Citations

Introduction: Advances in the understanding of disease biology, the introduction of new drugs, and better supportive care have improved outcomes in multiple myeloma (MM). Most improvements have been observed in clinical trial and tertiary referral center populations but questions remain about the generalizability of these findings to patients treated in the community. Methods: We studied all patients diagnosed with MM between 01/01/2001 and 12/31/2015 who had complete demographic and overall survival (OS) data available and were seen at Mayo Clinic (MAYO) or followed in the Surveillance, Epidemiology, and End Results Program (SEER, 18 registry data 2000 - 2016, 11/2018 submission). We retrieved age at diagnosis, sex, date of diagnosis, date of last follow-up, and OS for all patients. OS was defined as the time from diagnosis to death from any cause. Patients who were alive at the end of follow-up (12/31/ 2016) were censored. OS estimates were calculated using the Kaplan-Meier method. Age- and sex-adjusted Cox models were used to assess the association between the 5-year interval of diagnosis and OS. Expected OS estimates were calculated based on United States general population rate tables (Human Mortality Database) using a conditional approach. Standardized mortality ratios (SMR) were calculated by dividing the number of observed deaths by the number of expected deaths in age- and sex-matched general United States population controls. Linear regression models were fit to test for linear trends in early mortality and SMR over time (per 5-year interval). P-values below 0.05 were considered statistically significant. Results: The median age at diagnosis was 3 years lower in patients at MAYO (64 years, 15% ≥ 75 years, 60% male, n = 3293) compared to SEER (67 years, 29% ≥ 75 years, 55% male, n = 61779). After a median follow-up of 2.8 years the median OS was longer in MAYO compared to SEER (5.4 versus 4.0 years, HR 0.82, 95% CI 0.78 - 0.86, p < 0.001) and remained statistically significant after adjusting for age and sex (HR 0.91, 95% CI 0.86 - 0.95, p < 0.001). Early mortality (1-year mortality) decreased between 2001-2005 and 2011-2015: From 20% to 11% at MAYO and from 26% to 19% in SEER. When grouping OS by year of diagnosis (in 5-year-intervals) improvements were seen in both populations (A) and remained statistically significant after adjusting for age and sex. The relative improvements were similar comparing the 5-year period after the introduction of the novel therapies (2006 - 2010) to 2001 - 2005 and more pronounced in MAYO for the most recent 5-year interval (2011 - 2015, A). This trend was reflected in a steady temporal improvement in 5-year OS estimates in MAYO including the most recent 5-year interval (2011 - 2015, B bottom left). In SEER there was a comparable increase between the first two 5-year intervals but a lesser improvement in more recently (2011 - 2015, B bottom left). A diagnosis of MM remained associated with significant excess mortality in all age groups over time in both populations (B top). There was a decrease in excess mortality over time at MAYO (SMR decline per 5-year interval 1.3, 95% CI 0.9 - 1.8, p < 0.001) while there was little change in SEER (SMR decline 0.0, 95% CI -0.3 - 0.3, p = 0.917, B bottom right). Further stratifying by age at diagnosis, the decrease in excess mortality was observed mostly in patients < 75 years at MAYO (SMR decline per 5-year interval 1.7, 95% CI 1.5 - 2.0, p < 0.001, C bottom left) and to a lesser extent in older patients (SMR decline 0.4, 95% CI 0.2 - 0.6, p < 0.001, C bottom right). No such trends towards improvement were observed in either age group in SEER (C bottom). In older patients, early mortality remained approximately 30% in both populations despite continued improvements, while the 5-year OS estimates for the most recent 5-year interval (2011 - 2015) were 37% at MAYO and 26% in SEER (C top). Conclusions: Both early mortality and long-term survival have improved over time. Reductions in excess mortality were largely confined to younger patients with access to specialized care. Patients ≥ 75 years represent more than a quarter of all patients in the community, a third of them died within one year of the diagnosis, and only one in four was alive five years later. Older patients with MM remain a vulnerable population and have derived only limited benefit from recent advances in the field. Safe and effective therapies for older patients with MM remain an unmet need. Figure Disclosures Gertz: Ionis/Akcea: Consultancy; International Waldenstrom Foundation: Research Funding; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Research to Practice: Consultancy; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Other: Development of educational programs and materials; Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding. Dispenzieri:Alnylam: Research Funding; Akcea: Consultancy; Takeda: Research Funding; Pfizer: Research Funding; Janssen: Consultancy; Intellia: Consultancy; Celgene: Research Funding. Lacy:Celgene: Research Funding. Maurer:Nanostring: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Kapoor:Takeda: Honoraria, Research Funding; Celgene: Honoraria; Janssen: Research Funding; Amgen: Research Funding; Sanofi: Consultancy, Research Funding; Glaxo Smith Kline: Research Funding; Cellectar: Consultancy. Leung:Takeda: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; Aduro: Membership on an entity's Board of Directors or advisory committees; Omeros: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

6 Background: Rates and survival outcomes for second-line therapy for mCRC for OA vs. YA are poorly understood. Methods: Pts with available subsequent treatment data after progression from 10 1st line trials were included. Associations between key clinical/disease characteristics, time to initial progression (TTiP) and rate of receipt of second-line therapy were evaluated. Time to progression (TTP) and overall survival (OS) were compared between OA and YA who were enrolled on second-line trials by Cox regression, adjusting for age, sex, ECOG PS, number of metastatic sites, presence of metastasis in lung/liver/peritoneum. Results: OA comprised 16.4% of first-line trials. OA and ECOG PS >0 were less likely to receive second-line therapy than YA. Odds of receiving second-line therapy decreased by 11% for each additional decade of life in multivariate analysis (p=0.0117). OA enrolled in second-line trials experience similar mTTP and mOS as YA (5.1 vs. 5.2mos; 11.6 vs 12.4mos, respectively). Conclusions: OA are less likely to receive 2nd line therapy for mCRC. We did not observe a statistical difference in survival outcomes for OA vs. YA following second-line therapy. Further study is needed to examine unmeasured factors, including comorbidity and functional status given observed inferior outcomes among adults with ECOG PS >0, and consideration given to inclusion of geriatric assessment to select OA likely to benefit from 2nd line therapy for mCRC. [Table: see text]

AbstractOur prior studies identified the prognostic significance of quantifying cPCs by multiparametric flow cytometry (MFC) in newly diagnosed multiple myeloma (NDMM) patients. We evaluated if a similar quantification of cPCs could add prognostic value to the current R‐ISS classification of 556 consecutive NDMM patients seen at the Mayo Clinic, Rochester from 2009 to 2017. Those patients that had ≥5 cPCs/μL and either R‐ISS stage I or stage II disease were re‐classified as R‐ISS IIB stage for the purposes of this study. The median time to next therapy (TTNT) and overall survival (OS) for patients with ≥5 cPCs/μL at diagnosis was as follows: R‐ISS I (N = 110) ‐ 40 months and not reached; R‐ISS II (N = 69) ‐ 30 and 72 months; R‐ISS IIB (N = 96) ‐ 21 and 45 months and R‐ISS III (N = 281) ‐ 20 and 47 months respectively. Finally, ≥ 5 cPCs/μL retained its adverse prognostic significance in a multivariable model for TTNT and OS. Hence, quantifying cPCs by MFC can potentially enhance the R‐ISS classification of a subset of NDMM patients with stage I and II disease by identifying those patients with a worse than expected survival outcome.

AbstractBackgroundProstate‐specific membrane antigen (PSMA) is a well‐established therapeutic and diagnostic target overexpressed in both primary and metastatic prostate cancers. PSMA antibody‐drug conjugate (PSMA ADC) is a fully human immunoglobulin G1 anti‐PSMA monoclonal antibody conjugated to monomethylauristatin E, which binds to PSMA‐positive cells and induces cytotoxicity. In a phase 1 study, PSMA ADC was well tolerated and demonstrated activity as measured by reductions in serum prostate‐specific antigen (PSA) and circulating tumor cells (CTCs). To further assess PSMA ADC, we conducted a phase 2 trial in metastatic castration‐resistant prostate cancer (mCRPC) subjects who progressed following abiraterone/enzalutamide (abi/enz) therapy.MethodsA total of 119 (84 chemotherapy‐experienced and 35 chemotherapy‐naïve) subjects were administered PSMA ADC 2.5 or 2.3 mg/kg IV q3w for up to eight cycles. Antitumor activity (best percentage declines in PSA and CTCs from baseline and tumor responses through radiological imaging), exploratory biomarkers, and safety (monitoring of adverse events [AEs], clinical laboratory tests, and Eastern Cooperative Oncology Group performance status) were assessed.ResultsPSA declines ≥50% occurred in 14% of all treated (n = 113) and 21% of chemotherapy‐naïve subjects (n = 34). CTC declines ≥50% were seen in 78% of all treated (n = 77; number of subjects with ≥5 CTCs at baseline and a posttreatment result) and 89% of chemotherapy‐naïve subjects (n = 19); 47% of all treated and 53% of chemotherapy‐naïve subjects had a transition from ≥5 to less than 5 CTCs/7.5 mL blood at some point during the study. PSA and CTC reductions were associated with high PSMA expression (CTCs or tumor tissue) and low neuroendocrine serum markers. In the chemotherapy‐experienced group, the best overall radiologic response to PSMA ADC treatment was stable disease in 51 (60.7%) subjects; 5.7% of subjects in the chemotherapy‐naïve group had partial responses. The most common treatment‐related AEs ≥Common Terminology Criteria for AE (CTCAE) grade 3 were neutropenia, fatigue, electrolyte imbalance, anemia, and neuropathy. The most common serious AEs were dehydration, hyponatremia, febrile neutropenia, and constipation. Two subjects who received 2.5 mg/kg died of sepsis.ConclusionsPSMA ADC demonstrated some activity with respect to PSA declines, CTC conversions/reductions, and radiologic assessments in abi/enz treated mCRPC subjects. Clinically significant treatment‐related AEs included neutropenia and neuropathy.

Abstract Acute myeloid leukemia (AML) is challenging to treat with antigen-specific immunotherapy due to the lack of leukemia-specific surface antigens that are absent from normal hematopoiesis. We propose a novel solution to this problem by removing CD33, an AML-associated antigen, from normal hematopoietic stem and progenitor cells (HSPCs) by gene editing, thus rendering them resistant to CD33-targeted therapy. This enables powerful CD33-directed immunotherapy such as chimeric antigen receptor T cells (CAR T cells) to be employed against AML without disrupting normal myeloid function. We developed an optimized protocol to generate CD33 KO HSPCs with CRISPR/Cas9 and obtained up to 90% CD33 KO in primary human CD34+ cells as confirmed by flow cytometry and DNA sequencing. To test whether CD33 KO HSPCs retained multilineage potential, we engrafted NSG mice with CD34+ cells treated with Cas9 and either a CD33-targeting gRNA or a control gRNA. CD33 KO HSPCs were able to engraft and differentiate into both lymphoid and myeloid lineages in the mice to the same degree as controls. Human myeloid cells in the peripheral blood (PB) of the CD33 KO-engrafted mice were deficient for CD33, consistent with the KO efficiency measured in vitro, while expression of other myeloid markers such as CD11b and CD14 were similar to controls (Figure 1A, B). To ensure that long-term repopulating stem cells were present in the CD33 KO HSPCs, we performed secondary transplants of bone marrow from mice after four months of primary engraftment. Persistent engraftment for up to three additional months was observed in both CD33 KO HSPCs and controls, proving that gene editing with CRISPR/Cas9 and the resulting CD33 KO does not affect the self-renewal capability of human hematopoietic stem cells. To determine whether CD33 loss would lead to any functional defects in the myeloid progeny, we investigated the properties of myeloid cells derived from CD33 KO HSPCs differentiated with SCF, GM-CSF, G-CSF, IL-3, IL-6 and EPO. Cell morphology and immunophenotype of the myeloid cells after in vitro differentiation were consistent with normal neutrophils and macrophages. Phagocytosis ability, as measured by uptake of E. coli particles, was identical in CD33 KO myeloid cells as compared to controls. CD33 KO myeloid cells were also able to secrete inflammatory cytokines (IL-1b, IL-8, IL-8, IL-10, IL-12, TNF) in response to LPS stimulation to the same degree as controls. RNA-seq showed a highly concordant gene expression profile of CD33 KO HSPCs and controls (R2=0.99), thus excluding any major impact of CD33 loss on downstream gene expression. Prior studies have shown that CAR T cells targeting CD33 (CART33) can eliminate AML in mouse models but also cause toxicity to normal HSPCs (Kenderian et al, Leukemia 2015). To test our hypothesis that CD33 KO HSPCs can evade CART33-mediated toxicity, we treated mice engrafted with either control or CD33 KO HSPCs with CART33. CD33-expressing cells were eliminated in both control and CD33 KO-engrafted mice, which led to the expected myeloablation in control mice; in contrast CD33 KO-engrafted mice continued to sustain human myeloid cells (Figure 2A). Bone marrow (BM) analysis showed significantly more human stem cells (CD34+38-) and myeloid progenitors (CD34+38+) in CD33 KO-engrafted mice compared to controls after CART33 treatment (Figure 2B). We then proceeded to engraft Molm14, an AML cell line that was engineered to express luciferase, into mice bearing control or CD33 KO hematopoiesis, and studied the effect of CART33 treatment in this model. As expected, AML was eliminated in both groups as measured by bioluminescent imaging (BLI) (Figure 2C), as were peripheral blood monocytes in the control group, while monocytes were still present in the CD33 KO-engrafted mice (Figure 2D). In conclusion, we show that CD33 is dispensable in hematopoietic differentiation, and that absence of CD33 from myeloid progeny does not cause any discernible functional changes. Gene editing to remove CD33 from normal HSPCs allows persistent myelopoiesis during CART33-mediated eradication of AML, thus paving the way to a novel system that maximizes efficacy while minimizing toxicity. We envision future clinical translation of this approach by administering CD33 KO HSPCs as an allogeneic stem cell transplant in combination with CART33 in patients with AML. Disclosures Kenderian: Novartis: Patents & Royalties, Research Funding. Ruella:Novartis: Patents & Royalties. Gill:Novartis: Patents & Royalties, Research Funding.

BACKGROUND: pPCL is a rare and aggressive form of multiple myeloma (MM) with poor survival outcomes compared to that experienced by MM patients. It has been traditionally defined by the presence of an absolute plasma cell count of > 2000/microL or >20% circulating plasma cells (cPCs) in the peripheral blood. However, several recent studies have validated the optimal cutoff for defining pPCL to be >5% cPCs on a peripheral blood smear due to equally poor outcomes in this less restrictive cohort. Hence, given the rarity of this disease entity, we evaluated the clinical outcomes and cytogenetic features of patients diagnosed with pPCL at our institution with the new proposed definition of pPCL by >5% cPCs on peripheral blood smear that were treated with novel agent induction therapies. METHODS: We evaluated all patients with pPCL diagnosed between 2000 - 2018 evaluated at Mayo Clinic in Rochester, Minnesota. Data regarding these patients were extracted from a prospectively maintained database and from the review of the electronic medical records. Patients were categorized as having high risk cytogenetics if any of the following abnormalities were present: del 17p, t(4;14), t(14;16) or t(14;20). Chi-square tests and Fisher exact tests were used to compare differences between the sub-groups of interest. Survival analysis was performed by the Kaplan-Meier method and differences assessed using the log rank test. RESULTS: This cohort consisted of 71 patients with pPCL with a median age of 62 years (range: 34-91) of which 33 (46%) were male. The median follow up was 46 months (95% CI: 41 - 90). The median bone marrow plasma cell content was 84% (Range: 10 - 100) and the median plasma cell percentage on the peripheral smear was 23% (range: 5 - 93). There were 48 (68%) patients with >20% cPCs in their peripheral blood smear. Only 23 (32%) patients had concurrent information on the number of cPCs by multiparametric flow cytometry at diagnosis and the median number of cPCs detected was 32,807 per 150,000 events analyzed (Range: 354 - 132,256). There were 15/54 (28%) patients who presented with a creatinine of 2 mg/dL or greater and 17/55 (31%) pts who presented with hypercalcemia (11 mg/dL or greater). Data for ISS classification was available in 45 patients and is as follows: Stage 1- 3 (7%) patients, Stage 2- 10 (22%) patients and Stage 3- 32 (71%) patients. Data on the presence of primary cytogenetic abnormalities were available in 60 (85%) patients of which 29 (49%) had high risk cytogenetics. The distribution of primary cytogenetic abnormalities among this cohort was as follows: t(11;14) - 27 (45%), t(4;14) - 5 (8%), t(14;16) - 8 (13%), t(14;20)- 3(5%) and del 17p- 15(25%). All patients received novel agent induction therapy with 40 (57%) of them having received at least one autologous stem cell transplant and 1 patient undergoing an allogeneic stem cell transplant. The median overall survival (OS) for all pPCL patients in this cohort was 23 months (95% CI: 19 - 38). The OS was similar in patient with 5-19% cPCs vs. >20% cPCs (24 vs. 23 months, P = 0.999). However, when the entire cohort was stratified by cytogenetic risk, the median OS was 51 months for standard risk vs. 19 months for high risk (P = 0.005) (FIGURE). There were only 17 (30%) patients in this cohort who were alive for 48 months or longer since diagnosis (i.e. twice the median OS of this cohort) and they were more likely to not have high risk cytogenetics at diagnosis (P = 0.05). CONCLUSION: In this analysis of one of the largest contemporary cohorts of pPCL patients, the outcomes of patients diagnosed with pPCL remain poor despite the use of novel agent induction therapy. However, some patients appear to do better than expected and this phenomenon may be influenced by the absence of high risk cytogenetics. Disclosures Kumar: Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Dingli:Karyopharm: Research Funding; Rigel: Consultancy; Millenium: Consultancy; Janssen: Consultancy; alexion: Consultancy. Lacy:Celgene: Research Funding. Kapoor:Glaxo Smith Kline: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Cellectar: Consultancy; Celgene: Honoraria; Janssen: Research Funding. Russell:Imanis: Equity Ownership. Leung:Omeros: Research Funding; Takeda: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; Aduro: Membership on an entity's Board of Directors or advisory committees. Gertz:Celgene: Consultancy; Prothena Biosciences Inc: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding; Janssen: Consultancy; Ionis/Akcea: Consultancy; Alnylam: Consultancy; Annexon: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Research to Practice: Consultancy; Teva: Speakers Bureau; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Spectrum: Consultancy, Research Funding; i3Health: Other: Development of educational programs and materials; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau.

M.T.J. and M.D.J. contributed equally; A.G. and F.L.L. contributed equally. Introduction Axicabtagene ciloleucel (axi-cel) is an autologous anti-CD19 CAR T-cell therapy that is approved for the treatment of adults with relapsed or refractory large B-cell lymphoma (LBCL) who have failed at least two prior systemic lines of therapy. In the ZUMA-1 trial that led to axi-cel approval, 93% of patients developed cytokine release syndrome (CRS) (Neelapu, Locke et al. NEJM 2018). CRS is a non-antigen-specific toxicity that occurs as a result of CAR T and bystander immune cell activation. Whether lack of development of CRS after treatment with axi-cel is associated with inferior lymphoma outcomes is unknown. Here we evaluate the outcomes of patients that did not develop CRS after receiving axi-cel in a large multicenter cohort. Methods and Results The US Lymphoma CAR T Consortium includes seventeen US academic centers that contribute data independently of manufacturers. As of 8/31/2018, 300 patients were apheresed with intent to manufacture standard of care axi-cel for LBCL. In this study, we analyzed the modified intent-to-treat (mITT) population of 276 patients receiving CAR T infusion with a median follow up of 9 months. In this group, 25 patients (9%) did not develop CRS and 251 patients (91%) developed CRS following axi-cel infusion. CRS was graded according to Lee criteria (Lee et al. Blood 2014) or CARTOX (Neelapu SS et al. Nat Rev Clin Oncol. 2018). At baseline, a higher proportion of patients in the no CRS group had ECOG score of 0-1 (no CRS group 100% vs. CRS group 82%, p= 0.019) and IPI score of 0-2 (no CRS group 72% vs. CRS group 46%, p = 0.019) After CAR T cell infusion, patients who did not develop CRS had a lower chance of developing grade 3 or higher neurotoxicity (no CRS group 4% vs. CRS group 35%, p=0.001), lower rates of ICU admission (no CRS group 8% vs. CRS group 35%, p = 0.006), and shorter length of hospital stay (median 10 days for no CRS group vs 14 days for CRS group, p < 0.001). Of the 25 patients who had grade 0 CRS, 23 (92%%) also had grade 0 neurotoxicity. In univariate analysis, no CRS was associated with lower complete response (CR) rate (no CRS group 40% vs. CRS group 66%, p=0.015) but no statistically significant difference in overall response rate (ORR) (no CRS group 72% vs. CRS group 84%, p= 0.158). In relation to CRS there was no difference in treatment related mortality among the two groups (CRS group 4% vs. no CRS group 4.4%, p = 0.85). In multivariate analysis correcting for confounding features, no CRS was associated with statistically significant lower complete response rate (p = 0.002), but there was no significant difference in ORR (p = 0.13), overall survival (P=0.15), progression free survival (P=0.16), and time to progression (P= 0.14) between the two groups (figure 1.). Conclusions In this large cohort of LBCL patients receiving axi-cel with median follow up of 9 months, patients that did not develop CRS, compared with those that developed CRS, achieved lower rates of complete response but there was no difference in overall response rate, progression free survival, time to progression, overall survival, and treatment related mortality between the two groups. Disclosures Jain: Kite/Gilead: Consultancy. Nastoupil:Bayer: Honoraria; TG Therapeutics: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Genentech, Inc.: Honoraria, Research Funding; Gilead: Honoraria; Janssen: Honoraria, Research Funding; Novartis: Honoraria; Spectrum: Honoraria. Lunning:Spectrum: Consultancy; Seattle Genetics: Consultancy; Portola: Consultancy; OncLive: Consultancy; Novartis: Consultancy; Kite: Consultancy; Gilead Sciences, Inc.: Consultancy; DAVA: Consultancy; Bayer: Consultancy; AbbVie: Consultancy; TG Therapeutics: Consultancy, Research Funding; MiRagen: Research Funding; Juno Therapeutics: Consultancy, Research Funding; Janssen Scientific Affairs, LLC: Consultancy, Research Funding; Curis: Research Funding; VANIUM: Consultancy; Verastem: Consultancy. Reagan:Kite, A Gilead Company: Consultancy; Curis: Consultancy; Seattle Genetics: Research Funding. Oluwole:Pfizer: Consultancy; Spectrum: Consultancy; Gilead Sciences: Consultancy; Bayer: Consultancy. McGuirk:Novartis: Research Funding; Kite Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Gamida Cell: Research Funding; Pluristem Ltd: Research Funding; ArticulateScience LLC: Other: Assistance with manuscript preparation; Juno Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bellicum Pharmaceuticals: Research Funding; Fresenius Biotech: Research Funding; Astellas: Research Funding. Deol:Agios: Other: Advisory board; Novartis: Other: Advisory board; Kite: Other: Advisory board. Sehgal:Juno/Celgene: Research Funding; Merck: Research Funding; Kite/Gilead: Research Funding. Goy:Acerta: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants outside of the submitted work, Research Funding; University of Nebraska: Research Funding; Astrazenca: 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; Hakensackumc: Research Funding; Hackensack University Medical Center, RCCA: Employment; Kite, a Gilead Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants outside of the submitted work; Takeda: Other: Grants outside of the submitted work; COTA: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Other: leadership role for profit healthcare company; Pharmacyclics/Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants outside of the submitted work, Research Funding; Genentech: Other: Grants outside of the submitted work, Research Funding. Hill:Kite: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celegene: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Research Funding; TG therapeutics: Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Research Funding. Andreadis:Juno: Research Funding; Celgene: Research Funding; Novartis: Research Funding; Roche: Equity Ownership; Jazz Pharmaceuticals: Consultancy; Kite: Consultancy; Gilead: Consultancy; Genentech: Consultancy, Employment; Pharmacyclics: Research Funding; Merck: Research Funding. Munoz:Incyte: Research Funding; Portola: Research Funding; AstraZeneca: Speakers Bureau; Fosunkite: Speakers Bureau; Pfizer: Consultancy; Alexion: Consultancy; Bristol-Myers Squibb: Consultancy; Pharmacyclics /Janssen: Consultancy, Research Funding, Speakers Bureau; Bayer: Consultancy, Speakers Bureau; Merck: Consultancy; Kyowa: Consultancy, Honoraria, Speakers Bureau; Seattle Genetics: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene/Juno: Consultancy, Research Funding; Genentech: Consultancy, Research Funding, Speakers Bureau; Kite/Gilead: Consultancy, Research Funding, Speakers Bureau. Chavez:Janssen Pharmaceuticals, Inc.: Speakers Bureau; Genentech: Speakers Bureau; Kite Pharmaceuticals, Inc.: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Bennani:Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Adicet Bio: Other: Advisory board; Adicet Bio: Other: Advisory board; Adicet Bio: Other: Advisory board; Kite Pharma: Other: Advisory board; Kite Pharma: Other: Advisory board; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Purdue Pharma: Other: Advisory board. Vose:Acerta Pharma: Honoraria, Other: Grants, Research Funding; Bristol-Meyers Squibb Company: Research Funding; Celgene Corporation: Research Funding; Incyte Corporation: Research Funding; Kite Pharma: Honoraria, Other: Grants, Research Funding; Novartis: Research Funding; Seattle Genetics: Research Funding; AbbVie: Consultancy, Honoraria; Epizyme: Consultancy, Honoraria; Legend Pharmaceuticals: Honoraria. Miklos:Becton Dickinson: Research Funding; Miltenyi Biotech: Membership on an entity's Board of Directors or advisory committees; AlloGene: Membership on an entity's Board of Directors or advisory committees; Precision Bioscience: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Kite-Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Neelapu:Poseida: Research Funding; Cellectis: Research Funding; Precision Biosciences: Consultancy; Cell Medica: Consultancy; Novartis: Consultancy; Incyte: Consultancy; Celgene: Consultancy, Research Funding; Allogene: Consultancy; Acerta: Research Funding; Unum Therapeutics: Consultancy, Research Funding; Pfizer: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding; BMS: Research Funding; Merck: Consultancy, Research Funding; Karus: Research Funding. Ghobadi:Wugen: Consultancy; Celgene: Consultancy; EUSA: Consultancy; Kite Pharma a Gilead Company: Consultancy, Research Funding, Speakers Bureau. Locke:Novartis: Other: Scientific Advisor; Cellular BioMedicine Group Inc.: Consultancy; Kite: Other: Scientific Advisor.

Introduction: Abnormal metaphase cytogenetics are associated with inferior survival in newly diagnosed multiple myeloma (MM). These abnormalities are only detected in one third of cases due to the low proliferative rate of plasma cells. It is unknown if metaphase cytogenetics improve risk stratification when using contemporary prognostic models such as the revised international staging system (R-ISS), which incorporates interphase fluorescence in situ hybridization (FISH). Aims: The aims of this study were to 1) characterize the association between abnormalities on metaphase cytogenetics and overall survival (OS) in newly diagnosed MM treated with novel agents and 2) evaluate whether the addition of metaphase cytogenetics to R-ISS, age, and plasma cell labeling index (PCLI) improves model discrimination with respect to OS. Methods: We analyzed a retrospective cohort of 483 newly diagnosed MM patients treated with proteasome inhibitors (PI) and/or immunomodulators (IMID) who had metaphase cytogenetics performed prior to initiation of therapy. Abnormal metaphase cytogenetics were defined as MM specific abnormalities, while normal metaphase cytogenetics included constitutional cytogenetic variants, age-related Y chromosome loss, and normal metaphase karyotypes. Multivariable adjusted proportional hazards regression models were fit for the association between known prognostic factors and OS. Covariates associated with inferior OS on multivariable analysis included R-ISS stage, age ≥ 70, PCLI ≥ 2, and abnormal metaphase cytogenetics. We devised a risk scoring system weighted by their respective hazard ratios (R-ISS II +1, R-ISS III + 2, age ≥ 70 +2, PCLI ≥ 2 +1, metaphase cytogenetic abnormalities + 1). Low (LR), intermediate (IR), and high risk (HR) groups were established based on risk scores of 0-1, 2-3, and 4-5 in modeling without metaphase cytogenetics, and scores of 0-1, 2-3, and 4-6 in modeling incorporating metaphase cytogenetics, respectively. Survival estimates were calculated using the Kaplan-Meier method. Survival analysis was stratified by LR, IR, and HR groups in models 1) excluding metaphase cytogenetics 2) including metaphase cytogenetics and 3) including metaphase cytogenetics, with IR stratified by presence and absence of metaphase cytogenetic abnormalities. Survival estimates were compared between groups using the log-rank test. Harrell's C was used to compare the predictive power of risk modeling with and without metaphase cytogenetics. Results: Median age at diagnosis was 66 (31-95), 281 patients (58%) were men, median follow up was 5.5 years (0.04-14.4), and median OS was 6.4 years (95% CI 5.7-6.8). Ninety-seven patients (20%) were R-ISS stage I, 318 (66%) stage II, and 68 (14%) stage III. One-hundred and fourteen patients (24%) had high-risk abnormalities by FISH, and 115 (24%) had abnormal metaphase cytogenetics. Three-hundred and thirteen patients (65%) received an IMID, 119 (25%) a PI, 51 (10%) received IMID and PI, and 137 (28%) underwent upfront autologous hematopoietic stem cell transplantation (ASCT). On multivariable analysis, R-ISS (HR 1.59, 95% CI 1.29-1.97, p < 0.001), age ≥ 70 (HR 2.32, 95% CI 1.83-2.93, p < 0.001), PCLI ≥ 2, (HR 1.52, 95% CI 1.16-2.00, p=0.002) and abnormalities on metaphase cytogenetics (HR 1.35, 95% CI 1.05-1.75, p=0.019) were associated with inferior OS. IR and HR groups experienced significantly worse survival compared to LR groups in models excluding (Figure 1A) and including (Figure 1B) the effect of metaphase cytogenetics (p < 0.001 for all comparisons). However, the inclusion of metaphase cytogenetics did not improve discrimination. Likewise, subgroup analysis of IR patients by the presence or absence of metaphase cytogenetic abnormalities did not improve risk stratification (Figure 1C) (p < 0.001). The addition of metaphase cytogenetics to risk modeling with R-ISS stage, age ≥ 70, and PCLI ≥ 2 did not improve prognostic performance when evaluated by Harrell's C (c=0.636 without cytogenetics, c=0.642 with cytogenetics, absolute difference 0.005, 95% CI 0.002-0.012, p=0.142). Conclusions: Abnormalities on metaphase cytogenetics at diagnosis are associated with inferior OS in MM when accounting for the effects of R-ISS, age, and PCLI. However, the addition of metaphase cytogenetics to prognostic modeling incorporating these covariates did not significantly improve risk stratification. Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Alnylam: Research Funding; Celgene: Research Funding; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding. Kapoor:Celgene: Honoraria; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; Cellectar: Consultancy; Takeda: Honoraria, Research Funding; Amgen: Research Funding; Glaxo Smith Kline: Research Funding. Leung:Prothena: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Omeros: Research Funding; Aduro: Membership on an entity's Board of Directors or advisory committees. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Background: The overall participation of cancer patients in interventional clinical trials in the United States remains very low, with ~5% of patients being enrolled in clinical trials nationwide. The outcomes of patients with MM have improved significantly over the past decade, but available data suggest that the participation rates for patients with MM is comparable to other cancers. The drivers of participation and the potential impact of clinical trial participation have not been systematically studied in MM. Patients and Methods: We identified 228 patients who were enrolled into clinical trials for initial therapy of newly diagnosed MM between 2004 and 2018, and 4 controls for each of these patients. Controls were patients with NDMM, who were diagnosed closest in time to the index patients and did not participate in an interventional treatment trial. Various baseline characteristics as well as overall survival were compared between the two groups. Results: The baseline characteristics of the two groups are as shown in the Table. Patients who entered clinical trials were more likely to be female, resided closer to the clinic, and were more likely to have a prior history of MGUS. They were more likely to have higher ISS Stage, and a higher serum LDH, but there was no difference in the FISH risk status. Other indices of disease burden such as lower hemoglobin and platelets, higher serum creatinine were all seen more often in the control group, but may have been influenced by the trial entry criteria. Looking at the outcomes, the overall survival was longer among those enrolled into clinical trials compared to those who did not [median 103 (95% CI; 86, 136) vs. 63 (95% CI; 53, 69) months, p<0.001 (Figure). Conclusions: The current study provides important clues regarding demographic determinants of trial participation and disease biology related features that reflect likelihood of trial participation. Overall survival was significantly longer among the trial participants, which likely represent a mix of reasons including baseline status of patients, intensity of monitoring and efficacy of novel treatment approaches. Table Disclosures Kapoor: Janssen: Research Funding; Celgene: Honoraria; Cellectar: Consultancy; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Glaxo Smith Kline: Research Funding; Takeda: Honoraria, Research Funding. Dispenzieri:Alnylam: Research Funding; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Akcea: Consultancy; Intellia: Consultancy. Gertz:Ionis: Honoraria; Alnylam: Honoraria; Prothena: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Spectrum: Honoraria, Research Funding. Lacy:Celgene: Research Funding. Dingli:Karyopharm: Research Funding; Rigel: Consultancy; alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy. Leung:Omeros: Research Funding; Aduro: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees. Russell:Imanis: Equity Ownership. Kumar:Takeda: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.