapy and 14% (N=9) proceeding to ASCT, of which only 6 remain alive in long-term remission. 41 patients (30%) were treated on clinical trials after becoming refractory. Response rate for the first therapy after becoming refractory was 21%, while 29% of patients had a response to any subsequent therapy. Once patients became refractory, there was no difference in survival based on response at end of initial IC (p=0.33), cell of origin at diagnosis (p=0.64), IPI at diagnosis (p=0.33), or age when refractory (p=0.66). Outcomes in patients with transient response to IC (n=58) were poor, with the majority (N=37, 63%) becoming refractory to subsequent therapy. Median OS after first relapse was 6.7 months in patients with transient response to IC, which was equivalent to patients refractory to IC (p=0.99). The majority of patients with transient response to IC (69%) were next treated with platinum based salvage therapy which had a response rate of 40%. Ultimately 15 of the 58 patients (26%) proceeded to transplant, of which only 5 (9%) achieved long-term remission. Conclusions. Approximately 13% of patients with DLBCL become refractory to treatment in their disease course. Outcomes once patients become refractory are extremely poor regardless of when patients become refractory. Standard prognostic factors are no longer predictive of outcome and stem cell transplant had limited benefit in this group of patients. Patients with transient response to initial immunochemotherapy should be included when classifying patients as refractory. New therapy strategies are needed in the refractory setting. Figure 1. Figure 1. Disclosures Maurer: Kite Pharma: Research Funding. Thompson:Kite Pharma: Research Funding. Farooq:Kite Pharma: Research Funding. Cerhan:Kite Pharma: Research Funding. Ansell:Bristol-Myers Squibb: Research Funding; Celldex: Research Funding. Link:Genentech: Consultancy, Research Funding; Kite Pharma: Research Funding.

Abstract Background: Patients (pts) with refractory aggressive non-Hodgkin lymphoma (NHL) have poor outcomes with currently available therapies, with a complete response (CR) rate of 8%, a partial response (PR) rate of 18%, and median overall survival (OS) of 6.6 months (mo) as demonstrated in the 635 pt SCHOLAR-1 meta-analysis (Crump, ASCO 2016; abstract 7516). ZUMA-1 is the first multicenter trial of anti-CD19 chimeric antigen receptor (CAR) T cells in refractory, aggressive NHL (NCT02348216). The phase 1 portion of ZUMA-1 showed ongoing CRs at 12+ mos in 43% of pts (Locke, ESMO 2016; abstract 1048O). The pivotal phase 2 portion of ZUMA-1 comprises 2 cohorts based on tumor type: DLBCL (cohort 1) and primary mediastinal B-cell lymphoma or transformed follicular lymphoma (cohort 2). Here, we present results of a prespecified interim analysis from cohort 1. Methods: Pts received a target dose of 2 × 106 anti-CD19 CAR T cells/kg after a low-dose conditioning regimen of cyclophosphamide (500 mg/m2) and fludarabine (30 mg/m2) daily for 3 days. The primary endpoint is objective response rate (ORR) per 2007 IWG criteria. Key secondary endpoints include duration of response, frequency of adverse events (AEs), and levels of CAR T cells and serum cytokines. Key inclusion criteria include age ≥18 years, ECOG performance status (PS) 0-1, and refractory disease defined as progressive disease or stable disease as best response to last line of therapy, or disease progression ≤12 mos after autologous stem cell transplant (ASCT). Pts must have received a prior anti-CD20 antibody and an anthracycline-containing regimen. A prespecified interim analysis was to be conducted to determine early efficacy with a nominal alpha level of 0.017 in 50 treated pts in cohort 1 with a minimum follow-up of 3 mos. Results: In total, 111 pts from 22 institutions were enrolled and leukapheresed, and 101 pts received KTE-C19. As of August 24, 2016, 51 pts in cohort 1 were eligible for analysis. Median age was 58 years (range, 25-76), 73% were male, 71% had ECOG PS 1, 78% were refractory to ≥2 lines of therapy, 20% relapsed ≤12 mos of ASCT, and 61% were treated with ≥3 lines of prior therapy. KTE-C19 was successfully manufactured in 99% of pts enrolled. Average turnaround time from apheresis to receipt of KTE-C19 at the clinical site was 17.4 days. With an ORR of 76%, the study met the primary endpoint (P<0.0001; exact binomial test comparing observed ORR to a historical control assumption of 20%), with 47% CRs and 29% PRs. 92% of responses occurred within the 1st mo, and 39% of pts had ongoing responses (CR in 33%) at 3 mos. Responses were seen across key covariates, including refractory subgroup (refractory to chemotherapy=76%, relapse post ASCT=80%). Kaplan-Meier estimates of progression-free survival at 1 and 3 mos were 92% and 56%, respectively. The most common grade ≥3 treatment-emergent AEs were neutropenia (67%), anemia (39%), thrombocytopenia (29%), febrile neutropenia (27%), and encephalopathy (24%). Grade ≥3 cytokine release syndrome (CRS) and neurologic events occurred in 20% and 29% of pts, respectively. There was 1 grade 5 KTE-C19-related event of hemophagocytic lymphohistiocytosis. CAR T cells expanded within 14 days of KTE-C19 infusion, and peak expansion was associated with ongoing response at mo 3 (P=0.008). Pts who developed grade ≥3 neurological events had increased serum levels of IL-15 (P=0.0002), IL-6 (P=0.003); IL-10 (P=0.009) and IP-10 (P=0.0003). Cytokines/chemokines returned to baseline levels in most pts by day 28. Data from 93 pts with at least 1 mo of follow-up at the data cutoff will be presented. Conclusions: ZUMA-1 is the first reported multicenter trial of CAR T cell therapy in pts with refractory aggressive NHL. KTE-C19 induced a nearly 6-fold higher CR rate compared to historical outcomes in SCHOLAR-1. Efficacy strongly associated with peak CAR T levels. Central manufacturing, logistics, and AE management were successfully implemented across 22 sites, most with no prior CAR T therapy experience. Results from cohort 2 of ZUMA-1 are also presented (Abstract #998). KTE-C19 demonstrated significant clinical benefit in pts with no curative treatment options. Supported in part by funding from The Leukemia & Lymphoma Society Therapy Acceleration Program®. Drs Neelapu and Locke contributed equally to this study. Disclosures Neelapu: Kite Pharma: Membership on an entity's Board of Directors or advisory committees, Research Funding. Locke:Kite: Membership on an entity's Board of Directors or advisory committees. Miklos:pharmacyclics: Research Funding; Kite Pharma: Research Funding; Roche: Research Funding; Novartis: Research Funding. Jacobson:Kite: Membership on an entity's Board of Directors or advisory committees. Siddiqi:Pharmacyclics: Speakers Bureau; Janssen: Speakers Bureau; Seattle Genetics: Speakers Bureau. Lin:Mayo Clinic: Employment; Janssen: Research Funding. Timmerman:Bristol-Myers Squibb, Kite Pharma, Valor Biopharmaceuticals, Janssen: Research Funding; Seattle Genetics, Genmab, Celgene: Consultancy, Honoraria. Goy:COTA: Membership on an entity's Board of Directors or advisory committees; Janssen/Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Research funding for clinical trials through institution, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Research funding for clinical trials through institution; Acerta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Genentech: Other: Research funding for clinical trials through institution. Smith:Abbvie: Research Funding; Celgene: Honoraria; Spectrum: Honoraria; Genentech: Honoraria. Deol:Jazz Pharmaceuticals: Consultancy. Avivi:Tel Aviv Sourasky Medical center: Consultancy, Other: consultancy to :BMS Roche. Westin:Genentech: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Spectrum: Membership on an entity's Board of Directors or advisory committees; ProNAi: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Chavez:Janssen: Speakers Bureau. Levy:Kite Pharma: Consultancy; Five Prime Therapeutics: Consultancy; Innate Pharma: Consultancy; Beigene: Consultancy; Corvus: Consultancy; Dynavax: Research Funding; Pharmacyclics: Research Funding. Reagan:Seattle Genetics: Research Funding. Bot:Kite Pharma: Employment, Equity Ownership. Rossi:Kite Pharma: Employment, Equity Ownership. Navale:Kite Pharma: Employment, Equity Ownership. Jiang:Kite Pharma: Employment, Equity Ownership. Aycock:Kite Pharma: Employment, Equity Ownership. Elias:Kite: Employment, Equity Ownership. Wiezorek:Kite Pharma: Employment, Equity Ownership. Go:Kite Pharma: Employment, Equity Ownership.

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: Patients with light chain amyloidosis (AL) often have delayed diagnosis and present with significant symptomatology; this may result in decreased quality of life (QOL). With improving treatment options providing longer survival, it is increasingly important to assess QOL. However there is paucity of data in the literature addressing QOL in AL patients. We prospectively employ a "Hematology Patient Reported Symptom Screen" (HPRSS) which consists of three questions about fatigue, pain and overall QOL. The aim of this study is to understand if HPRSS parameters predict various clinical outcomes. Methods: Eligibility for this retrospective study was as follows: 1) New diagnosis of AL between 2009-2014; 2) baseline HPRSS documented in the medical record; and 3) at least a year of follow-up, which included either death within or follow-up through 12 months after diagnosis. The HPRSS questions were rated on a 1-10 scale, with 10 being the worst for fatigue and pain, and 10 being the best for overall QOL. Scores were abstracted from visits at time of diagnosis, and at 12 months +/- 1 month post-diagnosis. We considered a 2-point difference in serial scores a "change" over time. Results: For the 302 patients in this study, the baseline median scores [interquartile range] for fatigue, pain, and QOL were 6 [3,7], 2 [0,5] and 5 [3,8], respectively. Median overall survival (OS) was 39.1 months, with 102 deaths in the first year. There were significant differences in baseline HPRSS between those who lived longer than one year and the early death patients in the domains of fatigue (5 [IQR 3, 7] vs. 7 [IQR 5, 8], p<0.0001) and QOL (6 [IQR 4, 8] vs. 5 [IQR 3, 7], p=0.006), but not in pain (2 [IQR 0, 5] vs. 2 [IQR 0, 5]). There were significant baseline differences in the early death group for alkaline phosphatase, bilirubin, creatinine, and Mayo stage. Patients who received ASCT had the best baseline fatigue 4 [2.5,6] and QOL 7 [5,8] scores and were significantly different from those who did not receive ASCT [fatigue p<0.0001) and QOL (p<0.0001)] On univariate analysis fatigue and QOL were prognostic for OS. On multivariate analysis Mayo 2012 staging, autologous stem cell transplant and baseline fatigue remained independently prognostic. When analyses were restricted to the 125 patients with HPRSS measurements at 12 months, we found that over time QOL scores improved significantly 6 [IQR 3.5, 8] to 7 [IQR 5, 8] (two sided Wilcoxon signed rank p=0.01), but fatigue (5 [IQR 2, 5] to 4.5 [IQR 3, 6]) and pain scores (2 [IQR 0 ,4] to 1.5 [IQR 0, 4]) did not. Patients with worse baseline parameters tended to have improvement in QOL by 12 months while those with the best baseline parameters tended to decline in QOL although not statistically significant. When we included the 102 patients who died within 12 months to the comparison, the early death patients had the worst baseline parameters and there were significant differences across all 4 groups for most characteristics (Table 1). There was no association between achieving hematologic or organ response with change in QOL. Conclusion: Asking patients with AL to rate their fatigue and QOL using a 10-point scale has predictive value. Patient reported fatigue at diagnosis is an independent prognostic factor for survival. Survival at one year was associated with significant improvement in QOL. Table 1. Baseline parameters between patients with early death and/or survive 12 months. Grouped by Patient Reported QOL at 12 months Relative to Baseline Dead by 12 months, n=102 Improved, n=44 Stable, n=55 Worsened, n=26 pa HPRSS scores [IQR] Baseline QOL Baseline fatigue Baseline pain 12 month QOL 12 month fatigue 12 month pain 5 [3,7] 7 [5,8] 2 [0,5] NA NA NA 4 [3-5] b,c,d6 [4-8] b,c2 [0-4] 7 [6-9] b,d4 [1.25-6] 1 [0-3] 7 [4-8] 4 [2-7] 2 [1-5] 7 [4-8] 5 [3-6] 2 [0-4] 8 [7-10] 2.5 [0-5.25] 2 [0-6.25] 5 [3-7] 5 [3-6] 2.5 [1-4] <0.0001 <0.0001 NS NS 0.001 NS dFLC, mg/dL 48 (2.89-726) 30 (1.1-494) 19 (36-455) 22 (0.2-2097) 0.008 Troponin, ng/mL 0.065 (<0.01-0.84) 0.02 (<0.01-1.6) 0.01 (<0.01-0.19) 0.01 (<0.01-0.14) <0.0001 NT-proBNP pg/mL 5222 (159-70,000) 1766 (26-16868) 1381 (24-19180) 496 (56-2973) <0.0001 Received Transplant (%) 4 (4) 13 (33) 36 (50) 13 (50) 0.0002 a Significant by Wilcoxon across all 4 categories; b Significant difference between Improved and Worsened; c Significant difference between Improved and Stable; d Significant difference between Worsened and Stable Disclosures Kumar: Millenium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Abbvie: Research Funding; Janssen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Novartis: Research Funding; Onyx: Consultancy, Research Funding. Thompson:Kite Pharma: Research Funding.

Abstract Background: Both MM specific and patient specific parameters place patients at risk for death. Patient frailty has been delineated primarily by age and ECOG performance score (PS) and secondarily with creatinine, eGFR, and the International Staging System (ISS), which reflect both renal function and disease burden. In an attempt to improve upon these commonly used measures, a frailty score for elderly patients that combines functional status [Activity of Daily Living (ADL) and Instrumental Activity of Daily living scores], comorbidities [Charlson comorbidity index (CCI)] and age has been developed by the IMWG. Incorporation of these tools into a busy clinical practice is challenging due to time constraints. Therefore, the identification of frail patients with an easily applicable, rapid and objective tool remains a challenge and an unmet need. A reliable, non-invasively assessable, biochemical marker of frailty would be an ideal tool to identify patients at higher risk of death. It was our goal to determine the role of NT-proBNP, a well-established cardiovascular risk biomarker, as a marker of frailty in patients with MM and in predicting overall survival (OS). Methods: Patients were elegible for this retrospective study if they were seen at the Mayo Clinic, Rochester, MN within 30 days of their myeloma diagnosis during the interval between 1/1/2007 and 12/31/2011. As part of the Mayo Clinic registration, all patients complete forms containing their past medical history, symptoms, and ADLs. Data from that first visit was abstracted and used to calculate a CCI. We excluded all patients with a concomitant diagnosis of light-chain AL amyloidosis. NT-proBNP concentration was measured in frozen sera collected within 30 days of diagnosis. NT-proBNP assay was run on the E170 Modular analyzer (Roche Diagnostics, Penzberg, Germany). We evaluated the prognostic role of NT-proBNP and these indices on OS using the Kaplan-Meier method. Results: Among the 351 consecutive patients satisfying entry criteria, median age was 65 years (range 22-95), 33% were ≥70 years, and 56% were male. Twenty-eight percent were ISS stage III, 13% had a creatinine ≥2 mg/dL, 19% had PS ≥2, and 11% had ADL score ≥2, and 30% CCI ≥2. The median value of NT-proBNP was 109 ng/L (interquartile range: 30-375 ng/L). NT-proBNP concentrations differed in the three ISS stages (median: 122 ng/L stage I, 190 ng/L stage II and 1822 ng/L stage III, P<0.0001). Median OS was 5.6 years. The best cutoff of NT-proBNP predicting OS at one year was 301 ng/L (sensitivity: 57.88%, specificity: 74.29%; AUC=0.668) and distinguished two groups with different OS (median not reached vs. 35 months, P<0.0001). Variables predictive for OS are shown in the Table and included PS, age, CCI, ISS, NT-proBNP. On multivariate analysis, ISS and NT-proBNP were independent of each other as long as age, PS and/or CCI were excluded from the model. NT-proBNP withstood these clinical variables better than did ISS (data not shown). We built two different models (table). In model 1, NT-proBNP >301 ng/L was an independent predictor of survival while age ≥70 and PS ≥2 and CCI were not significant. However, if we considered ISS stage instead of NT-proBNP in the same model, ISS stage was not significant. Conclusions: In this unselected cohort of patients with newly diagnosed multiple myeloma, NT-proBNP was a useful predictor of survival independent of age and PS. The threshold of 301 ng/L is remarkably similar to the well-established cutoff for heart failure of 300 ng/L. NT-proBNP outperformed the CCI and the ISS as risk factors. NT-proBNP is a widely available biomarker that could be added to the panel of laboratory tests of newly diagnosed MM patients and serve as a simple means of determining patient frailty in a busy clinical practice. Table. Results of univariate and multivariate analysis of various prognostic factors (NS, not significant; NI, not included). Univariate Multivariate Multivariate RR (95% CI) P Model 1 P Model 2 P PS ≥2 3.4 (2.4-4.8) <0.0001 2.5 (1.7-3.6) <0.0001 2.8 (1.9-4.0) <0.0001 Age ≥70 2.7 (1.9-3.6) <0.0001 2.1 (1.5-2.9) <0.0001 1.9 (1.3-2.7) 0.0003 CCI >=2 1.9 (1.4-2.6) <0.0001 NS NS 1.5 (1.0-2.0) 0.03 ISS stage 1.1 (1.1-1.8) 0.0004 NI NI NS NS NT-proBNP >301 ng/L 2.3 (1.7-3.2) <0.0001 1.6 (1.1-2.2) 0.007 NI NI Disclosures Merlini: Janssen-Cilag: Honoraria; Prothena: Honoraria; Millennium-Takeda: Honoraria; Pfizer: Honoraria. Kumar:Janssen: Research Funding; Celgene: Research Funding; Sanofi: Research Funding; Millenium/Takeda: Research Funding; AbbVie: Research Funding; Onyx: Research Funding; Celgene, Millenium, Sanofi, Skyline, BMS, Onyx, Noxxon,: Other: Consultant, no compensation,; Skyline, Noxxon: Honoraria.

Abstract Introduction T-cell prolymphocytic leukemia (T-PLL) is a rare mature T-Cell malignancy typically associated with aggressive clinical course. Leukemic T-cells demonstrate post-thymic T-cell phenotypes (Tdt-, CD1a-, CD5+, CD2+ and CD7+) and commonly are CD4+/CD8- T-cells, but co-expression of CD4+/CD8+ or CD8+/CD4- have also been observed. Rearrangement of chromosome 14 involving TCL1 locus is the cornerstone for T-PLL diagnosis which leads to overexpression of oncogene TCL1. As a binding partner for TCL1, AKT expression correlates with worse prognosis. Despite advances in identification of novel mutations, therapeutic option is limited with most patients having very short survival. Herein, we performed a detailed analysis of specific T-cell subsets affected in T-PLL and a comprehensive genomic analysis by whole exome sequencing (WES) and RNA sequencing. We also explored the preclinical efficacy of targeting AKT activation by AKT inhibitor MK2206 on leukemic T-cells isolated from T-PLL patients. Methods T-PLL leukemic cells were isolated from blood or marrow samples of T-PLL patients (n=9) and were tested for involved T-cell subsets by multicolor flow cytometric analysis. Leukemic T-cells were treated with escalating doses of MK2206 (0 to 10 µM) for about 80 hours and were assessed for their apoptosis levels using Annexin V flow cytometric analysis. Whole exome sequencing (WES) and RNA sequencing were conducted using genomic DNA and RNA isolated from purified leukemic T cells from T-PLL patients. Results Phenotypic analysis of T-cell subsets in T-PLL patients showed that leukemic T-cells in 4 untreated T-PLL patients are consistent with naïve T-cell phenotype (CD45RA+, CD45RO-, CCR7+). Leukemic T-cells in 3 of the untreated patients and in 2 of the treated patients have central memory T (CD45RA-, CD45RO+, CCR7+) and effector memory T phenotypes (CD45RA-, CD45RO+,CCR7-) respectively. MK2206 treatment was able to induce dose-dependent apoptosis on the isolated PBMC (containing > 90% leukemic T-cells) of T-PLL patients (n=4) (IC50: 5 µM). FISH analysis found a rearrangement of TCL1 locus on chromosome 14 in all T-PLL cases (n=9). Three cases have also been detected to have del (11q) involving ATM locus and one patient has both del(11q) and del(17p). Subsequent WES (n=7) and RNA sequencing (n=6) analysis revealed recently reported mutations in ATM (frame shift mutation and early stop mutation W579*) in 2 cases, JAK3 (M511I) in 2 cases and STAT5B (T628S and N642H) in 2 cases. Importantly, novel somatic mutations in gene IKZF1 (N159S), NTRK1 (R33W), AP2A2 (P514L), HDAC8 (I115R), RARB (G90W) and TNIP2 (K104Q) were detected by WES. Mutations in EML4 (L548W and F304S) and VAV3 (C282Y and splice site mutation) were also identified in 2 different T-PLL cases. RNA sequencing revealed several fusion transcripts resulting in early stop of several different genes including PTPRT, L3MBTL1, UCKL1 in one T-PLL case. Conclusion T-PLL leukemic T-cells are consistent with either naïve or central memory T-cell subsets in untreated patients. The AKT inhibitor MK-2206 was capable of inducing apoptosis and could be a potential therapeutic agent for T-PLL patients. In addition, we detected known mutations in ATM and JAK-STAT pathways. Novel mutations in genes involving DNA binding and chromatin remodeling (IKZF1, HDAC8) or kinase signal pathway (NTRK1, TNIP2, VAV3, EML4) were uncovered. These results suggest that further therapeutic approaches could be developed to target DNA binding factors or JAK-STAT or AKT-TCL1 signal pathway with an ultimate goal to improve survival of T-PLL patients. Disclosures Off Label Use: Off label use of MK2206: MK-2206 is an AKT inhibitor obtained from Selleck Chemicals and is used to treat leukemic cells in vitro to test the leukemic sensitivity to AKT inhibition. .

Abstract Abstract 3972 Background: The treatment paradigm for myeloma has undergone a dramatic shift in the past decade with the introduction of the novel agents and their application at every stage of the treatment. We and others had previously shown that survival of patients with myeloma had improved in the earlier half of the last decade and attributed this to a combination of novel therapies as well as increased use of stem cell transplant. It is not clear if this momentum in improving survival has been maintained. We examined the survival trends of patients with newly diagnosed myeloma seen within the past decade to examine this question. Patients and Methods: We studied 1056 patients with newly diagnosed myeloma, who were seen at Mayo Clinic between January 1, 2001 and December 31, 2010; who were seen within 30 days of their diagnosis. For examination of the time trends, we grouped the time interval into two five year periods, 2001–2005 and 2006–2010. Survival was estimated using Kaplan Meier method and survival curves were compared by log rank test. Impact of various prognostic factors was evaluated using Cox proportional hazards test. Results: The median age at diagnosis was 65 (range; 22–92), and 59% were male. The median estimated follow up for the entire cohort was 4.6 years (95% CI; 4.4, 4.9) and 57% of the patients were alive at last follow up. The median overall survival (OS) for the entire cohort was 5.4 years (95% CI; 5, 6.3). The overall survival for patients in the 2001–2005 group was 4.6 years compared with not reached for the 2006–2010 cohort (P< 0.001). The five-year estimated OS was 48% for the earlier group compared with 66% for the latter group. The estimated 1-year survival was 90% for the recent cohort compared with 83% for the earlier cohort, suggesting improvements in the early mortality. Interestingly, the improvement was predominantly seen in the older age group (>65 years; 49%). The 5-year survival of the older patients improved significantly from 31% (2001–2005) to 56% (2006–2010) (P<0.001). In contrast, among younger patients (≤65 years of age), the 5-year survival improved only marginally from 63% (2001–2005) to 73% (2006–2010) (P=NS). One or more novel agents (Lenalidomide, thalidomide or bortezomib) were used as part of initial therapy in 631 (62% of 1021 in whom treatment data was available). The OS among of this group was 7.3 years (95% CI; 5.9, NR) compared with 3.8 years (95% CI; 3.1, 4.6). In a multivariate model that included both use of novel agent and the year group, only the novel agent use was associated with improved survival suggesting that the improvement in the survival is related to the increased use of novel agents in the initial therapy. No significant differences were observed between the groups in terms of conventional prognostic factors. Conclusions: The current results confirm continued improvement in the overall survival of patients, even within the last 10 year period, and highlight the impact of initial therapy with novel agents. Most importantly, we demonstrate that the improved survival has primarily benefited older patients. Our study highlights that urgent need for additional new agents to provide further survival improvement for younger patients, and in order achieve a cure for this disease. Disclosures: Kumar: Merck: Consultancy, Honoraria; Celgene: Research Funding; Millennium: Research Funding; Novartis: Research Funding; Cephalon: Research Funding; Genzyme: Research Funding. Dispenzieri:Celgene: Research Funding; Millennium Pharmaceuticals, Inc.: Research Funding; Janssen Research & Development: Research Funding. Gertz:Binding Site: Honoraria.

Abstract Abstract 946 Background: The emerging therapies directed at the plasma cell clone have dramatically increased overall survival (OS) for both myeloma and amyloidosis patient populations. As more treatment trials are done in patients (pts) with AL, benchmarks for outcomes among previously treated AL pts are required, especially for those pts who are not candidates for high-dose chemotherapy with peripheral blood stem cell transplantation (ASCT). Inadequate information is available about the number of non-transplant pts who go on to receive second line treatment for AL amyloidosis. Methods: To ascertain the outcomes of pts who did not receive ASCT as primary therapy but who required a second line of therapy, we reviewed the experience of pts seen at Mayo Rochester between 1990 and 2010 according to an IRB approved retrospective review protocol. 1828 pts had their first Mayo visit for AL during this time period. Pts were excluded from this study for the following reasons: 571 had upfront transplant; 907 pts had received only one line of treatment for their amyloid; 91 had longstanding other associated malignancy [Waldenstrom's macroglobulinemia (8), lymphoma (15), CLL (6), multiple myeloma (62)]; and 93 had inadequate follow-up information. One-hundred and sixty-six pts received 2 or more lines of therapy for their AL amyloid and are the subject of these analyses. Statistical analyses were done using JMP statistical software (SAS, Carey, NC). Results: Of the 166 pts, the median age was 64 years (range 34, 84). 49% were male. Baseline organ involvement was as follows: cardiac 84/166 (50%); renal 118/166 (71); liver 23/166 (13.8%); peripheral nerves 19/166 (11.4%); and gastrointestinal 14/166(8.4%). Thirty-one percent (52/16) had both cardiac and renal involvement. Only 73 pts had cardiac biomarkers (NT pro BNP and Troponin T) done at baseline. Of these pts, 26% were stage 1, 49.3% were stage 2, and 24.6% were stage 3 according to original Mayo cardiac biomarker staging system. By inclusion criteria definition, all 166 pts received 1st and 2nd line therapies; 53 (32%) pts received 3rd line of treatment; 20 (12%) received 4th line of treatment; and 10 (6%) received 5th line of treatment. For first line therapy, the most common drugs given either singly or in combination were corticosteroid (147/166; 88.5 %), alkylator (99/166; 59.6%), IMID (34/166; 20.4 %), and bortezomib (19/166; 11.4%). The median time from diagnosis to 2nd line therapy was 10.3 months. Second line regimens received included: corticosteroid, 108/166 (65.1%); alkylator, 76/166 (45.8 %); IMID, 46/166 (27.7%); and bortezomib, 46/166 (27.8%). The median time from diagnosis to 3rd line therapy was 19.8 months. For the 53 pts who received 3rd line treatment, regimens included: corticosteroid, 41/53 (77.3%); IMIDs, 17/53 (32.1%); alkylator, 17/53 (32.1%); bortezomib, 12/53 (22.6%). The median time from diagnosis to 4th line therapy was 31.8 months. For the 20 pts receiving 4th line treatment, regimens included: corticosteroids, 15/20(75%); alkylator, 12/20 (60%), bortezomib, 7/20 (35%); and IMIDs, 4/20(20%). Eighty-three pts have died. The 1 year mortality of our study population was only 8%. The median follow-up of surviving pts was 47.6 months. Figure 1 demonstrates Kaplan-Meier estimates of overall survival (OS) from initiation of each successive therapy. The median OS from initiation of 1st, 2nd, and 3rd lines of treatment were 65, 49.5 and 36.7 months respectively. The median OS after the 4th line of treatment was not reached. The 4 year OS rates from initiation of 1st, 2nd, 3rd and 4th lines of therapy were 58%, 50.8 %, 50 % and 53.4% respectively. Conclusion: Outcomes among relapsed or refractory AL pts are better than what one might expect. Multiple publications have demonstrated that the 1 year mortality of newly diagnosed AL is in the vicinity of 40%. Thereafter, the rate at which pts die dramatically decreases. Our study provides explicit data characterizing the fate of pts unfortunate enough to require additional therapy but fortunate enough to survive past the exceedingly high risk period of death that occurs within 6–12 months of diagnosis. These data provide useful information for benchmarking future trials for treatments of AL amyloidosis. Disclosures: No relevant conflicts of interest to declare.