Liu, Liang

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.

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