Binder, Moritz

e20001 Background: High dose melphalan followed by autologous stem cell transplant (HDM-ASCT) remains the standard of care for transplant-eligible patients with newly diagnosed multiple myeloma (NDMM) despite advances in treatments. Achievement of complete response (CR) is associated with improved overall survival (OS) and progression-free survival (PFS); Minimal Residual Disease (MRD) negativity (-) using next generation flow cytometry with a sensitivity of 10-5 is strongly associated with improved PFS and OS. We investigated the rates of conversion to MRD(-), especially MRD(-) CR following HDM-ASCT in patients with NDMM. Methods: We retrospectively reviewed patients with NDMM who underwent early HDM-ASCT at Mayo Clinic Rochester from May 2018 to July 2019. Response assessment was conducted after induction and within 100 days post-ASCT based on 2016 IMWG criteria, except for using Mass-Fix instead of immunofixation. MRD was assessed in bone marrow using the established Euro Flow protocol with sensitivity of 10-5. The FISH assay was used to risk-stratify patients as high-risk (HR) and standard risk (SR) cytogenetics as per the mSMART guidelines. Primary outcome measure was the conversion to MRD(-) CR after ASCT. Secondary outcomes include the overall conversion to MRD(-) irrespective of IMWG response, the impact of HR cytogenetics and pre-ASCT IMWG response on conversion to MRD(-) CR. Results: Two-hundred and ten patients were included; 126 (60%) were male and median age 62 years (range 32–77 years). There were 78 (44%) patients with HR cytogenetics. Pre-ASCT, 23 patients (11%) achieved MRD(-) CR, and 66 (31%) patients achieved MRD(-) CR post ASCT. Of 187 patients not in MRD(-) CR pre-ASCT, 45 (24%) converted to MRD(-) CR. Table provides a breakdown of the conversion rate of pre-ASCT IMWG response category to MRD(-) CR post ASCT and patients with MRD(+) CR had the highest rate (78%) of conversion. The presence of HR cytogenetics did not impact rates of MRD(-) CR achievement post ASCT irrespective of pre-ASCT IMWG response (p = 1.0). Overall, irrespective of IMWG response, 43 (20%) patients were MRD(-) pre-ASCT (19 in VGPR, 24 in CR or better) and 102 (49%) patients were MRD(-) post-ASCT (36 in VGPR, 66 in CR or better). Among 85 patients in VGPR post-ASCT, 36 were MRD(-) of which 8 (22%) progressed, while 49 were MRD(+) of which 24 (49%) progressed (p = 0.014). Conclusions: Upfront HDM-ASCT in patients with NDMM leads to deeper responses with 24% converting to MRD(-) CR and more than doubling of the total rate of MRD(-) irrespective of IMWG response. [Table: see text]

Abstract Almost all patients with multiple myeloma (MM) eventually relapse, either asymptomatically or with end-organ damage. However, it remains unclear whether initiating therapy at the time of biochemical progression (BP) improves the outcomes compared with initiating therapy at the clinical progression (CP) stage. Here, we retrospectively assessed 1347 patients with relapsed MM. Most progressions were BP (60.4%); 39.6% had CP. The most prevalent symptoms at relapse were new or evolving bone disease (80.9%), anemia (38.0%), and renal failure (12.7%). Patients with BP had longer median time from second-line treatment to the next treatment compared with patients who had CP (17.0 vs 9.6 months; P < .001) as well as longer median overall survival from first relapse (59.4 vs 26.2 months; P < .001). Male sex (odds ratio [OR], 1.49; 95% confidence interval [CI], 1.02-2.18; P = .04), plasma cell labeling index ≥2% (OR, 1.58; 95% CI, 1.02-2.45; P = .04), and extramedullary disease at diagnosis (OR, 1.84; 95% CI, 1.08-3.13; P = .03) were associated with higher risk of CP, whereas very good partial remission or better had decreased risk of CP (OR, 0.62; 95% CI, 0.43-0.91; P = .02). To conclude, patients with CP have inferior postprogression outcomes compared with patients who have BP. Patients with deeper response to first-line therapy are less likely to develop CP. The presence of a specific CRAB (C, hypercalcemia; R, renal failure; A, anemia; B, bone disease) symptom at diagnosis predicts for the development of similar CRAB symptoms at relapse.

Abstract Multiple myeloma (MM) is a plasma cell malignancy that is characterized by diverse clinical presentations. Although biochemical assessment of disease activity is commonly used to monitor treatment response, findings on magnetic resonance imaging and positron emission tomography (PET)/computed tomography (CT), among other imaging modalities, have proven to harbor prognostic value. We sought to corroborate these findings by examining the prognostic significance of fluorodeoxyglucose PET/CT scanning in the setting of newly diagnosed MM. We retrospectively analyzed 195 patients with a PET/CT available at diagnosis and at 6 months posttreatment to examine their value as an adjuvant metric to conventional hematologic responses in terms of time to next treatment (TTNT) and overall survival (OS). The median TTNT and OS for the entire cohort were 24.6 months (95% confidence interval [CI], 20.4-29.1) and 79 months (95% CI, 63.1-119.1), respectively. When comparing PET/CT negative (−) with PET/CT positive (+) patients, we found significantly prolonged median TTNT (55.2 vs 17.8 months, P < .0001) and OS (unreached vs 60.8 months, P < .0001) in the former group. We then examined the additive value of PET/CT on the hematologic response achieved at 6 months and found that PET/CT (−) is associated with significantly increased median TTNT and OS for the very good partial response (VGPR) group and the less than VGPR group. Importantly, PET/CT retained prognostic significance after adjusting for multiple other predictive variables. We conclude that a PET/CT (−) at 6 months confers a significant prognostic advantage for patients with newly diagnosed MM and adds significant value to the hematologic response assessment.

AbstractCastleman disease (CD) is a rare lymphoproliferative disease characterized by diverse clinical and pathologic features. Due to its rarity, there are limited studies comparing currently available therapies. The role of autologous stem cell transplantation (ASCT) in CD has not yet been established. In this paper, we describe the clinical characteristics, treatment choices, and outcomes in 34 Mayo Clinic patients diagnosed with multicentric CD from July 1, 2003 to April 30, 2018. Eighteen patients (53%) also met the criteria for POEMS, including 14 with the osteosclerotic variant. The first‐line treatments included: steroid monotherapy (4), cytotoxic chemotherapy (6), rituximab alone (8) or with chemotherapy (2), anti‐IL6 treatment (3), and ASCT (10). The median follow‐up was 4.8 (range: 0.1–15.2) years. The 5‐ and 10‐year overall survival rates were 84% and 71%, respectively. Sixteen patients received high‐dose chemotherapy followed by ASCT during their disease course. Among those, 14 had multicentric CD associated with POEMS. There were no transplant‐related deaths. All patients had at least a partial response to ASCT, most of whom achieved a complete response. The favorable outcomes seen with ASCT in this cohort suggest that transplantation may have a role in multicentric CD, particularly for patients with multicentric CD associated with POEMS.

AbstractAchievement of a complete response (CR) in multiple myeloma (MM) correlates with improvement in survival outcomes; however, its impact on prognostic variables at baseline outside of clinical trial settings is not well described. We sought to determine the impact of achieving a CR within 2 years from diagnosis, its effect on the prognostic value of fluorescence in situ hybridization (FISH) and International Staging System (ISS) risk, and examined additional predictors of outcome among those achieving a CR in a routine clinical setting. We evaluated 1869 newly diagnosed MM patients who had ≥ 2 monoclonal protein immunofixation studies in the serum and urine available within 24 months from diagnosis, categorizing those with ≥ 2 negative serum and urine immunofixations as achieving CR. With a landmark at 24 months, median progression‐free survival (PFS) for CR versus non‐CR patients was 29.8 versus 20.9 months (p ≤ .0002); median overall survival (OS) was 104 versus 70 months (p < .0001). The impact of achieving a CR was retained after adjusting for FISH, ISS, sex, transplant status, and involved heavy chain. Baseline FISH and ISS stage were not associated with PFS or OS among patients achieving a CR. The following variables were found as predictors of inferior OS within the CR cohort: age > 75 years, male gender, hypoalbuminemia, and non‐immunoglobulin G involved heavy chain. Our study confirms that achievement of CR within 2 years from diagnosis is associated with improvement in survival outcomes and neutralization of the impact of FISH and ISS risk, thereby confirming observations from the clinical trial setting among a clinical practice cohort.

Abstract Background: There has been a steady improvement in the survival of patients with multiple myeloma (MM) due to better understanding of the pathophysiology, use of novel agents, and risk-adapted therapy. These improvements were largely observed in clinical trials and tertiary center populations and questions remain about the generalizability of these findings to patients in community settings. Here, we compared the experience of patients seen at Mayo Clinic, Rochester (MAYO) and those followed in the Surveillance, Epidemiology, and End Results Program (SEER), to gain a better understanding of current trends in survival. Methods: We studied all patients with MM diagnosed between 01/2004 and 12/2018 seen at MAYO and those followed in SEER (18 registry research data 2000-2018, 11/2020 submission). For comparison with SEER, MAYO patients who were alive at the end of SEER follow-up (12/31/2018) were censored. For the estimation of relative survival, patients alive at the end of 2019 were censored to align with the published United States general population rate tables. Overall survival (OS) estimates were calculated using the method described by Kaplan and Meier. Multivariable-adjusted proportional hazards regression models were used to assess the association between the 5-year interval of diagnosis and overall survival. Expected OS estimates were calculated based on United States general population rate tables from the Human Mortality Database using a conditional approach. Standardized mortality ratios (SMR) were calculated by dividing the number of observed deaths by the number of expected deaths in age- and sex-matched general United States population controls. Linear regression models were fit to test for trends in SMRs over time. Results: The median age at diagnosis was 3 years lower in patients seen at MAYO compared to patients followed in SEER. The proportion of patients 75 years and older at the time of diagnosis was higher in SEER (26.3%) compared to MAYO (15.3%). Median OS was 6.7 years (95% CI 6.3-7.1) for MAYO compared to 4.6 years (95% CI 4.5-4.7) in SEER (Figure 1). When stratifying OS by year of diagnosis (in 5-year-intervals: 2004-2008, 2009-2013, 2014-2018), improvements were seen in both patient populations over time, albeit to a greater extent in patients seen at MAYO (Figures 2 and 3). The results were consistent after adjusting for age and sex in both MAYO and SEER. There were improvements in OS across all three 5-year intervals and age groups in both patient populations. In MAYO, these improvements were most pronounced during the second 5-year interval for younger patients (&lt; 65 years) and more pronounced during the last 5-year interval for older patients (&gt; 65 years). In SEER, the improvements were more gradual across the three 5-year intervals, but it was noted that the relative improvements in younger patients were greater than in older patients during the last 5-year interval. Early mortality decreased over time in both patient populations: from 11% to 6% at MAYO and from 23% to 16% in SEER (Figure 4). To examine the observed improvements in the context of the survival trends of the general population, we stratified the SMRs by patient population, age at diagnosis, and year of diagnosis, and a lack of improvement in excess mortality was observed among older patients (&gt;75 years) in both populations over time (Figure 5). Three- and five-year overall survival estimates were higher in patients seen at MAYO compared to patients followed in SEER, but the survival advantage diminished with increasing follow-up time (Figure 6). On further sub-group analysis within MAYO patients, excess mortality was observed for all International staging system (ISS) stages and patients with high-risk (HR) cytogenetics. Stratifying the SMRs by age and risk group, decreases in excess mortality were most pronounced among older patients, particularly those with indolent disease (Figure 7). Conclusions: Survival outcomes in MM continued to improve in both patient populations. These improvements were more pronounced in MAYO compared to SEER, which may be partially explained by differences in access to specialized care. The most pronounced improvements were observed among younger patients and those with favorable disease characteristics. Future efforts need to focus on improving therapies for patients with unfavorable disease characteristics and on increasing access to specialized care in community settings. Figure 1 Figure 1. Disclosures Kapoor: Glaxo SmithKline: Research Funding; Takeda: Research Funding; Sanofi: Research Funding; Amgen: Research Funding; Sanofi: Consultancy; Pharmacyclics: Consultancy; Ichnos Sciences: Research Funding; BeiGene: Consultancy; Regeneron Pharmaceuticals: Research Funding; AbbVie: Research Funding; Karyopharm: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy. Dingli: Alexion: Consultancy; Apellis: Consultancy; Janssen: Consultancy; Novartis: Research Funding; GSK: Consultancy; Sanofi: Consultancy. Gertz: Ionis Pharmaceuticals: Other: Advisory Board; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy. Lin: Novartis: Consultancy; Celgene: Consultancy, Research Funding; Juno: Consultancy; Takeda: Research Funding; Gamida Cell: Consultancy; Vineti: Consultancy; Merck: Research Funding; Bluebird Bio: Consultancy, Research Funding; Legend: Consultancy; Sorrento: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding. Dispenzieri: Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding; Takeda: Research Funding; Oncopeptides: Consultancy; Alnylam: Research Funding; Pfizer: Research Funding. Kumar: Tenebio: Research Funding; Amgen: Consultancy, Research Funding; Oncopeptides: Consultancy; Bluebird Bio: Consultancy; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Antengene: Consultancy, Honoraria; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Abstract Background: SARS-Cov-2 infections are associated with increased mortality and morbidity, largely due to inflammatory cascades and cytokine release syndrome (CRS). Clonal hematopoiesis of indeterminate potential (CHIP) is defined by the presence and subsequent expansion of somatic, leukemia-associated driver mutations in apparently healthy individuals with normal blood counts. CHIP has been associated with increased inflammation, with cytokines such as IL1-b, IL6 and TNF-a being elevated at baseline in affected individuals. We hypothesized that the presence of CHIP in patients with COVID-19 would result in excessive inflammation-related mortality and morbidity. Methods: We used the Mayo Clinic COVID-19 database to identify patients with COVID-19 on whom peripheral blood mononuclear cells (PBMC) were available for research use (IRB approved). We carried out target-capture next generation sequencing for 220 CH related genes, by previously described methods (1000 x coverage, variant allele fraction/VAF detection limit &gt;0.5%; Kusne Y et al AJH 2021). CHIP was defined by the presence of a CH mutation with a VAF&gt;1% in an individual with normal baseline blood counts. Demographics, blood counts, and inflammatory markers (CRP and cytokine levels- ELISA assay) at COVID-19 diagnosis and during follow-up (as clinically indicated) were collected. COVID-19 disease severity was classified based on the presence and severity of CRS, graded using the Penn Grading Scale (Porter et. al., 2018), and the WHO ordinal scale (WHO Blueprint, 2020). We used Fisher's exact test and the Wilcoxon rank sum test to compare categorical and continuous variables. Survival analysis was performed using the Kaplan-Meier method. We accounted for differences in age and sex using multivariable-adjusted proportional hazards regression models. Results: Seventy-two CHIP mutations were detected in 56 (25%) of the 227 patients with COVID-19 that had PBMC available; median age 69 years (range; 42-99 years), 61% male. Fifteen (26%) patients had 2 CHIP mutations, while 1 patient had 3 CHIP mutations. Common mutations encountered included DNMT3A (32%) , TET2 (19%) , SF3B1 (8%) , ASXL1 (6%) , MPL (5%) , and TP53 (5%; Figure 1A). COVID-19 patients with CHIP were older in age (median 69 vs 57 years; p&lt;0.0001) and had higher baseline MCP-1 (p=0.04) levels. However, there were no differences in sex, comorbidities, blood counts, IL1-b, IL6 and TNF-a levels between the two groups. The median follow-up for the entire cohort was 9 months. The relative change from baseline in blood counts and inflammatory markers (CRP and cytokines) during follow-up was similar in CHIP and non-CHIP patients, with the exception that COVID-19-onset neutropenia was more common in CHIP patients (8% vs 1%; p=0.017) compared to those without CHIP. At last follow up neutropenia had resolved in all patients. Both groups had comparable number of patients with CRS (61% CHIP vs 53% non-CHIP patients, p=0.354, Figure 1B), however, CHIP patients had more severe CRS (median Penn Grade 3 versus 2 in non-CHIP, p=0.018, Figure 1C). Based on the WHO ordinal scale, CHIP patients were more likely to experience hospitalization with severe disease and death (61% versus 45% in non-CHIP, p = 0.049). Moreover, COVID-19 CHIP patients experienced worse overall survival in comparison to patients without CHIP (median 13.1 months vs not reached, p&lt;0.001, Figure 1D). This association remained consistent after adjusting for age and sex at the time of COVID-19 diagnosis (HR 3.15, 95% 1.32 - 7.55, p = 0.010). At last follow-up, 22 deaths were documented: 13 (23%) in patients with CHIP and 9 (5%) in the non-CHIP group (p=0.02), with the primary cause for mortality being hypoxic respiratory failure (62% in CHIP vs 44% non-CHIP, p=0.04). Conclusions: In this study, we observe an age-independent impact of CHIP on COVID-19 associated inflammatory morbidity (CRS) and mortality (hypoxemic respiratory failure). We are currently carrying out detailed single cell (ssDNA, RNA and ATAC-seq) and proteomic studies (O-link PEA assays) to better elucidate this pathophysiology. Figure 1 Figure 1. Disclosures Patnaik: Kura Oncology: Research Funding; StemLine: Research Funding.

Abstract Introduction: Clonal hematopoiesis of indeterminate potential (CHIP) is defined by the presence and subsequent expansion of leukemia-associated driver mutations (MT). These MT predominantly involve epigenetic regulators such as DNMT3A, ASXL1, and TET2 (DAT, 75%). CHIP is a disease of aging and is associated with increased all-cause mortality. Clonal Hematopoiesis (CH), when present in the context of unexplained cytopenias and MT variant allele fractions (VAF) &gt;20%, is termed as clonal cytopenias of undetermined significance (CCUS). Chronic myelomonocytic leukemia (CMML) is a hematological malignancy characterized by TET2, ASXL1, and SRSF2MT as well as sustained monocytosis. It usually arises in the setting of existing CH and clonal monocytosis. Here, we assessed the clonal compositions involving DAT genes in patients (pts) with CHIP, CCUS, and CMML. Methods: We included 1008 pts: 54 (5%) with CHIP, 334 (33%) with CCUS, and 620 (62%) with CMML. Demographics, laboratory parameters, and mutational spectrum at diagnosis were collected. We characterized and compared DAT MT in all three cohorts and assessed correlations with clinical parameters. MT locus and type along with protein sequences were analyzed using ProteinPaint. All statistical analyses were performed using R. Results: Of the 1008 pts, 427 (42%) had DAT MT; 36 had CHIP (67%); 96 had CCUS (29%), and 296 had CMML (48%). The median age was 71 years (IQR 65-76), and 68% were male. CMML pts had higher white blood cell counts, absolute neutrophil counts, absolute monocyte counts, and lower hemoglobin and platelet counts in comparison to CCUS and CHIP pts. The distribution of age and sex were similar among the three groups. After a median follow-up of 11 months (IQR 9.5-12.8), there were no myeloid progressions in the CHIP group and 17 (18%) in the CCUS group (8 of which developed CMML, Table 1). There were 738 protein-altering or splice-site DATMT in 495 unique MT hotspots. Pts with TET2MT were older (71 years, compared to DNMT3AMT: 69 years and ASXL1MT: 69 years , p&lt;0.022). ASXL1MT were more common in males (75%, compared to DNMT3AMT: 52% and TET2MT: 66%, p=0.005). The mean VAF (mVAF) were 15.5% for DNMT3AMT, 35% for ASXL1MT and 39.2% TET2MT, respectively (p&lt;0.001). We then compared DATMT characteristics in CHIP, CCUS, and CMML groups: DNMT3AMT were most common in CHIP, followed by CCUS, and were very rare in CMML (35% vs. 15% vs. 3%, p&lt;0.001), with mVAF of DNMT3AMT increasing across this spectrum (CHIP: 6.5% vs. CCUS: 17.1% vs. CMML: 43.4%, p&lt;0.0001). While DNMT3A missense MTs were most common (n=62, 67.4%), the AML-associated R882 hotspot MT was seen in 26 (28%) pts (CHIP: n=3, 5%, CCUS: n=10, 16%, and CMML n=13, 21%, Figure 1a). None of the DNMT3AMT CHIP and CCUS pts progressed to CMML.ASXL1MT were most frequently seen in CMML (n=178, 28.6%), followed by CHIP (n=4, 7.4%), and CCUS (n=17, 5%, p&lt;0.001). The mVAF of ASXL1MT was significantly lower in CHIP, followed by CCUS, and CMML (11% vs. 34% vs. 36%, p&lt;0.0001). Truncating ASXL1 MTs were most common (n=205, 53%). Mutational hotspots included G646W (n=81, CCUS: n=6, 3%, CMML: n=75, 37%) and E635 (n=27, CHIP: n=1, 0.5%, CCUS: n=1, 0.5%, CMML: n=27, 13%, Figure 1b). Four ASXL1MT CCUS pts transformed to CMML (R965, E635, G646W, Q910*, and Q925*); of which 2 co-mutated with TET2MT, one with SRSF2MT, and one with an additional ASXL1MT.TET2MT were frequently encountered in CMML, followed by CCUS and CHIP pts (CMML: n=205, 33% vs. CCUS: n=88, 26.3% vs. CHIP: n=15, 27.8%, p=0.02). The mVAF of TET2MT progressively increased across the 3 groups (CHIP: 14.1%, CCUS: 31.9%, CMML: 45.5%, p&lt;0.001). TET2MT occurred across the span of the gene, with no clear hotspots identified, with nonsense MT being most frequent (n=150, 37.3%, Figure 1c). Among the nonsense and frameshift TET2MT (n=209), 131 (63%) involved the N terminal region, and 78 (37%) involved the catalytic domain. Among 8 CCUS pts that transformed to CMML, 6 had TET2MT, including 4 with spliceosome co-MT. Conclusion: While CMML, a disease of aging, arises in the background of CH, the most common CH MT, DNMT3AMT, plays a minor role in this process, and in fact, DNMT3AMT tend to occur at younger ages. While DNMT3A MT and ASXL1MT are preferentially observed in hotspots, TET2MT span the entire gene. Clonal compositions largely involving truncating TET2MT and frameshift ASXL1MT, in conjunction with splicing MT, shape the CMML genotype. Figure 1 Figure 1. Disclosures Komrokji: Geron: Honoraria; Novartis: Honoraria; Agios: Honoraria, Speakers Bureau; Abbvie: Honoraria, Speakers Bureau; JAZZ: Honoraria, Speakers Bureau; BMS: Honoraria, Speakers Bureau; Acceleron: Honoraria. Zeidan: Genentech: Consultancy; BeyondSpring: Consultancy; Kura: Consultancy, Other: Clinical Trial Committees; Amgen: Consultancy, Research Funding; Cardiff Oncology: Consultancy, Other: Travel support, Research Funding; Astex: Research Funding; Epizyme: Consultancy; Geron: Other: Clinical Trial Committees; Boehringer Ingelheim: Consultancy, Research Funding; AstraZeneca: Consultancy; Acceleron: Consultancy, Research Funding; Astellas: Consultancy; Novartis: Consultancy, Other: Clinical Trial Committees, Travel support, Research Funding; Agios: Consultancy; Aprea: Consultancy, Research Funding; AbbVie: Consultancy, Other: Clinical Trial Committees, Research Funding; Loxo Oncology: Consultancy, Other: Clinical Trial Committees; Pfizer: Other: Travel support, Research Funding; ADC Therapeutics: Research Funding; Gilead: Consultancy, Other: Clinical Trial Committees; BMS: Consultancy, Other: Clinical Trial Committees, Research Funding; Jazz: Consultancy; Incyte: Consultancy, Research Funding; Ionis: Consultancy; Jasper: Consultancy; Daiichi Sankyo: Consultancy; Janssen: Consultancy; BioCryst: Other: Clinical Trial Committees. Coombs: LOXO: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Genentech: Honoraria; MEI Pharma: Honoraria. Madanat: Blue Print Pharmaceutical: Honoraria; Stem line pharmaceutical: Honoraria; Onc Live: Honoraria; Geron Pharmaceutical: Consultancy. Griffiths: Takeda Oncology: Consultancy, Honoraria; Novartis: Honoraria; Taiho Oncology: Consultancy, Honoraria; Apellis Pharmaceuticals: Research Funding; Alexion Pharmaceuticals: Consultancy, Research Funding; Boston Biomedical: Consultancy; Astex Pharmaceuticals: Honoraria, Research Funding; Celgene/Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Genentech: Research Funding; Abbvie: Consultancy, Honoraria. Lai: Jazz Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astellas: Speakers Bureau; Jazz Pharma: Speakers Bureau; Macrogenics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Savona: CTI: Consultancy, Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; BMS-Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; NOVARTIS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Taiho: Consultancy, Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; ALX Oncology: Research Funding; Astex: Research Funding; Incyte: Research Funding. Litzow: AbbVie: Research Funding; Actinium: Research Funding; Pluristem: Research Funding; Amgen: Research Funding; Astellas: Research Funding; Jazz: Other: Advisory Board; Omeros: Other: Advisory Board; Biosight: Other: Data monitoring committee. Al-Kali: Novartis: Research Funding; Astex: Other: Research support to institution. Patnaik: StemLine: Research Funding; Kura Oncology: Research Funding.

Abstract Background: MASS-FIX is a screening method for serum and urine monoclonal proteins in multiple myeloma and related plasma cell disorders, which uses immunoglobulin enrichment coupled with matrix-assisted laser desorption ionization time-of-flight mass-spectrometry (MALDI-TOF). In addition to superior sensitivity over conventional gel-based techniques, MASS-FIX can distinguish therapeutic monoclonal antibodies (MoAb) from patient's M protein. As the utilization of therapeutic MoAbs increases, it is essential to understand the persistence pattern of these therapeutic antibodies in the serum. We designed this study to evaluate the duration of daratumumab detection by MASS-FIX in the serum of treated patients. Methods: We used a prospectively maintained database at Mayo clinic to identify patients with multiple myeloma and related plasma cell disorders who were treated with a daratumumab-containing regimen anytime during their disease course and had serial MASS-FIX data available after discontinuation of daratumumab. A univariate analysis was performed to assess for factors that may impact the clearance of daratumumab. Results: We included 125 patients with plasma cell disorders who received daratumumab as first or subsequent line of treatment between March 15 th, 2016, and March 4 th, 2020. The median age was 60.2 years and 57% were male. The most common diagnoses were multiple myeloma (70%) and light chain amyloidosis (18%). Daratumumab-based treatments were initiated after a median of 28.8 (IQR: 6.4-76.3) months from initial diagnosis. The most common regimen used was daratumumab, bortezomib and dexamethasone (23%); 26% underwent transplant after daratumumab-based induction. The median duration of treatment with a daratumumab-based regimen was 208 (IQR: 99-479) days. The median follow-up from the time of daratumumab discontinuation was 457 (95% CI: 346-NR) days. By last follow up, daratumumab was not detected by MASS-FIX in 93 (74%) patients but remained detectable in 32 (26%) patients. The median time from daratumumab discontinuation to disappearance of daratumumab by MASS-FIX was 160 (IQR: 107-233) days. On univariate analysis, the presence of ≥0.5 grams of urine protein was associated with earlier disappearance of daratumumab on MASS-FIX [risk ratio (RR): 2.0, P=0.02). The median time from daratumumab discontinuation to disappearance of daratumumab on MASS-FIX was 116 (95%CI: 76-160) days in patients with urine protein ≥0.5 grams and 203 (95%CI: 162-216) days in patients with urine protein &lt;0.5 grams (P=0.02). There was no association between the time to disappearance of daratumumab by MASS-FIX and old age ≥70 (RR: 0.9, P=0.81], male gender (RR: 0.9, P=0.60), eGFR &lt;60 (RR: 1.0, P=0.98), daratumumab schedule (every 1/2 weeks vs &gt;2weeks) (RR: 1.0, P=0.97), treatment duration (&lt;200 days vs ≥200 days) ( RR: 1.0, P=0.95), or transplantation status (RR: 1.0, P=0.98). Conclusion: The therapeutic monoclonal antibody daratumumab remains detectable in the serum of treated patients by MASS-FIX for several months after discontinuation and the duration varies between individual patients. This data has implications for diagnostic and monitoring testing and may provide guidance for reuse of daratumumab in clinical trials and practice. Proteinuria is associated with earlier disappearance of daratumumab by MASS-FIX and may have implications in patients with amyloidosis and monoclonal immunoglobulin deposition disease (MIDD). Further studies are needed to identify additional factors associated with the timing of disappearance. Disclosures Murray: Mayo Clinic: Other: Has received patents for the Mass-Fix technology which has been licensed to the Binding Site with potential royalties.. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring. Dingli: Alexion: Consultancy; Novartis: Research Funding; Apellis: Consultancy; Janssen: Consultancy; Sanofi: Consultancy; GSK: Consultancy. Kumar: Antengene: Consultancy, Honoraria; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Merck: Research Funding; Roche-Genentech: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Oncopeptides: Consultancy; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Carsgen: Research Funding; Tenebio: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.