Citations

Introduction: Daratumumab (D) is an anti-CD38 monoclonal antibody, used frequently in combination with immunomodulatory drugs (IMiDs), lenalidomide (Len) and pomalidomide (Pom). There are no studies comparing DRd to DPd in Len-exposed or refractory multiple myeloma (MM). We present the Mayo Clinic experience of DPd and DRd utilization and outcomes. Methods: We identified consecutive MM pts who received D, between 1/2015 and 4/2019 at Mayo Clinic. We included pts who were exposed (at least one full cycle, 21/28 days) or refractory (progression on full dose or maintenance Len during treatment or within 60 days of stopping Len) to Len prior to D and received 1 to 4 prior lines of therapy. Only Pts who received DRd and DPd were included. Results: Out of 411 evaluable pts 162 met the inclusion criteria; 67 were Len exposed, but not refractory and 95 were Len refractory. Pts' characteristics are shown in Table 1. DRd was used in 76 (47%) and DPd in 86 (53%) pts. Majority of pts (105; 65%) received DPd or DRd in the 2nd or 3rd line and 104 pts (64%) are still alive. In Len refractory pts, the median time from last dose of Len to D initiation was 1 mths (interquartile range 0-6.5). Seventy pts (43%) had high-risk cytogenetics (HR). Only 11 pts (7%) underwent autologous hematopoietic cell transplant after DPd or DRd regimen. There was no significant difference between pts who received DRd and DPd in terms of age (>65 years), gender, race, proportion exposed or refractory to Bortezomib, number of prior lines of treatment (>2), or HR status (p>0.05 for all). Pts who received DPd were 4 times more likely to be Len refractory compared to pts who received DRd, p=0.0008. Median follow up time for the whole cohort from initial diagnosis was 92 mths (CI 95%; 79.5-107), while from D start date was 30 mths (CI 95%; 27-34). Median PFS for the whole cohort was 21 mths (CI 95%; 15-25) and median OS was 138 mths (CI 95%; 111-193). In Len exposed but not refractory pts, n=67, the overall response rate (ORR) was 82% in the DRd group compared to 68% in the DPd group, p=0.2. There was no difference in median PFS; 25.5 mths (CI 95%; 23-NR) for DRd compared to 25 mths (CI 95%; 5-NR) for DPd, p=0.37. Similarly, there was no difference in median OS for DRd compared to DPd; NR mths (CI 95%; 138-NR) and 145.5 mths (CI 95%; 70-NR), respectively, p=0.06. In the 48 Len exposed but refractory pts who received DRd or DPd in 2nd or 3rd line, there was no difference in median PFS; 39 mths (CI 95%; 23-NR) for DRd compared to 21 mths (CI 95%; 3-NR) for DPd, p=0.11. Similarly, there was no difference in median OS for DRd compared to DPd; NR mths (CI 95%; NR-NR) and 145.5 mths (CI 95%; 36-NR), respectively, p=0.13. In Len refractory pts only, n=95, the ORR was 84% in the DRd group compared to 58% in the DPd group, p=0.009. There was no difference in median PFS; 25 mths (CI 95%; 13-32) for DRd compared to 9 mths (CI 95%; 5-15) for DPd, p=0.18. Similarly, there was no difference in median OS for DRd compared to DPd; 103 mths (CI 95%; 78-NR) and 106 mths (CI 95%; 66-183), respectively, p=0.5. In the 57 Len refractory pts who received DRd or DPd in 2nd or 3rd line, there was no difference in median PFS; 25 mths (CI 95%; 13-32) for DRd compared to 13 mths (CI 95%; 5-NR) for DPd, p=08. Similarly, there was no difference in median OS for DRd compared to DPd; 103 mths (CI 95%; 69-NR) and 105 mths (CI 95%; 47-NR), respectively, p=0.35. In the 16 Len exposed but not refractory pts with HR MM who received DRd or DPd in 2nd or 3rd line, the median PFS was better in the DRd group; 24.4 mths (CI 95%; 12-NR) compared to 3.3 mths (CI 95%; 1.9-27.5) for DPd, p=0.0093. However, there was no difference in median OS for DRd compared to DPd; NR mths (CI 95%; 51-NR) and NR mths (CI 95%; 18-NR), respectively, p=0.13. In the 29 Len refractory pts with HR MM who received DRd or DPd in 2nd or 3rd line, there was no statistically significant difference in median PFS; 18 mths (CI 95%; 6-43) for DRd compared to 6 mths (CI 95%; 4-13) for DPd, p=0.22.Similarly, there was no difference in median OS for DRd compared to DPd; 103 mths (CI 95%; 47-NR) and 53 mths (CI 95%; 26-105), respectively, p=0.2. Conclusions: D+IMiD regimens after prior Len exposure/refractoriness are commonly used in real-world, despite the lack of data from prospective clinical trials. Combining D with IMiDs in Len exposed or refractory pts is efficacious, whether the IMiD is Len or Pom. Our study shows that regardless of prior Len use, DRd is at least equivalent to DPd. Prospective studies should be done to confirm these observations. Disclosures Alhaj Moustafa: Acrotech: Consultancy. Larsen:Janssen Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Kapoor:Janssen: Research Funding; GlaxoSmithKline: Research Funding; Cellectar: Consultancy; Celgene: Honoraria; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Consultancy, Research Funding. Fonseca:Amgen: Consultancy; BMS: Consultancy; Celgene: Consultancy; Takeda: Consultancy; Bayer: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Merck: Consultancy; Juno: Consultancy; Kite: Consultancy; Aduro: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy; GSK: Consultancy; AbbVie: Consultancy; Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees. Dingli:Karyopharm Therapeutics: Research Funding; Rigel: Consultancy; Bristol Myers Squibb: Research Funding; Millenium: Consultancy; Sanofi-Genzyme: Consultancy; Janssen: Consultancy; Alexion: Consultancy; Apellis: Consultancy. Ailawadhi:Celgene: Honoraria; Amgen: Research Funding; Takeda: Honoraria; Janssen: Research Funding; Pharmacyclics: Research Funding; Cellectar: Research Funding; BMS: Research Funding; Medimmune: Research Funding; Phosplatin: Research Funding.

Background: The combination of a proteasome inhibitor (PI), an immunomodulatory drug (IMiD), and dexamethasone is the current standard induction therapy for myeloma. Daratumumab (Dara), a monoclonal antibody directed against CD38, is highly effective in treating myeloma and improves response rates and progression free survival (PFS) when added to PI or IMiD. Ixazomib, lenalidomide and dexamethasone (IRd) is an effective, all oral, induction regimen that has been studied in phase 2 and 3 trials. We designed this trial to examine the feasibility and efficacy of adding daratumumab to the IRd regimen as well as early discontinuation of dexamethasone in two sequential cohorts of patients. Patients and Methods: Patients with previously untreated MM who had measurable disease and adequate organ function were enrolled, irrespective of their autologous stem cell transplant eligibility. The primary objective was to determine the rate of complete response to IRD-Dara combination. A one-stage binomial design was utilized in each cohort independently to test the null hypothesis that the complete response rate is at most 25% against the alternative hypothesis that it is at least 45%, with 89% power and 9% type I error. Treatment involved 28-day cycles consisting of ixazomib 4 mg days 1, 8, 15; lenalidomide 25 mg days 1-21, dexamethasone 40 mg, weekly and Dara 16 mg/kg, weekly for two cycles, every other week during cycles 3-6 and then every 4 weeks thereafter during induction (12-cyles) followed by Dara-ixazomib maintenance (maximum 24 cycles). Cohorts A (n=38) and B (N=40) comprised the study population, with dexamethasone discontinued after two cycles in Cohort B. Results: Baseline demographics and patient disposition are outlined in the table. Among those who have gone off study, 9 and 5 patients, respectively in Cohort A and B went off for progression, while 11 and 8 patients in the respective arms discontinued treatment for an alternative therapy, most frequently a transplant. Responses were rapid and deepened over the duration of treatment as shown in the figure; 32% of patients in Cohort A and 28% of patients in Cohort B achieved a complete response; 29% and 23%, respectively, achieved a marrow minimal residual disease (MRD) negative status. After a median follow up was 31.4 months for Cohort A and 18.2 months for Cohort B, median PFS has not been reached in either cohort. A grade 3 or higher adverse event at least possibly attributed to the study drugs was seen in 58% of patients in Cohort A (hematologic in 47% and non-hematologic in 26%) and 50% of patients in Cohort B (hematologic 43%, non-hematologic 20%). The most common toxicities included fatigue, neutropenia, lymphopenia, peripheral neuropathy and nausea. Stem cells were collected in 30 and 31 patients in Cohorts A and B respectively; median (range) of CD34 cells/kg were 8.5 (2.8, 15.9) x 106and 7.0 (2.9, 12.1) x 106, with plerixafor used in 83% and 94% of patients, respectively, in Cohorts A and B as per our standard of care "on-demand" approach based on blood CD34 count. Conclusion: Dara-IRd is an active regimen in newly diagnosed MM, with high overall rates of response and deep responses that improved over time with therapy. Early discontinuation of dexamethasone does not appear to impact the depth, rate or kinetics of response. The toxicities were manageable, with dose modifications. All patients were able to collect stem cells when required, though majority needed plerixafor. Disclosures Kumar: Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Kite Pharma: Consultancy, Research Funding; Carsgen: Other, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Cellectar: Other; Dr. Reddy's Laboratories: Honoraria; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Tenebio: Other, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genecentrix: Consultancy; Sanofi: Research Funding; Novartis: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding. Kapoor:GlaxoSmithKline: Research Funding; Celgene: Honoraria; Takeda: Honoraria, Research Funding; Amgen: Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; Cellectar: Consultancy. Dingli:Apellis: Consultancy; Karyopharm Therapeutics: Research Funding; Janssen: Consultancy; Bristol Myers Squibb: Research Funding; Alexion: Consultancy; Rigel: Consultancy; Millenium: Consultancy; Sanofi-Genzyme: Consultancy. Dispenzieri:Pfizer: Research Funding; Takeda: Research Funding; Alnylam: Research Funding; Janssen: Research Funding; Celgene: Research Funding; Intellia: Research Funding. Gertz:Abbvie: Other; Sanofi: Other; Celgene: Other; Research to Practice: Other; Physicians Education Resource: Other: personal fee; Amgen: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Appellis: Other: personal fee; Annexon: Other: personal fee; Alnylam: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Teva: Speakers Bureau; Aurora Bio: Other; Springer Publishing: Patents & Royalties; Proclara: Other; DAVA oncology: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Ionis/Akcea: Other: personal fee; Prothena: Other: personal fee.

Background: Newly diagnosed patients with AL Amyloidosis are a heterogeneous population, ranging from incidentally found nephrotic syndrome to delayed advanced cardiac disease. For the purposes of trials, patients with the highest-risk disease are often excluded from trial participation. An NT-proBNP of 8500 or higher is the criterion most often used for exclusion from clinical trials due to high rates of early death. It is well documented that overall survival is improving over time, in part due to earlier diagnosis and in part due to more effective therapies. It is our aim to describe outcomes of patients with very high (NT-proBNP >=8500) and advanced stage amyloidosis excluding very high (VH) NT-proBNP. Methods: To address this need, we examined the outcomes of AL patients diagnosed between 1/2012 and 7/2020 and seen at our institution within 90 days of diagnosis. Of the 1290 patients, 291 were seen beyond the 90 day threshold and were thus excluded. Another 170 patients were excluded due to missing biomarkers to calculate stage, leaving 829 patients for our analysis. Thresholds for troponins and BNPs were used according to Muchtar Blood 133(7):2019 to correct for assay used. The vast majority of patients had troponin T measured, and for them the 0.025 mcg/L and the 0.035 mcg/L cut-points were used for the 2012 and 2004 staging systems. A minority of patients did not have troponin T, but rather high sensitivity troponin T (n=129) or troponin I (n=23). For patients with high sensitivity troponin T, cut-points of 41 and 50 ng/L were used, respectively, for the 2012 and 2004 systems, and for patients with troponin I only, a cut-point of 0.1 mcg/L was used for both systems. In the 3 patients with no NT-proBNP but with BNP, 400 and 81 ng/L were used respectively for the 2012 and 2004 systems; otherwise, the 1800 ng/L and 332 ng/L cut-offs were used. A BNP of > 700 ng/L was considered equivalent to NT-proBNP greater than or equal to 8500 ng/L. For the 2012 system, the dFLC of 18 mg/dL was used as a cut-off. Survival estimates were done using the method of Kaplan-Meier, and differences in survival were by determined by Log-Rank. Results: The median age of patients was 65 (range 29, 89), and 65% were male. 148 (17%) of these newly diagnosed patients had a VH (>=8500) NT-proBNP. Patients with VH NT-proBNP were older (67 versus 64 years, p=0.004). Only 4% of the VH NT-proBNP patients received an ASCT in contrast to 34% without VH NT-proBNP. With a median follow-up of 30 months for surviving patients, median OS for VH NT-proBNP patients was 3.3 months in contrast to patients without VH NT-proBNP at 68.4 months (Figure). Breakdown of early death for patients with VH NT-proBNP by stage is shown in Table. Of Mayo 2012 patients staged I, II, III, and IV, the percent of patients with VH NT-proBNP was 0, 3, 20, and 45%. In contrast, for the European modification of the Mayo 2004 system, the percent with VH NT-proBNP by stage was 0, 6, 0, 100 for stages I, II, IIIa, and IIIb, respectively. Among the VH NT-proBNP patients, there was stage discrimination using the Mayo 2012 system (6-month death rates were 17, 45, and 66% for patients with stages II, III, and IV, respectively, p=0.02). In contrast, using the Mayo 2004 system in the patients with VH NT-proBNP, 6-month death rates were 45 and 60% for stage II and IIIb patients, respectively (p= 0.12). Among patients without VH NT-proBNP, rates of death in the first year were 21% including stage I patients whose death rates were well under 10%. Patients without VH NT-proBNP but Mayo 2012 Stage III and IV had 1-year mortalities of 28 and 43% respectively. Using the modified Mayo 2004 system, excluding the VH NT-proBNP 1-year mortality was 19 and 37% for patients with stage II and IIIa, respectively. Discussion: Establishing expected outcomes for the sickest AL amyloidosis patients is a means by which trials can be designed for these patients with an unmet need. Patients with VH NT-proBNP should be considered for specially designed trials, and patients without VH NT-proBNP and advanced stage should be included in trials for newly diagnosed patients regardless of stage as long as there is appropriate stratification. Disclosures Dispenzieri: Janssen: Research Funding; Pfizer: Research Funding; Intellia: Research Funding; Alnylam: Research Funding; Celgene: Research Funding; Takeda: Research Funding. Kumar:AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Sanofi: Research Funding; Carsgen: Other, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Merck: Consultancy, Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Adaptive Biotechnologies: Consultancy; Dr. Reddy's Laboratories: Honoraria; Novartis: Research Funding; MedImmune: Research Funding; Genecentrix: Consultancy; Kite Pharma: Consultancy, Research Funding; Cellectar: Other; Karyopharm: Consultancy; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments. Dingli:Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Millenium: Consultancy; Janssen: Consultancy; Alexion: Consultancy; Rigel: Consultancy; Apellis: Consultancy; Sanofi-Genzyme: Consultancy. Kapoor:Celgene: Honoraria; Cellectar: Consultancy; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding. Lin:Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy; Legend BioTech: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy. Gertz:Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding; NCI SPORE MM: Research Funding; Ionis/Akcea: Consultancy; Alnylam: Consultancy; Prothena: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Data Safety Monitoring board from Abbvie: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Advisory Board for Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Advisory Board for Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Consultancy.

Introduction: Patient-reported outcomes (PROs) such as quality of life (QOL) are variably affected in patients with myelodysplastic syndromes (MDS), but the heterogeneous composition of disease states grouped together as "MDS" increases the difficulty of assessing and understanding these outcomes. Moreover, little is known about the potential relationship between QOL and frailty in this population. Methods: The NHLBI MDS Natural History Study (NCT02775383) is a prospective cohort enrolling patients undergoing diagnostic work up for suspected MDS or MDS/myeloproliferative neoplasms (MPNs) in the setting of cytopenias. Untreated participants undergo bone marrow assessment with centralized histopathology review at enrollment for assignment into subcategories for longitudinal follow-up: MDS, MDS/MPN, ICUS, AML (<30% blasts), and "At-Risk" (cases with sub-threshold dysplasia or select karyotypic or genetic mutations). PRO and frailty data are collected at enrollment and every six months thereafter. PRO instruments include MDS-specific (QUALMS) and general (FACT-G, PROMIS Fatigue Short Form 7a, EQ-5D-5L) instruments, and a measure of frailty (VES-13). While no frailty instrument alone has been shown to be a substitute for comprehensive geriatric assessment, VES-13 has been successfully used in cancer-related studies for basic screening, where a score of 3 or more is considered frail (vulnerable). An analysis of variance (ANOVA) was used for the overall comparisons of mean baseline scores between diagnostic categories. Pairwise comparisons of scores between diagnostic categories and vulnerability subgroups were performed via two-sample t-tests. Results : Of 835 participants assessed for eligibility, 369 (44%) were classified as MDS, MDS/MPN, AML, ICUS or At-Risk, and further evaluated. Mean age was 72 years (standard deviation (SD)=10.7) and 68% were male. Mean baseline scores on the PRO measures are compared between diagnostic categories in the Table; scores did not differ significantly across categories. In particular, no significant differences were found between MDS and the other diagnostic categories. ICUS had similar QOL scores to MDS and MDS/MPN (e.g., means (SD) on EQ-5D-5L of 74.1 (17.8) in ICUS and 70.8 (19.4) in MDS, p=0.348) but had significantly higher scores than those for AML on EQ-5D-5L (60.7 (28.4), p=0.031). For the 216 participants with diagnostically-confirmed MDS, QOL impairment was similar to that routinely seen in other cancers; for example, the mean total FACT-G was 81.8 (SD=15.9), similar to localized breast cancer (82.4, SD=16.2), localized colorectal cancer (79.6, SD=16.1), and lung cancer with no current evidence of disease (82.6, SD=15.5; comparison means from Pearlman, Cancer, 2014). For frail/vulnerable participants with MDS or MDS/MPN (N=87), the most common reasons for vulnerability were age ≥75 years (68%), overall rating of health as poor or fair (62%), and difficulty with prolonged physical activity (90%) such as walking a quarter mile (75%) or doing heavy housework (70%). A minority also were vulnerable due to requiring help with instrumental activities of daily living (iADLS) such as shopping (28%) or managing money (16%). Mean QOL scores were compared between vulnerability subgroups (Figure). Vulnerable participants pooled over all diagnostic categories had significantly worse PROs than non-vulnerable participants for all measures (p<0.001). In particular, vulnerable MDS participants scored significantly worse on the QUALMS (mean 64.4, SD=13.4) vs. non-vulnerable MDS participants (mean 72.7, SD=13.3), p<0.001. Conclusions: Participants in our cohort with histologically-confirmed MDS-even low-grade MDS-had similar impairments in PROs as those with other cancers. Among those with histologically-confirmed MDS, vulnerable participants had significantly worse QOL on many measures compared to non-vulnerable participants, suggesting that this domain of function be specifically assessed in clinic. Moreover, while a "gestalt" of frailty may be inferred by observing how patients present and move in the office, these data suggest that other contributing domains, such as difficulty with prolonged physical activity and iADLs, should be evaluated explicitly. Disclosures Foran: H3Biosciences: Research Funding; Aptose: Research Funding; Kura Oncology: Research Funding; Takeda: Research Funding; Servier: Membership on an entity's Board of Directors or advisory committees; Xencor: Research Funding; Agios: Honoraria, Research Funding; Boehringer Ingelheim: Research Funding; Actinium: Research Funding; Aprea: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Trillium: Research Funding; Revolution Medicine: Consultancy; Pfizer: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding. Gore:Abbvie: Consultancy, Honoraria, Research Funding. Padron:Incyte: Research Funding; Kura: Research Funding; Novartis: Honoraria; BMS: Research Funding. Sekeres:BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda/Millenium: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Introduction: The bone marrow plasma cell (BMPC) clone burden is typically low in light chain (AL) amyloidosis and some patients do not have a detectable serum monoclonal spike (M-spike). Increased BMPC% and serum free light chain (FLC) are associated with poorer outcomes. However, the outcomes of patients with AL amyloidosis based on the presence or an absence of a measurable serum M-spike before autologous stem cell transplantation (ASCT) has not been explored. Methods: This was a retrospective review of patients who had a diagnosis of AL amyloidosis and received ASCT between March 1996 and September 2017. The serum M-spike was recorded before ASCT and patients were divided according to the presence or absence of a measurable serum M-spike. Progression-free survival (PFS) was defined as time from ASCT to disease progression, relapse or death of any cause. Overall survival (OS) was calculated from time of ASCT to death of any cause. Univariate and multivariate analysis for PFS and OS were done using the following variables: age>65 vs. ≤65 years, Mayo 2012 stage 3/4 vs. 1/2, BMPC ≥ 10% vs. <10%, organs involved >2 vs. ≤2, melphalan conditioning 200mg/m2 vs. 140 mg/m2 ,ASCT year >2010 vs. ≤2010, and presence vs. absence of a measurable serum M-spike. Results: Seven-hundred and sixteen patients were identified and 521 (73%) had a measurable serum M-spike. Patients who had a measurable serum M-spike were more likely to have BMPC≥ 10% than patients without a measurable serum M-spike (46% vs. 34%, P=0.002) and they were more likely to have a difference in FLC ≥18 mg/dl (47% vs. 29%, P=0.0001). Overall, PFS and OS were significantly shorter in patients who had a measurable serum M-spike compared to patients without a measurable serum M-spike (Figure 1 A,B). The shorter survival was irrespective of the administration of induction therapy before ASCT. We also evaluated the difference in survival in patients with Mayo 2012 stage 3/4 based on the presence or absence of a measurable serum M-spike. The PFS and OS were also significantly different in these patients (Figure 1 C,D). Predictors for PFS included Mayo 2012 stage 3/4 vs. 1/2 (hazard ratio (HR): 1.5, P=0.003), BMPC ≥ 10% vs. <10% (HR: 1.4,P=0.004), melphalan conditioning 200mg/m2 vs. 140 mg/m2 (HR:0.6, P=0.001), ASCT year >2010 vs. ≤2010 (HR: 0.8, P=0.03), and the presence vs. absence of a measurable serum M-spike (HR: 1.82, P<0.0001). For OS, Mayo 2012 stage 3/4 vs. 1/2 (HR: 2, P<0.0001), melphalan conditioning 200mg/m2 vs. 140 mg/m2 (HR:0.4, P<0.0001), ASCT year >2010 vs. ≤2010 (HR: 0.6, P=0.002), and the presence vs. absence of a measurable serum M-spike (HR:1.9, P=0.003) were predictive. Conclusion: The presence of a measurable serum M-spike before ASCT is a negative independent predictor for PFS and OS in AL amyloidosis. Figure 1 Disclosures Sidiqi: Amgen: Honoraria; Celgene: Honoraria, Other: Travel grant; Janssen: Honoraria. Dingli:Karyopharm Therapeutics: Research Funding; Apellis: Consultancy; Alexion: Consultancy; Janssen: Consultancy; Bristol Myers Squibb: Research Funding; Rigel: Consultancy; Millenium: Consultancy; Sanofi-Genzyme: Consultancy. Kapoor:Amgen: Research Funding; Celgene: Honoraria; Cellectar: Consultancy; Janssen: Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Consultancy, Research Funding; GlaxoSmithKline: Research Funding. Dispenzieri:Intellia: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding. Kumar:Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Tenebio: Other, Research Funding; Genecentrix: Consultancy; MedImmune: Research Funding; Cellectar: Other; Dr. Reddy's Laboratories: Honoraria; Merck: Consultancy, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Novartis: Research Funding; Adaptive Biotechnologies: Consultancy; Kite Pharma: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Carsgen: Other, Research Funding; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding. Gertz:Proclara: Other; Abbvie: Other; DAVA oncology: Speakers Bureau; Aurora Bio: Other; Prothena: Other: personal fee; Teva: Speakers Bureau; Physicians Education Resource: Other: personal fee; Annexon: Other: personal fee; Ionis/Akcea: Other: personal fee; Sanofi: Other; Appellis: Other: personal fee; Amgen: Other: personal fee; Janssen: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Medscape: Other: personal fee, Speakers Bureau; Research to Practice: Other; Alnylam: Other: personal fee; Johnson and Johnson: Speakers Bureau; Springer Publishing: Patents & Royalties; Celgene: Other.

Introduction Autologous stem cell transplantation (ASCT) has been used for treating multiple myeloma (MM) for over three decades and is generally reserved for patients younger than 65 years of age. The definition of transplant eligible is ill-defined and different centers have different policies to determine which patients are transplant eligible. Some centers have an age cut-off, others use clinical judgment, and some use various frailty scores (a scoring system based on comorbidities and physical and cognitive assessments) aiming to objectively assess transplant eligibility. There are limited data about outcomes in patients ≥ 75 years. Aim To report on outcomes of ASCT in a cohort of patients with MM aged 75 years or older. Methods Retrospective study of all consecutive MM patients aged ≥ 75 years that underwent ASCT at Mayo Clinic, Rochester, Minnesota. Stem cell transplantation at our center is routinely performed as an outpatient, with patients being hospitalized when deemed clinically necessary upon physician review. Results Between October 2005 and March 2020, 46 patients aged 75 years or older, received an ASCT at Mayo Clinic, Rochester. The median hematopoietic stem cell transplantation specific comorbidity index (HCT-CI) was 0 (range 0-6) with 8 patients having HCT-CI of 5 or 6. Median time from diagnosis to ASCT was 6.45 months (IQR 5.2-10.52) and 54% received reduced intensity conditioning with melphalan 140 mg/m2. All patients except one (that was treated with dexamethasone only) received induction with novel agents (listed in table 1) and 6 patients (13%) received doublet induction. All others received triplet induction. 46% of patients completed the ASCT without requiring hospitalization and 54% (n=25) of patients required hospitalization with a median duration of hospital admission of 9 days (IQR 5-13). Reasons for hospitalization included fever or infection (32%), cardiac arrhythmia (36%) and dehydration (32%). Overall response rate was 100% with a complete response seen in 57% of patients and 16 patients achieving MRD negative sCR. Median overall survival and progression free survival for the cohort were 82 months and 33 months, respectively. One patient died within 100 days of transplant representing a 2% 100-day mortality rate. Univariable cox regression model that evaluated the effect of gender, high risk cytogenetics, hemoglobin, renal function and melphalan dose did not detect any variable that was predictive of OS or PFS (Table 3). Conclusions ASCT is efficacious and can be safely delivered in the outpatient setting in carefully screened patients aged 75 or above. An arbitrary cutoff for age should not be used to exclude patients from ASCT, rather a careful assessment of "physiological age" including performance status and co-morbidities is required by an experienced treating team. Disclosures Kumar: Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Cellectar: Other; Carsgen: Other, Research Funding; Dr. Reddy's Laboratories: Honoraria; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Merck: Consultancy, Research Funding; MedImmune: Research Funding; BMS: Consultancy, Research Funding; Tenebio: Other, Research Funding; Karyopharm: Consultancy; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genecentrix: Consultancy; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Adaptive Biotechnologies: Consultancy. Dispenzieri:Pfizer: Research Funding; Janssen: Research Funding; Alnylam: Research Funding; Intellia: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Dingli:Bristol Myers Squibb: Research Funding; Rigel: Consultancy; Janssen: Consultancy; Alexion: Consultancy; Karyopharm Therapeutics: Research Funding; Apellis: Consultancy; Sanofi-Genzyme: Consultancy; Millenium: Consultancy. Kapoor:Cellectar: Consultancy; Takeda: Honoraria, Research Funding; Celgene: Honoraria; Amgen: Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; GlaxoSmithKline: Research Funding. Gertz:Prothena: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Appellis: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee; Janssen: Other: personal fee; Research to Practice: Other; Sanofi: Other; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Proclara: Other; Springer Publishing: Patents & Royalties; Celgene: Other; Physicians Education Resource: Other: personal fee; Aurora Bio: Other; Amgen: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Abbvie: Other.

Introduction: The NHLBI National MDS Study (NCT02775383) is a prospective cohort study conducted at 92 community hospitals and 29 academic centers. It enrolls patients undergoing work up for suspected MDS to understand the genetic, epigenetic, and biological factors associated with the initiation and progression of the disease. Previously untreated, cytopenic participants undergo both local and centralized pathology review and are assigned a diagnosis, including MDS, MDS/MPN, AML with blasts < 30%, and "Other". Emerging data suggests that Next Generation Sequencing (NGS), along with cytogenetics and clinical variables, may improve MDS diagnostic precision. Given that our study relies on central review (with additional tertiary pathology review used to adjudicate disagreements), we examined whether targeted gene sequencing data could be used to increase the agreement between local and central pathologic diagnosis of MDS vs. Other. Methods: Peripheral blood and bone marrow (BM) biopsy specimens from cytopenic patients, along with clinical history, CBC, and other results including karyotyping, FISH and pathology reports from local pathologists were reviewed by central pathologists. The updated 2016 WHO classifications were used to diagnose MDS. Targeted exon sequencing of 96 genes was performed using BM specimens. A subset of 648 individuals that were classified as MDS (n=212) or Other (n=436, including 90 CCUS and 89 individuals with other cancers) by pathology assessments were selected. A mean coverage of 1,317X was achieved and variants had a minimum variant allele frequency (VAF) of 2% (except FLT3). Variants for 596 subjects were manually reviewed to retain likely disease-causing variants to build a binary classifier (MDS vs. Other) using the maximum VAF per gene as input (Figure 1). Subjects diagnosed with MDS or Other by both central and local pathology were used for training, validation, and testing, and were considered "gold standard" (GS) cases (n=546). These subjects were split into 4 random groups with equal proportions of MDS cases. 75% of the GS cases were used to train and validate lasso-regularized logistic regression models using 3-fold cross validation. ROC curve analysis was carried out using the remaining 25% of GS cases (Test Set 1) on the best model to identify an optimal probability cut off point for classifying subjects as MDS. Model performance was then tested on 50 subjects for which the central and local pathology diagnosis disagreed (Test Set 2), as well as on 52 additional subjects irrespective of agreement (Test Set 3). Results : The best performing logistic regression model retained 7 genes as most informative in a discriminating diagnosis of MDS from Other based on their VAFs, in order of impact: TP53, SF3B1, U2AF1, ASXL1, TET2,STAG2, and SRSF2. We used this model to assign probabilities for each of the subjects in Test Set 1 and to estimate the performance using ROC analysis (Figure 1), resulting in a high area under the curve (AUC) of 0.89. We chose a probability cut-off of ≥0.17, being associated with a high percentage of correct classification of MDS with a sensitivity and specificity of 0.90 and 0.81, respectively. Among the cohort of 50 subjects with a discordant local and central pathology diagnosis (Test Set 2), the classifier accurately reassigned 37 subjects (accuracy = 74%) from the local to the central pathology. The blinded tertiary pathology reviewer agreed with central in all Test Set 2 cases. This included 24/34 MDS cases that had been labeled as Other by local pathology (positive predictive value [PPV]=0.89). 3/16 final pathology-classified Other cases were mis-classified as MDS by the local pathologist (negative predictive value [NPV] = 0.57). Next, we assessed the ability of the model to predict MDS vs. Other for 52 additional independent subjects using the third pathologist's diagnosis to break any ties (Test Set 3). The classifier correctly predicted 15/21 MDS cases (PPV=0.83) and misclassified 6/31 Others as MDS (NPV=0.82). The overall accuracy was 83%. Conclusions: We identified that VAFs for 7 genes can correctly re-classify subjects as either MDS or Other in 74% of cases that were misclassified between local and central pathology review. Further assessment on an independent cohort showed an accuracy of 83% of the model. Taken together, these data suggest that complementing pathology reviews with targeted sequencing of 7 genes could improve MDS diagnosis. Disclosures Lindsley: MedImmune: Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Bluebird Bio: Consultancy; Takeda Pharmaceuticals: Consultancy. Bejar:Aptose Biosciences: Current Employment; AbbVie/Genentech: Honoraria; Astex/Otsuka: Honoraria; Takeda: Honoraria, Research Funding; Celgene/BMS: Honoraria, Research Funding; Daiichi-Sankyo: Honoraria; Forty-Seven/Gilead: Honoraria; Genoptix/NeoGenomics: Honoraria. DeZern:MEI: Consultancy; Astex: Research Funding; Abbvie: Consultancy; Celgene: Consultancy, Honoraria. Foran:H3Biosciences: Research Funding; Aptose: Research Funding; Kura Oncology: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Revolution Medicine: Consultancy; Xencor: Research Funding; Agios: Honoraria, Research Funding; Aprea: Research Funding; Actinium: Research Funding; Servier: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding. Gore:Abbvie: Consultancy, Honoraria, Research Funding. Komrokji:Acceleron: Honoraria; Incyte: Honoraria; Abbvie: Honoraria; Agios: Speakers Bureau; BMS: Honoraria, Speakers Bureau; Jazz: Honoraria, Speakers Bureau; Geron: Honoraria; Novartis: Honoraria. Maciejewski:Alexion, BMS: Speakers Bureau; Novartis, Roche: Consultancy, Honoraria. Padron:Novartis: Honoraria; BMS: Research Funding; Incyte: Research Funding; Kura: Research Funding. Starczynowski:Captor Therapeutics: Consultancy; Tolero Therapeutics: Research Funding; Kurome Therapeutics: Consultancy, Current equity holder in private company, Research Funding. Sekeres:BMS: Consultancy; Takeda/Millenium: Consultancy; Pfizer: Consultancy.

Abstract Background A population-based study of infective endocarditis (IE) in Olmsted County, Minnesota, provides a unique opportunity to define temporal and seasonal variations in IE incidence over an extended time period. Methods This was a population-based review of all adults (≥18 years) residing in Olmsted County, Minnesota, with definite or possible IE using the Rochester Epidemiology Project from January 1, 1970, through December 31, 2018. Poisson regression was used to characterize the trends in IE incidence; models were fitted with age, sex, calendar time, and season, allowing for nonlinearity and nonadditivity of their effects. Results Overall, 269 cases of IE were identified over a 49-year study period. The median age of IE cases was 67.2 years, and 33.8% were female. The overall age- and sex-adjusted incidence of IE was 7.9 cases per 100 000 person-years (95% CI, 7.0–8.9), with corresponding rates of 2.4, 2.4, 0.9, and 0.7 per 100 000 person-years for Staphylococcus aureus, viridans group streptococci (VGS), Enterococcus species, and coagulase-negative staphylococci IE, respectively. Temporal trends varied by age, sex, and season, but on average IE incidence increased over time (P = .021). Enterococcal IE increased the most (P = .018), while S. aureus IE appeared to increase but mostly in the winter months (P = .018). Between 1996 and 2018, the incidence of VGS IE was relatively stable, with no statistically significant difference in the trends before and after the 2007 AHA IE prevention guidelines. Conclusions Overall, IE incidence, and specifically enterococcal IE, increased over time, while S. aureus IE was seasonally dependent. There was no statistically significant difference in VGS IE incidence in the periods before and after publication of the 2007 AHA IE prevention guidelines.

AbstractBackgroundUnderstanding factors that impair quality of life (QOL) in gastroparesis is important for clinical management. Aims: (a) Determine QOL in patients with gastroparesis; (b) Determine factors that impair QOL.MethodsGastroparetic patientsAQ6 underwent history and questionnaires assessing symptoms (PAGI‐SYM and Rome III), QOL (SF‐36v2 and PAGI‐QOL), depression (Beck Depression Inventory [BDI]), and anxiety (State Trait Anxiety InventoryAQ7).Key Results715 gastroparesis patients (256 diabetic (DG), 459 idiopathic (IG)) were evaluated. SF‐36 physical component (PC) score averaged 33.3 ± 10.5; 41% had impaired score <30. SF‐36 PC scores were similar between diabetic and idiopathic gastroparesis. Impaired SF‐36 PC associated with increased nausea/vomiting and upper abdominal pain subscores, acute onset of symptoms, higher number of comorbidities, use of narcotic pain medications, and irritable bowel syndrome (IBS). SF‐36 mental component (MC) score averaged 38.9 ± 13.0; 26% had impaired score <30. Poor SF‐36 MC associated with diabetic etiology, higher Beck depression inventory, and state anxiety scores. PAGI‐QOL score averaged 2.6 ± 1.1; 50% had a score of <2.6. Low PAGI‐QOL associated with higher fullness, bloating, and upper abdominal pain subscores, more depression and Trait anxiety, smoking cigarettes, need for nutritional support, progressively worsening symptoms and periodic exacerbations.Conclusions & InferencesMultiple measures show poor QOL present in gastroparesis. Several areas impacted on reduced QOL: (a) Symptoms of nausea, vomiting, and abdominal pain, as well as IBS; (b) Etiology and acute onset and progressively worsening symptoms; (c) Comorbidities and psychological factors such as anxiety and depression; (d) Patient‐related factors such as smoking. Targeting the modifiable factors may improve patient outcomes in gastroparesis.

27 Background: Colorectal cancer (CRC) is the second most deadly and fourth most frequently diagnosed cancer in the United States. Early detection can improve CRC outcomes, but overall screening rates (62%) remain below the 80% goal set by the National Colorectal Cancer Roundtable. Multiple options are endorsed for average-risk CRC screening, including the multi-target stool DNA (mt-sDNA) test, which includes patient and provider navigation support. Cross-sectional adherence with the mt-sDNA test was previously reported in a large Medicare population (71%). In the current study we investigated cross-sectional adherence with the mt-sDNA test in a broader, national sample of insured patients. Methods: Aggregate data from Exact Sciences Laboratories LLC (ESL; Madison, WI) were retrospectively analyzed in compliance with HIPAA requirements. Study participants included individuals ages 50 years and older who were covered by commercial insurance or Medicare, had a valid mt-sDNA test order placed between January 1–December 31, 2018, and received a test kit shipped from ESL. Cross-sectional adherence, defined as successful completion and return of the test kit within 365 days of the shipment date, was assessed overall and by patient- and provider-level factors. Results: In total, 1,420,460 participants met the study criteria (61.2% women; mean age 65.7 years). Overall cross-sectional adherence was 66.8%. Adherence was 72.1% in participants with Traditional Medicare, 69.1% in participants with Medicare Advantage, and 61.9% in participants with commercial insurance (p<0.001). Adherence increased by participant age (p<0.001): 60.8% for ages 50-64, 71.3% for ages 65-75, and 74.7% for ages 76+ years. For Traditional Medicare patients, ages 65-75, adherence was 73.6%. Participants with mt-sDNA tests ordered placed by gastroenterologists had a higher adherence rate (78.3%) than those with orders placed by primary care clinicians (67.2%) (p<0.001). Adherence rates were highest among patients with ordering providers in the Pacific region (71.4%) and West North Central region (70.1%), and lowest in the Mid-Atlantic region (65.7%), New England (65.2%), West South Central region (64.6%), and Puerto Rico and US territories (60.7%). Conclusions: Novel data from this large, national sample of insured patients demonstrate high cross-sectional adherence with the mt-sDNA test (66.8%), supporting the substantial contribution this guideline-endorsed option plays in average-risk CRC screening. At the patient-level, adherence increased with patient age, and was highest in those covered by Traditional Medicare. Provider-level stratification showed the highest adherence for mt-sDNA tests ordered by gastroenterologists. This study adds to data regarding the impact of accompanying navigation support and at-home convenience of mt-sDNA on screening completion rates.