Callander, Natalie S.

Abstract Background: Multiple myeloma (MM) is an incurable disease with a anticipated overall survival (OS) ranging from months to decades. Modest improvements in OS have been made with high-dose chemotherapy with peripheral blood stem cell transplant (PBSCT), but to date prognostic factors have a greater impact on OS than do individual therapies. Patients with adverse risk factors such as elevated beta-2 microglobulin (B2M), plasma cell labeling index, deletions of the long arm of chromosome 13 by metaphase cytogenetics (del 13q) require innovative new treatment strategies. Bortezomib has significant activity in patients with both newly diagnosed and relapsed/refractory MM, but its specific role in patients with adverse features has not yet been defined. Methods: Patients with newly diagnosed “high-risk” myeloma (B2M ≥ 5.5., PCLI ≥ 1, or del 13q) and adequate organ and functional status were eligible. Patients were treated with bortezomib 1.3 mg/m2 day 1, 4, 8, and 11 every 21 days for 8 cycles as induction. After induction, patients were scheduled to receive bortezomib 1.3 mg/m2 every other week indefinitely. Elective peripheral stem cell mobilization (growth factor alone) was allowed after 4 cycles of bortezomib. Patients relapsing on maintenance schedule were to have the full induction schedule resumed. Responses were by the EBMT criteria but a very good partial response category was included. The primary end-point was the response rate in these high-risk patients (90% power to detect a response rate of 50% or higher). The study decision rule requires that 16 or more responses, among 39 eligible patients, are seen in order to declare this treatment effective. Results: Between March 15, 2004 and March 10, 2005, 44 patients enrolled on study. Among the 43 eligible patients, median age was 63; 51% were male. All patients had high risk disease: del 13q (6/41); plasma cell labeling index ≥1% (16/34); and B2M≥5.5 (34/43). Preliminary response data are available for 18 of the 44 cases enrolled, of which 7 had partial response, 1 had minimal response, 1 had no response, 2 had progressive disease, and 5 were unevaluable. Among those patients completing induction therapy and with response information, the median number of cycles of therapy administered is 5, range (0,8). The most common non-hematologic adverse events (AEs) of grade 3 or higher included hyponatremia (9 patients) and diarrhea (6 patients). Mild sensory peripheral neuropathy was common: grade 1, 16 patients; grade 2, 2 patients. Only 1 patient had grade 3 peripheral neuropathy. One patient died after receiving 2 doses bortezomib due to heart block and asystole. Two patients had a grade 4, 25 patients had grade 3, and 13 had grade 1 or 2 as the worst grade non-hematologic adverse event. Based on data received by August 1, 2005, 18 patients have gone off study: AEs (2); death (1); progressive disease (9); and other reasons (6). Updated results on the full study population along with FISH data for IgH translocations and deletions of 13q and 17p will be presented at the meeting. Conclusions: Preliminary results suggest that upfront bortezomib has activity in patients with high-risk MM, but further follow-up is required.

Abstract Background: Venous thrombotic events (VTE) are a common complication of therapy with the lenalidomide plus dexamethasone regimen. The incidence of VTE with RD is approximately 20%, and can be lowered with the use of effective thromboprophylaxis, avoidance of erythropoietin, and the use of lower doses of dexamethasone. The goal of this study was to determine the impact of VTE on overall survival of patients with newly diagnosed myeloma by studying events occurring in ECOG E4A03 phase III trial of lenalidomide plus high (standard) dose dex (RD) versus lenalidomide plus low dose dex (Rd) in newly diagnosed myeloma (MM). Methods: Pts with untreated, symptomatic MM were eligible. Pts in the RD arm (Arm A) received lenalidomide 25 mg/day PO days 1–21 every 28 days plus dex 40 mg days 1–4, 9–12, and 17–20 PO every 28 days; pts in the Rd arm (Arm B) received lenalidomide at the same dose plus dex 40 mg days 1, 8, 15, and 22 PO every 28 days. The trial initially did not mandate routine thromboprophylaxis, but recommended that such treatment be considered. After the first 264 patients were enrolled the trial was amended to require mandatory thromboprophylaxis of aspirin for all patients, with a recommendation to use stronger thromboprophylaxis with either warfarin (target INR 2–3) or low molecular weight heparin among patients in the RD arm. Results: 445 pts (median age, 65 yrs) were accrued; 223 randomized to RD, 222 to Rd. Median follow-up time is 30 months. Overall VTE including deep vein thrombosis (DVT) and pulmonary embolism (PE) occurred in 18.5% of patients; 25.6% in Arm A and 11.4% in Arm B. Rates for the first 4 cycles of treatment were 20.2% in Arm A and 8.2% in Arm B, P<0.01. Rates did not change substantially before and after the prophylaxis amendment. A partial response (PR) or higher was seen in 82.1% of pts who experienced VTE compared with 74.6% of pts who did not experience VTE, P=0.19. Overall VGPR rates also were not inferior. Pts who had VTE, however, had significantly higher other grade 3–5 toxicities such as hyperglycemia (14.6% vs 7.5%, P=0.051), cardiac ischemia (4.9% vs 0.8%, P=0.002), non-neuropathic weakness (13.4% vs 6.4%, P=0.039), infection/pneumonia (17.1% vs 11.1%, P=0.138) and fatigue (18.3% vs 10.5%, P=0.060). In a Cox PH model, VTE status as a time-varying covariate was marginally significant: HR 1.54 95%CI (0.96–2.47), P=0.074, suggesting patients that develop VTE have a higher hazard of death. Conclusions: The occurrence of VTE may adversely affect the survival of patients with newly diagnosed myeloma receiving Rev-Dex. VTE was associated with a higher frequency of other serious adverse events. Prevention of VTE events is a priority. Besides lowering the dose of dexamethasone, studies investigating optimum thromboprophylaxis are needed.

Abstract Background: Outcome of patients with Multiple Myeloma (MM) is influenced by a variety of baseline prognostic factors, most importantly presence of chromosomal abnormalities. Nevertheless, these biologically determined risk-factors do not account for a significant subset of patients whose outcome varies greatly from what one expects based on the underlying prognostic characteristics. We have previously demonstrated that outcome in myeloma is dictated not only by baseline risk-factors but also response to therapy (R2, risk and response dependent outcome). We studied response duration following initial therapy as a prognostic factor for long-term overall survival in myeloma in three ECOG clinical trials that enrolled patients with newly diagnosed myeloma. Methods: Data from three studies with long-term, mature follow up were analyzed: E9486, E5A93, and E1A00. The regimens used in these studies included Thalidomide/Dex, Dex, VBMCP, VBMCP + alpha-IFN, and VBMCP + Cyclophosphamide. Among progressed/relapsed patients, the association between time to progression and overall survival since relapse was explored using Cox proportional hazards model, in which time to progression was analyzed as a continuous variable. In addition, the association between response duration and overall survival since relapse was explored similarly among relapsed responders. Treatment effect and calendar time of diagnosis have been adjusted in the model. Also, to determine the best cut off point associated with the best differentiation of patients with short OS after relapse, an outcome-oriented method using log likelihood value was applied. Results: Among the 1136 patients enrolled in the three studies, 625 patients who have documented disease relapse have been included in the current study. Of these, 471 patients had responded to the treatment before relapse. Only 33 patients are alive as of Dec., 2007. For all 625 patients, the time to progression (continuous variable) was significantly associated with overall survival from the time of relapse/progression (P<0.0001), with hazard ratio of 0.77 (95%CI: 0.72~0.81) at time to progression increasing by 1 year (i.e., the later the progression/relapse, the lower the risk). The best cutoff point of the time to progression is 3 yrs (the 75th percentile). The hazard ratio of patients progressing within 3 yrs since randomization vs. after 3 yrs is 2.4 (95% CI: 1.9 ~ 2.9) and P-value<0.0001. The median OS from relapse was 0.96 years for the former vs. 2.43 years in the latter group (Figure). Among the 471 relapsed responders, the response duration (continuous variable) was also significantly associated with overall survival since relapse (P<0.0001), with hazard ratio of 0.76 (95%CI: 0.70~0.81) at response duration increasing by 1 year (i.e., the longer the response duration, the lower the risk). The effects seen with each regimen are detailed in the table. The best cutoff point of the response duration is 2 yrs (median). The hazard ratio of patients with response duration less than or equal to 2 yrs vs. more than 2 yrs is 2.1 (95% CI: 1.7 ~ 2.6) and P-value<0.0001. Conclusions: Among patients treated with alkylator based therapy, the duration of response from the initial therapy is an important predictor of the subsequent outcome among patients with myeloma. Given the heterogeneity of the disease and imprecise predictive ability of the known baseline prognostic factors, the duration of response to initial therapy should be taken into account, to deliver risk and response-adapted therapy. The prognostic value of this feature across different clinical trials, points towards the role of underlying disease biology, both disease aggressiveness and ability to rapidly develop resistance to therapies as two important determinants of outcome. Table 1: Hazard ratio of overall survival since relapse for patients progressed within 3 yrs since randomization vs. after 3 yrs in each treatment arm Treatment arm Treatment arm HR (95% CI) P-value TTP<=3yrs vs. >3 yrs Thal/Dex N/A N/A Dex 0.4 (0.05, 3.9) 0.46 VBMCP(E5A93+ E9486) 1.9 (1.4, 2.7) 0.0001 VBMCP+alpha2IFN (E5A93+ E9486) 3.0 (2.2, 4.1) <0.0001 VBMCP+CYCLOPHOSPHAMIDE 2.3 (1.5, 3.6) 0.0001 Response duration <=2 yrs vs. >2 yrs Thal/Dex 0.2 (0.003, 18.5) 0.51 Dex 0.15 (0.02, 0.98) 0.048 VBMCP(E5A93+ E9486) 1.7 (1.2, 2.3) 0.0009 VBMCP+alpha2IFN (E5A93+ E9486) 3.0(2.1, 4.3) <0.0001 VBMCP+CYCLOPHOSPHAMIDE 2.1 (1.4, 3.3) 0.006 Figure 1: Overall survival since relapse between patients progressed within 3 yrs since randomization vs. after 3 yrs. Figure 1:. Overall survival since relapse between patients progressed within 3 yrs since randomization vs. after 3 yrs.

TPS8052 Background: The most common translocation in multiple myeloma (MM) is t(11;14)(q13;q32), present in approximately 20% of cases. MM cells with t(11;14) usually have a favorable high BCL-2 level and inferior outcomes compared to standard risk MM. Venetoclax (VEN) is a potent, selective, orally available small-molecule BCL-2 inhibitor that induces cell death in MM cell lines and primary samples. VEN has single agent activity in relapsed/refractory MM (RRMM) with an acceptable safety profile, especially in t(11;14) MM; however, non- t(11;14) MM patients may benefit from single agent VEN and VEN incorporated in multi-agent RRMM regimens. Dexamethasone (d) promotes Bcl-2 dependence in MM resulting in sensitivity to VEN and this combination with bortezomib (Vd-VEN) has an acceptable safety profile with high response rates in heavily pre-treated MM. Combination therapy with daratumumab and bortezomib (DVd) has become a standard of care in RRMM. Our hypotheses are that the addition of VEN will improve upon this standard and be most effective in the t(11;14) positive subset. Methods: Eligibility criteria include RRMM with measurable disease, not bortezomib refractory, platelet count > 100K. t(11;14) is an integral biomarker with status (positive or negative) established at registration. After a Ph1 study to determine the recommended phase 2 VEN dose, patients are randomized to DVd +/- VEN [stratified by prior lines of therapy and R-ISS]. The primary Ph2 objectives are to compare 8-cycle minimal residual disease (MRD) negative rate and to inform the role of t(11;14) as a biomarker. The Ph2 design proposed by Freidlin et al. follows a decision algorithm as outlined in the table below. Simulations were run to establish an optimal sample size given various parameters including biomarker prevalence and power to make appropriate decisions for a Ph3 design. Target Ph2 accrual is 240 patients with a 1/3 positive:2/3 negative t(11;14) split. Clinical trial information: NCT03701321. [Table: see text]

8592 Background: Accrual to NCI clinical trials(CT)is often slower than planned at times mandating premature closure resulting in loss of valuable resources and delay of scientific progress. Methods: The NCI-MYSC AWG identified 10 potential BtA. SWOG, ECOG and Alliance investigators were queried and agreed that these barriers impede accrual (results stratified for academic and community sites). The MYSC AWG developed in collaboration with NCI and FDA strategies to overcome these barriers. Results: Strategies listed for the 3 most often cited BtA: 1. Reimbursement for CT related expenses:increase awareness of improved reimbursement for phase II CT; tailor reimbursement according to CT complexity; request funds from industry and other sources ( http://biqsfp.cancer.gov ) for qualifying ancillary CT components. 2. Spectrum of available treatment options influences CT participation: educate patients and providers about the significance of a new CT using social media, presentations at national meetings and by adding educational material to CT protocol; encourage opinion leaders and advocacy groups not to promote a new therapy as “standard” in the absence of phase III data. 3. Requirement of CT specific therapy at NCI designated sites only: “MYSC AWG Drug Administration Table” describes NCI/FDA approved rules for CT specific drug administration; CT protocol will outline which standard treatment components of a CT can be administered at any site as long as protocol specific guidelines are followed and conduct is supervised by enrolling investigator. Examples of additional strategies to overcome identified BtA: determine feasibility, indication and insurance coverage of CT specific tests during protocol development; discourage narrow eligibility criteria; avoid competing CT; allow up to 1 cycle of commercially available therapy prior to enrollment; CIRB support for phase II CT. Conclusions: The MYSC Accrual Working Group developed in collaboration with NCI and FDA strategies to overcome barriers to myeloma clinical trial accrual. These strategies may be applicable to NCI-sponsored clinical trials evaluating interventions in other diseases.

e19517 Background: Investigators cite complicated test (T) schedules as barriers to the conduct of clinical trials, especially T that do not contribute to outcome or pt safety. In MM protocols, some T are prone to being done inaccurately (e.g. UPEP, 24 hour urine collections), or are not useful (e.g. uric acid, AST/ALT) in determination of response (R) or safety. These T lead to increased cost, protocol violations, and do not enhance outcome. Methods: We analyzed data submitted for pts on E4A03 to examine frequency of missing data for R T: serum and urine (U) PEP, immunofixation (IFE) bone surveys (BS), and safety labs for C1-4. Results: Table outlines % pts with completed T. Most had T for serum M protein, as well as heme T but serum and U PEP, and IFE dropped off by C4. Other T e.g. uric acid were completed in 77%. Only 79% of pts had a BS repeated at C4. Incorrect or missing U data led to categorization of 16/445 (3.6%) pts as ineligible and was most frequent reason for ineligibility (69%). Missing U data led to 13/26 pts not evaluable. Analysis of SAE during the C1-4 revealed no SAE for hyperuricemia and < 5 SAE for AST/ALT. Only 5% of pts had lab-based SAE filed in 4 C. Conclusions: Required U T and BS to assess R in E4A03 were missing or completed inadequately and caused pts to be ineligible and or not evaluable. Such T need to be eliminated or replaced. Strategies to monitor data submission in real time may reduce subject loss due to T error. The requirement for routine T should be reassessed to create simpler trial design. Clinical trial information: NCT00098475. [Table: see text]

LBA8025 Background: We compared lenalidomide plus high (standard) dose Dex (R+HighD) versus lenalidomide plus low dose Dex (R+LowD) in newly diagnosed MM. Methods: Pts with untreated, symptomatic MM were eligible. Pts in both arms received lenalidomide 25 mg/day PO days 1–21 every 28 days. In addition, pts in the R+HighD arm received Dex 40 mg days 1–4, 9–12, and 17–20 PO every 28 days; pts in the R+LowD arm received Dex 40 mg days 1, 8, 15, and 22 PO every 28 days. The primary null hypothesis was that response rates at 4 months on the 2 arms are equivalent. Planned sample size was 196 eligible pts per arm with one-sided 0.10 Type I and 0.05 Type II error rate. Pre-planned interim analysis is performed by an independent DMC when full information is available on 25%, 50% and 75% of accrual. All analysis were intent to treat. Results: 445 pts (median age, 65 yrs) were accrued; 223 randomized to R+HighD, 222 to R+LowD. Arms were well balanced for age, gender, stage, bone lesions, hemoglobin, beta-2 microglobulin, performance status, bone marrow plasma cells, and M protein levels at baseline. Major grade 3 or higher toxicities included thromboembolism (22.1% with R+HighD vs 6.1% in R+LowD), infection/pneumonia (15.7% vs 7.5%) and hyperglycemia (9.7% vs 6.6%). Grade 3 or higher non-hematologic toxicities occurred in 65.9% (R+HighD) versus 54.9% (R+LowD) respectively; corresponding grade 4 or higher rates were 20.3% vs 13.1% respectively. Overall survival (OS) at first interim analysis was significantly superior with R+LowD, P<0.001; one year survival 96.5% (R+LowD) versus 86% (Rev+HighD). OS differences in favor of R+LowD were seen in pts <65 (P=0.015; one year rate 98% vs 90%) and pts 65 and older (P=0.004; one year rate 95% vs 83%), respectively. DMC recommended release of survival results, and recommended switching all pts to R+LowD. DMC also recommended closure of an expansion phase trial of R+HighD investigating optimal thromboprophylaxis. Conclusions: Lenalidomide plus low-dose dexamethasone is associated with superior OS compared to lenalidomide plus high-dose dexamethasone. This study has major implications for future use of high-dose dexamethasone in the treatment of MM. No significant financial relationships to disclose.

Background: Novel agent induction and AHCT remains the preferred initial therapeutic strategy for transplant-eligible MM patients. Current prognostic tools in MM focus solely on disease-specific factors at diagnosis to determine patient prognosis-International Staging System (ISS) and revised-ISS (R-ISS). A major limitation to both, the ISS and R-ISS, is that they are not specific for HCT-eligible patients and do not take into account other patient factors that may enter into a decision to pursue AHCT. The data used to generate these staging systems were from broad populations with varying upfront treatment strategies and included patients who were ineligible for intensive therapy. Additionally, there is considerable interest in identifying the population that relapses early despite modern induction/AHCT approaches who are candidates for novel approaches for maintenance/consolidation. To address these problems, we used data from the Center for Blood and Marrow Transplant Research (CIBMTR) registry to identify disease-, patient-, and transplantation-specific variables that are associated with progression-free survival (PFS) in patients undergoing upfront AHCT (within 12 months of diagnosis). Methods: We used the outcomes of 2528 MM patients undergoing upfront AHCT from 2008-2017 reported to the CIBMTR. Patients were divided into training and validation sets with a 50% random split. High risk cytogenetics was defined as the presence of one or more of the following: t(4;14), t (14;16), t (14;20), del 13q, del 17p, 1q gain, or 1p deletion. We used a Cox multivariable model to identify factors prognostic of progression free survival (PFS) in a training subset. The regression coefficients of the final model was transformed into a risk score with an appropriate transformation. A weighted score using these factors was assigned to the training cohort (n = 917) and validation cohort (n=897) using subset that had all values that entered the final model. Kaplan-Meier estimates of the individual scores were used to classify patients into risk groups for both cohorts. Results: Baseline characteristics of these patients are shown in Table 1. No cytogenetic abnormality, VRD induction, pre-AHCT bone marrow plasma cells (BMPCs) &lt;10% and 1 line of induction chemotherapy were assigned 0 points. Pre-AHCT BMPCs ≥10% (hazard ratio HR, 1.47; 95% CI, 1.19-1.83), use of ≥2 lines of induction chemotherapy prior to AHCT (HR 1.32; 95% CI 1.06-1.64), standard cytogenetic risk vs. no abnormality (HR 1.41; 95% CI 1.13-1.77) and induction regimens (non-VRD regimens vs. VRD) (HR 1.4, 95% CI 1.17-1.74) were associated with increased hazard of progression and assigned 1 point in the scoring system. Presence of high-risk cytogenetics vs. no abnormality (HR 1.87; 95% CI 1.45-2.42) was assigned 2 points, and the use of thalidomide and dexamethasone (TD) as an induction regimen (HR 2.19; 95% CI 1.48-3.2) was assigned 3 points. A two-category system was created based on the scoring: low risk (0-3) and high risk (4-6). The scoring system was prognostic for PFS when applied to both cohorts. High-risk group was found to have significantly higher risk of progression and/or death compared to low risk in training (HR 2.2; 95% CI 1.74-2.86; p&lt;0.0001) and validation cohort (HR 1.7, 95% CI 1.30-2.22; p=0.0001) respectively (Table 2). The 3-year PFS in the training cohort was 60% (95% CI 56%-64%) in low risk and 27% (95% CI 17%- 36%) in high risk while in the validation cohort was 51% (95% CI 47%-55%) in low risk and 28% (95% CI 16%- 39%) in high risk (Figure 1A and 1B). Conclusions: We describe a prognostic model specifically for patients undergoing upfront AHCT in MM which can identify patients at very high risk for early relapse/progression. These patients should be ideal candidates for studies of immunotherapy or other interventions after AHCT aimed at reducing relapse. Disclosures Dhakal: Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria; Takeda: Membership on an entity's Board of Directors or advisory committees. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Shah:Genentech, Seattle Genetics, Oncopeptides, Karoypharm, Surface Oncology, Precision biosciences GSK, Nektar, Amgen, Indapta Therapeutics, Sanofi: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Nkarta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees; Teneobio: Consultancy, Membership on an entity's Board of Directors or advisory committees; University of California, San Francisco: Employment; Poseida: Research Funding; Indapta Therapeutics: Equity Ownership; Celgene, Janssen, Bluebird Bio, Sutro Biopharma: Research Funding. Qazilbash:Amgen: Consultancy, Other: Advisory Board; Autolus: Consultancy; Bioclinical: Consultancy; Genzyme: Other: Speaker. D'Souza:EDO-Mundapharma, Merck, Prothena, Sanofi, TeneoBio: Research Funding; Prothena: Consultancy; Pfizer, Imbrium, Akcea: Membership on an entity's Board of Directors or advisory committees. Hari:AbbVie: Consultancy, Honoraria; Cell Vault: Equity Ownership; Sanofi: Honoraria, Research Funding; Spectrum: Consultancy, Research Funding; Amgen: Research Funding; Kite: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; BMS: Consultancy, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding.

Introduction: Proteasome inhibitors (PI), immunomodulatory agents (IMiDs) and the CD38 monoclonal antibody daratumumab (dara) have transformed the management of MM, yet eventual refractoriness to these agents seems inevitable. Relapsed and refractory MM (RRMM) which becomes triple class refractory (TCR, i.e. refractory to a PI, an IMiD and Dara) uncommonly responds to further lines of therapy and survival is dismal. Selinexor is a selective inhibitor of nuclear export compound targeting exportin 1 (XPO1) which is overexpressed in MM cells and essential for their survival. In the STORM study, selinexor in combination with low-dose dexamethasone (Sd) demonstrated promising efficacy in TCR, penta-exposed (TCR-PE, i.e. exposed to lenalidomide, pomalidomide, bortezomib, carfilzomib and dara) MM. Establishing the natural history for outcomes in the TCR-PE population can help provide context to understand the outcomes observed with Sd in STORM. In the retrospective MAMMOTH study, we reported the outcomes of patients with RRMM after they became refractory to dara, including a subset of patients who were TCR. We further analyzed the MAMMOTH dataset to generate a cohort of patients similar to patients in STORM in order to compare conventional care vs. Sd. Methods: We included all patients in STORM who received Sd as the first line therapy after they achieved TCR-PE status (n=64). We extracted from the MAMMOTH dataset all patients who were not exposed to Sd in a subsequent line of therapy, became TCR-PE and who received subsequent MM-directed therapy (n=128). Overall response rate (ORR) was evaluated according to IMWG criteria. Overall survival (OS) was calculated from the time of initiation of next line of therapy after TCR-PE status until death or last follow-up. We compared OS in STORM vs. MAMMOTH utilizing cox-regression analysis with adjustment for covariables potentially influencing the outcome. Results: Baseline patient characteristics and prior therapies are per table. The two cohorts were similar in terms of age, number of prior lines of therapy and presence of high-risk cytogenetic abnormalities. STORM patients had longer time between MM diagnosis and post TCR-PE therapy with a higher proportion of refractoriness to carfilzomib. Patients in STORM had ORR to Sd of 32.8% vs 25.0% for patients receiving conventional care in MAMMOTH (P=0.078). In direct comparison, patients in STORM had better OS than patients in MAMMOTH (median 10.4 vs. 6.9 months) (P=0.043, figure). In multivariate analysis, STORM patients had lower risk of death in comparison with MAMMOTH patients (aHR=0.55, 95%C.I. 0.35-0.86, P=0.009). Refractoriness to carfilzomib (aHR=2.20, 95%C.I. 1.16-4.15, P=0.015) and high-risk cytogenetics (aHR-1.66, 95% C.I. 1.13-2.42, P=0.009) were also associated with inferior OS. Conclusion: Despite inherent limitations in comparison of trial enrollees vs. real world patients, this analysis suggests improved OS with Sd vs conventional care in patients with TCR-PE RRMM. Prognosis for these patients remains poor and underscores the need for therapeutic advancements. Disclosures Costa: Janssen: Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria, Speakers Bureau; GSK: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy; Karyopharm: Consultancy; Fujimoto Pharmaceutical Corporation Japan: Other: Advisor; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau. Hari:Kite: Consultancy, Honoraria; Amgen: Research Funding; Spectrum: Consultancy, Research Funding; Sanofi: Honoraria, Research Funding; Janssen: Consultancy, Honoraria; BMS: Consultancy, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Cell Vault: Equity Ownership; AbbVie: Consultancy, Honoraria. Kumar:Janssen: Consultancy, Research Funding; Takeda: Research Funding; Celgene: Consultancy, Research Funding. Tang:Karyopharm: Employment. Shah:Karyopharm Therapeutics Inc: Employment, Equity Ownership. Jagannath:BMS: Consultancy; Merck: Consultancy; Medicom: Speakers Bureau; Celgene: Consultancy; Novartis: Consultancy; Multiple Myeloma Research Foundation: Speakers Bureau. Chari:Oncoceutics: Research Funding; Novartis Pharmaceuticals: Research Funding; GlaxoSmithKline: Research Funding; Array Biopharma: Research Funding; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium/Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding. Shacham:Karyopharm Therapeutics Inc: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Ma:Karyopharm: Employment, Equity Ownership. Siegel:Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Bristol-Myers Squibb Company: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Biran:Amgen: Consultancy, Honoraria, Research Funding; Merck: Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Bristol Meyers Squibb: Research Funding. Lonial:BMS: Consultancy; Genentech: Consultancy; GSK: Consultancy; Janssen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Amgen: Consultancy; Celgene Corporation: Consultancy, Research Funding; Karyopharm: Consultancy. Richardson:Amgen: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Research Funding. Kauffman:Karyopharm Therapeutics Inc: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Malek:Adaptive: Consultancy; Amgen: Speakers Bureau; Janssen: Speakers Bureau; Celgene: Consultancy; Takeda: Consultancy; Sanofi: Consultancy; Medpacto: Research Funding. Fiala:Incyte: Research Funding. Usmani:Amgen, Celgene, Janssen, Sanofi, Takeda: Speakers Bureau; Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, SkylineDX, Takeda: Other: Consultant/Advisor; Amgen Array Biopharma, Bristol-Myers Squibb, Celgene, Janssen, Merck, Pharmacyclics, Sanofi, Takeda: Other: Research Grant. Kang:Takeda Oncology: Consultancy; InCyte Corportation: Research Funding. Cornell:Takeda: Consultancy; KaryoPharm: Consultancy.

Patients who develop therapy-related myelodysplastic syndromes (t-MDSs) or acute myeloid leukemia (t-AML) following prior chemotherapy or an autologous hematopoietic cell transplant (HCT), have a poor prognosis. An earlier analysis of allogeneic HCT (n=868, 1990-2004) showed 5-year overall survival (OS) and disease free survival (DFS) were 22% and 21% (reference). Furthermore, older age, graft source other than a HLA-matched sibling or HLA well matched unrelated donor (URD), t-AML not in remission or advanced t-MDS, and poor risk cytogenetics were associated with worse outcomes. Modern supportive care and conditioning regimens including reduced intensity (RIC) regimens may have improved outcomes. Therefore we analyzed 1531 HCT for t-AML (n = 772) or t-MDS (n = 759) performed from 2000 to 2014. The median age at transplant was 52 (18-77) for t-AML and 59 (18-74) for t-MDS. Eleven percent of patient with t-AML and 24% of patient with t-MDS had a prior autologous transplant. A myeloablative regimen was used for conditioning in 61% of patients with t-AML and 49% of patients with t-MDS (Table 1). For t-AML, the 5-year non-relapse mortality (NRM) and relapse rates (RR) were 33% (95% confidence interval [CI], 30-36) and 43% (40-47), respectively. For t-MDS, the 5 year TRM and RR were 32% (29-36) and 46% (43-50), respectively. Five year DFS and OS were 24% (21-27) and 25% (22-28), respectively, for patients with t-AML. Five year DFS and OS were 21% (18-24) and 27% (23-31), respectively, for patients with t-MDS. In multivariate analysis, t-AML OS and DFS was worse for: previous autologous transplant, relapsed disease at HCT, intermediate or adverse cytogenetics, partially matched and cord blood grafts, and RIC. For t-MDS: age greater than 60, previous autologous transplant, very high IPSS score, and use of HLA-partially matched unrelated grafts. A significant minority of patients with t-AML and t-MDS can achieve long-term remission with allogeneic HCT, yet risks of both NRM and relapse are still excessive. Relapse is the major cause of treatment failure. Disclosures Metheny: Takeda: Speakers Bureau; Incyte: Speakers Bureau. Weisdorf:Incyte: Research Funding; Fate Therapeutics: Consultancy; Pharmacyclics: Consultancy. Kebriaei:Jazz: Consultancy; Amgen: Research Funding; Pfizer: Honoraria; Kite: Honoraria.