Citations

e20000 Background: In the novel agents’ era, refractoriness to induction in Multiple Myeloma (MM) is relatively rare. This population remain an unmet need and are often excluded from clinical trials. In the current era, chemotherapy-induced stem cell collections are used at Mayo Clinic in “poor responders” to induction, such as patients that progress prior to ASCT or patients with significant disease burden after induction. Methods: This is a retrospective study that includes all MM patients the underwent chemo-mobilization between January 2012 and September 2020 at Mayo Clinic. We compared our cohort to a cohort of 125 matched patients that were transplanted over the same time period and underwent mobilization with G-CSF and “on-demand” plerixafor. We matched the cohorts by level of response by IMWG at pre-transplant evaluation. Results: 125 newly diagnosed MM patients who received novel agents’ induction and had a poor response to induction were mobilized using IV intermediate-dose cyclophosphamide (83%) or VDT-PACE (17%) plus G-CSF and “on-demand” plerixafor. The median PFS and OS of the chemo-mobilized cohort were 16 months (95% CI 11-20) and 47 months (95% CI 37-71), respectively. Patients receiving chemo-mobilization had higher stem cell yields than the growth factor only cohort (median 9.88X106 cells/kg versus median 8.77X106 cells/kg, respectively (P<0.001)). The safety profile of chemo-mobilization was favorable, with no difference between the two groups in length of hospitalization during ASCT (P=0.95), days to neutrophil or platelet engraftment, and risk of bacteremia (P=0.38). 29% of the chemo-mobilized cohort and 66% of the matched cohort required plerixafor for adequate mobilization (P<0.001). Conclusions: Chemo-mobilization enhances stem cell collection in MM patients with a suboptimal response to induction and reduces the need for plerixafor without adversely impacting the post-transplant clinical course. [Table: see text]

7554 Background: Chimeric antigen receptor T-cell therapy (CAR-T) are commonly administered inpatient due to concern for early onset cytokine release syndrome (CRS), especially with axicabtagene ciloleucel (axi-cel). We report Mayo Clinic Rochester experience for hospital-based outpatient (HBO) management of patients (pts) receiving axi-cel and identify opportunities for improvement. HBO is closely integrated with inpatient practice and includes the same specialty trained clinical team. It is the first point of contact 24/7 for pts and triage evaluations. Lymphodepletion chemotherapy and CAR-T infusion is given on HBO followed by daily monitoring till day 8 and thereafter, as clinically needed until admission criteria is met. Methods: We retrospectively analyzed database of pts who received axi-cel between 1/2018 and 1/2021. After 06/2020, remote patient monitoring (RPM) tools were implemented to collect patient-reported neurologic symptoms and vital signs via bluetooth-enabled devices 4 times daily through month 1. Adverse data trends are addressed by the HBO team. Results: Among 72 recipients, 89% received their cells outpatient; 8% remained outpatient for the entire month. CRS and neurotoxicity incidence were comparable to those reported from CIBMTR. Median time to first admission was 2 days (Table). Use of bridging therapy, increased CRP and LDH were associated with early admission (≤3 days). Median time to tocilizumab, steroid, oxygen support, vasopressor was 4 days after admission. Half of HBO visits required intervention such as blood transfusions, IV medications through the first month. Nine pts had enrolled in RPM to date; with 8 having evaluable data. With 4 scheduled entries/day, a median of 1 entry/day was skipped and 2 entries/day were answered incompletely. An average of 57 additional unscheduled entries were generated per pt. Among a median of 373 (range 91-522) readings per pt over the first month, 4% (2%-20%) of the readings generated alerts. An average of 4 alerts were seen within 48 hours prior to admission. Data including additional subjects will be presented at ASCO meeting. Conclusions: We report a feasible outpatient care model for management of axi-cel recipients with safe outcomes. Clinical characteristics associated with more aggressive disease are associated with likelihood of early admission. Early RPM experience suggest use of digital tools could improve monitoring compliance and may predict evolution to symptoms requiring escalation of care.[Table: see text]

6594 Background: Patient reported financial hardship (FH) in cancer care is a growing challenge for patients, their caregivers and healthcare providers. As treatment costs escalate, it is imperative to develop effective strategies to proactively recognize and mitigate FH within oncology practice. Using automated processes to screen and refer patients to appropriate resources is a potential option. At Mayo Clinic, screening for FH involves using a single financial strain question ‘ How hard is it for you to pay for the very basics like food, housing, medical care, and heating?’ completed by all cancer patients annually as part of the Social Determinants of Health (SDOH) assessment. In this study, we describe the prevalence and predictors for FH (denoted by the answer ‘hard and very hard’) in our patient population. Methods: Patients receiving cancer care at the three Mayo Clinic sites (Minnesota, Arizona, and Florida) who completed the FH screen at least once were included in this study. Demographics (age, gender, race/ ethnicity, insurance, employment status, marital status, and zip code) and disease state data for included patients was extracted from the EMR and Mayo Clinic Cancer Registry. Disease state was categorized by type of cancer (hematological or solid malignancy) and cancer stage. Zip code was used to derive median income, rural/urban residence and distance from the cancer center. Multivariable logistic regression models were utilized to examine factors associated with FH. Results: The final study cohort included 31,969 patients with median age 66 years (IQR 57,73), 51% females, and 76% married. Race/ethnicity composition was 93% White, 3% Black, and 4% Hispanic. 52% of patients had Medicare and 43% had commercial insurance. Other notable factors included 48% retired, 41% working/ students, 76% married, and 72% urban residents. Median time from cancer diagnosis was 1.1 year (IQR 0.1, 3.8) and median income was $64,406 (IQR 53,067, 82,038). 31% of patients had hematological malignancies, 20% of the cancers for which staging information was available were metastatic. FH was reported by 4% (n = 1194) of the patients. A significantly higher likelihood of endorsing FH (p < 0.001 for all) was noted in Hispanic (OR 1.64), Black (OR 1.84), American Indian/Alaskan native (OR 2.02), below median income (OR 1.48), rural (OR 1.17), self-pay (OR 2.77), Medicaid (OR 2.29), Medicare (OR 1.43), unemployed/disabled (OR 2.39), single (OR 2.07), or divorced (OR 2.43) patients. Older age, being retired, and living farther from the cancer center were associated with significantly less likelihood of endorsing FH. Conclusions: Our study successfully leveraged the EMR to identify key sociodemographic groups more likely to report FH. An electronic trigger to flag such patients at high-risk of FH and proactively address FH is currently being developed.

Abstract The utility of systemic light chain (AL) amyloidosis staging systems has been validated for newly diagnosed patients, but their role in restaging after treatment has not been explored. We designed this study to evaluate whether the currently used systems are of prognostic value at 3 and 6 months of starting first-line treatment, and whether stage migration from diagnosis impacts survival. This is a retrospective study including Mayo Clinic patients with AL amyloidosis diagnosed between 1 January 2006 and 30 June 2019; 536 and 204 patients had restaging data for at least 1 system at 3 and 6 months, respectively. Using modified Mayo 2004 staging at 3 months, median overall survival (OSs) were 11.8, 10.8, 4.6, and 1.1 years for stage I, II, IIIa, and IIIb, respectively. Using Mayo 2012, median OSs were 11.8, 9.0, 5.2, and 0.8 years for stage I, II, III, and IV, respectively. Using modified Mayo 2004 staging at 6 months, median OSs were not reached (NR), NR, 5.4, and 0.9 years for stage I, II, IIIa, and IIIb, respectively. Using Mayo 2012, OSs were NR, NR, 4.6, and 0.9 years for stage I, II, III, and IV, respectively. Worsening stage at 3 or 6 months was associated with worse survival than retaining baseline stage. In conclusion, the current staging systems can be used for restaging at 3 and 6 months from treatment initiation. Migration to higher stage predicts poor prognosis.

BACKGROUND: Advances in novel therapies and supportive care have contributed to improved outcomes for patients with Multiple myeloma (MM) and Light Chain Amyloidosis (AL). This progress comes at a high price; with high financial costs to patients increasing distress, decreasing compliance, and even decreasing survival. Our aim was to screen patients for financial distress and understand its impact on various domains of health-related quality of life (HRQOL). METHODS: We conducted a prospective study of adult patients with MM or AL that received follow-up care at Mayo Clinic, Rochester, MN. Financial distress was measured using the validated COmprehensive Score for financial Toxicity (COST) questionnaire; high financial distress was defined as a score of 23 or less. HRQOL was measured using the Patient Reported Outcome Measurement Information System (PROMIS)-29 questionnaire. Baseline demographic information and clinical characteristics were abstracted from the medical record. Statistical analysis included descriptive statistics, Spearman correlations, and comparison of COST scores between groups by Jonckheere-Terpstra, Kruskal-Wallis, and Wilcoxon rank-sum tests for ordered, unordered, and binary categorical variables, respectively. RESULTS: Patients: To date 77 patients (MM 64 [83%], AL 13 [17%]) have been enrolled, 55% male, 53% age 65 or older (18% &lt;55), 91% White (5% Black), 92% non-Hispanic, 56% at least some college, 47% income at least US$75K/year (25% &lt;US 50K/year), 36% employed (49% retired), 73% married (14% divorced) and 22% traveled at least 300 miles to clinic. Clinical characteristics included 45% newly diagnosed, 55% relapsed/refractory disease. 66% had been transplanted previously. Insurance types included 52% Medicare (44% private insurance) with 27% overall reporting supplemental insurance. Financial Distress: The mean COST score was 26.5 (SD 10.0) with 42% reporting high financial distress. PROMIS-29 domain descriptive statistics appear in Table 1. Higher financial distress was significantly associated with higher anxiety, depression, and pain (all p&lt;0.05). Group Differences: Financial distress significantly differed by gender, education, marital status, employment status, income, insurance type, and distance traveled reported in Table 2. Financial distress was higher: in women than men (p=0.003); in high school graduates vs those who attended some college or more (p=0.03); in divorced versus married individuals (p=0.02); among unemployed or disabled versus employed versus retired people (p=0.04); in those with income &lt;US$50K/year versus US$50K-&lt;$75K/year versus at least US$75K/year (p&lt;0.001); among those with Medicaid vs private insurance versus Medicare (p=0.02); and for those whose distance from Mayo was at least 300 miles vs &lt; 300 miles (p=0.03). Differences in age neared but failed to reach strict statistical significance (age 35-54: mean 22.4, SD 12.1; age 55-64: mean 26.5, SD 9.5; age 65+: mean 28.0, SD 9.2; p=0.051). Financial distress did not significantly differ by race, ethnicity, diagnosis, disease status (newly diagnosed/relapsed), prior transplant, or supplemental insurance, though some subgroups were small. CONCLUSION: Financial distress was prevalent in this well-educated and high earning MM and AL cohort that is able to receive tertiary care at Mayo Clinic. This financial distress was moderate to strongly associated with anxiety and pain intensity, and mild to moderately associated with depression and pain interference. Longitudinal assessment is ongoing. Disclosures Dispenzieri: Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Pfizer: Research Funding; Alnylam: Research Funding; Intellia: Research Funding.

Introduction: Cardiac involvement is one of the main predictors for survival in patients with light chain (AL) amyloidosis. Biomarkers such as Troponin T and N-terminal pro b-type natriuretic peptide (NT-proBNP) are used routinely for detecting cardiac involvement. In addition echocardiogram (ECHO) is used to determine septal and left ventricular wall thickness and strain. Most patients with AL present with preserved ejection fraction (EF) however, the outcomes of AL patients undergoing autologous stem cell transplantation (ASCT) with decreased EF are not very well described. Methods: We retrospectively reviewed patients who had a diagnosis of AL amyloidosis and received ASCT between March 1996 and September 2017. All patients had an ECHO done before ASCT and the EF was documented. In our practice, the threshold for performing ASCT is an EF &gt;40%. We evaluated the outcomes of patients who had an EF &lt;55% compared to patients with an EF ≥55%. The baseline characteristics were compared between patients with high and low EF. 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&gt;65 vs. ≤65 years, Mayo 2012 stage 3/4 vs. 1/2, bone marrow plasma cell percentage (BMPC) ≥ 10% vs. &lt;10%, organs involved &gt;2 vs. ≤2, melphalan conditioning 200mg/m2 vs. 140 mg/m2 ,ASCT year &gt;2010 vs. ≤2010, and EF &lt;55% vs. ≥55%. Results: We identified 716 patients and 69 (10%) had an EF&lt;55%, with most (n=63, 91%)having cardiac involvement . Compared to patients with EF ≥55%, patients with EF &lt;55% were more likely to have Mayo 2012 stage 3/4 (58% vs. 22%, P&lt;0.0001) and more likely to have thicker interventricular septum (median 14 vs. 12 mm, P&lt;0.0001). The day 100 transplant related mortality (TRM) was higher in patients with EF &lt;55% compared to EF ≥55% (19% vs. 6%, P=0.0006). In patients with Mayo 2012 stage 3/4, the day 100 TRM was higher in patients with an EF&lt;55% compared to EF ≥55% (27% vs. 7%, P=0.004). Overall, PFS and OS were significantly shorter in patients with EF &lt;55% compared to patients with EF ≥55% (Figure 1 A,B). Evaluating PFS and OS according to EF specifically in Mayo 2012 stage 3/4 patients is displayed in Figure 1 (C,D). Predictors for PFS included Mayo 2012 stage 3/4 vs. 1/2 (hazard ratio (HR): 1.4, P=0.006), BMPC ≥ 10% vs. &lt;10% (HR: 1.5,P=0.0005), melphalan conditioning 200mg/m2 vs. 140 mg/m2 (HR:0.7, P=0.01), ASCT year &gt;2010 vs. ≤2010 (HR: 0.7, P=0.01), and EF &lt;55% vs. ≥55% (HR: 1.5, P=0.02). For OS, age &gt;65 vs. ≤65 years (HR:1.4, P=0.04), Mayo 2012 stage 3/4 vs. 1/2 (HR: 1.96, P&lt;0.0001), melphalan conditioning 200mg/m2 vs. 140 mg/m2 (HR:0.5, P&lt;0.0001), BMPC ≥ 10% vs. &lt;10% (HR: 1.8, P=0.03), ASCT year &gt;2010 vs. ≤2010 (HR: 0.5, P&lt;0.0001), and EF &lt;55% vs. ≥55%(HR:1.9, P=0.003) were predictive. Conclusion: Having an EF &lt;55% is associated with a higher day 100 TRM and is an independent predictor for PFS and OS in patients with AL amyloidosis undergoing ASCT. Disclosures Sidiqi: Janssen: Honoraria; Amgen: Honoraria; Celgene: Honoraria, Other: Travel grant. Dingli:Alexion: Consultancy; Apellis: Consultancy; Sanofi-Genzyme: Consultancy; Millenium: Consultancy; Bristol Myers Squibb: Research Funding; Karyopharm Therapeutics: Research Funding; Janssen: Consultancy; Rigel: Consultancy. Kapoor:Janssen: Research Funding; GlaxoSmithKline: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy, Research Funding; Celgene: Honoraria; Takeda: Honoraria, Research Funding; Amgen: Research Funding. Dispenzieri:Janssen: Research Funding; Pfizer: Research Funding; Alnylam: Research Funding; Intellia: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Kumar: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; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Tenebio: Other, Research Funding; Genecentrix: Consultancy; Cellectar: Other; Carsgen: Other, Research Funding. Gertz:Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Sanofi: Other; Research to Practice: Other; Celgene: Other; Medscape: Other: personal fee, Speakers Bureau; Proclara: Other; DAVA oncology: Speakers Bureau; Alnylam: Other: personal fee; Johnson and Johnson: Speakers Bureau; Physicians Education Resource: Other: personal fee; Teva: Speakers Bureau; Ionis/Akcea: Other: personal fee; Amgen: Other: personal fee; Springer Publishing: Patents & Royalties; Aurora Bio: Other; Appellis: Other: personal fee; Abbvie: Other; Annexon: Other: personal fee; Prothena: Other: personal fee.

Background: Bortezomib, a proteasome inhibitor, has shown efficacy in the treatment of newly diagnosed and relapsed light chain (AL) amyloidosis, and the combination of bortezomib, cyclophosphamide and dexamethasone is a commonly used regimen in AL. Ixazomib is the first oral proteasome inhibitor to be approved, and the combination of ixazomib with cyclophosphamide and dexamethasone is an all oral effective regimen for the treatment of multiple myeloma. This phase 2 trial was designed to evaluate the efficacy of this regimen in patients with AL, who have not received any therapy. Patients and methods: Newly diagnosed patients with biopsy proven AL amyloidosis, with organ involvement requiring therapy, were enrolled if they had measurable disease (Serum immunoglobulin free light chain ≥5 mg/dL AND abnormal serum free light chain ratio) and adequate organ function. Patients with severe organ involvement were excluded (Alkaline phosphatase &gt;750 U/L, creatinine clearance &lt;30 mL/min or NT-ProBNP ≥ 7500 ng/dL). Treatment consisted of ixazomib 4 mg days 1, 8, 15; cyclophosphamide 500 mg PO weekly and dexamethasone 40 mg, weekly for twelve 28-day cycles, followed by ixazomib maintenance (days 1, 8, 15) at the last tolerated dose till progression. The primary objective was to determine the hematologic response rate of ixazomib, used in combination with cyclophosphamide and dexamethasone in patients with previously untreated AL. A one-stage binomial design was utilized to test the null hypothesis that the hematologic response rate is at most 30% against the alternative hypothesis that it is at least 50%, with 85% power and 9% type I error. Results: Thirty-five patients were enrolled, median age was 67 (range 38-78) years; 69% were male. Organ involvement included cardiac in 23 (65.7%), renal in 19 (54.3%), and nervous system involvement in 5 (14.3%). At data cutoff 8 patients still remain on study with a median follow up of 4.4 months for those who are alive. Across the trial a median of 4 cycles (range 0-23) of treatment have been completed; the most common reason for going off study was institution of alternate therapy in 17 patients (63%). The overall hematologic response was 57% (20/35) and included amyloid CR in 5 (14%), VGPR in 9 (26%) and a PR in 6 (17%) patients. Confirmed organ responses have been observed in 5 patients so far, 2 each for cardiac and renal and 1 hepatic. The median PFS and OS have not been reached; 4 patients had hematological progression; 6 patients (17%) have died. Across 193 cycles of treatment administered, dose modification was required in 5, 3, and 10 patients, respectively, for ixazomib, cyclophosphamide and dexamethasone. A grade 3 or higher adverse event (AE), at least possibly attributed to the study drugs, was observed in 41% of patients. The figure shows the maximum grade of adverse events for individual patients seen in more than one patient across the study. Conclusions: The all-oral regimen of ixazomib, cyclophosphamide, and dexamethasone is active in patients with previously untreated AL amyloidosis with hematologic responses observed in 57% of patients, including complete responses. Organ response has been observed but will likely need longer follow up for accurate assessment, given the delay in organ responses in this disease. Further evaluation of this combination is warranted. Disclosures Gertz: Alnylam: Consultancy; Ionis/Akcea: 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; Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding; NCI SPORE MM: Research Funding; Prothena: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy. Kapoor:Celgene: Honoraria; GlaxoSmithKline: Research Funding; Takeda: Honoraria, Research Funding; Amgen: Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; Cellectar: 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. Dingli:Apellis: Consultancy; Janssen: Consultancy; Sanofi-Genzyme: Consultancy; Rigel: Consultancy; Bristol Myers Squibb: Research Funding; Karyopharm Therapeutics: Research Funding; Alexion: Consultancy; Millenium: Consultancy. Dispenzieri:Janssen: Research Funding; Intellia: Research Funding; Alnylam: Research Funding; Celgene: Research Funding; Pfizer: Research Funding; Takeda: Research Funding. Kumar:Adaptive Biotechnologies: Consultancy; Carsgen: Other, Research Funding; 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; Genecentrix: Consultancy; Dr. Reddy's Laboratories: Honoraria; Tenebio: Other, Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; BMS: Consultancy, Research Funding; Sanofi: Research Funding; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Karyopharm: Consultancy; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; 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; Genentech/Roche: 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; Cellectar: Other; MedImmune: Research Funding.

Background: Multiple myeloma (MM) is a heterogeneous disease that may be evaluated by a broad array of imaging and laboratory techniques to measure disease activity and predict prognosis. FDG PET/CT has been shown to be predictive of patient outcomes throughout the disease course, with several studies demonstrating that PET/CT is an independent prognostic factor for progression free survival and overall survival (OS). We sought to corroborate these findings by specifically examining the prognostic impact of PET/CT in the post-transplant setting. We retrospectively analyzed PET/CT in MM patients after consolidation therapy with autologous stem cell transplant (ASCT) and correlated these findings with time to progression (TTP) and OS to assess the impact of day 100 PET/CT findings as an independent prognostic factor. Methods: A retrospective cohort study was conducted on 231 myeloma patients who underwent ASCT between 2003-2016 and had a FDG PET/CT exam available for analysis at an average of day 104 post-transplant. We recorded the findings on PET/CT prior to transplant, where available. PET/CT without evidence of active/residual disease (PET-) was defined per IMWG guidelines (disappearance of every area of increased tracer uptake found on preceding PET/CT, or uptake &lt; mediastinal blood pool, or decrease &lt; surrounding normal tissue). PET/CT indicating active disease (PET+) was defined as any abnormal uptake or incompletely resolved uptake from previous exam. A Kaplan-Meier model was used to estimate median TTP and OS and the 2-sided log-rank test to compare groups. TTP and OS were calculated from the date of ASCT to the date of confirmed disease progression or death, respectively. Outcomes were then compared among patients with a PET/CT versus those without a PET/CT post-ASCT to assess for the presence of selection bias. A proportional hazards fit model was used for multivariate analysis. Results: The median length of follow-up for the entire cohort was 49 months (range: 43-58 mo), median TTP was 18.5 months (95% CI; 15.4-21.8), and median OS was 61.5 months (95% CI; 49-75). Among the entire cohort (n=231), 150 (65%) patients had a positive PET/CT exam at day 100 post-ASCT while 81 (35%) had a negative PET exam. There were 195 (84%) patients with a PET/CT exam prior to ASCT available for comparison, of which 161 (85%) were PET+ and 29 (15%) were PET-. Median time between PET/CT exams was 4.1 months (range 1.4-55). Median TTP among PET+ patients near day 100 was 12.4 months vs. 24 months PET- patients (p&lt;.0001, Fig 1, panel A). Median OS in the PET+ group was 46 months compared to 99 months in the PET- group (p&lt;.0001, Fig 1, panel B). Among patients with a prior PET/CT (195, 84%), median TTP was longer in patients with both exams negative compared to those who were day 100 PET- and previously PET+ (42.6 mo vs. 21.1 mo respectively; p&lt;.0001). TTP was shorter in those who were day 100 PET+ and previously PET- compared to those with persistently PET+ on both exams (4.5 vs. 12.3 mo; p&lt;.0001, Figure 2). Since PET/CT was not routinely ordered post ASCT, we also compared the outcomes between patients getting a PET/CT (n=231) and remaining patients undergoing ASCT (n=1764). Among patients with a day 100 PET/CT vs. those without a PET/CT exam, there was a slightly longer median TTP and OS in the group who did not have a post-ASCT PET/CT. Hazard ratios (HR) after adjusting for disease response (CR at day 100 vs. non-CR) were as follows: TTP PET+ HR 1.76 (1.2-2.4; p=0.003), OS PET+ HR 1.8 (1.2-2.6; p=.0016). Conclusions: MM is a heterogeneous disease that relies on different assessments for determining response, activity, and prognosis. Among these, PET/CT has shown promise in predicting prognosis, independent of disease state and conventional prognostic factors. Our study confirms these findings, demonstrating that an abnormal PET/CT near day 100 post-transplant is predictive of shorter TTP and OS. This prognostic significance remained even after adjusting for disease response (CR vs. non-CR), which could be explained by the sometimes patchy distribution of myeloma in the bone marrow, and identification of extramedullary disease by PET/CT. Taken together, these results demonstrate a possible role for incorporating PET/CT in the post-transplant setting as an independent prognostic variable in stratifying disease risk. Disclosures Dingli: Apellis: Consultancy; Janssen: Consultancy; Rigel: Consultancy; Millenium: Consultancy; Karyopharm Therapeutics: Research Funding; Sanofi-Genzyme: Consultancy; Bristol Myers Squibb: Research Funding; Alexion: Consultancy. Gertz:NCI SPORE MM: Research Funding; International Waldenstrom Foundation: Research Funding; Amyloidosis Foundation: Research Funding; Springer Publishing: Patents & Royalties; i3Health: Consultancy; Advisory Board for Proclara: Membership on an entity's Board of Directors or advisory committees; Advisory Board for Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; DAVA oncology: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Celgene: Consultancy; Data Safety Monitoring board from Abbvie: Membership on an entity's Board of Directors or advisory committees; Physicians Education Resource: Consultancy; Medscape: Consultancy, Speakers Bureau; Amgen: Consultancy; Appellis: Consultancy; Annexon: Consultancy; Spectrum: Consultancy, Research Funding; Janssen: Consultancy; Sanofi: Consultancy; Prothena: Consultancy; Alnylam: Consultancy; Ionis/Akcea: Consultancy. Dispenzieri:Janssen: Research Funding; Celgene: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Intellia: Research Funding; Takeda: Research Funding. Kapoor:Takeda: Honoraria, Research Funding; Amgen: Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; Celgene: Honoraria; Cellectar: Consultancy; GlaxoSmithKline: Research Funding. Lin:Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy; 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; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding. Kumar:Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Karyopharm: Consultancy; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; 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; Cellectar: Other; Tenebio: Other, Research Funding; Sanofi: Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Genecentrix: Consultancy; MedImmune: Research Funding; BMS: Consultancy, Research Funding.

Background: The absence of residual monoclonal protein in the serum and urine by IFE using specific antibodies to individual heavy and light chains has been an important part of response assessment and is required for categorizing patients as in complete response. MASS FIX has been shown to be more sensitive in picking up small amounts of monoclonal protein and represents an advancement in the field. Ongoing studies are examining the clinical significance of this increased sensitivity. We designed the following study using clinically obtained test results to examine this question. Patients and methods: The clinical laboratory at Mayo Clinic changed the process from IFE to MASS FIX in July 2018. We identified patients who had sequential testing before and after this date and collected test results from the last IFE prior to the date of transition and the first MASS FIX after the date of transition. Patients were grouped based on the paired results and outcomes compared between groups. Time to next therapy (TTNT) was defined as the time from the first MASS FIX date to the start of next therapy. Survival was estimated by the Kaplan-Meier method and these curves were compared using log rank test. Results: Overall, 739 patients with MM, who had a MASS FIX within 12 months of the IFE were studied; 380 (51%) patients had a negative IFE prior to implementation of MASS FIX. These patients had a MASS FIX test performed at a median of 3.7 (0.03-12) months from the last available IFE. The gap between IFE and MASS FIX was &lt;6 months and &lt; 3 months in 71% and 54% of the patients. Among the patients with a negative IFE, 130 (34%) tested positive on the subsequent MASS FIX. Limiting the analysis to those with a MASS FIX within 6 and 3 months yielded 32% in each group that turned positive from previous negative IFE. The median TTNT from the MASS FIX date was significantly shorter for those who became positive on MASSFIX; median was not reached for either group (P=0.002) (Figure). We then limited the analysis to those patients with a gap of &lt;6 months and &lt;3 months between the tests. The results were consistent: P= 0.012 for those with a gap of &lt; 6 months and P=0.01 for those with a gap &lt; 3 months. Conclusion: The results suggest that the additional sensitivity offered by MASS FIX have clinical significance in patients with MM, given that patients with residual disease identified by MASS FIX have an earlier relapse. The data supports the use of the more sensitive MASS FIX in the laboratory compared to the conventional IFE approaches. The study has the disadvantage that the samples were not tested simultaneously and some of the samples turning positive may reflect an early evidence of relapse, but the relative consistency of the finding irrespective of the gap between the tests argues against that. Ongoing studies are examining MASS FIX on the samples that were called to be negative by IFE initially. Figure Disclosures Murray: The Binding Site: Patents & Royalties: Patent Use of Mass Spec to identify monoclonal proteins licensed to The Binding Site. Dispenzieri:Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Intellia: Research Funding; Pfizer: Research Funding; Alnylam: Research Funding. Kapoor:Cellectar: Consultancy; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; Celgene: Honoraria; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Amgen: Research Funding. Gertz:Janssen: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Springer Publishing: Patents & Royalties; Abbvie: Other; Appellis: Other: personal fee; Annexon: Other: personal fee; Celgene: Other; Amgen: Other: personal fee; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Research to Practice: Other; Sanofi: Other; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Proclara: Other; Aurora Bio: Other; Prothena: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee. Dingli:Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Rigel: Consultancy; Sanofi-Genzyme: Consultancy; Millenium: Consultancy; Alexion: Consultancy; Janssen: Consultancy; Apellis: Consultancy. Lin:Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy; Legend BioTech: Consultancy; Merck: Research Funding; Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy. Kumar:Dr. Reddy's Laboratories: Honoraria; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; Tenebio: Other, Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Adaptive Biotechnologies: Consultancy; Kite Pharma: Consultancy, Research Funding; Sanofi: 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; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Merck: Consultancy, Research Funding; MedImmune: Research Funding; Cellectar: Other; Genecentrix: Consultancy; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Novartis: Research Funding.

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 (&gt;65 years), gender, race, proportion exposed or refractory to Bortezomib, number of prior lines of treatment (&gt;2), or HR status (p&gt;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.