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Abstract Background: Normalization of serum free light chain ratio (FLCr) following achievement of a complete response (CR) to therapy denotes a stringent CR in multiple myeloma, and is associated with improved overall survival (OS). However, its value in patients achieving less than a CR is not clear. We hypothesized that patients in whom FLCr normalizes with the initial anti-myeloma therapy will have an improved outcome, even in the absence of a CR. Methods: We analyzed the medical records of patients with MM who were evaluated at Mayo Clinic, Rochester, MN between January 2004 and December 2011, seen within 90 days of diagnosis. We selected patients with measurable disease on serum protein electrophoresis, defined as a serum M-spike ≥1 g/dl at the time of diagnosis. Then, we excluded all patients with negative immunofixation for monoclonal M-protein in serum and urine at their first response as well as those who did not have serum FLC results available from the time of their first best response. M protein measurements were collected serially from the time of diagnosis until the time of the first relapse or last follow up date if no relapse was recorded. Progression-free survival (PFS) and OS were analyzed using the Kaplan-Meier method. Results: Out of the 1354 MM patients seen at our institution during this period, a total of 453 patients were included in our study. The median age of the cohort at the time of diagnosis was 65 (range, 29-91); 49% were older than 65 years and 284 (63%) were male. The estimated median follow up for the whole cohort was 66 months (95% CI; 61, 71); 241 patients were alive with a median follow up of 4.7 years (range, 0.4 to 10). Three hundred and seventy three (82%) patients had relapsed following the initial therapy with a median time to progression (TTP) of 19.5 months (95% CI; 18, 22) and PFS of 19 months (95% CI; 17, 20). The median OS for the entire cohort is 67 months (95% CI; 59, 73). The median time to the best first response was 6.9 months (range: 0.3-83 months). At the time of the best first response 154 patients (34%) had normal FLCr. Patients with normal FLCr had a longer PFS (29 vs. 16 months, P< .0001) and OS (91 vs. 58 months, P= .0002). We then examined the impact of FLCr normalization on survival outcomes according to their IMWG response categories. We found that FLCr normalization had a favorable impact on PFS in each of the three groups [very good partial response (VGPR), Partial response (PR), and Stable disease (SD)], However, when looking at the OS, only patients with PR had a better OS associated with a normal sFLC κ/λ ratio (Table 1). Conclusions: Obtaining a normal sFLC ratio appears to confer a more favorable prognosis irrespective of the depth of the response, suggesting an important role for serial-sFLC measurements in disease monitoring even in patients who achieve only a PR to therapy as their best response. This supports the inclusion of sFLC at all levels of response included in the current International Myeloma Working Group (IMWG) criteria. Abstract 3427. Table 1 Effect of FLCr normalization according to IMWG response categories SD PR VGPR Normal FLCr Abnormal FLCr p-value Normal FLCr Abnormal FLCr p-value Normal FLCr Abnormal FLCr p-value Number of patients 7 70 62 157 85 60 PFS, month, median (95% CI) 27 (14, 36) 7 (5, 12) < .02 26 (20, 36) 17 (13, 20) .0005 29 (23, 32) 21 (18, 26) .03 OS, months, median (95% CI) 68 (49, 68) 41 (31, 61) > .1 NR (65, NR) 61 (50, NR) .004 74 (67, 107) 73 (59, NR) > .9 • Abbreviations: NR; statistically not reached •• Progressive disease (PD) was not included because none of the 12 patients achieved a normal FLCr. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Multiple Myeloma (MM) patients have a substantially reduced Health related Quality of Life (HQOL) at diagnosis (dx) due to disease related symptoms like bone pain (58%) and fatigue (32%). HQOL monitoring is becoming increasingly important, owing to improved survival and the impact of treatment-related toxicity. As a result HQOL assessments are increasingly being used in clinical trials, but the literature regarding the relationship between HQOL and outcomes in MM is sparse. We used the Mayo Clinic “Hematology Patient Reported Symptom Screen” (HPRSS) to assess the impact of HQOL on outcomes in newly dx patients with MM. Methods:We retrospectively reviewed charts of 453 patients with newly dx MM seen at Mayo Clinic, Rochester from 2009 to 2014. All patients who visit Mayo clinic hematology clinic complete a 3-point questionnaire (HPRSS) on pain, fatigue and quality of life (QOL) (scored on a scale of 0-10; with 0 being the least fatigue or pain and 10 being the best QOL). Pain, fatigue and QOL scores documented at the time of dx and at 6 months were collected. JMP version 10 was used for the data analysis. Results: The median age at diagnosis was 67 years (range, 33-95); 60% were male. The estimated median OS for the cohort was 21 m (95% CI19, 23); 387 (85%) of the patients were alive at last follow up and the median OS for the population was not reached. The median (IQR) scores for pain, fatigue and QOL were 4 (2, 6), 3 (1, 5), and 7 (5, 9), respectively. First, we examined the relationship between each of the scores (dichotomized at the median) and the baseline characteristics. Higher fatigue scores were associated with lower Hb and serum albumin and higher beta 2 microglobulin, LDH and marrow plasmacytosis. Higher pain scores were seen in female patients, and associated with higher B2M, serum calcium and lytic bone lesions. Lower QOL scores were associated with lower absolute lymphocyte count and serum albumin levels. Next, we examined the relationship between the scores and the OS from diagnosis. The overall survival was inferior for patients with higher pain scores, fatigue scores and lower QOL scores (Figure). In a multivariable analysis, fatigue scores were most strongly associated with survival outcome. Patients with adverse scores in two or more of pain, fatigue and QOL had significantly inferior outcomes (Figure). In univariate analysis, age, B2M, LDH, FISH high risk and the presence of two or more adverse scores were all significantly associated with poorer OS. In a multivariable analysis, age, LDH and the presence >=2 adverse scores were all associated with shorter OS. Of the 453 patients included in the study, 222 patients had pain, fatigue and QOL scores at 6 month from diagnosis. At 6 months, the median (IQR) scores for pain, fatigue and QOL were 2 (1, 5), 4 (2, 5), and 7 (5, 9), respectively; suggesting improved pain, worsened fatigue and static QOL scores. Improvement in the scores by at least one point was seen in 50%, 49% and 38% for the fatigue, pain and QOL scores. While the pain and fatigue scores at 6 months correlated inversely with OS, improvements in the scores in any of the three were not associated with any improved outcomes. Conclusion: A simple, patient reported scoring system for pain, fatigue, and overall perceived QOL at the time of diagnosis is a powerful predictor of survival outcomes in patients with newly diagnosed MM and should be considered routinely in clinical practice. The results of these patient reported measures can be utilized to develop risk-adapted trials in patients with MM. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Race/ethnicity is associated with disparate incidence and outcomes in MM, as seen in population-based studies. Their effect on outcomes has not been reported in prospective studies. Obesity is the most consistently associated modifiable risk factor for MM and is influenced by race/ethnicity but its association with outcomes has not been explored. We analyzed patient-level data from published ECOG-ACRIN/SWOG clinical trials in newly diagnosed MM (NDMM) patients (pts) to explore the interplay of race/ethnicity, obesity and outcomes. Methods: Pooled data from 9 ECOG-ACRIN/SWOG clinical trials (E1A06, E4A03, E1A00, E2A02, E5A93, E9486, S0204, S0232, S9321) in NDMM (1988-2011) were analyzed. Pts were divided by race: White (W), African-American (AA), other (O); race/ethnicity: Hispanic (H), non-Hispanic White (NHW), non-Hispanic AA (NHAA), non-Hispanic other (NHO); and body mass index (BMI): <25, 25-29.9, ≥30. Associations between these and baseline pt/disease characteristics were assessed using chi-square (categorical) and Wilcoxon rank sum (continuous) tests. Survival distributions were estimated with Kaplan-Meier method and compared between groups using log-rank test. Cox proportional hazards regression was used to estimate hazard ratios in univariate and multivariate models. Time to event data was censored at 6 yrs. Results: Pt distribution by race, race/ethnicity and BMI is shown in Table 1. Race: AA were younger than W (median 59 vs 62 yr), had significantly more females (48% vs 40%; p=0.001) and had a smaller proportion of pts ≥70 yr (18% vs 26%; p<0.001). Median BMI was highest in AA (27.2) and lowest in O (24) (p=0.001) but not significantly different categorically between W and AA only (p=0.908). AA had significantly more pts with hemoglobin (Hb) ≤10 g/dL than W (55% vs 36%; p<0.001). Median creatinine (Cr) was 1.3 mg/dL in O and 1.1 mg/dL in W (p=0.03). There were no differences by race for ECOG performance status (PS), MM stage, lytic lesions, paraprotein subtype, serum calcium (Ca) or β2-microglobulin (β2M). Enrollment to clinical trials over years was significantly different by race (p=0.009). The only study design showing different enrollment by race was with/out stem cell transplant (SCT) (p=0.03; 37% of AA vs 31% of W got SCT trials). Race/Ethnicity: NHO were the youngest (median 58 yr) and NHW the oldest (median 62 yr) subgroup (p<0.001). NHAA had the highest proportion of pts with BMI ≥30 (16%) and NHO the lowest (7%) (p=0.018). H had the smallest proportion of females (33%) while NHO had the largest (54%) (p=0.002). H had the highest number of pts ≥70 yr (28%) and NHAA the smallest (18%) (p=0.003). Anemia rates were significantly different (p<0.001) with Hb ≤10 g/dL in 36% NHW vs 56% in NHAA. No significant differences were seen for PS, MM stage, lytic lesions, paraprotein subtype or other lab parameters. H and NHAA were enrolled in larger numbers in 1992-2011 rather than prior or later years (p<0.001). Among the subgroups, H had largest proportion of patients (75%) on trials without novel agent vs 61.5% for NHW (p=0.047). NHAA had the highest proportion of patients on trials with SCT (38%) while NHO had the smallest (27.3%) (p=0.034). BMI: By gender, 30% of males and 39% of females having BMI <25 (p<0.001). BMI <25 had the highest proportion of pts with ISS stage III (31%) vs 21.5% for ≥30 (p=0.001). A similar trend was seen for DS stage (p=0.005). 64% of ≥30 pts had Hb >10 while 51% of <25 did (p=0.003). There was significant difference in continuous Cr distribution by BMI (p=0.004). Efficacy analysis did not show any significant difference in response rate by race (p=0.132), race/ethnicity (p=0.286) or BMI (p=0.896). In univariate/multivariate analysis, significantly worse overall survival (OS) was seen in males, age ≥70 yr, ECOG PS >0, ISS and DS stage III, presence of lytic lesions, Cr ≥2 mg/dL, Ca >12 mg/dL, Hb ≤10 g/dL. No significant difference was seen in OS or progression free survival by race, race/ethnicity or BMI (Figure 1). Conclusions: Significant differences exist in demographic and clinical characteristics of NDMM pts by race/ethnicity. Median OS was significantly associated with these characteristics but not with race/ethnicity itself. Observed racial/ethnic disparity in outcomes for MM pts may be overcome by access to comparable therapeutic options as seen in clinical trials. Obesity, while associated with MM incidence, does not seem to influence outcomes. Figure 1 Figure 1. Disclosures Ailawadhi: Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy. Stewart:Janssen Pharmaceuticals: Consultancy; Takeda Oncology: Consultancy; Celgene: Consultancy; Bristol Myers Squibb: Consultancy. Hussein:Celgene: Employment. Zonder:Takeda: Consultancy, Honoraria; Bristol Myers Squibb: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Pharmacyclics: Other: DSMC membership; Prothena: Consultancy, Honoraria. Barlogie:Mount Sinai Hospital: Employment.

Abstract Background: Cytogenetic evaluation using fluorescence in situ hybridization (FISH) at the time of diagnosis is essential for initial risk stratification in multiple myeloma. The presence of specific cytogenetic abnormalities is known to confer a poor prognosis, less is known about the cumulative effect of multiple cytogenetic high-risk abnormalities. We aimed to evaluate the prognostic implications of the presence of multiple cytogenetic high-risk abnormalities at the time of diagnosis. Methods: We studied 226 patients who were diagnosed with multiple myeloma between July 2004 and July 2014 at Mayo Clinic Rochester, underwent FISH evaluation within six months of diagnosis, and presented with cytogenetic high-risk abnormalities. High-risk cytogenetics were defined as t(4;14), t(14;16), t(14;20), del(17p), or gain(1q). Bone marrow aspirates were evaluated for deletions, monosomies, trisomies, and tetrasomies using chromosome- or centromere-specific FISH probes. IGH rearrangements were evaluated using an IGH break-apart probe and evaluating up to five potential partners (FGFR3, CCND1, CCND3, MAF, and MAFB). Kaplan-Meier overall survival estimates were calculated and the log-rank test was used to compare overall survival in patients with single and multiple cytogenetic high-risk abnormalities. A multivariable-adjusted Cox regression model was used to assess the effect of multiple cytogenetic high-risk abnormalities on overall survival adjusting for age, sex, and Revised International Staging System (R-ISS) stage. P-values below 0.05 were considered statistically significant. Results: The median age at diagnosis was 65 years (32 - 90), 129 (57%) of the patients were male. The median overall survival was 3.5 years (3.1 - 4.9) for the entire cohort (n = 226), 4.0 years (3.3 - 5.1) for those with one cytogenetic high-risk abnormality (n = 182, 80%), and 2.6 years (1.7 - 3.1) for those with two cytogenetic high-risk abnormalities (n = 44, 20%). There were no patients with more than two cytogenetic high-risk abnormalities. Ninety-eight patients (45%) had a high-risk translocation, 77 (35%) had del(17p), 39 (18%) had a high-risk translocation plus del(17p), and 5 (2%) had gain(1q) plus either a high-risk translocation or del(17p). Figure 1 shows the Kaplan-Meier overall survival estimates stratified by the number of cytogenetic high-risk abnormalities (n = 226). The presence of two cytogenetic high-risk abnormalities (compared to one) was of prognostic significance after adjusting for age, sex, and R-ISS stage (HR 2.01, 95% CI 1.27 - 3.19, p = 0.003, n = 205). Conclusions: Approximately one in five patients with newly diagnosed high-risk multiple myeloma presented with two high-risk abnormalities at the time of diagnosis. These patients experienced inferior overall survival suggesting a cumulative effect of multiple cytogenetic high-risk abnormalities. The relatively low number of observed gain(1q) was likely related to the fact that not all patients were evaluated for that abnormality. Therefore the presented hazard ratio represents a conservative effect estimate and may underestimate the true effect. Figure 1 Figure 1. Disclosures Dispenzieri: GSK: Membership on an entity's Board of Directors or advisory committees; Jannsen: Research Funding; Alnylam: Research Funding; Celgene: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; pfizer: Research Funding. Kapoor:Takeda: Research Funding; Celgene: Research Funding; Amgen: Research Funding. Kumar:Janssen: Consultancy, Research Funding; BMS: Consultancy; AbbVie: Research Funding; Millennium: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Array BioPharma: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Kesios: Consultancy; Glycomimetics: Consultancy.

Introduction: The clinical presentation and frequency of organ involvement are quite distinct in patients with IgM amyloidosis compared to patients with non-IgM amyloidosis, with less heart involvement and more nerve, soft tissue and lung involvement in IgM patients. It has been observed that immunoglobulin light chain variable region (IGVL) gene and gene family of the plasma cell clone impact phenotypic manifestations in AL amyloidosis, particularly organ tropism. (Kourelis et al. Blood. 2017;129). Given the variability in clinical features amongst patients with IgM vs. non IgM AL amyloidosis, we hypothesized that IGVL gene usage would be different between these two groups. Methods: Patients with newly diagnosed IgM and non-IgM amyloidosis seen at our institution from 01/2006 to 12/2015 were identified. IGVL gene usage was assessed by liquid chromatography tandem mass spectrometry (LC/MS/MS) as previously described. (Vrana et al Blood 2009;Dasari et al J of Proteome Res; Kourelis et al. Blood. 2017). Mass spectrometry data for IGVL analysis was obtained from clinically available data. LC/MS/MS was performed on available archival specimens when such data was not available clinically. Results: Patients with newly diagnosed amyloidosis who had sufficient mass spectrometry data on fat aspirate or tissue biopsy for IGVL gene usage identification were included (IgM AL, N=44 and Non-IgM AL, N=391). Clinical Features: As expected, differences were noted in baseline characteristics of patients with IgM vs. non-IgM AL amyloidosis. Patients with IgM amyloidosis were older (68 vs. 64 years, p=0.04) and more likely to have kappa as the involved light chain (34% vs. 25%, p=0.2), though the difference did not reach statistical significance. IgM amyloidosis patients had lower difference in involved and uninvolved free light chains (dFLC) (15.5 vs. 25.8 mg/dL, p=0.01) and lower NTProBNP levels (median: 1987 vs. 2655 pg/mL, p=0.02) compared with non-IgM amyloid patients. Presence of t(11;14) was less common by FISH (30% vs. 48%, p=0.1), though the difference did not reach statistical significance. Patterns of organ involvement were different, with heart involvement being less frequent in IgM patients (64% vs. 76%), while peripheral nerve (30% vs. 18%, p=0.05), soft tissue (41% vs. 21%, p=0.005) and lung involvement (7% vs. 3%, p=0.1) were more common in patients with IgM vs. non-IgM AL amyloidosis. There was no difference in liver (9% vs. 15%), kidney (50% vs. 51%) GI (23% vs. 25%) or autonomic nervous system involvement (18% vs. 14%). IGVL Gene Usage: As shown in Figure 1, IGVL usage differed across the two groups. In the lambda group, LV2-08 (14% vs. 2%, p<0.001) and LV2-14 (36% vs. 10%, p<0.001) were more common in IgM amyloid patients, while LV1-44 (0% vs. 10%, p=0.02) and LV6-57 (2% vs. 18%, p=0.004) were less common in the IgM group. There was also a trend towards less frequent involvement of LV3-01 (2% vs. 12%, p=0.07) in IgM amyloid patients. In the kappa group, KV4-01 (11% vs. 4%, p=0.04) was more common in patients with IgM amyloidosis. Correlation Between IGVL Gene usage and Clinical Features: IGVL gene usage correlated with disease characteristics and differences in the clinical presentation of patients across the two groups. LV2-14 was more commonly seen in IgM amyloid patients (above). It has been previously associated with a higher frequency of peripheral nerve involvement (Kourelis et al. Blood 2017), which was more frequent in IgM group. LV2-14 is also associated with low dFLC levels, which were noted to be lower in the IgM AL cohort. LV1-44 has been associated with higher likelihood of cardiac involvement. LV1-44 was seen less frequently in the IgM amyloid patients, who also had lower rates of cardiac involvement. LV6-57 has been historically associated with higher rates of t(11;14). It was less common in IgM AL patients, who also had lower rates of t(11;14). Conclusions: IGVL gene usage differed significantly in patients with IgM vs. non-IgM amyloidosis, correlating with differences in disease characteristics and organ involvement. This is the first study to our knowledge to report IGVL gene usage differences in IgM vs. non-IgM AL amyloidosis. Differences in IGVL gene usage may explain the distinct clinical presentation seen in IgM amyloidosis, the biology of which has so far remained poorly understood. *SS and SD contributed equally Disclosures Dasari: The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Dispenzieri:Alnylam: Research Funding; Celgene: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Janssen: Consultancy; Akcea: Consultancy; Intellia: Consultancy. Murray:The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Kumar:Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Takeda: Research Funding. Gertz:Prothena: Honoraria; Alnylam: Honoraria; Ionis: Honoraria; Janssen: Honoraria; Spectrum: Honoraria, Research Funding; Celgene: Honoraria.

Abstract Abstract 1828 Poster Board I-854 Background IgM Multiple Myeloma (MM) and Waldenstrom's Macroglobulinemia (WM) are two hematologic diagnoses with the common variable of an IgM monoclonal gammopathy. Distinguishing these two diagnoses is critical as the approach to therapy is different. A study by Avet-Loiseau et al demonstrated the presence of t(11;14) translocations in 7 of 8 patients with IgM MM that was absent in all of a series of 17 cases of WM (Semin Oncol 2003 30:2;153). However, 6 of the 8 IgM MM cases lacked classic lytic lesions. Method A priori, based on the literature and the natural history of MM, we defined IgM MM as a symptomatic clonal plasma cell proliferative disorder characterized by a serum IgM monoclonal protein (regardless of size) plus presence of t(11;14) on fluorescent in situ hybridization (FISH) and/or lytic bone lesions felt to be related to the underlying plasma cell disorder. The cases for the study were screened by a computerized database search for ‘IgM’ and ‘Myeloma’ of all patients seen at Mayo Clinic in the last 30 years at all three sites (Rochester, Arizona and Florida). Patients identified on the computerized screen were then audited by chart review to identify the study cohort. Results 38 cases were identified on initial screen of the computerized database as potential patients with IgM MM. Of these, a total of 22 cases met our specific definition of IgM myeloma (t(11;14 and/or lytic lesions). Of the remaining 16 cases, 8 were IgM MGUS, 5 were WM based on clinical presentation (hyperviscosity, lymphadenopathy and organomegaly) and biopsy findings of lymphoplasmacytic lymphoma, 1 was excluded due to lack of information, and the remaining 2 patients were indeed considered to have clinical IgM MM. Interestingly, these two patients did not have either the t(11;14) or lytic lesions, but rather had immunophenotypic features suggestive of MM and not WM (CD138+, CD20-). Table 1 summarizes the clinical characteristics of the 22 patients who met our criteria for IgM MM. All 22 patients had lytic bone lesions. Of the 17 evaluated with FISH, 6 (35%) demonstrated the t(11;14) abnormality. Median overall survival by Kaplan-Meier analysis was 37 months represented in Figure 1. Conclusion IgM MM is a discrete clinical entity that can and should be distinguished from WM. Our definition of IgM MM is designed to be specific and requires the presence of a symptomatic IgM secreting plasma cell proliferative disorder plus presence of t(11;14) and/or lytic bone lesions felt related to the underlying plasma cell disorder. In this, the largest series of patients with IgM MM, the t(11;14) abnormality is very specific for IgM MM, but may not be sensitive, being present in approximately 1/3 of patients. The median overall survival is similar to non-IgM myeloma patients treated during this period, and much shorter than what would be expected for WM. The minority of symptomatic patients with IgM monoclonal gammopathy who do not meet this criteria, but have immunophenotypic features more suggestive of MM rather than WM need further study. Disclosures No relevant conflicts of interest to declare.

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

Introduction: Primary cold agglutinin disease (CAD) is a rare disorder and accounts for 15% of all autoimmune hemolytic anemia. It is associated with an underlying monoclonal protein, which is IgM kappa in the majority of patients. The IgM protein triggers complement mediated extravascular hemolysis. The underlying pathophysiology by which autoimmune hemolysis affects only a small subset of patients with IgM monoclonal protein is poorly understood. Changes in the IgM structure via post-translational modifications of light chains (LCs), such as glycosylation are enriched in patients with AL amyloidosis, another rare disorder where disease manifestations are driven by the protein structure. (Kumar S et al Leukemia 2017). We hypothesized that presence of post-translational glycosylation is a potential mechanism allowing the IgM protein to trigger complement mediated hemolysis in CAD. Methods: Serum samples of patients being evaluated for monoclonal protein disorders were analyzed by immuno-enrichment-based matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), termed MASS-FIX. Patients who had an underlying IgM monoclonal protein identified by MASS-FIX from 07/23/2018 to 5/14/2019 were included this study. Glycosylated LCs were identified by the shift in their molecular mass due to the added molecular mass of the carbohydrates. Glycosylation was compared in patients with IgM associated CAD vs. other IgM disorders. Results: 438 unique patients with an IgM monoclonal protein identified on MASS-FIX were included in the study. CAD was present in 3% (n=14) of patients. The primary underlying diagnosis in the remaining patients was monoclonal gammopathy of undetermined significance (MGUS): 47% (n=206), lymphoplasmacytic lymphoma (LPL)/Waldenstrom Macroglobulinemia (WM): 30% (n=132), non-LPL lymphoma: 6% (n=28), AL amyloidosis: 4% (n=19), CLL: 4% (n=18), cryoglobulinemia: 2% (n=10), multiple myeloma: 2% (n=9) and other: 0.5% (n=2) Glycosylation was present in 7% (31/438) of patients in this cohort. Glycosylation was significantly more prevalent in patients with CAD than other IgM gammopathies (64% vs. 5%, p &lt;0.001). CAD was present in 29% of patients with glycosylation and in only 1% of patients without glycosylation, p&lt;0.001. Disease characteristics of patients with CAD, including patients with and without glycosylated LCs are listed in Table 1. No statistically significant differences were observed in the features of CAD patients with and without glycosylation, though sample size was small. All patients (100%) had IgM kappa monoclonal protein. Median M-spike was 0.5 g/dL. The associated disorder was IgM MGUS in 50% of patients, LPL/WM in 29%, marginal zone lymphoma in 14% and a non-specific B-cell lymphoproliferative disorder in 7% of patients. Median hemoglobin was 11.2 g/dL. All patients had characteristic RBC agglutination on peripheral smear. Elevated LDH and undetectable haptoglobin were seen in 100% of patients. Cold agglutinin titer was positive (&gt;1:64) in 12 of 13 patients (85%) in whom it was tested. The remaining patient had a titer of 1:8. Polyspecific Coombs test/direct antiglobin test (DAT) was positive in 100% of patients (n=12 tested) and all patients who were tested with monospecific DAT had an antiC3 antibody (n=10). One patient also had monospecific anti IgG antibody. Transfusions were needed in 21% of patients. Other clinical manifestations included acrocyanosis in 43% (n=6) and Raynaud's phenomenon in 50% (n=7) of patients, respectively. Treatment for CAD included rituximab with or without steroids in 50% (n=7) of patients, rituximab-based chemotherapy in 29% (n=4) of patients, with observation alone in 21% (n=3) of patients. Conclusions: Modification of the IgM immunoglobulin structure by post-translational glycosylation of LCs was significantly more common in patients with CAD compared with other IgM monoclonal gammopathies (64% vs. 5%, p &lt;0.001). CAD was seen in only 1% of patients without glycosylation, while one-third of patients with glycosylation had CAD. This is a novel finding. As MASS FIX is now routinely done for detection of monoclonal proteins at our institution, the presence of LC glycosylation can provide diagnostic clues and can be a potential therapeutic target in the future. Future studies in larger, independent cohorts of patients are needed to confirm these findings. *SS & DLM contributed equally Disclosures Murray: The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Dasari:The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Dispenzieri:Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding; Intellia: Consultancy; Akcea: Consultancy. Gertz:Spectrum: Honoraria, Research Funding; Janssen: Honoraria; Celgene: Honoraria; Prothena: Honoraria; Ionis: Honoraria; Alnylam: Honoraria.

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

Introduction Minimal residual disease (MRD) status at day 100 following autologous stem-cell transplant (ASCT) in multiple myeloma (MM) patients is an important determinant of prognosis. Bone marrow (BM) based assays, i.e. next-generation flow cytometry (NGF) or next-generation sequencing (NGS) that are currently used in determining MRD are vulnerable to sampling biases due to patchy marrow involvement and extramedullary disease. BM examination alone may lead to false-negative results. MRD assessment through newer, more sensitive peripheral blood based methodologies such as mass spectrometry (MS) can potentially overcome the limitations associated with BM based assays. At our institution, traditional immunofixation electrophoresis (IFE) has been replaced by a MS method termed Mass-Fix which utilizes the unique light chain mass associated with each patient's monoclonal protein to monitor disease over time. In this study, we assessed the prognostic impact of serum Mass-Fix MRD status in MM patients who were MRD negative by NGF around day 100 post-ASCT. Methods Patients with MM who underwent ASCT between 01/01/2015 and 12/31/2018 at Mayo Clinic, Rochester were included in this study provided they had attained post ASCT day 100 complete response (CR) by IMWG 2016 criteria and MRD- state as assessed by BM based NGF, utilizing 2 eight-color tubes (total 10 colors), with a minimum sensitivity 10-5. Presence of non-secretory MM and unavailability of pre-ASCT serum samples or serum IFE results were important exclusion criteria. Peripheral blood samples drawn concurrently with the BM assessment were evaluated by Mass-Fix as described previously (Mills et al., Clin. Chem, 2016). The isotype and mass of the M-protein light chain (LC) obtained by Mass-Fix were compared to the pre-ASCT M-protein LC and/or IFE isotype. Patients with the following genetic alterations: deletion 17p, translocation (4;14), (14;16), t(14;20) and1q gain/amplification and were considered high risk. All time-to event analyses were performed on JMP 14.1.0 from the time of ASCT using the Kaplan-Meier method. Results Sixty-two patients with MM (57 newly diagnosed and 5 relapsed/refractory) who underwent ASCT and were MRD- by BM based NGF around day 100 (range: day 60-120) were included in the study. Median age at ASCT was 61 (range: 40-76) years and 61% were males. Thirty (48%) patients had IgG MM, 15 (25%) patients had IgA MM and 17 (27%) patients had light chain only disease. Forty-one (66%) patients received bortezomib, lenalidomide and dexamethasone (VRD) as induction regimen. Median time from diagnosis to ASCT was 6 months (IQ range: 4.7-7.2). Pre-ASCT fluorescence in- situ hybridization data were available on 47 (76%) patients; 23 (49%) were high risk. Of 62 patients, all of whom were day 100 MRD- by NGF, 36 (58%) patients had Mass-Fix identified MRD (MRD+). MRD positivity by Mass-Fix around day 100 was observed in 70% of patients with high risk MM versus 71% of patients with standard risk MM, p=0.9. The median follow-up was 18 months (95%CI: 14-21); 19 months (95%CI: 15-21) for patients who were MRD+ by Mass-Fix versus 17 months (95%CI: 12-21) for those who were MRD- by Mass-Fix at day ~100, p=0.5. Of 57 (92%) patients who received post ASCT maintenance therapy, 32 (89%) were MRD+ and 25 (96%) were MRD- by Mass-Fix, p=0.5. Eighty-seven percent of patients with IgG MM had MRD+ status by Mass-Fix at day~100. By contrast, only 33% and 30% of patients with IgA MM and light chain MM, respectively, had MRD+ status at day 100; p<0.0001. This suggests that IgG half-life which is longer than that of IgA or free light chains may affect the day 100 MRD status. At 18 months, 76% and 93% of patients, who were MRD+ and MRD- , respectively by Mass-Fix were alive and free from disease progression, p=0.03 (Table 1, Figure 1a). At 18 months after ASCT, none of the patients who were MRD- by Mass-Fix required salvage treatment following ASCT while 25% of patients who were MRD+ by Mass-Fix required next line of therapy due to disease progression, p=0.05 (Table 1, Figure1b). Conclusion Our data suggest that outcomes [progression free survival (PFS) and time-to-next therapy (TTNT)] of patients with MM who are in CR, and have achieved MRD- state by BM NGF post ASCT, can be adversely impacted if there is concurrent evidence of serum monoclonal protein by Mass-Fix, thereby demonstrating incremental prognostic value of this sensitive assay in clinical practice. Disclosures Murray: The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Dasari:The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Gertz:Teva: Speakers Bureau; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Celgene: Consultancy; Research to Practice: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Physicians Education Resource: Consultancy; Medscape: Consultancy, Speakers Bureau; Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy; Ionis/Akcea: Consultancy; Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Other: Development of educational programs and materials. Dingli:Karyopharm: Research Funding; Millenium: Consultancy; Rigel: Consultancy; Janssen: Consultancy; alexion: Consultancy. Lacy:Celgene: Research Funding. Leung:Omeros: Research Funding; Aduro: Membership on an entity's Board of Directors or advisory committees; Prothena: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Kapoor:Takeda: Honoraria, Research Funding; Janssen: Research Funding; Celgene: Honoraria; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Glaxo Smith Kline: Research Funding; Cellectar: Consultancy.