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8032 Background: The impact of t(11;14) (16%–24% of MM pts) on prognosis is not fully understood. Consensus is lacking on the effects of induction treatment (tx) on outcomes with t(11;14). The Connect MM Registry (NCT01081028) is a large, US, multicenter, prospective observational cohort study of pts with NDMM designed to examine real-world diagnostic patterns, treatment (tx) patterns, clinical outcomes, and HRQoL pt-reported outcomes in pts with NDMM. The impact of t(11;14) on tx outcomes are reported. Methods: Analysis included data from pts from 250 community, academic, and government sites in cohort (C) 1 (9/2009–12/2011) and C2 (12/2012–4/2016), who completed first-line (1L; induction) tx and were tested for t(11;14) by FISH or cytogenetics. Primary end points (progression-free survival [PFS] and overall survival [OS]) were measured from start of 1L tx to earliest event (PFS, death or progression; OS, death), loss to follow-up, or data cutoff, adjusted for baseline (BL) risk factors. A sensitivity analysis excluding pts with concomitant cytogenetic abnormalities [del 17p, t(4;14), t(14;16), 1q+] was also performed. Results: By 1/2018, 3011 pts were enrolled; 2938 were treated. Of 1574 enrolled pts tested for t(11;14), 378 were t(11;14)+ and 1196 were t(11;14)−. More pts in C2 vs C1 were t(11;14)+ (60% vs 40%). BL characteristics were similar between groups. t(11;14) status did not affect PFS ( P= NS) or OS ( P= NS; Table). Pts in C1 and C2 received similar 1L txs (IMiD agent + proteasome inhibitor [PI], 30% vs 42%; PI only, 42% vs 43%; IMiD agent only, 17% vs 11%). Results were similar when pts with concomitant abnormalities were excluded. Conclusions: Results of this analysis suggest that t(11;14) does not affect PFS and OS outcomes in NDMM pts. Clinical trial information: NCT01081028. [Table: see text]

8015 Background: Multiple myeloma (MM) is a heterogeneous disease with varying survival outcomes depending on the presence of certain genetic abnormalities. Common abnormalities include trisomies, translocations involving chromosome 14, and amplifications or deletions of chromosomes 1, 13, and 17. t(11;14), occurring in approx. 15% of patients (pts) with MM, is considered a standard risk abnormality, but recent data suggest that the prognosis may be inferior to what had been expected. This is of particular relevance as new therapeutic options such as the BCL-2 inhibitor venetoclax has been shown to be effective in t(11;14) pts. Methods: This was a multicenter study designed and conducted by the IMWG, to identify the outcomes of pts with t(11;14) using a retrospective cohort of pts. Pts with MM diagnosed between 2005 and 2015 with t(11;14) identified on FISH performed within six months (mos) of diagnosis, and with treatment details available and if alive, a minimum of 12 mos of follow up, were enrolled. Results: The current analysis includes 848 pts with a median age of 64.4 years; 60.0% are male. The median follow-up from diagnosis for the entire cohort was 45.7 mos; 84.7% of the pts were alive at the last follow up. ISS stage distribution included: Stage 1 (35.3%), Stage II (38.9%) and stage III (25.8%). The distribution of FISH abnormalities included: del 13q (14.5%), 1q amp (12.1%), del 17p or monosomy 17 (6.1%). Pts received initial therapy with different regimens: IMiD-24.3%, PI-41.0%, both-20.8% and 13.8% had no novel agent. The drug classes by line of therapy are shown in table. An early stem cell transplant (SCT) was used in 40.8% of pts. The median time to next treatment (TTNT) after initial treatment was 15.0 (95% CI: 12.2 to 17.7) mos. The median overall survival from diagnosis for the entire cohort was 82.5 (95% CI: 73.5 to 95.8) mos. Conclusions: This is the first study to examine the outcomes of a large group of myeloma pts with t(11;14) abnormality. Pts receiving a combination if a PI and an IMiD appear to have the best survival outcomes and thse receiving an early SCT appear to have excellent survival with median OS approaching 10 years. Additional pts are being accrued to this study and additional analysis examining the variables affecting response duration and survival will be presented. [Table: see text]

8000 Background: The diagnostic criteria for MM were revised in 2014, recategorizing ultra-high risk (i.e., 80% at two years) as active myeloma requiring therapy. The removal of patients at the highest risk of progression from the smoldering group requires reassessment of current risk stratification models. Methods: We designed a multicenter, retrospective study of SMM patients to develop a risk stratification model. Patients diagnosed with SMM on/after January 1, 2004 were included if they had no disease progression within 6 months, had baseline data from diagnosis (+/- 3 months), had a follow up of ≥1 year, and did not participate in a therapeutic trial of SMM. Various clinical and laboratory factors were explored to identify factors that predicted progression at 2 years. Univariate Cox regressions were run for each factor. For factors with p-values ≤ 0.25, optimal cut points were identified using Youden’s index. Binary factors were used in stepwise regression to fit multivariable Cox model and significant risk factors were determined (F-test). Results: Overall, 2004 patients were included (ages 26-93, 51% female). Factors independently associated with progression (optimal cutoffs) included: Serum M protein (2 g/dL), involved to uninvolved serum-free light chain ratio (20), and marrow plasma cell % (20%). Patients were stratified using the risk factors: Low- (0 factors), Intermediate- (1), and High-Risk (≥2). Previously used high risk markers such as Bence Jones proteinuria (≥500 mg/24 hours) and severe immunoparesis (50% decrease in uninvolved immunoglobulin levels) were both significant in univariate analysis, but were eliminated on step wise selection. Compared to the low risk group, intermediate- and high-risk groups had significantly higher rate of progression (Table). Within the high-risk group, having all 3 risk factors (n=61) versus 2 did not add to the model, with insufficient separation between 2 and 3 factors. Conclusions: We have developed a risk stratification model for SMM that incorporates revised cutoffs for previously used parameters (20/2/20) that can be universally applied. Additonal analysis are being conducted to develop models that utilize common cytogenetic abnormalities, as well as those without FLC given lack of availability of all tests across the world. [Table: see text]

8037 Background: Advances in the treatment of MM have greatly improved clinical outcomes for patients (pts). SPM occurrence has been observed in early and late stage MM as well as with increasing age. US SEER Cancer Registry reports a background incidence rate of SPM 2.1/100 person-yrs (PY) among persons ≥ 65 yrs of age. However, incidence of SPM in MM pts and the relationship to therapy still warrants further exploration. Methods: Connect MM is a US-based observational registry designed to characterize pts with newly diagnosed MM from 266 US sites. Initiated in Sep 2009, patient data were collected at baseline and each subsequent quarter with a standardized form. On Dec 14, 2011, Connect MM reached full enrollment at 1,500 pts. Results: As of Jan 13, 2012, preliminary retrospective SPM data is available for 1015 pts. Median age was 67 yrs, 56.8% male, and median follow-up was 10.6 mo (0.03-24.9 mo). 12 pts (7 male) with median age of 68.5 yrs developed SPM. Median time to SPM was 8.5 mo (0.8-17.7 mo) after treatment initiation. 11 invasive SPM were observed - 4 hematological (heme): 1 AML, 1 MDS, 1 CMML and 1 DLBCL, and 7 solid: 2 melanoma skin, 1 bronchus, 1 breast, 1 prostate, 1 tonsil, and 1 gastric carcinoid. Also, 1 pt had non-melanoma skin cancer (NMSC), and 1 pt with invasive skin cancer also had NMSC. Of the 4 pts developing heme SPM, 3 had bortezomib (BORT), 1 had thalidomide (THAL), 1 had lenalidomide (LEN), 2 had melphalan (MEL), and all 4 pts had steroids. Of the 7 pts who developed solid tumor SPM, 5 had BORT, 5 had LEN, 2 had doxorubicin, 1 had MEL, 5 had steroids, 1 had irradiation, and 1 had not received MM treatment. 2 pts with prior history of invasive malignancy developed solid tumor SPM (1 pt also developed NMSC).1 pt who received irradiation developed NMSC. Early overall incidence of invasive SPM was 1.21/100 PY (95% CI 0.60, 2.16) for all pts and 1.20/100 PY (95% CI 0.44,2.62) for pts ≥ 65 yrs of age. Conclusions: This preliminary analysis shows that SPM occurred at an expected rate in this disease specific registry of patients with NDMM and appeared to occur irrespective of MM treatment administered. Incidence rates of SPM may increase over time as patients receive transplantation and alkylators. Prospective observation will continue.

e18556 Background: Studies in the United States (US) have identified variation in incidence and survival of multiple myeloma (MM) patients of different races, and noted that MM is the most common hematologic cancer among African Americans. This analysis evaluated whether health-related quality of life (HRQOL) of patients in the US varies by race as they initiate treatment having been newly diagnosed with active, symptomatic MM. Methods: Data were collected in Connect MM, a prospective US observational registry begun in September 2009. Data on patient demographics and clinical characteristics were provided by clinicians. HRQOL was reported by patients at enrollment within 2 months of diagnosis. Patients completed the Brief Pain Inventory (BPI), EQ-5D, and Functional Assessment of Cancer Therapy-Multiple Myeloma (FACT-MM). Mean reported scores for BPI, EQ-5D and FACT-MM were analyzed by patient race. Statistical significance was ascertained by ANOVA using SAS 9.1. Results: Baseline HRQOL data were reported by 1144 patients (enrolled in 228 centers) of whom 82% were White, 13% Black, and 6% Other race. The cohorts did not differ statistically by ECOG status or by multiple myeloma stage (assessed by either the International Staging System or the Durie and Salmon system). Compared to non-Blacks, Black patients reported less anxiety/depression on the EQ-5D (p=0.030) and better emotional well-being on the FACT-MM (p=0.003). No other statistically significant differences were noted between cohorts on the BPI, other EQ-5D domains (mobility, self care, usual activities, pain/discomfort), or other FACT-MM domains (physical, social/family, functional, and MM-specific considerations). Conclusions: Initial results from the Connect MM Registry indicate that baseline HRQOL prior to initiation of treatment may vary by patient race with respect to emotional well-being, and specifically anxiety/depression. These results serve as a baseline reference for future analyses. As patients in the Connect MM Registry proceed through therapy, analyses should be conducted of patients by race, among other characteristics and factors, to determine whether it may be associated with subsequent clinical outcomes and HRQOL over time.

8095 Background: Multiple myeloma (MM) remains incurable and invariably relapses after initial therapy. There is no uniform approach to management of relapsed MM and is dictated by type of initial therapy and the response seen, and availability of new drugs. The outcomes associated with current approaches have not been systematically examined. Methods: We enrolled 383 patients (pts) with myeloma who had a documented relapse between Jan 2007 and June 2010, including 220 from Europe, 106 from Asia, and 31 from South America and 26 from North America. Time Zero (T0) was defined as date of treatment after first relapse. Results: Across the study, 61% were male and 49% were over 65 years at T0. ISS stage distribution at diagnosis included 26, 40 and 33% of patients in stages 1, 2 and 3, respectively. Among regimens used at first relapse; bortezomib (Btz) containing regimens were most common (54%), followed by lenalidomide (Len, 25%) and cyclophosphamide (21%). The overall response rate (>=PR) to first therapy after relapse was 58% including 14% with a CR. There was a progressive decrease in the response rates with successive regimen; 45%, 30% and 15% for regimens 2, 3 and 4 respectively. Len use was considerably lower in the Asian cohort, while Btz use was comparable across the regions. The median PFS from T0 was 13 mos and OS was 35 mos, for the entire cohort. The PFS to first salvage regimen was similar across the regions, while OS was shorter for the Asian and South American cohorts. In a univariate analysis, ISS stage 3, presence of cytogenetic abnormalities, history of plasma cell leukemia or extramedullary disease (EMD), bone marrow PC% > 33% and presence of renal insufficiency were all associated with a shorter PFS as well as shorter OS (P<=0.01). In a multivariate model, ISS stage 3 and presence of EMD were most associated with short OS. Conclusions: Median PFS for current second line regimens, typically containing Btz or Len appear to be 1 yr with an OS from first relapse of about 3 yrs. The OS from first relapse is nearly double that seen in a cohort of patients in first relapse prior to introduction of new drugs. Clear-cut regional differences can be seen in terms of patterns of drug use and likely reflect drug availability and healthcare costs.

Background: Multiple myeloma (MM) is common among the elderly, with 35% of patients (pts) diagnosed being aged ≥75 years (y). With increasing overall life expectancy, the incidence and prevalence of newly diagnosed and previously treated MM patients ≥80 y is expected to increase over time. Because elderly pts are often excluded from clinical trials, data focused on their treatment patterns and clinical outcomes are lacking. The Connect® MM Registry (NCT01081028) is a large, US, multicenter, prospective observational cohort study of pts with newly diagnosed MM (NDMM) designed to examine real-world diagnostic patterns, treatment patterns, clinical outcomes, and health-related quality of life patient-reported outcomes. This analysis reviews treatment patterns and outcomes in elderly pts from the Connect MM Registry. Methods: Pts enrolled in the Connect MM registry at 250 community, academic, and government sites were included in this analysis. Eligible pts were adults aged ≥18 y with symptomatic MM diagnosed ≤2 months before enrollment, as defined by International Myeloma Working Group criteria; no exclusion criteria were applied. For this analysis, pts were categorized into 4 age groups: <65, 65 to 74, 75 to 84, and ≥85 y. Pts were followed from time of enrollment to the earliest of disease progression (or death), loss to follow-up, or data cutoff date of February 7, 2019. Descriptive statistics were used for baseline characteristics and treatment regimens. Survival outcomes were analyzed using Cox regression. Time to progression (TTP) analysis excluded causes of death not related to MM. Results: Of 3011 pts enrolled (median age 67 y), 132 (4%) were aged ≥85 y, and 615 (20%) were aged 75-84 y at baseline. More pts aged ≥85 y had poor prognostic factors such as ISS stage III disease and reduced hemoglobin (<10 g/dL or >2 g/dL <LLN) compared with other age groups, although no notable differences between creatinine and calcium levels were observed across age groups (Table). A lower proportion of elderly pts (75-84 and ≥85 y) received triplet regimens as frontline therapy. More elderly pts received a single novel agent, whereas use of 2 novel agents was more common in younger pts (Table). The most common frontline regimens among elderly pts were bortezomib (V) + dexamethasone (D), followed by lenalidomide (R) + D, whereas those among younger pts included RVD, followed by VD and CyBorD (Table). No pt aged ≥85 y, and 4% of pts aged 75-84 y received high-dose chemotherapy and autologous stem cell transplant (vs 61% in the <65 y and 37% in the 65-74 y age group). The most common maintenance therapy was RD in pts ≥85 y (although the use was low) and R alone in other age groups (Table). In the ≥85 y group, 27%, 10%, and 4% of pts entered 2L, 3L, and 4L treatments respectively, vs 43%, 23%, and 13% in the <65 y group. Progression-free survival was significantly shorter in the ≥85 y age group vs the 75-84 y age group (P=0.003), 65-74 y age group (P<0.001), and <65 y age group (P<0.001; Fig.1). TTP was significantly shorter in the ≥85 y group vs the <65 y group (P=0.020); however, TTP was similar among the 65-74 y, 75-84 y, and ≥85 y cohorts (Fig. 2). Overall survival was significantly shorter in the ≥85 y group vs the 75-84 y, 65-74 y, and <65 y groups (all P<0.001; Fig. 3). The mortality rate was lowest (46%) during first-line treatment (1L) in pts aged ≥85 y (mainly attributed to MM progression) and increased in 2L and 3L (47% and 54%, respectively); a similar trend was observed in the younger age groups. The main cause of death was MM progression (29% in the ≥85 y vs 16% in the <65 y group). Other notable causes of death in the ≥85 y group included cardiac failure (5% vs 2% in <65 y group) and pneumonia (5% vs 1% in <65 y group). Conclusions: In this analysis, elderly pts received similar types of frontline and maintenance regimens as younger pts, although proportions varied with decreased use of triplet regimens with age. Considering similarities in TTP across the 65-74 y, 75-84 y, and ≥85 y cohorts, these real-world data support active treatment and aggressive supportive care of elderly symptomatic pts, including with novel agents. Additionally, further clinical studies specific to elderly patients with MM should be explored. Disclosures Lee: Amgen: Consultancy, Research Funding; GlaxoSmithKline plc: Research Funding; Sanofi: Consultancy; Daiichi Sankyo: Research Funding; Celgene: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy, Research Funding. Ailawadhi:Janssen: Consultancy, Research Funding; Takeda: Consultancy; Pharmacyclics: Research Funding; Amgen: Consultancy, Research Funding; Celgene: Consultancy; Cellectar: Research Funding. Gasparetto:Celgene: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; Janssen: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; BMS: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed . Jagannath:AbbVie: Consultancy; Merck & Co.: Consultancy; Bristol-Myers Squibb: Consultancy; Karyopharm Therapeutics: Consultancy; Celgene Corporation: Consultancy; Janssen Pharmaceuticals: Consultancy. Rifkin:Celgene: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Durie:Amgen, Celgene, Johnson & Johnson, and Takeda: Consultancy. Narang:Celgene: Speakers Bureau. Terebelo:Celgene: Honoraria; Jannsen: Speakers Bureau; Newland Medical Asociates: Employment. Toomey:Celgene: Consultancy. Hardin:Celgene: Membership on an entity's Board of Directors or advisory committees. Wagner:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; American Cancer Society: Other: Section editor, Cancer journal. Omel:Celgene, Takeda, Janssen: Other: Patient Advisory Committees. Srinivasan:Celgene: Employment, Equity Ownership. Liu:TechData: Consultancy. Dhalla:Celgene: Employment. Agarwal:Celgene Corporation: Employment, Equity Ownership. Abonour:BMS: Consultancy; Celgene: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Background: MM clinical trials often have stringent eligibility criteria that limit the enrollment of patients (pts) reflective of the general patient population (Shah, Clin Lymphoma Myeloma Leuk 2017). The Connect® MM Registry, a prospective observational study of pts with newly diagnosed MM (NDMM) in the US, provided the opportunity to examine differences between pts with MM who were identified as RCT-eligible vs -ineligible, to observe the generalizability of clinical trial results to real-world clinical settings. Differences in baseline characteristics, treatment, clinical outcomes, and HRQoL were examined in RCT-eligible and -ineligible pts from this registry, which represents an unselected, broad real-world population. Methods: Pts with NDMM were enrolled at 250 community, academic, and government sites. Eligible pts were ≥18 y of age with symptomatic MM diagnosed ≤2 months preenrollment per the International Myeloma Working Group (IMWG) criteria. For this analysis, pts were considered ineligible for RCT per the following key exclusion criteria previously described: absolute neutrophil count ≤1.5 × 109/L, platelet count ≤75 × 109/L, creatinine >2.5 mg/dL, AST/ALT >3 times the ULN, peripheral neuropathy grade >2; ECOG PS 3/4; history of myelodysplastic syndromes/other hematologic malignancies, or solid tumors (Shah 2017). Sites administered pt HRQoL questionnaires and provided clinical data at baseline and quarterly during follow-up until death or study discontinuation. Differences in HRQoL at baseline, changes from baseline to 1 and 2 years, and survival outcomes, adjusted for covariates via propensity score, were compared between RCT-eligible/-ineligible pts. Results: Of the 3011 pts enrolled, 2873 pts met the CRAB (hyperCalcemia, Renal failure, Anemia, and Bone disease) criteria per IMWG at enrollment. Of these, 1622 (56.5%) were identified as RCT-eligible and 1251 (43.5%) as RCT-ineligible (data cut-off February 7, 2019). Both groups were similar in median age, sex, race, and ethnicity distribution, although the RCT-ineligible group had more pts aged ≥75 y (26.3% vs 23.2%) and more pts with ECOG PS 3/4 (6.2% vs none). Overall, 34.5% of RCT-ineligible pts received a transplant vs 42.8% of RCT-eligible pts. More RCT-ineligible pts had ISS stage III disease (39.4% vs 19.8%), elevated calcium (≥11.5 mg/dL; 12.7% vs 6.8%), elevated creatinine (>2.0 mg/dL; 40.3% vs 6.5%), and low hemoglobin (<10 g/dL or >2 g/dL <LLN; 60.8% vs 40.3%). Use of triplet treatment (54.2% vs 56.2%) and alkylator (24.9% vs 20.1%) was similar between the RCT-ineligible/-eligible groups. Lenalidomide + bortezomib + dexamethasone (RVd) was the most common initial therapy, and R was the most common maintenance therapy in both groups, but fewer RCT-ineligible pts received RVd as initial therapy (23.9% vs 31.0%) and R as first maintenance regimen (18.1% vs 22.7%). Absolute baseline HRQoL scores were significantly higher, indicating better HRQoL, in RCT-eligible (115.9) vs -ineligible (111.5) pts on the Functional Assessment of Cancer Therapy-Multiple Myeloma (FACT-MM) Total score (P=0.007), FACT-MM Trial Outcome Index (74.3 vs 70.3, P=0.002), and FACT-MM Subscale (37.3 vs 35.5, P=0.003). Scores were similar for EuroQol-5D Overall Index (0.73 vs 0.72, P=0.5) and Brief Pain Inventory (3.42 vs 3.43, P=0.9). Both RCT-eligible and -ineligible pts showed significant improvement in HRQoL from baseline at years 1 and 2, although the magnitude of improvement was similar between both groups (Fig. 1a and b). RCT-ineligible pts showed significantly shorter median PFS and OS vs RCT-eligible pts (Fig. 2 & 3, respectively). Conclusions: The CONNECT MM registry provided the opportunity to examine key differences between RCT-eligible and -ineligible pts. By applying common RCT eligibility criteria, a substantial proportion of MM pts (43.5%) in this real-world population may have been ineligible to participate in a RCT. RCT-ineligible pts had advanced disease, poor performance status, and poor laboratory parameters at baseline vs RCT-eligible pts, which could affect PFS and OS. These findings enhance our understanding of HRQoL among MM pts, which at present, is largely based on RCT participants. A similar magnitude of HRQoL improvement in both groups at 1 and 2 years suggests the need to evaluate RCT eligibility criteria in MM to help broaden enrollment and maximize external validity. Disclosures Wagner: Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; American Cancer Society: Other: Section editor, Cancer journal. Toomey:Celgene: Consultancy. Ailawadhi:Takeda: Consultancy; Amgen: Consultancy, Research Funding; Celgene: Consultancy; Cellectar: Research Funding; Janssen: Consultancy, Research Funding; Pharmacyclics: Research Funding. Jagannath:Merck & Co.: Consultancy; Bristol-Myers Squibb: Consultancy; AbbVie: Consultancy; Celgene Corporation: Consultancy; Janssen Pharmaceuticals: Consultancy; Karyopharm Therapeutics: Consultancy. Gasparetto:Janssen: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; BMS: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; Celgene: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed . Durie:Amgen, Celgene, Johnson & Johnson, and Takeda: Consultancy. Narang:Celgene: Speakers Bureau. Rifkin:Amgen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Terebelo:Celgene: Honoraria; Jannsen: Speakers Bureau; Newland Medical Asociates: Employment. Omel:Celgene, Takeda, Janssen: Other: Patient Advisory Committees. Hardin:Celgene: Membership on an entity's Board of Directors or advisory committees. Lee:Janssen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Daiichi Sankyo: Research Funding; Celgene: Consultancy, Research Funding; Sanofi: Consultancy; GlaxoSmithKline plc: Research Funding; Amgen: Consultancy, Research Funding. Srinivasan:Celgene: Employment, Equity Ownership. Liu:TechData: Consultancy. Dhalla:Celgene: Employment. Catamero:Celgene: Employment, Equity Ownership. Abonour:BMS: Consultancy; Takeda: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.

Introduction: Daratumumab, a CD38-directed monoclonal antibody, in combination with lenalidomide and dexamethasone (D-Rd), recently received FDA approval for the treatment of patients with newly diagnosed multiple myeloma (NDMM) ineligible for autologous stem cell transplantation (ASCT). FDA approval was based on results of the prespecified interim analysis of a pivotal phase III trial (MAIA) in which D-Rd was compared to Rd among patients with NDMM who were ineligible for ASCT. In the MAIA trial, D-Rd significantly reduced the risk of progression or death compared to Rd. However, no trials have compared D-Rd to other standard-of-care (SOC) regimens. The present study compared progression-free survival (PFS) of D-Rd from the MAIA trial database to common SOC regimens from the Flatiron Health EHR Database, a de-identified nationwide US database of records primarily from community-based oncology practices. Methods: Patient-level data were obtained from the MAIA trial and the Flatiron database. Patients in the MAIA trial were enrolled between March 2015 and January 2017. To be included in MAIA, patients had to be deemed ineligible for high-dose chemotherapy with ASCT due to either age (≥65 years) or presence of comorbidities, have Eastern Cooperative Oncology Group performance status (ECOG PS) ≤2, creatinine clearance ≥30mL/min, and adequate bone marrow reserve. In the Flatiron Database, patients had to be diagnosed with MM between January 2011 and April 2019, age ≥65 years at initiation of first line treatment (LOT1), could not have received stem cell transplant as part of LOT1, and met MAIA inclusion/exclusion criteria. Regimens received by fewer than 10% of patients in Flatiron were excluded due to sample size and statistical power considerations. Bortezomib-lenalidomide-dexamethasone (VRd), bortezomib-dexamethasone (Vd), and Rd were the most commonly used regimens in non-transplant NDMM patients, representing 67% of regimens used in this setting. Multiple imputation by chained equations was used to address missing data in Flatiron. Eligible Flatiron patients treated with VRd, Vd, or Rd as LOT1 were reweighted to resemble the MAIA trial population on measured baseline characteristics using propensity-score (PS) weighting. An anchored adjusted indirect treatment comparison (ITC) was performed to compare D-Rd to VRd and D-Rd to Vd, using a stratified Cox proportional hazards regression model with Rd as the common anchor across both data sources. The model calculates hazard ratios (HRs) for direct comparisons within MAIA (D-Rd vs Rd) and within Flatiron (VRd vs. Rd, Vd vs. Rd) to estimate the HRs indirectly for D-Rd vs. VRd and D-Rd vs. Vd. Results: After application of MAIA inclusion criteria and PS-reweighting, the Flatiron VRd, Rd, and Vd patients resembled the MAIA trial population on baseline patient demographics and clinical characteristics (Table 1). D-Rd statistically significantly reduced the risk of progression or death compared to Rd (HR=0.55; 95% CI, 0.41-0.72) based on the direct comparison with D-Rd using the MAIA trial data; D-Rd statistically significantly reduced the risk of progression or death compared to VRd (HR=0.66; 95% CI, 0.46-0.95) and Vd (HR=0.47; 95% CI, 0.33-0.67) based on the anchored ITC (Figure 1). Sensitivity analyses will be performed and updated analysis using longer follow-up data from the MAIA study will be presented at the meeting. Conclusion: This analysis demonstrated that D-Rd reduced the risk of progression or death compared to other SOCs VRd and Vd for patients with NDMM who are transplant-ineligible. In the absence of head-to-head trials, this type of patient-level analysis provides important information that can help optimize treatment for patients with NDMM who are transplant-ineligible. Disclosures Durie: Amgen, Celgene, Johnson & Johnson, and Takeda: Consultancy. Kumar:Takeda: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Usmani:Amgen, Celgene, Janssen, Sanofi, Takeda: Speakers Bureau; Amgen Array Biopharma, Bristol-Myers Squibb, Celgene, Janssen, Merck, Pharmacyclics, Sanofi, Takeda: Other: Research Grant; Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, SkylineDX, Takeda: Other: Consultant/Advisor. Ammann:Janssen: Employment, Equity Ownership. Lam:Janssen: Employment, Equity Ownership. Kobos:Janssen: Employment. Maiese:Janssen: Employment, Equity Ownership. Facon:Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees.

Background: Multiple myeloma (MM) is a heterogeneous disease with varying survival outcomes depending on the presence of certain genetic abnormalities. Common abnormalities include trisomies, translocations involving the chromosome 14, and amplifications or deletions of chromosomes 1, 13, and 17. t(11;14), occurring in 15% of patients with myeloma, had been considered a standard risk abnormality, but recent data suggest inferior outcome. This is important as new therapeutic options such as the BCL-2 inhibitor venetoclax has been shown to be particularly effective in t(11;14) patients. Methods: This was a multicenter study to identify the outcomes of patients with t(11;14), using a retrospectively assembled cohort. Patients with MM diagnosed between 2005 and 2015 with t(11;14) identified on FISH performed within six months of diagnosis, and with treatment details available and if alive, a minimum of 12 months of follow up, were enrolled. Results: The current analysis includes 1216 patients; median age of 62.56 years; 58.7% male. The median follow-up from diagnosis for the entire cohort was 51.9 months; 69.1% of the patients were alive at the last follow up. ISS stage distribution included: Stage I (35.7%), Stage II (34.0%) and Stage III (15.1%), data was missing for the rest. The distribution of concurrent FISH abnormalities included: trisomies (3.5%), del 13q (13.3%), 1q amp (8.8%), and del 17p or monosomy 17 (5.8%). Initial regimen included: 27.2% had an immunomodulatory (IMiD), 45.9% had a proteasome inhibitor (PI), 17.7% had both, and 9.0% had no novel agent. The drug classes by line of therapy are shown in Table 1. An early stem cell transplant (defined as within 12 months of start of first line treatment) was used in 49.4% of patients. The median time to next treatment (TTNT) after starting initial treatment was 26.6 (95% CI: 23.9 to 29.2) months. The median overall survival (OS) from diagnosis for the entire cohort was 95.1 (95% CI: 85.9 to 105.9) months; 4-year estimates for those diagnosed from January 2005 to December 2009, and from January 2010 to December 2014 were 77.5% and 78.6%, respectively. The median OS for those with any one high risk FISH lesion (del 17p/ 1q amp) was 67.5 (55.2, 97.1) versus 101.7 (89.7, 107.3) months. Patients with early SCT (within 12 months of diagnosis) had better OS: 108.3 (103.8, 133.0) vs. 69.8 (61.5, 80.3) months. Conclusion: Patients with t(11;14) without high risk FISH abnormalities have an excellent survival. Patients receiving a PI + IMiD combination and those receiving autologous SCT as part of initial therapy had best survival. Though numbers are limited, patients in the later lines receiving newer drugs such as venetoclax and daratumumab had high response rates and durable responses. Disclosures Kumar: Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Bittrich:Celgene: Other: Travel Funding, Research Funding; Else Kröner Fresenius Foundation: Research Funding; Otsuka Pharmaceuticals Europe: Other: N/A; SANOFI Aventis: Membership on an entity's Board of Directors or advisory committees, N/A, Research Funding; University Hospital Wuerzburg: Employment; Bristol Myers Squibb: Research Funding; Pfizer: Other: Travel Funding; AMGEN: Other: Travel Funding; JAZZ Pharmaceuticals: Other: Travel Funding; Wilhelm Sander Foundation: Research Funding; German Research Foundation (DFG): Other: N/A; University of Würzburg: Other: N/A. Goldschmidt:Mundipharma: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; John-Hopkins University: Research Funding; Dietmar-Hopp-Stiftung: Research Funding; Janssen: Consultancy, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Research Funding; Molecular Partners: Research Funding; John-Hopkins University: Research Funding; Amgen: Consultancy, Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Chugai: Honoraria, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding. Reece:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Otsuka: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; BMS: Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Merck: Research Funding. Mateos:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmamar: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria; EDO: Membership on an entity's Board of Directors or advisory committees. Ludwig:Celgene: Speakers Bureau; Amgen: Research Funding, Speakers Bureau; Takeda: Research Funding, Speakers Bureau; PharmaMar: Consultancy; Janssen: Speakers Bureau; BMS: Speakers Bureau. Mangiacavalli:celgene: Consultancy; Amgen: Consultancy; Janssen cilag: Consultancy. Dimopoulos:Sanofi Oncology: Research Funding. Kastritis:Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Honoraria; Prothena: Honoraria; Genesis: Honoraria. Yee:Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding; Karyopharm: Consultancy; Adaptive: Consultancy. Raje:Amgen Inc.: Consultancy; Bristol-Myers Squibb: Consultancy; Celgene Corporation: Consultancy; Takeda: Consultancy; Janssen: Consultancy; Merck: Consultancy. Rosta:Cornerstone Research Group: Employment. Haltner:Cornerstone Research Group: Employment. Cameron:Cornerstone Research Group: Employment, Equity Ownership. Durie:Amgen, Celgene, Johnson & Johnson, and Takeda: Consultancy.