Gasparetto, Cristina

8027 Background: The Connect MM Registry is a large, US, multicenter, prospective observational cohort study of pts with newly diagnosed multiple myeloma (NDMM) and one of the largest, longest running MM registries. Long-term survivors (LTS), defined as patients (pts) who have ≥ 8 years of follow-up, comprise a large portion of the Connect MM Registry. The purpose of this analysis was to assess LTS demographic and clinical characteristics. Methods: Adult pts with NDMM (N = 3011) were enrolled from 250 community, academic, and government sites: Cohort 1 from 2009 – 2011 and Cohort 2 from 2012 – 2016. As 99% of LTS were enrolled in Cohort 1, only pts from Cohort 1 were included in this analysis. Pt data were unevaluable if there were missing treatments, disease assessments, or large gaps in activity during follow-up (n = 28). Baseline characteristics, treatment patterns, and quality of life (QoL) form completion rates were examined. Results: At data cutoff (5/17/21), of the 1493 pts in Cohort 1 with evaluable data, 279 were LTS and 1186 were non-LTS. LTS were generally younger and had better performance status at enrollment (Table). Most (66%) LTS received stem cell transplants and few experienced progression within the first 6 months (3%). Top first-line (1L) regimen for LTS was lenalidomide/bortezomib/dexamethasone (31%) vs bortezomib/dexamethasone (22%) in non-LTS. At data cutoff, 73% of LTS were still on treatment at their most recent visit. LTS underwent disease assessments more frequently (2.0 vs 1.3 per year) and had a higher QoL completion rate by year 5 (58% vs 46%). This analysis showed an estimated 8-year survival of 36% vs an observed 8-year survival of 39% from the SEER database. Additional analyses are ongoing. Conclusions: LTS were younger and healthier than non-LTS. Most LTS received triplets at induction, stem cell transplants in 1L, and were less likely to relapse within the first 6 months of treatment than non-LTS. These findings are consistent with what has been observed in MM clinical trials. Further, this analysis demonstrates the value of longitudinal data in the CONNECT MM Registry and provides insights on long surviving pts with MM. Clinical trial information: NCT01081028. [Table: see text]

Abstract Background: Multiple myeloma (MM) is a heterogenous cancer of terminally differentiated plasma cells that typically express elevated levels of antiapoptotic proteins, such as BCL-2. Venetoclax (Ven), a highly selective, potent, oral BCL-2 inhibitor, induces apoptosis in MM cells, and when combined with bortezomib and dexamethasone showed promising efficacy in patients (pts) with relapsed/refractory MM (RRMM; Moreau et al. Blood. 2017;130:2392-2400). The Phase 3 BELLINI study primary analysis showed significantly improved response rates and progression-free survival (PFS) in pts with RRMM treated with Ven added to bortezomib and dexamethasone versus placebo (Pbo); however, increased mortality was observed in the Ven group (Kumar et al. Lancet Oncol. 2020;21:1630-1642). At the initial data cutoff (November 26, 2018), the PFS hazard ratio (HR) was 0.63 (95% CI, 0.44-0.90) and overall survival (OS) HR was 2.03 (95% CI, 1.04-3.95). Pts with t(11;14) translocation or high BCL2 expression showed improved responses and PFS without increased mortality. Here, we present updated safety and efficacy data from the prespecified final OS analysis. Methods: BELLINI (NCT02755597) is a Phase 3, randomized, double-blind, multicenter study of Ven or Pbo combined with bortezomib and dexamethasone in pts with RRMM who had received 1-3 prior lines of therapy and were either sensitive or naïve to proteasome inhibitors. Pts were randomized 2:1 to receive Ven 800 mg/day or Pbo plus bortezomib and dexamethasone. Cycles 1-8 were 21-day cycles with bortezomib 1.3 mg/m 2 on Days 1, 4, 8, and 11 and dexamethasone 20 mg on Days 1, 2, 4, 5, 8, 9, 11, and 12. Cycles 9 and beyond were 35-day cycles with bortezomib 1.3 mg/m 2 on Days 1, 8, 15, and 22 and dexamethasone 20 mg on Days 1, 2, 8, 9, 15, 16, 22, and 23. The primary endpoint was PFS assessed by independent review committee. Key secondary endpoints included overall response rate and OS. BCL2 expression was measured by quantitative polymerase chain reaction with the cutoff for high BCL2 determined using bootstrapping and aggregating thresholds from trees. Results: Of 291 randomized pts (194 to Ven and 97 to Pbo), 33 pts were receiving ongoing treatment (28 with Ven and 5 with Pbo) as of the final OS analysis data cutoff (March 15, 2021). At a median follow-up of 45.6 months, there were 78 (40%) deaths in the Ven arm versus 36 (37%) in the Pbo arm. Updated PFS and OS among all pts and those with t(11;14) or high BCL2 expression are shown in the Table. Among all pts, the median PFS per investigator was 23.4 months in the Ven arm versus 11.4 months in the Pbo arm (HR, 0.58 [95% CI, 0.43-0.78]). In pts with t(11;14), the median PFS was 36.8 months in the Ven arm versus 9.3 months in the Pbo arm (HR, 0.12 [95% CI, 0.03-0.44]). In pts with high BCL2, the median PFS was 30.1 months in the Ven arm versus 9.9 months in the Pbo arm (HR, 0.37 [95% CI, 0.21-0.64]). Median OS was not reached in the Ven or Pbo arm among all pts (HR, 1.19 [95% CI, 0.80-1.77]), pts with t(11;14) (HR, 0.61 [95% CI, 0.16-2.32]), pts with high BCL2 (HR, 0.70 [95% CI, 0.32-1.51]), and pts with t(11;14) or high BCL2 (HR, 0.82 [95% CI, 0.40-1.70]). The most common treatment-emergent adverse events (AEs) with Ven (versus Pbo) were diarrhea (60% versus 50%), nausea (38% versus 23%), and constipation (35% versus 31%). The most common Grade 3/4 AEs (Ven versus Pbo) were thrombocytopenia (16% versus 30%), neutropenia (23% versus 8%), pneumonia (19% versus 13%), anemia (16% versus 15%), and diarrhea (15% versus 11%). Serious AEs occurred in 57% of Ven- and 55% of Pbo-treated pts, with serious infections and infestations occurring in 35% and 29% of pts, respectively. Overall, 26% of pts in the Ven arm and 11% of pts in the Pbo arm experienced an AE leading to Ven or Pbo discontinuation. AEs led to 12 deaths in the Ven arm, with 9 of these deaths due to serious infection; an AE led to 1 death in the Pbo arm. A total of 16 (6%) treatment-emergent deaths occurred (14 [7%] with Ven and 2 [2%] with Pbo), with 3 of these deaths due to disease progression (2 [1%] with Ven and 1 [1%] with Pbo). Conclusion: In the final OS analysis, the addition of Ven to bortezomib and dexamethasone showed significantly improved PFS but resulted in increased mortality versus Pbo in the total population. Consistent with results from previous analyses, Ven added to bortezomib and dexamethasone showed the greatest PFS improvement in pts with t(11;14) or high BCL2, with a favorable benefit-risk profile. Figure 1 Figure 1. Disclosures Kumar: Beigene: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Merck: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Tenebio: Research Funding; BMS: Consultancy, Research Funding; Antengene: Consultancy, Honoraria; Roche-Genentech: Consultancy, Research Funding; Novartis: Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Harrison: Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene/ Juno/ BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche/Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Haemalogix: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Eusa: Consultancy, Honoraria, Speakers Bureau; Terumo BCT: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Cavo: Novartis: Honoraria; GlaxoSmithKline: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Adaptive Biotechnologies: Consultancy, Honoraria; 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, EXPENSES, Speakers Bureau; Bristol-Myers Squib: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. de la Rubia: Ablynx/Sanofi: Consultancy; Amgen, Bristol Myers Squibb,: Honoraria, Speakers Bureau; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Celgene, Takeda, Janssen, Sanofi: Honoraria; AbbVie: Consultancy; Bristol Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Accommodations; GSK: Consultancy; Takeda: Consultancy; Sanofi: Membership on an entity's Board of Directors or advisory committees. Popat: Abbvie, Takeda, Janssen, and Celgene: Consultancy; AbbVie, BMS, Janssen, Oncopeptides, and Amgen: Honoraria; Takeda: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; Janssen and BMS: Other: travel expenses. Gasparetto: Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Karyopharm Therapeutics Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES, Speakers Bureau; Oncopeptite: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy; Connect Registry: Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES, Research Funding, Speakers Bureau. Hungria: Sanofi: Honoraria, Other: Support for attending meetings/travel ; Takeda: Honoraria; Abbvie: Honoraria; Amgen, BMS, Celgene, Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support for attending meetings/travel . Salwender: Oncopeptides: Honoraria; GlaxoSmithKline: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Sanofi: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Takeda: Honoraria; Pfizer: Honoraria; Amgen: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Chugai: Honoraria; AbbVie: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Janssen-Cilag: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Bristol-Myers Squibb/Celgene: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES. Suzuki: Japanese Red Cross Medical Center: Current Employment; Janssen: Honoraria; AbbVie: Honoraria; Sanofi: Honoraria; Bristol-Myers Squibb: Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; ONO: Honoraria; Novartis: Honoraria. Kim: Seoul National University Hospital: Current Employment. Onishi: Roche: Current Employment, Current equity holder in publicly-traded company; Genentech: Current Employment. Ku: Roche: Current Employment, Current equity holder in publicly-traded company, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Genentech: Current Employment, Other: TRAVEL, ACCOMMODATIONS, EXPENSES. Pothacamury: AbbVie: Current Employment, Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company. Sehgal: AbbVie: Current Employment, Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company. Masud: AbbVie: Current Employment, Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company. Ross: AbbVie: Current Employment, Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company. Dobkowska: AbbVie: Current Employment, Current equity holder in publicly-traded company, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Pharmacyclics: Current Employment. Moreau: Celgene BMS: Honoraria; Amgen: Honoraria; Abbvie: Honoraria; Janssen: Honoraria; Sanofi: Honoraria; Oncopeptides: Honoraria.

Background: Multiple myeloma (MM) is typically diagnosed in patients (pts) aged 65-74 y (SEER: Myeloma. 2019); therefore, many pts present with concomitant metabolic disorders such as diabetes (18%-22% prevalence of type 2 diabetes [T2D; BMC Cancer. 2020;20:489]). Obesity (body mass index [BMI], ≥ 30 kg/m2) is associated with increased prevalence of T2D (Int J Clin Pract. 2007;61:737), and both are suggested risk factors for MM (Blood. 2012;119:4845; Bone Marrow Transpl. 2014;49:1009). Results from single-center, retrospective studies have shown poorer clinical features and survival outcomes in diabetic pts with MM vs their nondiabetic counterparts (Eur J Haematol. 2012;89:320, Br J Cancer. 2014;111:628). The Connect® MM Registry (NCT01081028) is a large, US, multicenter, prospective observational cohort study of largely community-based pts with NDMM. Reported here is a descriptive analysis assessing differences in baseline (BL) characteristics, treatment patterns, and survival outcomes in diabetic vs nondiabetic pts enrolled in the Connect MM Registry. Methods: Pts with NDMM (N = 3011) were enrolled at 250 community, academic, and government sites. Eligible pts were aged ≥ 18 y with symptomatic MM diagnosed ≤ 2 months (mo) pre-enrollment per International Myeloma Working Group criteria (Leukemia. 2009;23:3). Diabetic pts were defined as those with a history of diabetes and also receiving antidiabetic treatment at BL; those without a history of diabetes and not receiving antidiabetic treatment at BL were defined as nondiabetic pts. Descriptive statistics were used for BL characteristics and treatment regimens. Survival outcomes (progression-free survival [PFS] and overall survival [OS]) were analyzed using Cox regression and adjusted for covariates. Results: Of the 2845 pts included in this analysis, 467 (16%) were diabetic, and 2378 (84%) were nondiabetic. The median age was 69 y for diabetic pts and 66 y for nondiabetic pts, with fewer Black pts (12.2% vs 19.5%) in the nondiabetic group. The proportion of men was higher in the diabetic vs the nondiabetic group (61.9% vs 56.6%). Similar percentages of pts had ECOG PS of 0-1 in both groups (53.3% vs 55.3%). Obesity was more prevalent in diabetic vs nondiabetic pts (55.9% vs 30.4%). More diabetic pts had a history of hypertension requiring treatment vs nondiabetic pts (84.2% vs 52.5%). The prevalence of chromosomal abnormalities was comparable between the groups (within the limitation that data were missing in a substantial number of pts). Among MM-defining criteria, diabetic pts had a higher incidence of hypercalcemia (11.8% vs 8.5%), anemia (50.3% vs 46.5%), and increased creatinine (23.8% vs 19%), whereas measured kidney function was similar. A lower proportion of diabetic than nondiabetic pts received stem cell transplantation (SCT; 28.9% vs 41.5%) and triplet regimens during first induction (48.2% vs 52.8%%). The use of ≥ 2 novel agents during first line (1L) was lower in diabetic than nondiabetic pts (27.8% vs 34.6%), but use of a single novel agent (63.4% vs 60%) and alkylator in 1L (20.6% vs 22.4%) was comparable. The top five 1L regimens were similar for both groups, with lenalidomide + bortezomib + dexamethasone being the most common 1L regimen, and lenalidomide the most common maintenance therapy. Diabetic pts had significantly shorter adjusted median PFS (24.4 vs 31.5 mo; hazard ratio [HR], 1.24; P = 0.001; Fig. 1A) and median OS (60 vs 72.6 mo; HR, 1.29; P = 0.001; Fig. 1B) than nondiabetic pts. In a subgroup analysis by BMI, diabetic pts had significantly shorter OS than nondiabetic pts (for BMI < 30 [50.8 vs 73.1 mo; HR, 1.51; P = 0.0001] and BMI ≥ 30 [56.4 vs 78.6 mo; HR, 1.51; P < 0.0001]). Conclusions: Diabetic pts with NDMM had poorer BL features and were less likely to receive SCT and triplet regimens and/or aggressive upfront treatment. Regardless of BMI, diabetic pts had shorter median OS than nondiabetic pts, suggesting that diabetes might be a stronger factor for survival than obesity. These results support a previous analysis of the Connect MM Registry that identified history of diabetes as a predictive prognostic factor for poor OS (Br J Haematol. 2019;187:602). Limitations of this analysis include limited detail on the care/management of diabetes and steroid use/dosage (which can be challenging for glycemic control). These findings highlight the need to provide better supportive care for diabetes management in MM pts to improve survival. Disclosures La: Celgene BMS: Consultancy. Jagannath:BMS, Janssen, Karyopharm, Legend Biotech, Sanofi, Takeda: Consultancy. Ailawadhi:Amgen: Research Funding; Celgene: Honoraria; Takeda: Honoraria; Janssen: Research Funding; Pharmacyclics: Research Funding; Cellectar: Research Funding; BMS: Research Funding; Medimmune: Research Funding; Phosplatin: Research Funding. Durie:Amgen, Celgene, Johnson & Johnson, and Takeda: Consultancy. Gasparetto:Adaptive Biotechnologies: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau; Karyopharm: Consultancy, Honoraria, Other: TRAVEL, ACCOMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau; Janssen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; GSK: Consultancy, Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Consultancy, Honoraria. Hardin:Celgene Pharmaceutical Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES. Lee:Sanofi: Consultancy; Janssen: Consultancy, Research Funding; GlaxoSmithKline: Consultancy, Research Funding; Genentech: Consultancy; Takeda: Consultancy, Research Funding; Regeneron: Research Funding; Genentech: Consultancy; Amgen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Daiichi Sankyo: Research Funding. Narang:Maryland Oncology Hematology: Current Employment; Beigene: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; J&J: Consultancy, Honoraria. Omel:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; BMS/Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Rifkin:McKesson: Current equity holder in publicly-traded company, Ended employment in the past 24 months, Other: Stock ownership; Takeda, Amgen, Celgene, BMS, Mylan, Coherus BioSciences, Fresenius: Consultancy; AbbVie: Other: Investigator in AbbVie sponsored clinical trials; Takeda, Amgen, BMS (Celgene): Membership on an entity's Board of Directors or advisory committees. Terebelo:Newland Medical Associates: Current Employment; BMS: Membership on an entity's Board of Directors or advisory committees. Toomey:Celgene/BMS: Membership on an entity's Board of Directors or advisory committees. Wagner:Celgene Inc.: Membership on an entity's Board of Directors or advisory committees; Connect Multiple Myeloma Registry: Membership on an entity's Board of Directors or advisory committees. Dhalla:BMS: Current Employment, Current equity holder in publicly-traded company. Liu:TechData Inc: Consultancy. Yang:BMS: Current Employment, Current equity holder in publicly-traded company. Joshi:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company; Eisai Inc.: Ended employment in the past 24 months. Abonour:Takeda: Consultancy; Janssen: Honoraria, Research Funding; Celgene: Consultancy; BMS: Consultancy, Research Funding.

8521 Background: Several clinical and molecular prognostic factors (e.g, International Staging System [ISS] stage, plasma cell labeling index, genomic models) exist for multiple myeloma (MM). We hypothesized that exploiting gene signatures representative of oncogenic pathway deregulation (i.e., Ras, Myc, etc.), would improve MM prognostication and also aid with the identification of novel therapeutic targets. Methods: Using a discovery cohort (n=47) of patients with MM and corresponding gene expression data, we built upon current molecular risk-stratification and devised a Bayesian genomic (“metagene”) model for prognosis. We validated that model in an independent patient cohort (n=207). Finally, we incorporated ISS staging and clinical variables to construct a combined Clinico-Genomic Risk Stratification System. We further validated the combined model in a separate cohort (n=72), in a blinded manner. Results: Using gene signatures predictive of oncogenic pathway activation in the discovery cohort, we identified specific patterns (metagenes) of signaling pathway activation with prognostic relevance. In an independent validation cohort, this metagene-based model accurately predicted event free survival (EFS) independently of ISS (multivariate hazard ratio [HR] 3.4 for ISS stage, and 5.4 for the metagene model, p=0.002). Using multivariate risk modeling, we incorporated ISS staging and the metagene model into a Clinico-Genomic System and successfully stratified the validation cohort into three groups (low, intermediate, and high risk) with markedly different EFS (HR 4.2 for intermediate risk and 14.0 for high risk vs. the low risk cohort, p<0.0001). In an additional blinded validation, the Clinico-Genomic System again accurately predicted median overall survival (68.7 [low risk] vs 24.7 [intermediate risk] vs 18.7 months [high risk], p<0.0001); more accurately than either ISS or other reported genomic models. Conclusions: A combined Clinico-Genomic Risk Stratification System, building on patterns of oncogenic pathway activation and ISS staging system, improves upon current prognostic models in MM and identifies novel pathway targets for future therapeutic consideration. No significant financial relationships to disclose.

BackgroundStudies have reported racial disparities in access to and use of multiple myeloma (MM) treatments between African American (AA) and White patients. Although AA patients demonstrate longer disease‐specific survival, this has not uniformly translated into improved survival over time. The association between race and treatment patterns and survival outcomes was analyzed using data from the Connect MM Registry.MethodsThe Connect MM Registry is a large US, multicenter, prospective observational cohort study of patients with newly diagnosed MM. Patients who received first‐line (1L) stem cell transplantation (SCT) or who did not receive SCT (non‐SCT or non–stem cell transplantation [NSCT]) were grouped by raceEffects of race and transplantation status on the use of triplet treatment were estimated using logistic regression.ResultsTreatment patterns in 1L (types and duration of induction, posttransplantation maintenance) were similar between AA and White patients. SCT rates in 1L (32% vs 36%) and triplet treatment use (AA: 44% for NSCT patients and 72% for SCT patients; and White: 48% for NSCT patients and 72% for SCT patients) during first induction were similar. No significant effect of race or transplantation status on 1L triplet treatment use was observed. Race was not found to be associated with survival outcomes among patients who underwent NSCT; however, AA patients who received SCT had significantly longer overall survival compared with White patients who underwent SCT (not reached vs 88.2 months; hazard ratio, 0.56; 95% CI, 0.35‐0.89 [P = .0141]).ConclusionsAA and White patients were found to have similar treatment patterns in the Connect MM Registry, suggesting that both groups had equal access to health care. In this real‐world setting, AA patients received standard‐of‐care treatment, which might have contributed to better MM‐specific survival compared with White patients.

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]

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.

Background: Overexpression of the anti-apoptotic BCL-2 protein promotes multiple myeloma (MM) cell survival. Venetoclax (Ven) is a highly selective, potent, oral BCL-2 inhibitor that induces apoptosis and has shown synergistic activity with bortezomib (B) and dexamethasone (d). Phase 1 studies in relapsed/refractory (RR) MM demonstrated encouraging clinical efficacy of Ven + d in t(11;14) MM and in a broader patient (pt) population in combination with Bd. Recent results from the Phase 3 BELLINI study of Ven vs placebo (Pbo) + Bd in pts with RRMM demonstrated that pts treated with Ven + Bd had improved clinical response rates and progression-free survival (PFS) vs Pbo, although the overall survival (OS) result was in favor of Pbo. Subgroup analyses showed different efficacy and survival outcomes based on tumor cytogenetics and BCL-2 expression. Results of pre-specified subgroup analyses and additional retrospective correlative biomarker analyses in the Phase 3 BELLINI study are described herein. Methods: BELLINI (NCT02755597) was a randomized, double-blind, multicenter Phase 3 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. The following biomarker analyses were performed by central laboratory assessments of pre-treatment tumor samples: BCL-2 protein expression by immunohistochemistry (IHC) analysis of bone marrow (BM) core biopsies; BCL2 gene expression by quantitative PCR (qPCR) and cytogenetic abnormalities by interphase fluorescence in situ hybridization (FISH) analysis of CD138-enriched BM mononuclear cells. Correlation between BCL-2 (protein and gene) expression, cytogenetics, and outcomes were examined by Kruskal-Wallis tests and by hazard ratio (HR) using the Cox proportional hazard model. Results: As of the data cut-off of 18 Mar 2019, 291 pts were randomized, 194 to the Ven arm and 97 to the Pbo arm. Out of the 291 pts randomized, 177 pts (61%) were evaluable by IHC, 257 pts (88%) by qPCR, and 262 pts (90%) by FISH. A broad range of BCL2 gene expression was observed (median 2-DCt: 0.212 [range: 0-5.21]), which strongly correlated with protein expression (median 2-DCt 0.115 in BCL-2 IHC Low vs 0.277 in BCL-2 IHC High, p=0.0021). t(11;14) MM had the highest levels of BCL-2 expression (23/23 BCL-2 High by IHC; median 2-DCt 0.406 vs 0.212 in t(11;14) negative, p=0.0132), however high BCL-2 expression was not limited to the t(11;14) subgroup. Univariate analyses showed higher BCL2 expression in pt tumor samples with del(13q) (median 2-DCt 0.333 vs 0.159 in pts without del(13q), p=0.0008) and gain(1q) (median 2-DCt 0. 295 vs 0.180 in pts without gain(1q), p=0.0059). Bootstrapping and aggregating thresholds from trees (BATTing) was used retrospectively to identify an estimated threshold value for BCL2 expression (2-DCt ≥0.323) that could provide optimum selection of pts with maximum improvement in PFS when treated with Ven+Bd. Biomarker subgroups with the greatest PFS improvement were t(11;14) (HR=0.10; 95% CI: 0.02-0.46, p=0.003) and High BCL2 by qPCR (HR=0.26; 95% CI: 0.13-0.51, p&lt;0.001; Table 1). Since the t(11;14) and High BCL2 patient populations do not completely overlap (20% of High BCL2 pts were t(11;14) and 54% of t(11;14) were High BCL2), a combined subgroup analysis was performed. For pts with t(11;14) or High BCL2, the median PFS was not reached in the Ven arm vs 9.9 mo in Pbo (HR=0.26, 95% CI: 0.14-0.48, p&lt;0.001; Table 1). Higher overall response (ORR, 88% vs 70%), very good partial response or better (≥VGPR, 73% vs 33%), and complete response or better (≥CR, 42% vs 3%) rates were observed in the Ven vs Pbo arm (Table 2). Minimal residual disease negativity (MRD-, 10-5) rate was also higher for t(11;14) or High BCL2 pts in the Ven vs Pbo arm (19% vs 0%). Median overall survival (OS) was not reached in either arm but was similar between treatment arms for the combined group with t(11;14) or High BCL2 pts (HR=0.92, 95% CI=0.39-2.16, p=0.85). In contrast, in the t(11;14) negative and Low BCL2 pts, OS favored Pbo (HR=3.13, 95% CI=1.2-8.13, p=0.019; Table 1). Conclusions: Adding Ven to Bd demonstrates significant efficacy in pts with RRMM harboring either t(11;14) or tumor cells expressing high levels of BCL2. The benefit-risk profile appears to be favorable in these subsets of pts and additional studies to gain further safety and efficacy information are warranted. Disclosures Harrison: GSK: Consultancy, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: investigator on studies, 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; Janssen Cilag: 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:celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; novartis: Honoraria; 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; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; bms: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. De La Rubia:AMGEN: Consultancy; Takeda: Consultancy; AbbVie: Consultancy; Janssen: Consultancy; Celgene Corporation: 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; GSK: Consultancy, Honoraria; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Other: travel, accommodations, expenses. 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 . Hungria: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; Janssen: 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; BMS: Consultancy, Honoraria, 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; Celgene: 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; BMS: Consultancy, Honoraria, Speakers Bureau; Takeda: 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. Salwender:Amgen: Honoraria, Other: Travel or accommodations; Bristol-Myers Squibb: Honoraria, Other: Travel or accommodations; Janssen Cilag: Honoraria, Other: Travel or accommodations; Sanofi: Honoraria, Other: Travel or accommodations; Celgene: Honoraria, Other: Travel or accommodations; AbbVie: Honoraria; Takeda: Honoraria, Other: Travel or accommodations. Suzuki:Ono: Research Funding; BMS: Honoraria, Research Funding; Takeda: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Moreau:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Spencer:AbbVie: 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, Speakers Bureau; Secura Bio: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Specialised Therapeutics Australia: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Servier: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Haemalogix: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen Oncology: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. O'Dwyer:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy; GlycoMimetics Inc: Research Funding; BMS: Research Funding; Onkimmune: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Research Funding. Garg:Janssen: Honoraria; Novartis, Janssen: Research Funding; Janssen, Takeda, Novartis: Other: Travel expenses. Punnoose:Roche: Other: Stock/stock options; Genentech, Inc.: Employment. Jalaluddin:AbbVie: Employment, Other: Stock/stock options. Jia:AbbVie: Employment, Other: Stock/stock options. Yang:AbbVie: Employment, Other: Stock/stock options. Sun:AbbVie: Employment, Other: Stock/stock options. Ward:AbbVie: Employment, Other: Stock/stock options. Maciag:AbbVie: Employment, Other: Stock/stock options. Ross:AbbVie: Employment, Other: Stock/stock options. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, 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.