Citations

Background: Despite treatment advances, multiple myeloma (MM) remains a condition with high unmet medical need as patients (pts) relapse and become resistant to therapy. MM pts experience a range of serious disease-related symptoms and side effects impacting their functioning and health-related quality of life (HRQL). The median overall survival (OS) has improved with the advent of new treatments in the last two decades, however, the impact of newer combination treatments on pt quality of life remains unknown (Beckner, N et al. Cancer Res. 2011;183:25; Bharat, N et al. J Clin Oncol 2019;37:15(suppl):8039). Venetoclax is a novel, orally bioavailable small molecule inhibitor of BCL-2 activity in MM. In the Phase 3 double-blind, randomized clinical trial (M14-031, BELLINI) progression free survival (PFS) was studied in relapsed/refractory (RR) MM pts receiving venetoclax or placebo in combination with bortezomib and dexamethasone. In addition, patient-reported outcomes (PRO) data focused on physical functioning, pain, and fatigue from BELLINI were evaluated to better understand the overall impact on pt HRQL of adding venetoclax to bortezomib and dexamethasone-based doublet therapy. Methods: The BELLINI Phase 3 study (NCT01794520) enrolled patients ≥18 y old with R/R MM who had received 1-3 prior lines of therapy. The study met its primary endpoint of PFS (HR 0.63, 95% CI=0.44-0.89) but higher risk of death (HR 2.027, 95% CI=1.04-3.95) was observed in the treatment arm compared with placebo, although the OS data are not yet mature (Kumar, S et al. EHA Library. Jun 16 2019;273254:LB2601). The secondary HRQL endpoints included in this study were pain severity, fatigue, physical functioning (PF), and global health status, which were measured using the Brief Pain Inventory-Short Form (BPI-SF), PROMIS Fatigue Short Form surveys, and the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30). Change from baseline to day 1 of each cycle visit (up to 25 cycles or last treatment visit) was assessed for each measure in both the treatment and placebo groups. Summary analyses compared mean and median scores between arms at each cycle. The treatment effect was evaluated in a mixed effect model controlling for the patient's baseline score, total visits (or cycles of treatment), age (<65 or ≥65), prior therapy lines, and prior proteasome inhibitor exposure. The model also included an interaction term examining treatment by visits. Results: The intention-to-treat (ITT) dataset included 194 pts (median age: 66y; 53% with 2 or 3 prior lines of therapy) in the treatment group and 97 pts (median age: 65y; 55% with 2 or 3 prior lines of therapy) in the placebo group (2:1 randomization). There was no clear evidence for an independent effect of treatment on PF (P=0.522). Pain scores across multiple measures showed a similar trend, with a statistically non-significant improvement of unadjusted average "Worst Pain" scores for the venetoclax group (P=0.289; Figure B). Non-inferiority in pain results were replicated by the pain subscale of the QLQ-30 (P=0.778), the BPI pain severity index (P=0.418), and the related BPI pain interference subscale score (P=0.603). Fatigue scores likewise demonstrated no significant differences between treatment arms whether using PROMIS Cancer Fatigue t-scores (P=0.442), raw scores (P=0.568), or the 3-item QLQ-C30 subscale (P=0.959), although there was a positive trend across cycle summary scores for the treatment group compared with the placebo group. Unadjusted QLQ-C30 PF subscale scores showed declines from baseline that were generally worse in the placebo group across 25 treatment cycles, although differences were smaller and non-significant in the adjusted model (Figure A). Conclusions: Comparable HRQL in pain severity, fatigue, and PF was observed in RRMM pts receiving venetoclax in combination with bortezomib and dexamethasone compared to pts receiving bortezomib and dexamethasone. The summary scores showed outcomes that were comparable or slightly improved for those randomized to the venetoclax combination. Results of concurrent measures of the same or associated concepts reinforced confidence in these results. Additional analyses of subgroups are ongoing (eg, t(11;14), BCL-2 expression status) and may provide further insights surrounding HRQL in these populations. Figure Disclosures Gasparetto: BMS: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; Celgene: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; Janssen: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed . Popat:Takeda: Honoraria, Other: travel, accommodations, expenses; GSK: Consultancy, Honoraria; Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel, accommodations, expenses; Janssen: Honoraria, Other: travel support to meetings; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Kumar:Celgene: Consultancy, Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Cavo:celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; AbbVie: Consultancy, 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, Speakers Bureau; amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; novartis: Honoraria; sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; bms: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. de la Rubia:Janssen: Consultancy; AbbVie: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Takeda: Consultancy. Hungria:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Consultancy, 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, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Salwender:Sanofi: Honoraria, Other: Travel or accommodations; Amgen: Honoraria, Other: Travel or accommodations; Janssen Cilag: Honoraria, Other: Travel or accommodations; AbbVie: Honoraria; Bristol-Myers Squibb: Honoraria, Other: Travel or accommodations; Celgene: Honoraria, Other: Travel or accommodations; Takeda: Honoraria, Other: Travel or accommodations. Suzuki:Ono: Research Funding; BMS: Honoraria, Research Funding; Takeda: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Maciel:Amgen: Other: funding for travel, teaching, participation in advisory boards; Janssen: Other: funding for travel, teaching, participation in advisory boards. Moreau:Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Harrison:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Consultancy, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: investigator on studies, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Jia:AbbVie: Employment, Other: Stock/stock options. Karve:AbbVie: Employment, Other: stock/stock options. Ma:Genentech: Employment, Other: stock options; AbbVie: Other: Alliance Partner. Devine:Genentech: Employment, Other: stock options; AbbVie: Other: Alliance Partner. Benjamin:AbbVie: Employment, Other: stock/stock options.

Background: Two-year follow-up from ZUMA-1 trial for axicabtagene ciloleucel (axi-cel) CD19 chimeric antigen receptor T-cell (CART) in aggressive non-Hodgkin lymphoma (NHL) demonstrated that patients (pts) achieving complete remission (CR) as their best response have the longest progression free survival (PFS), while PFS remained poor for others. Majority of the best response are achieved by month 3 post-infusion. Moreover, a subset of pts who do not achieve CR by month 1 may still achieve CR while others will progress within months. Having a clinically available test to predict for durable response can assist clinicians in selecting pts who can be observed for continued response vs. those who may need intervention earlier. Peak CAR-T expansion has been correlated with best clinical response to axi-cel. However there is no clinically available test to quantify CART cells post treatment. Given the prolonged lymphotoxic effect of the lymphodepletion (LD) chemotherapy administered before CART infusion, we hypothesize that the peak expansion of absolute lymphocyte count (ALC, ALCpeak) after infusion likely corresponds to CART expansion. We examined for correlation between ALCpeak and clinical response at month 3 post-infusion for pts who received axi-cel. Methods: Data was collected from pts who received axi-cel between June 2016 and March 2019 at Mayo Clinic Rochester (NCT02348216, NCT03153462, and standard of care). All infused pts were included in the intention to treat analysis for response and event-free survival (EFS). Lugano 2014 criteria were used for clinical response. EFS was defined as the date of infusion until progression or death due to any cause and evaluated using Kaplan Meier curves with log-rank test. Comparison between subgroups was investigated using Fisher's exact test and Wilcoxon test for categorical and continuous variables, respectively. Statistical analysis performed using JMP Pro 14.1. Results: Of the thirty-six NHL pts treated with axi-cel, the median age was 56 yrs (range 26-65); 78% (28) were male; 44% (16) had DLBCL; the median number of prior therapies was 3 (2-6), 47% (17) had stem cell transplant. Nineteen (53%) pts received bridging therapy after leukapheresis. All pts received fludarabine and cyclophosphamide for LD chemotherapy and achieved ALC nadir by the day of CART infusion (median 0.03 x 10^9/L, range 0.01-0.11). As CART expansion were found to peak within the first two weeks in ZUMA-1 trial, we examined ALC trend over 15 days post infusion and found that ALCpeak generally happened within the same timeframe (median ALCpeak day: 9, range 6-15). At 3 months post infusion, 33.3% (12/36) of pts achieved CR, 8.3% (3/36) pts were in partial remission (PR). No correlation was found between CR response and clinical characteristics: age >60 years, stage III/IV, B symptoms, elevated LDH, IPI score 3-4, number of previous treatments, use of bridging therapy, peak CRP and ferritin. However, the ALCpeak was significantly different between CR and non-CR pts (median, range: 1.09, 0.35-2.55; 0.67, 0.15-1.03; p=0.04). Using receiver operator curve (ROC)-derived area under the curve (AUC) estimates, ALCpeak 1.08 x 10^9/L was identified as the best threshold to discriminate patients at different likelihood to achieve CR at month 3. Pts achieving ALCpeak ≥ 1.08 showed a strong increased likelihood of achieving CR at month 3 (OR 2.8; 95% CI, 1.12-6.99; P=0.02). There was no statistical difference between the ALCpeak high and low groups in terms of use of bridging therapy, occurrence of any grade or higher grade cytokine release syndrome or neurotoxicity, or the use of tocilizumab or steroid. Interestingly, for pts who had changes in clinical response from month 1 to month 3, all 3 pts who converted to CR by month 3 had ALCpeak≥1.08, while the 13 of the 15 pts who had progressed by month 3 had ALCpeak<1.08. In addition, EFS was significantly different between pts who had ALCpeak above and below 1.08 (6 months EFS rate 75% vs. 25%, respectively, Figure 1). Conclusions: We found that the ALC expansion occurred in the first 15 days post axi-cel infusion, consistent with the known time frame for CART expansion. Higher ALCpeak level in this timeframe correlated with higher likelihood of achieving CR, and is associated with conversion to CR. This study is limited by the small sample size and limited follow-up, but the results are promising for further prospective investigation in a larger cohort of patients. Disclosures Paludo: Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding; Celgene: Research Funding; Celgene: Research Funding. Ansell:Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding. Bennani:Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Adicet Bio: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Kite Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Seattle Genetics: Other: Advisory board; Adicet Bio: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Other: Advisory board; Purdue Pharma: Other: Advisory board. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Karyopharm: Research Funding; Rigel: Consultancy. Kapoor:Celgene: Honoraria; Janssen: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding. Kenderian:Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding. Kumar:Takeda: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.

INTRODUCTION: Primary plasma cell leukemia (pPCL) is the most aggressive form of multiple myeloma (MM). Recently, pPCL has been defined by as few as >5% circulating plasma cells (cPCs) detected morphologically on a peripheral blood smear. However, this technique may not be sufficiently sensitive and is dependent on inter-observer bias to properly identify and quantify cPCs. Multiparametric flow cytometry (MFC) provides a readily available and highly sensitive method to identify and quantify cPCs. However, an optimal quantitative cutoff for cPCs by MFC to define the presence of pPCL has not been established to date. Thus, this is the first study to date that determines an optimal cutoff of cPCs/ microliter that could identity patients with pPCL at diagnosis. METHODS: We retrospectively evaluated all newly diagnosed MM patients seen at the Mayo Clinic, Rochester from January 2007 to December 2017 who had their peripheral blood samples evaluated morphologically by peripheral blood smear and immunophenotypically by MFC prior to beginning therapy. Patients with a peripheral blood smear detecting >5% cPCs were classified as having pPCL. Six-color MFC was performed on peripheral blood mononuclear cells by isolated by Ficoll gradient, and stained with antibodies to CD45, CD19, CD38, CD138 and cytoplasmic Kappa and Lambda immunoglobulin light chains. The data was collected using Becton Dickinson FacsCanto II instruments collecting 150,000 events and analyzed using the BDFacs DIVA Software. The gating strategy employed first used the expression of CD38, CD138, and cytoplasmic immunoglobulin light chains to identify all plasma cells in the specimen. The cPCs were then discriminated from polyclonal/normal plasma cells based on differential CD19 and CD45 expression. The cPCs detected were reported as the number of clonal events/150,000 collected total events and converted to the absolute number of cPCs/microliter using their absolute lymphocyte count and monocyte count determined at the time of the blood draw for cPC MFC assessment. A receiver operator curve (ROC) was performed to determine the absolute cPCs/microliter by MFC that best identified those patients with >5% cPC on their peripheral blood smear. Survival analysis was performed by the Kaplan-Meier method and differences assessed using the log rank test. RESULTS: A total of 591 patients were included in this analysis of which 59% were male and the median age was 66 years (range: 27 - 95) with 22% being 75 years of age or older. From this cohort, 133 (24%) patients had high risk FISH cytogenetics, 172 (30%) were classified as ISS 3 at diagnosis, 83 (15%) had an elevated LDH level and 61 (17%) had a plasma cell labeling index (PCLI) of 2% or greater. There were 65 (11%) patients with any amount of cPCs detectable by peripheral blood smear of which only 22 (4% of the total population) met criteria for pPCL with >5% cPCs. With MFC, 403 (68%) patients had detectable cPCs. The median number of cPCs per microliter was 0.81 (0 - 10,455) with 273 (46%) having >1 cPC/microliter. A ROC analysis determined that the presence of >50 cPCs/microliter by MFC was the optimal cutoff to identify patients with >5% cPCs by blood smear with approximately a specificity of 94% and a sensitivity of 86%. The presence of >50 cPCs/microliter by MFC was associated with higher presence of high risk FISH cytogenetics, ISS 3 classification, elevated LDH and PCLI > 2%. The median time to next treatment (TTNT) for patients with and without >5% cPCs by peripheral blood smear was 18 months vs. 30 months (P < 0.001). The median TTNT for patients with and without >50 cPCs/microliter by MFC was 19 months vs. 30 months (P < 0.01). The median overall survival (OS) for patients with and without >5% cPCs by peripheral blood smear was 25 months vs. 71 months (P < 0.001; Fig 1A). The median OS for patients with and without >50 cPCs/microliter by MFC was 38 months vs. 71 months (P < 0.01; Fig 1B). CONCLUSION: This is the largest study that attempts to identify an optimal cutoff of cPCs/microliter by MFC for diagnosing pPCL patients. The presence of >50 cPCs/microliter is an optimal cutoff by MFC that best predicts for the presence of >5% cPCs by peripheral blood smear. However, there remains discordance in the OS outcomes between the two cutoffs by different methodologies for pPCL. This could signify the presence of biological processes associated with the presence of >5% cPCs when detected by peripheral blood smear that are not captured by MFC. Disclosures Dispenzieri: Pfizer: Research Funding; Janssen: Consultancy; Intellia: Consultancy; Akcea: Consultancy; Alnylam: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Dingli:Karyopharm: Research Funding; Rigel: Consultancy; Millenium: Consultancy; Janssen: Consultancy; alexion: Consultancy. Lacy:Celgene: Research Funding. Kapoor:Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding; Sanofi: Consultancy, Research Funding; Cellectar: Consultancy; Janssen: Research Funding; Celgene: Honoraria. Leung:Aduro: Membership on an entity's Board of Directors or advisory committees; Omeros: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding. Russell:Imanis: Equity Ownership. Gertz:DAVA oncology: Speakers Bureau; Ionis/Akcea: Consultancy; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Research to Practice: Consultancy; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Other: Development of educational programs and materials; Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Introduction : Daratumumab (DARA) is a human CD38 antibody approved in combination with standard-of-care (SoC) regimens in pts with NDMM who are TIE. DARA-based treatments showed significantly improved progression-free survival (PFS) in pts with TIE NDMM in ongoing phase 3 studies ALCYONE (DARA + bortezomib/melphalan/prednisone [D-VMP] vs VMP) and MAIA (DARA + lenalidomide/dexamethasone [D-Rd] vs Rd continuous). An NMA allows estimation of the relative efficacy of regimens not compared in head-to-head trials. A previous NMA examined D-VMP and D-Rd vs comparators (Facon T et al., EHA 2019), excluding the SWOG S0777 study (bortezomib/lenalidomide/dexamethasone [VRd]; Durie BG, et al. Lancet 2017) as it enrolled both transplant-eligible (TE) and TIE pts, and data for pts who are TIE only (~50% [aged ≥65 y and frail]) were unavailable. In this NMA, D-Rd and D-VMP had the highest probabilities of being more effective than reference treatment Rd continuous in terms of PFS. Recently, VRd received EMA approval for treatment of TIE NDMM based on SWOG S0777, but results specific to TIE pts are still unavailable. Recent NMAs of TIE pts (Blommestein HM et al., Haematologica, 2019; Weisel et al., EHA 2019; Cao Y et al., Clin Lymphoma Myeloma Leuk, 2019) have included data from the the intent-to-treat (ITT) population of SWOG S0777, though its inclusion violates the similarity assumption. Here, we present a sensitivity analysis of the previously-conducted NMA including all pts who received VRd in SWOG S0777 for a comprehensive view of the comparative effectiveness of DARA-based treatments in TIE NDMM. Methods: VRd was included as part of a sensitivity analysis of the previous NMA based on the ITT population, reporting PFS and overall survival (OS). The Guyot method was used to estimate OS hazard ratios (HRs) for pts aged ≥65 y (proxy for TIE) from SWOG S0777 (Durie BG et al., ASH 2018). Median follow-up in ALCYONE and MAIA was 27.8 months and 28.0 months, respectively. Based on a systematic literature review conducted through January 2019, both PFS and OS were extracted and synthesized in Bayesian NMAs. Choice of fixed- or random-effects (FE or RE) model was based on lowest deviance information criterion (DIC) and/or presence of heterogeneity in the network. Rd continuous was selected as reference, as it was commonly included in guidelines across regions. For PFS and OS, HR <1 indicates the comparison is not in favor of Rd continuous. In addition to the previous NMA, we also report an NMA sensitivity analysis including only comparators approved by the EMA that are relevant for the European, Middle East and/or Africa (EMEA) region (EMEA NMA). Results: Global NMA: RE model was used for both PFS and OS. Compared with Rd continuous, the PFS HR for VRd in the sensitivity analysis was 0.74 (95% credible interval [CrI], 0.42-1.30), which was similar to SWOG S0777 (0.71; [96% Wald confidence interval [CI], 0.56-0.91]) and higher than HRs for D-Rd (0.55; 95% CrI, 0.31-0.97) and D-VMP (0.58; 95% CrI, 0.20-1.62; Table). For OS, the SWOG S0777 HR estimated by Guyot algorithm for pts aged ≥65 y was 0.80 (95% CI, 0.56-1.16). Compared with Rd continuous, the OS HR for VRd in the sensitivity analysis was 0.80 (95% CrI, 0.51-1.26), which was similar to SWOG S0777 and higher than D-Rd (0.78; 95% CrI, 0.51-1.18). EMEA NMA: FE model was used for both PFS and OS. Compared with Rd continuous, the PFS HR for VRd in the sensitivity analysis was 0.74 (95% CrI, 0.60-0.92), which was higher than HRs of D-Rd (0.55; 95% CrI, 0.43-0.71) and D-VMP (0.64; 95% CrI, 0.41-1.02). Compared with Rd continuous, the OS HR for VRd in the sensitivity analysis was 0.80 (95% CrI, 0.55-1.17), which was higher than for D-Rd (0.78; 95% CrI, 0.56-1.09). These results are consistent with the Global NMA, but differ slightly as the EMEA NMA has fewer evidence-loops (only EMEA SoC regimens were included). Conclusions: This study demonstrated favorable efficacy outcomes for DARA-based regimens vs other relevant frontline options, such as VRd, for pts with NDMM who are TIE. Limitations of the sensitivity analysis include lack of comparative trial data and demographic differences between pts from SWOG S0777 and trials of frontline MM treatments for pts who are TIE included in our network. The majority of SWOG S0777 pts are TE (<65 y), who often have better prognoses than TIE pts (≥65 y), and thus violates the similarity assumption of NMAs. However, DARA-based regimens still showed a comparative clinical advantage. Disclosures Facon: Takeda: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; 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; Sanofi: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. San-Miguel:Amgen, Bristol-Myers Squibb, Celgene, Janssen, MSD, Novartis, Roche, Sanofi, and Takeda: Consultancy, Honoraria. Usmani: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; Amgen, Celgene, Janssen, Sanofi, Takeda: Speakers Bureau. Dimopoulos:Sanofi Oncology: Research Funding. Kumar:Janssen: Consultancy, Research Funding; Takeda: Research Funding; Celgene: Consultancy, Research Funding. Mateos:Adaptive: Honoraria; EDO: Membership on an entity's Board of Directors or advisory committees; Pharmamar: Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, 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; GSK: Membership on an entity's Board of Directors or advisory committees; 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. Cavo:Janssen, Celgene, Amgen, Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene, Janssen, Amgen, BMS, Abbvie, Takeda: Honoraria; Janssen, Celgene: Other: Travel Accommodations; Janssen, Celgene: Speakers Bureau. Heeg:Ingress-Health: Employment. Van Beekhuizen:Ingress-health: Consultancy. Pisini:Janssen: Employment, Equity Ownership. Nair:Janssen: Employment, Equity Ownership. Lam:Janssen: Employment, Equity Ownership. Slavcev:Janssen: Employment, Equity Ownership. He:Janssen: Employment, Equity Ownership.

Background: Based on results from the phase 3 trials, maintenance therapy after autologous stem cell transplantation has become the standard of care. While lenalidomide is typically used as the maintenance agent, patients with high risk MM are often maintained on proteasome inhibitor-based maintenance treatment. We examined the trends in maintenance use and outcomes in a large group of patients transplanted at a single institution over two decades spanning the years when maintenance gradually became standard of care. Methods: We included patients who underwent their first autologous stem cell transplantation between 2000 and 2016 in the current study. Patients who received an allogeneic SCT or a planned tandem SCT were excluded. Clinical data was extracted from the medical records or from a prospectively maintained database. Early transplant was defined as SCT within 12 months of diagnosis. High risk (HR) myeloma was defined as per IMWG criteria, based on presence of high-risk FISH abnormalities. Progression free survival and overall survival were estimated from either diagnosis as well as from the date of SCT. Results: We included 1961 patients with MM who were transplanted between January 2000 and August 2016 in the current analysis. Majority (n=1496; 76%) had an early SCT while the remaining patients were transplanted beyond 12 mos from diagnosis. Maintenance was employed in 31% of the patients, 33% of the early SCT and 23% of the delayed SCT. Proportion of patients receiving maintenance increased over the years: <1% in 2000 to 85% in 2016. The most common maintenance approach was an IMiD (56%), followed by a PI (33%) and a PI+IMiD (8%). FISH risk was available in 875 patients, all assessed within 6 months of diagnosis, and 22% were HR. Overall, maintenance was more commonly used in HR patients (64% vs. 36%), and a PI containing maintenance was more commonly used in HR (42% vs. 12%). The PFS was superior for those receiving a maintenance therapy (70 vs. 23 mos, P<0.001); NR vs. 27 mos for early SCT and 25 vs. 16 mos for delayed SCT. The impact of maintenance therapy was more evident in the HR group HR vs SR risk ratio was 2.3 without maintenance, and 1.5 with maintenance. Among the HR patients, PI based maintenance had a trend towards better outcome, while the PFS was better with non-PI maintenance among the SR patients. OS from diagnosis was also better among the early SCT group who received maintenance (99 vs. 88 mos; p=0.01); however, the OS advantage appeared most evident among the HR patients. Conclusions: The experience with maintenance therapy post autologous SCT for myeloma in a non-clinical trial setting appear to confirm the findings from the phase 3 trials. Maintenance provided benefit in patients who had a delayed SCT in our experience. The benefit appear to be particularly relevant for high risk patients, who appear to benefit from PI based regimens. In contrast, SR patients appear to benefit primarily from IMiD based regimen. Disclosures Gertz: Spectrum: Consultancy, Research Funding; Johnson and Johnson: Speakers Bureau; Amgen: Consultancy; Ionis/Akcea: Consultancy; Research to Practice: Consultancy; Appellis: Consultancy; Celgene: Consultancy; Teva: Speakers Bureau; Alnylam: Consultancy; Janssen: Consultancy; Annexon: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Medscape: Consultancy, Speakers Bureau; Prothena Biosciences Inc: Consultancy; Physicians Education Resource: Consultancy. Lacy:Celgene: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Dingli:Millenium: Consultancy; Rigel: Consultancy; Janssen: Consultancy; alexion: Consultancy; Karyopharm: Research Funding. Kapoor:Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding; Celgene: Honoraria; Janssen: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy, Research Funding. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Background: The treatment of Multiple Myeloma (MM) has evolved significantly in the past decade with the introduction of novel agents and drug combinations, thus enhancing treatment efficacy and allowing more patients to achieve complete response (CR). This has created a need to identify surrogates for depth of treatment response. Serum free light chain (sFLC) ratio normalization has been shown to be prognostic for progression free survival as well as overall survival in patients achieving a complete response to therapy. Consequently, it has been incorporated as a defining feature for stringent CR, along with lack of clonal plasma cells by immunohistochemistry (IHC) or low sensitivity flow cytometry. The routine use of multiparametric flow cytometry with higher sensitivity to detect residual disease than IHC or the older 4-color flow cytometry, has raised the question as to whether sFLC ratio is still a valid indicator of response depth. Moreover, in nearly half of the patients with an abnormal sFLC ratio after treatment, the abnormality is secondary to suppression of one or both serum light chains. Therefore, we designed a retrospective study to address these issues. Patients and Methods: This is a retrospective study using the Multiple Myeloma Database at Mayo Clinic, Rochester. We included patients who, after any line of therapy, had negative serum and urine immunofixation and absence of clonal bone marrow plasma cells by flow cytometry (PC-PRO), which has a sensitivity of >10-4. Simultaneous sFLC data was also extracted. Patients were grouped into three categories based on their sFLC ratios: 1) normal ratio (normal), 2) abnormal ratio due to suppression of the uninvolved light chain (LC), involved LC, or both (Abn-suppressed) and 3) abnormal ratio due to elevation of the involved LC (Abn-inv elevated). The primary endpoint was the median time to next treatment (TTNT), defined as the time from sample collection to the time of initiation of the subsequent therapy or time of last follow up if a subsequent line of treatment was not initiated. Results: The cohort consisted of 510 patients. 285 (56%) were males and 225 (44%) females. Median age was 61 years (IQR: 55-67). Median Follow-up was 41 months. The last treatments administered prior to data collection included stem cell transplant (SCT) (with or without maintenance) in 290 (57%) patients, and non-SCT regimens in the others. The sFLC ratio was normal in 337 (66%) and abnormal in 173 (34%) patients. Among the patients with abnormal sFLC ratios, 81 had elevated involved LC, 25 had suppression of the involved LC, 45 had suppression of the uninvolved LC and 22 had suppression of both LCs. We first examined the TTNT for the three groups and found that the TTNT was identical for those with a normal ratio and those with an abnormal ratio due to suppression of one or both light chains (Figure 1). So, we combined these two groups (Normal-Abn suppressed) and compared their outcomes to the patients with abnormal sFLC ratio due to elevated involved LC. The Abn-inv elevated group had a shorter TTNT as shown in Figure 2 (log-rank 0.06, Wilcoxon <0.01). The Abn-inv elevated group also had decreased overall survival compared to the other group (log-rank: 0.05, Wilcoxon: 0.01) (Figure 3). Conclusion: This study provides 2 important observations. First, patients with an abnormal ratio due to suppression of one or both LCs have outcomes similar to those with a normal ratio, suggesting a need to clarify the current definition of stringent CR. Second, the study suggests an important prognostic value for an abnormal sFLC ratio due to elevated involved LC, suggesting this as an important surrogate for depth of response. Disclosures Kapoor: Janssen: Research Funding; Takeda: Honoraria, Research Funding; Cellectar: Consultancy; Celgene: Honoraria; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Glaxo Smith Kline: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Gertz:Ionis: Honoraria; Alnylam: Honoraria; Prothena: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Spectrum: Honoraria, Research Funding. Lacy:Celgene: Research Funding. Dingli:Karyopharm: Research Funding; Rigel: Consultancy; Millenium: Consultancy; Janssen: Consultancy; alexion: Consultancy. Leung:Takeda: Research Funding; Aduro: Membership on an entity's Board of Directors or advisory committees; Prothena: Membership on an entity's Board of Directors or advisory committees; Omeros: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Introduction: High-risk multiple myeloma can be defined by the presence of specific cytogenetic abnormalities (structural) or by characteristic changes in bone marrow and peripheral blood biomarkers (functional). While both entities are characterized by therapeutic resistance, frequent disease relapses, and adverse survival outcomes, the underlying molecular mechanisms remain incompletely understood. Methods: We performed gene expression profiling (GEP) using an Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray on CD138+ bone marrow cells from 137 patients diagnosed with multiple myeloma between 2004 and 2012. All patients underwent Fluorescence In-situ Hybridization (FISH) evaluation, plasma cell labeling, International Staging System (ISS) risk stratification, and GEP prior to initiating treatment with novel agents. The presence of del(17p), t(4;14), t(14;16), and t(14;20) on FISH, a plasma cell labeling index (PCLI) > 2%, and ISS stage III were considered high-risk abnormalities: FISH-HR (n = 15, structural high-risk, at least one high-risk FISH lesion), PCLI-HR (n = 20; functional high-risk, PCLI > 2%), and ISS-HR (n = 12; functional high-risk, ISS stage III). For each HR group we sampled standard risk (SR) controls in a 4:1 ratio. After data quality control and normalization, differential gene expression was estimated using limma. Statistical significance was adjusted for multiple comparisons using a false discovery rate-based approach for genome-wide experiments (q-value). We employed PANTHER pathway analysis for the differentially expressed genes in each HR group. We implemented a simple gene expression score (GES) by calculating the sum of quartiles of the normalized gene expression values for genes differentially expressed in more than one HR group (GES = ΣUP(quartile - 1) + ΣDN(4 - quartile)) and externally validated its prognostic significance (UAMS TT2 / TT3, GSE24080). Survival outcomes were analyzed using the methods described by Kaplan, Meier, and Cox. Computation and visualization were performed in R. Results: Median age at diagnosis was 63 years (32 - 87), 53% of the patients were male. High-risk disease was associated with inferior overall survival, regardless of the used definition (left Kaplan-Meier plots): FISH-HR (HR 4.3, 95% CI 1.9 - 9.8, p < 0.001), PCLI-HR (HR 2.7, 95% CI 1.4 - 5.3, p = 0.004), and ISS-HR (HR 2.8, 95% CI 1.2 - 6.5, p = 0.015). There were 59 (FISH-HR), 424 (ISS-HR), and 507 (PCLI-HR) differentially expressed genes (q < 0.050 for all genes, volcano plots). PCLI-HR and FISH-HR demonstrated a predominance of transcriptional up-regulation while ISS-HR had a balanced gene expression profile with a similar number of genes being up- and down-regulated. The involved cellular pathways were different across the HR groups except for anti-apoptotic signaling (bar graphs). All HR groups had distinct gene expression profiles with no complete overlap between all HR groups. There were 71 genes with overlap between two HR groups (69 up-regulated, 2 down-regulated, Venn diagrams). The median GES was 97 (18 - 206, higher numbers indicating higher expression of up-regulated and lower numbers of down-regulated high-risk genes) in 559 patients treated on UAMS TT2 / TT3 (GSE24080). Tertiles of the GES were associated with event-free survival (HR 1.4, 95% CI 1.2 - 1.6, p < 0.001) and remained independently prognostic after adjusting for age, sex, and ISS stage (HR 1.3, 95% CI 1.1 - 1.5, p < 0.001). Conclusions: High-risk multiple myeloma remains associated with inferior overall survival, regardless of the used definition (structural or functional). The subtypes of high-risk disease have distinct gene expression profiles and involve different cellular pathways, providing important clues to the underlying biology. A 71 gene signature derived from the different high-risk subtypes was of prognostic significance in a clinical trial population after adjusting for known prognostic factors. Figure Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Stewart:Takeda: Consultancy; Seattle Genetics: Consultancy; Roche: Consultancy; Ono: Consultancy; Celgene: Consultancy, Research Funding; Ionis: Consultancy; Janssen: Consultancy, Research Funding; Oncopeptides: Consultancy; Amgen: Consultancy, Research Funding; Bristol Myers-Squibb: Consultancy. Bergsagel:Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Introduction: Daratumumab (DARA) is a human, CD38-targeted, IgG1κ monoclonal antibody approved as monotherapy in heavily pretreated relapsed/refractory multiple myeloma (RRMM) and in combination with standard-of-care regimens for transplant-ineligible NDMM and RRMM. The addition of DARA to standard-of-care regimens in phase 3 studies has consistently demonstrated a near doubling of complete response (CR) rates, tripling of minimal residual disease (MRD)-negativity rates, and reduction in the risk of disease progression or death by ≥44% in patients with transplant-ineligible NDMM or RRMM. In the primary analysis of the phase 3 MAIA study (median follow-up: 28.0 months), a significant progression-free survival (PFS) benefit (median not reached [NR] vs 31.9 months; hazard ratio [HR], 0.56; P<0.001) and a >3-fold increase in MRD-negativity rates (10-5 sensitivity threshold; 24.2% vs 7.3%; P<0.001) were observed for D-Rd vs Rd in patients with transplant-ineligible NDMM (Facon T, N Engl J Med 2019). Here, we report updated efficacy and safety findings from MAIA after 9 months of additional follow-up. Methods: Patients with NDMM ineligible for high-dose chemotherapy and autologous stem cell transplantation due to age ≥65 years or comorbidities were randomly assigned (1:1) to receive Rd ± DARA. Stratification factors included International Staging System stage (ISS [I vs II vs III]), region (North America vs other), and age (<75 vs ≥75 years). All patients received 28-day cycles of Rd (R: 25 mg orally once daily on Days 1-21; d: 40 mg orally on Days 1, 8, 15 and 22). In the D-Rd arm, DARA (16 mg/kg intravenously) was given weekly for Cycles 1-2, bi-weekly for Cycles 3-6, and every 4 weeks thereafter. Patients were treated until disease progression or unacceptable toxicity in both treatment arms. The primary endpoint was PFS. Key secondary endpoints included overall response rate (ORR), MRD-negativity rate (10-5 sensitivity, clonoSEQ® version 2.0), and safety. PFS on the next line of therapy (PFS2), defined as the time from randomization to progression on the next line of therapy or death, was also measured. Results: A total of 737 patients were randomized (D-Rd, N = 368; Rd, N = 369). Patient baseline characteristics were well balanced between the two treatment arms. Median (range) age was 73 (45-90) years, with 44% of patients ≥75 years of age. 27%, 43%, and 29% of all patients were ISS stage I, II, and III, respectively. Among 642 patients evaluable for FISH/karyotyping analysis, 86% had standard and 14% had high cytogenetic risk. After a median follow-up of 36.4 months, median PFS was NR with D-Rd vs 33.8 months with Rd (HR, 0.56; 95% confidence interval [CI], 0.44-0.71; P<0.0001; Figure). The estimated 36-month PFS rate was 68% with D-Rd vs 46% with Rd. The PFS benefit of D-Rd vs Rd was observed in all prespecified subgroups, except for patients with impaired hepatic function. Adding DARA to Rd continued to result in deeper responses with higher rates of ≥CR and ≥very good partial response (VGPR; Table). Median duration of response among responders was NR with D-Rd vs 40.7 months with Rd. Median PFS2 was NR vs 47.3 months with D-Rd vs Rd, respectively (HR, 0.69; 95% CI, 0.53-0.91; P=0.0079); follow up is ongoing. 143 (39%) vs 233 (64%) patients with D-Rd vs Rd, respectively, have discontinued treatment. 85 (23%) patients with D-Rd vs 103 (28%) patients with Rd have discontinued the study due to death. Grade 3/4 treatment-emergent adverse events (TEAEs; D-Rd/Rd) occurring in ≥10% of patients were neutropenia (51%/35%), lymphopenia (15%/11%), pneumonia (15%/9%), anemia (14%/21%), leukopenia (11%/6%), and hypokalemia (10%/10%); grade 3/4 infection rates were 36%/27%. The most common serious TEAE was pneumonia (14%/9%). 9% of patients in the D-Rd arm and 18% of patients in the Rd arm discontinued treatment due to TEAEs. The complete updated data set will be presented at the meeting with additional efficacy endpoints, including MRD-negativity rate. Conclusion: After longer follow up, the addition of DARA to Rd continues to demonstrate a significant PFS benefit and improved rates of deeper and more durable responses vs Rd alone in patients with transplant-ineligible NDMM. The longer follow-up also demonstrated a significant improvement in PFS2 favoring D-Rd, and no new safety concerns were observed. These results continue to support the use of D-Rd in the first line of treatment for transplant-ineligible patients with NDMM. Disclosures Bahlis: Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Facon:Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: 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; Sanofi: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Usmani:Amgen Array Biopharma, Bristol-Myers Squibb, Celgene, Janssen, Merck, Pharmacyclics, Sanofi, Takeda: Other: Research Grant; Amgen, Celgene, Janssen, Sanofi, Takeda: Speakers Bureau; Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, SkylineDX, Takeda: Other: Consultant/Advisor. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Plesner:Oncopeptides: Consultancy; Janssen: Consultancy, Research Funding; Takeda: Consultancy; AbbVie: Consultancy; Celgene: Consultancy; Genmab: Consultancy. Orlowski:Poseida Therapeutics, Inc.: Research Funding. Hulin:celgene: Consultancy, Honoraria; Janssen, AbbVie, Celgene, Amgen: Honoraria. Quach:Sanofi: Research Funding; Karyopharm: 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; GSK: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Goldschmidt:ArtTempi: Honoraria; John Hopkins University: Other: Grants and/or provision of Investigational Medicinal Product; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product, Research Funding; Novartis: Honoraria, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product, Research Funding; Dietmar-Hopp-Foundation: Other: Grants and/or provision of Investigational Medicinal Product; Mundipharma: Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; MSD: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product, Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product, Research Funding; Molecular Partners: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Chugai: Honoraria, Other: Grants and/or provision of Investigational Medicinal Product, Research Funding. O'Dwyer:GlycoMimetics Inc: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding; Onkimmune: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy. Venner:Janssen: Honoraria; J&J: Research Funding; Amgen: Honoraria, Research Funding; Sanofi: Honoraria; Takeda: Honoraria; Celgene: Honoraria. Weisel:GSK: Honoraria; Takeda: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Juno: Consultancy; Celgene Corporation: Consultancy, Honoraria, Research Funding; Adaptive Biotech: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding. Krevvata:Janssen: Employment. Pei:Janssen: Employment, Equity Ownership. Wang:Janssen: Employment. Van Rampelbergh:Janssen: Employment. Ukropec:Janssen: Employment, Equity Ownership. Uhlar:Janssen: Employment. Kobos:Janssen: Employment. Perrot:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria; Amgen: Honoraria; Sanofi: Honoraria.

Background: Venetoclax (Ven) is a highly selective, potent, oral BCL-2 inhibitor that induces apoptosis in multiple myeloma (MM) cells and has shown synergistic activity with the proteasome inhibitor (PI) bortezomib (B) and dexamethasone (d). Ven ± d had encouraging clinical efficacy in both t(11;14) MM and in pts irrespective of genetic background when administered with B, with a tolerable safety profile in Phase 1 studies. Here, we provide updated efficacy and safety of Ven vs placebo (Pbo) + Bd in pts with relapsed/refractory (RR) MM, including subgroup analyses, in the BELLINI study. Methods: BELLINI (NCT02755597) was a Phase 3, randomized, double-blind, multicenter study of Ven or Pbo + Bd in pts with RRMM who received 1 - 3 prior therapies and were either sensitive or naïve to PIs. Pts were randomized 2:1 to receive Ven 800 mg/day or Pbo + Bd. Cycles 1-8 were 21-day with B 1.3 mg/m2 on Days 1, 4, 8, 11 + d 20 mg on Days 1, 2, 4, 5, 8, 9, 11, 12. Cycles 9+ were 35-day with B 1.3 mg/m2 on Days 1, 8, 15, 22 + d 20 mg Day 1, 2, 8, 9, 15, 16, 22, 23. The primary endpoint was progression-free survival (PFS) by independent review committee (IRC). Results: A total of 291 pts were randomized, 194 to the Ven arm and 97 to the Pbo arm. Median age was 66 (range, 36 - 87); 53% had ISS II/III disease; 54% received 2 or 3 prior lines of therapy; 59% had prior stem cell transplant; 70% had prior PI, 68% had prior immunomodulatory drug, 41% had both. Among pts with evaluable results, 18% had high-risk cytogenetics, 13% had MM positive for t(11;14), and 79% had high levels of BCL-2 protein by immunohistochemistry (IHC). In the primary endpoint analysis per IRC, the median PFS was 22.4 months (m) in Ven vs 11.5 m in Pbo (HR=0.630, p=0.01), with a median follow-up of 18.7 m (as of 26 Nov 2018). As of updated analysis based on a data cut-off of 18 March 2019, the median PFS (per investigator [INV]) was 22.9 m in Ven vs 11.4 m in Pbo (HR=0.587, p=0.001; Table 1), with a median follow-up of 22.7 m. Per INV, higher overall response (ORR, 84% vs 70%, p=0.009) and very good partial or better response (≥VGPR, 61% vs 40%, p<0.001; Table 2) rates were observed in Ven vs Pbo. Minimal residual disease negativity rate (by next-generation sequencing) was also higher in the Ven arm vs Pbo (MRD- [10-5], 13% vs 1%). Median duration of response was 23.4 m for Ven and 12.8 m for Pbo. In the overall population, median overall survival (OS) was not reached in either arm but continued to favor Pbo (HR 1.474, 95% CI=0.870-2.498). A total of 70 deaths have been reported, 51 (26%) in the Ven arm and 19 (20%) in the Pbo arm. In the safety population (N=289), the most common treatment-emergent adverse events (TEAEs; Ven/Pbo) were diarrhea (59%/48%), nausea (37%/22%), constipation (35%/31%), and fatigue (31%/32%). The most common Grade 3/4 TEAEs were neutropenia (18%/8%), pneumonia (17%/12%), anemia (16%/15%), thrombocytopenia (15%/30%), and diarrhea (15%/12%); 23%/12% discontinued Ven due to a TEAE. The rates of serious AEs (51%/51%) and serious infections (30%/28%) were comparable between arms. There were 69 deaths in the safety population: in the Ven arm, 14 were treatment-emergent (TE; treatment start to 30 days after discontinuation) and 36 were non-TE (>30 days after treatment discontinuation); in the Pbo arm, 1 was TE and 18 were non-TE. In the t(11;14) subgroup, median PFS has not been reached for pts receiving Ven, but was 9.3 m for Pbo (HR=0.095; per INV). In the t(11;14)-negative (neg) subgroup, median PFS was 22.4 m and 10.7 m for Ven and Pbo, respectively (HR=0.627; per INV). Median OS has not been reached in either arm for the t(11;14) and t(11;14)-neg subgroups, although the HR favored Ven in t(11;14) pts, and Pbo in t(11;14)-neg pts. Analyses indicate that low BCL-2 expression by IHC and high-risk cytogenetics (defined as t(4;14, t(14;16), or del(17p)) were associated with decreased PFS and OS in the Ven arm (Table 1). In the high-risk cytogenetics pts, median PFS was 11.4 m in both arms (HR=0.99), and median OS has not been reached in either arm but favors Pbo (HR=10.6). In the subgroup with low BCL-2 expression by IHC, median PFS was 11.7 m and 17.0 m for Ven and Pbo, respectively (HR=1.42), and median OS was 21.3 m in the Ven arm and not reached in Pbo (HR=4.58). Conclusions: Updated analysis of BELLINI continue to reflect a favorable benefit-risk profile in t(11;14) pts, with meaningful clinical responses and improvement in PFS, as well as a positive trend in OS in this subgroup when treated with Ven + Bd. Disclosures Moreau: Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Harrison:Janssen Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Consultancy, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: investigator on studies, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cavo:sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; bms: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; novartis: Honoraria. De La Rubia:Janssen: Consultancy; Takeda: Consultancy; Celgene Corporation: Consultancy; AMGEN: Consultancy; AbbVie: Consultancy. Popat:Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel, accommodations, expenses; Janssen: Honoraria, Other: travel support to meetings; Takeda: Honoraria, Other: travel, accommodations, expenses; GSK: Consultancy, Honoraria; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Gasparetto:Celgene: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; BMS: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; Janssen: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed . Hungria:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: 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; BMS: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Consultancy, 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, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Salwender:Amgen: Honoraria, Other: Travel or accommodations; Takeda: Honoraria, Other: Travel or accommodations; Bristol-Myers Squibb: Honoraria, Other: Travel or accommodations; Sanofi: Honoraria, Other: Travel or accommodations; Celgene: Honoraria, Other: Travel or accommodations; AbbVie: Honoraria; Janssen Cilag: Honoraria, Other: Travel or accommodations. Suzuki:Ono: Research Funding; BMS: Honoraria, Research Funding; Takeda: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Gay:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: 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; Roche: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Janssen: 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; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees. Mikala:Takeda: Honoraria; Roche: Honoraria; Novartis: Honoraria; Janssen: Honoraria; Celgene: Honoraria, Research Funding; Amgen: Honoraria; AbbVie: Honoraria, Research Funding. Punnoose:Genentech, Inc.: Employment; Roche: Other: Stock/stock options. Hong:Genentech Inc.: Employment, Equity Ownership; Roche: Equity Ownership. Sood:AbbVie: Employment, Other: Stock/stock options. Jalaluddin:AbbVie: Employment, Other: Stock/stock options. Ross:AbbVie: Employment, Other: Stock/stock options. Ward:AbbVie: Employment, Other: Stock/stock options. Maciag:AbbVie: Employment, Other: Stock/stock options. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. OffLabel Disclosure: Venetoclax is a BCL-2 inhibitor that is FDA-approved in some indications. This presentation will focus on venetoclax for treatment of multiple myeloma, which is not an approved indication.

Introduction: Several patient and disease biology characteristics that impact overall survival (OS) outcomes of patients with newly diagnosed multiple myeloma (NDMM) have been well described. However, several prior population-based registry studies in the US such as SEER and NCDB databases have demonstrated the negative prognostic impact of socio-economic (SE) factors such as low median household income based on US national census bureau data for zip code of residence as well as absence of marital support on the OS of NDMM patients. Whether such SE factors are independent of established host and disease biology related factors remains unknown due to the absence of detailed patient-level data in population-based cancer registries. Thus, we evaluated whether such SE factors independently affected the OS of NDMM patients in our institution when accounting for patient and disease biology related factors. Methods: We analyzed a retrospective cohort of consecutive NDMM patients seen at the Mayo Clinic from January 2005 to December 2015. Median household income for each patient's area of residence was estimated by matching their home zip code at diagnosis with data available through the US National Census Bureau. Median household income < $63,000 for a zip code were used to classify patients as having low income based on the National Cancer Database classification of the bottom three quartiles. Absence of marital support was considered in patients divorced, single or widowed at the time of diagnosis. Survival estimates were calculated using the Kaplan-Meier method. Patient and disease biology related factors taken into consideration included age, FISH cytogenetics, ISS stage and LDH levels. Survival estimates were compared between groups using the log-rank test. Multivariable adjusted proportional hazards regression models were fit for the association between known prognostic factors and OS. Results: A total of 2,621 MM patients were analyzed from the Mayo Clinic cohort of which 60% were male and the median age was 64 (22 - 96) years with 14% being 75 years of age or older. In this cohort, 541 (33%) patients had ISS 3 disease and 370 (22%) had high risk cytogenetics by FISH. The median OS based on estimated average household income was 65 months for the group of patients with low household income (N = 32%) and 80 months for the remainder (P = 0.001) (Fig 1A). The median OS based on marital support was 59 months for those without marital support at diagnosis (N = 21%) versus 76 months for remainder (P = 0.003) (Fig 1B). However, in a multivariable analysis that included the aforementioned SE factors and patient and disease biology characteristics , only age of 75 years or older (p < 0.001), the presence of high-risk FISH cytogenetics (p < 0.001), presence of ISS 3 disease (p < 0.001) and elevated LDH (p = 0.005) retained independent statistical significance in predicting for worse OS. Lower household income (p = 0.264) and absence of marital support (p = 0.054) were not independent predictors of worse OS. Conclusions: With the caveat of patient selection bias in a tertiary academic center, SE factors such as estimated average household income and marital support at diagnosis do not appear to impact OS of NDMM patients when considered in the context of traditional host and disease biology risk factors. These findings are in contrast to those suggested by population based registry studies; nevertheless, similar patient-level assessments should be considered in patient cohorts from non-tertiary medical centers as these results may likely be different. Disclosures Dispenzieri: Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Lacy:Celgene: Research Funding. Kapoor:Amgen: Research Funding; Glaxo Smith Kline: Research Funding; Sanofi: Consultancy, Research Funding; Celgene: Honoraria; Janssen: Research Funding; Cellectar: Consultancy; Takeda: Honoraria, Research Funding. Leung:Prothena: Membership on an entity's Board of Directors or advisory committees; Aduro: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Omeros: Research Funding. Russell:Imanis: Equity Ownership. Gertz:Medscape: Consultancy, Speakers Bureau; Research to Practice: Consultancy; Springer Publishing: Patents & Royalties; Ionis/Akcea: Consultancy; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Other: Development of educational programs and materials; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.