Hardin, James W.

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 Introduction: Treatment resistance remains a challenge that most patients (pts) with MM will encounter in their disease course. With each subsequent line of therapy (LOT), pt outcomes and health-related quality of life (HRQoL) worsen. Pts with MM who are refractory to immunomodulatory drugs, proteasome inhibitors (PIs), and anti-CD38 antibodies (triple-class refractory; TCR) have a poor prognosis and the holistic burden is not well understood. To capture these features, the ongoing prospective Connect ® MM Disease Registry was used to report treatment patterns and outcomes in pts with TCR MM. Methods: Data from September 28, 2009 to February 4, 2021 were used. Eligible pts were ≥18 years of age at first documented diagnosis of MM, which became TCR during their disease course. MM was defined as refractory to therapies based on the International Myeloma Working Group Criteria. Index date was defined as first record of TCR during the disease course. Data analyzed included pt characteristics, treatment patterns pre- and post-index, overall survival (OS), healthcare resource utilization (HCRU), and HRQoL. General HRQoL was captured by EQ-5D-3L utility index (range −0.11-1, higher score indicated better HRQoL), EQ-5D visual analog scale (VAS) score (range 0-100, "worst imaginable" to "best imaginable" health status), and FACT-G total score (range 0-108). Disease-specific HRQoL was measured by FACT-MM total score (range 0-164), FACT-MM Trial Outcome Index (TOI) (range 0-112), and the Brief Pain Inventory (BPI) average pain item (range 0-10, "no pain" to "worst pain you can imagine"). Higher scores indicated better HRQoL for all FACT-related index scores. Cohort-level clinically meaningful change in HRQoL during post-index year 1 was defined as 0.08 for the EQ-5D utility index, 7 for the EQ-5D VAS, and 6-8 points for the FACT-G total score. Validated thresholds were unavailable for other index scores. All statistical analyses were descriptive. Results: This analysis included 240 pts identified from the Registry. Mean age at index date was 68.1 (standard deviation [SD] 10.4) years. Mean time from initial MM diagnosis was 64.1 (SD 26.9) months. 63.3% of pts had prior stem cell transplantation. Mean number of prior LOTs was 4 (SD 1.7). 64.6% of pts had received a subsequent MM LOT since index date. Median follow-up time post-index date was 4.6 months. Treatment pattern analysis of post-index treated pts (Table A) revealed that retreatment with an immunomodulatory drug, PI, or anti-CD38 agent post-index date was common, led by carfilzomib (47.1%) and pomalidomide (40.0%). However, no therapeutic combination was preferred in this pt population. Regarding their index therapy (first post-index LOT), 70.3% and 22.6% were on triplet and quadruplet combination therapy; 3.2% initiated belantamab mafodotin, selinexor, melflufen, and/or idecabtagene vicleucel; mean duration of treatment was 5.6 (SD 6.1) months. For all pts, median OS was 8.9 months; median OS for those who received < 4 prior LOTs (43.8%) versus those who received 4 or more prior LOTs (56.2%) was 10.0 and 8.0 months, respectively. Regarding HCRU during the post-index follow-up, all-cause and MM-related hospitalizations were observed in 49.6% and 23.8% of all eligible pts, respectively. Among these pts, annualized mean number of all-cause/MM-related hospitalization and length of hospital stay were estimated as 8.5 (SD 18.2)/11.0 (SD 25.2) and 64.0 days (SD 80.0)/ 69.2 days (SD 83.7), respectively. Analysis of HRQoL showed a numerical decline in HRQoL relative to index during the 1-year post-index period across all studied HRQoL instruments. There was a clinically meaningful decline in HRQoL from baseline following the index date based on the EQ-5D utility index, EQ-5D VAS, and FACT-G total score (Table B). Conclusion: Pts with TCR MM experienced poor survival, substantial hospitalizations, and a clinically meaningful decline in HRQoL. 35.4% of pts did not receive any new LOTs since the disease became TCR. Among those who did receive subsequent LOTs, re-treatment with an immunomodulatory drug, PI, or anti-CD38 antibody therapy occurred, showing a lack of novel treatment options. This study suggests novel tolerable and efficacious therapeutic agents are needed to address the burden of illness in pts with MM. Figure 1 Figure 1. Disclosures Tang: Bristol-Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Hari: Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Celgene-BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Adaptive Biotech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Karyopharm: Consultancy; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Research Funding. Ramasamy: Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: 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, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene - Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Weisel: Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Myers Squibb: 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; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Consultancy, Honoraria, 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; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy; Novartis: Honoraria; Pfizer: Honoraria. Joshi: Bristol Myers Squibb: Current Employment. Liu: Bristol Myers Squibb: Current Employment. Che: Bristol Myers Squibb: Current Employment. Hernandez: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Abonour: Jensen: Honoraria, Research Funding; Celgene-BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Consultancy, Honoraria, Research Funding; Takeda: Research Funding. Hardin: Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees. Rifkin: Sanofi: Membership on an entity's Board of Directors or advisory committees; McKesson: Current Employment, Current equity holder in publicly-traded company; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Fresenius-Kabi: Membership on an entity's Board of Directors or advisory committees; Coherus: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb (Celgene): Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Ailawadhi: BeiGene, Ltd.: Consultancy; Bristol Myers Squibb: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Ascentage: Research Funding; Medimmune: Research Funding; Cellectar: Research Funding; Xencor: Research Funding; GSK: Consultancy, Research Funding; Takeda: Consultancy; Genentech: Consultancy; AbbVie: Consultancy; Karyopharm: Consultancy; Sanofi: Consultancy; Oncopeptides: Consultancy. Lee: Legend Biotech: Consultancy; Sanofi: Consultancy; Oncopetides: Consultancy; Bristol Myers Squibb: Consultancy; Amgen: Consultancy, Research Funding; Celgene: Consultancy; Janssen: Consultancy, Research Funding; Takeda Pharmaceuticals: Consultancy, Research Funding; Karyopharm: Consultancy; Regeneron: Research Funding; Genentech: Consultancy; GlaxoSmithKline: Consultancy, Research Funding. Terebelo: Pharmacylics: Speakers Bureau; Celgene-BMS: Consultancy; Takeda: Speakers Bureau; Janssen: Speakers Bureau. Durie: Amgen, Celgene/Bristol-Myers Squibb, Janssen, and Takeda: Consultancy; Amgen: Other: fees from non-CME/CE services . Narang: Bristol Myers Squibb: Consultancy; TG Pharma: Consultancy. Toomey: Bristol Myers Squibb: Consultancy. Gasparetto: Oncopeptide: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy; Sanofi: Consultancy, Honoraria, Speakers Bureau; Karyopharm: Consultancy, Honoraria, Speakers Bureau; Gsk: Consultancy, Honoraria, Speakers Bureau. Wagner: Celgene-BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Athenex Inc: Consultancy; Eli Lilly, Johnson & Johnson: Other: Spouse, previously held individual stocks;. Jagannath: Janssen Pharmaceuticals: Consultancy; Bristol Myers Squibb: Consultancy; Karyopharm Therapeutics: Consultancy; Legend Biotech: Consultancy; Sanofi: Consultancy; Takeda: Consultancy.

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.

SummaryAlthough new multiple myeloma (MM) therapies are effective in alleviating some disease‐associated symptoms (e.g. bone pain, fatigue, functional decline), they can result in additional toxicities, further impacting health‐related quality of life (HRQoL). Here, we compared HRQoL and safety of lenalidomide‐bortezomib‐dexamethasone [RVd (n = 445)], bortezomib‐melphalan‐prednisone [VMP (n = 77)] and Vd or VMP (n = 588) in patients with newly diagnosed MM (NDMM) from the Connect® MM Registry, a large, USA, multicentre, prospective observational cohort study. Functional Assessment of Cancer Therapy‐Multiple Myeloma subscale, EuroQol‐5D overall score and Bone Pain Inventory HRQoL scores were significantly improved with RVd versus Vd/VMP. Serious adverse event rates were similar in all groups. Treatment with RVd maintained HRQoL in this real‐world, largely community‐based population of patients with NDMM.

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.

8518 Background: Patients (pts) with newly diagnosed multiple myeloma (NDMM) and renal impairment (RI) are often excluded from clinical trials. Data are limited on the effects of induction treatment in these pts, who may also be ineligible for autologous stem cell transplant (SCT) due to severity of RI. This analysis investigated the impact of RVd induction on renal function in transplant eligible (TE) and noneligible (TNE) pts from the Connect MM Registry, a US, multicenter, prospective, observational study. Methods: Eligible pts were ≥ 18 y and had symptomatic MM diagnosed ≤ 2 mos prior to enrollment, as defined by the International Myeloma Working Group criteria. For this analysis, pts that received front-line RVd for ≥ 3 cycles were grouped per transplant eligibility and renal function at baseline (BL; creatinine clearance [CrCl] < 30, 30-50, > 50-80, and > 80). Pts with progressive disease at BL were excluded. Renal function at 3 mos was measured. Median unadjusted progression-free survival (PFS) was calculated from start of regimen in TE and TNE populations, with pts grouped by CrCl (≤ 60 or > 60) at BL. Results: As of 7/23/19, 421 TE and 212 TNE pts received RVd for ≥ 3 cycles. TE and TNE pts were grouped by BL CrCl of < 30 (20 and 16 pts), 30-50 (36 and 50 pts), > 50-80 (117 and 63 pts), and > 80 (248 and 83 pts). Renal function improvement was observed in all pts receiving RVd, including those with moderate (30-50 CrCl) and severe (< 30 CrCl) RI at BL (Table). In pts with > 60 CrCl and ≤ 60 CrCl at BL, median PFS in TE pts was 48.6 mos and 43.2 mos, respectively. In TNE pts, median PFS was 36.4 mos and 30.6 mos, respectively. Conclusions: The results from the Connect MM Registry indicate that pts with NDMM and RI (including moderate and severe) who receive front-line RVd for ≥ 3 cycles may see improvement in renal function at 3 mos, regardless of transplant eligibility. RVd therefore can potentially be used in pts with RI. This analysis provides real-world data that support further investigation of RVd treatment in pts with moderate or severe RI. Clinical trial information: NCT01081028 . [Table: see text]

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]