Terebelo, Howard R.

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]

Abstract Introduction: Recent reviews indicate that transfusional hemosiderosis may be associated with an increased risk of mortality in lower-risk pts with MDS. This trial is designed to evaluate the efficacy and long-term safety of deferasirox (Exjade®, ICL670) in MDS. Deferasirox is an oral iron chelator approved for use in pts with transfusional iron overload. Methods: This is a Phase II, open-label, 3-yr clinical trial in 55 US centers, enrolling 150 pts (aged ≥18 years) with Low- or Int-1-risk MDS (by IPSS criteria) and transfusional iron overload (serum ferritin ≥1000 ng/mL and &gt;20 units RBC transfusions). Deferasirox dosing is 20–30 mg/kg/day. Serum ferritin, iron, transferrin and transferrin saturation are being assessed at screening and monthly in yr 1, then quarterly in yrs 2 and 3, while labile plasma iron (LPI) is assessed quarterly in yr 1. In addition, creatinine, calculated creatinine clearance, echocardiograms and endocrine and hematological status are being assessed. This report describes baseline data in these pts. Results: As of June 2006, 84 pts have enrolled. Demographic data are available from 79 pts: median age 71 years (range 47–87); sex (52 male, 27 female); ethnicity (74 Caucasian, 2 Black, 2 Hispanic, 1 Oriental); and IPSS Risk Group (Low: 22 pts; Int-1: 56 pts). Iron status is summarized in the table: Parameter n Mean ± SD Median Range Normal range n/a, not applicable Serum ferritin,μg/L 84 3779 ± 4070 2951 1160–36280 12–370 Serum iron, μg/dL 84 205 ± 64 201 48–409 37–180 Transferrin, mg/dL 82 153 ± 31 152 83–244 190–375 Transferrin saturation, % 83 85 ± 15 91 20–94 15–50 LPI, μmol/L 38 0.52 ± 0.63 0.25 0–2.9 0 Total transfusions, n 78 63.3 ± 66.3 41.5 14–435 n/a Years of transfusion 75 3.4 ± 1.9 3 1–12 n/a Baseline concurrent therapies: 5-azacytidine (Vidaza): 5 pts; lenalidomide (Revlimid): 1 pt. Calculated creatinine clearance: normal (&gt;80 mL/min): 37 pts; mildly abnormal (51–80 mL/min): 30 pts; moderately abnormal (30–50 mL/min): 9 pts. Hematological parameters: Anemia was present in all pts; other cytopenias included: neutropenia (&lt;1800/μL): 13 pts, thrombocytopenia (&lt;100,000/μL): 15 pts; neutropenia and thrombocytopenia: 12 pts. A total of 53 pts had received chelation prior to enrolling: 51 deferoxamine (Desferal®); and 2 deferasirox. Conclusions: Despite the prior availability of deferoxamine, these baseline data demonstrate significant levels of iron overload among transfused pts with myelodysplasia. Serum iron, ferritin and LPI are all well above the clinically significant thresholds associated with increased complications. Since recent data has suggested that iron overload may be a poor prognostic indicator in MDS, increased attention to maintaining appropriate iron balance is warranted. The recent availability of an oral iron chelator may be more acceptable to MDS pts and their physicians. This ongoing trial is designed to assess the long-term efficacy, safety, and clinical benefits of deferasirox in pts with MDS.

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]

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

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

Abstract Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P &lt; 1 × 10−6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P &lt; .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10−12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.

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

Multiple myeloma (MM) is a neoplasm thought to arise from a damaged germinal center B-cell that progresses to a plasma cell clone arising in bone marrow. MM comprises 20% of all hematologic cancer deaths. Persons of African ancestry (AA) have a 1.5 to 2-fold higher risk compared to individuals of European ancestry (EA). Genetically driven differences in hematopoiesis may lead to variation in the levels white blood cell (WBC) subsets which could, in turn, be associated with MM etiology. There are differences in genetic determinants of WBC traits between EA and AA populations, with possible implications for the racial disparity in risk. We tested the above hypothesis using Mendelian randomization (MR), an approach that leverages genetic determinants of specific traits (i.e. WBC counts) to estimate their effects on the risk of an outcome; and a transcriptome-wide association study (TWAS), which utilizes genetic predictors of gene expression to identify susceptibility genes. These analytic approaches were applied to data from the African American Multiple Myeloma Study (AAMMS) consisting of 1813 cases and 8871 AA cancer-free controls to examine how differences in heritable WBC gene expression profiles influence MM risk. Genetic determinants of variation in WBC subsets in AA were obtained from the literature and supplemented with new genome-wide association findings in AA subjects from the UK Biobank cohort (n=6108). Odds ratios (OR) for MM per 1 standard deviation (SD) increase in each WBC phenotype were estimated using independent (linkage disequilibrium (LD) r2<0.10) variants with P<10-6 as genetic instruments. Analyses based on variants associated with WBC traits in AA populations did not identify any statistically-significant associations between MM risk and WBC overall (p=0.81, using 15 SNPs) or subsets (lymphocytes, monocytes, eosinophils, neutrophils and basophils, p>0.05 for each). However, when we applied genetic determinants of WBC identified in 330,000 cancer-free EA UK Biobank participants (P<10-8, replication P<0.05, LD r2<0.05), a statistically significant inverse relationship emerged between increasing lymphocyte counts and MM risk (OR=0.80, 95% CI: 0.66-0.97, p=0.02, using 385 SNPs), as well as increasing basophil counts (OR=0.63, 95% CI: 0.41-0.96, p=0.03, using 140 SNPs). Next, we examined the association between WBC gene expression profiles and MM risk in AAMMS data. We applied published and validated ancestry-specific models developed using the PrediXcan approach, which leverage germline genetic and transcriptomic data from the Multi-Ethnic Study of Atherosclerosis (MESA) (Mogil et al. PMID: 30096133). The primary TWAS used gene expression models trained in AA subjects (n=233), with sensitivity analyses using models developed in AA and Hispanic subjects (n=585). The TWAS significance threshold was based on the number of genes with significant germline prediction models (p<0.05 and R2 ≥0.05) in AA, corresponding to P < 0.05/2700 = 1.85×10-5. The expression of two genes was significantly associated with MM risk: KANK1at 9p24.3 (P = 1.01×10-5) and DNAJC27at 2p23.3 (P = 1.56×10-5). KANK1is a candidate tumor suppressor gene for renal cell carcinoma and has recently been associated with MM risk in AA [Du, Blood 2017 130:3058]. Here we provide additional evidence for its role in MM etiology via gene expression-mediated mechanisms. DNAJC27 (previously known as RBJ) is a novel MM risk gene linked to constitutive activation of ERK in solid tumors. We also identified two suggestively associated genes: PRR14 (P = 1.34×10-4; combined AA-Hispanic sample: P = 1.56×10-6), which has been linked to MM risk in EA populations, and PARP16 (P = 9.46×10-5). To our knowledge this is the first study to comprehensively examine variation in WBC traits and gene expression profiles with respect to MM risk in AA. Our TWAS analysis leveraged data from the largest collection of genetic and gene expression data in AA, enabling ancestry-matched inference and identification of two novel risk genes. Although the limited availability of genetic instruments for WBC limited the power of MR analysis, findings using variants identified in European populations may offer some insight into trans-ethnic etiologic pathways and contribute to risk stratification strategies using genetic and blood cell count biomarkers. Future studies, particularly with MGUS-free controls, are needed to validate these results. Disclosures Song: Millennium Pharmaceuticals Inc: Employment. Rand:Ancestry.com: Employment. Ailawadhi:Cellectar: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy; Pharmacyclics: Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy. Nooka:Takeda: Honoraria, Other: advisory board participation; Janssen: Honoraria, Other: advisory board participation; GSK: Honoraria, Other: advisory board participation; Spectrum pharmaceuticals: Honoraria, Other: advisory board participation; Adaptive technologies: Honoraria, Other: advisory board participation; Amgen: Honoraria, Other: advisory board participation; Celgene: Honoraria, Other: advisory board participation; BMS: Honoraria, Other: advisory board participation. Singhal:Bureau of Millennium/Takeda, Celgene, Janssen, Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. van Rhee:Takeda: Consultancy; Sanofi Genzyme: Consultancy; Castleman Disease Collaborative Network: Consultancy; EUSA: Consultancy; Adicet Bio: Consultancy; Kite Pharma: Consultancy; Karyopharm Therapeutics: Consultancy. Mehta:Millennium/Takeda, Celgene; stock in Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. Wolf:Takeda: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Janssen: Consultancy; Amgen: Consultancy. Martin:Roche and Juno: Consultancy; Amgen, Sanofi, Seattle Genetics: Research Funding. Fiala:Incyte: Research Funding. Terebelo:Jannsen: Speakers Bureau; Celgene: Honoraria; Newland Medical Asociates: Employment. Anderson:Bristol-Myers Squibb: Other: Scientific Founder; Oncopep: Other: Scientific Founder; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Sanofi-Aventis: Other: Advisory Board. Vij:Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Genentech: Honoraria; Janssen: Honoraria; Karyopharm: Honoraria; Sanofi: Honoraria; Takeda: Honoraria, Research Funding. Bernal-Mizrachi:TAKEDA: Research Funding; Kodikas Therapeutic Solutions, Inc: Equity Ownership; Winship Cancer Institute: Employment, Patents & Royalties. Morgan:Amgen, Roche, Abbvie, Takeda, Celgene, Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Other: research grant, Research Funding. Zonder:Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Intellia: Consultancy, Membership on an entity's Board of Directors or advisory committees; Caelum: Consultancy, Membership on an entity's Board of Directors or advisory committees; Alnylam: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees. Huff:Member of Safety Monitoring Board for Johnson and Johnson: Membership on an entity's Board of Directors or advisory committees; Karyopharm, Sanofi, MiDiagnostics: Consultancy. Lonial:Karyopharm: Consultancy; Takeda: Consultancy, Research Funding; Amgen: Consultancy; BMS: Consultancy; Janssen: Consultancy, Research Funding; GSK: Consultancy; Celgene Corporation: Consultancy, Research Funding; Genentech: Consultancy. Orlowski:Poseida Therapeutics, Inc.: 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.

AbstractBackgroundThe Surveillance, Epidemiology, and End Results (SEER) database and National Cancer Database (NCDB) show improved overall survival (OS) in patients with multiple myeloma (MM) over the last 15 years. This analysis evaluated the validity of the largely community‐based Connect MM Registry as a national reference for MM.MethodsBaseline disease characteristics and survival in US newly diagnosed MM patients were examined using the Connect MM Registry as well as SEER and NCDB databases. Baseline characteristics predictive of longer survival in Connect MM were also identified.ResultsAs of February 2017, 3011 patients were enrolled in the Connect MM Registry; 2912 were treated. Median age at time of MM diagnosis and age range were numerically similar from 2010 to 2015 across all 3 registries; SEER had a higher representation of nonwhite racial groups than that in the other 2 registries. OS rates suggest proportionate improvement with year of diagnosis among the 3 registries. A Cox proportional hazards model suggests that younger age (<65 years) is associated with longer survival (vs ≥75; HR, 0.39; 95% confidence interval, 0.34‐0.46) in the Connect MM Registry. However, sex (HR, 0.91; P = .15) and race (black vs white; HR, 0.88; P = .21) were not associated with longer OS.ConclusionsData from the Connect MM Registry appear to be largely representative of national trends, comprehensive, and reliable representations of the national MM population. Baseline characteristics were comparable, and survival similarly improved over time among the 3 registries.ClinicalTrials.gov, identifierNCT01081028.