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INTRODUCTION: Primary plasma cell leukemia (pPCL) is the most aggressive form of multiple myeloma (MM). Recently, pPCL has been defined by as few as >5% circulating plasma cells (cPCs) detected morphologically on a peripheral blood smear. However, this technique may not be sufficiently sensitive and is dependent on inter-observer bias to properly identify and quantify cPCs. Multiparametric flow cytometry (MFC) provides a readily available and highly sensitive method to identify and quantify cPCs. However, an optimal quantitative cutoff for cPCs by MFC to define the presence of pPCL has not been established to date. Thus, this is the first study to date that determines an optimal cutoff of cPCs/ microliter that could identity patients with pPCL at diagnosis. METHODS: We retrospectively evaluated all newly diagnosed MM patients seen at the Mayo Clinic, Rochester from January 2007 to December 2017 who had their peripheral blood samples evaluated morphologically by peripheral blood smear and immunophenotypically by MFC prior to beginning therapy. Patients with a peripheral blood smear detecting >5% cPCs were classified as having pPCL. Six-color MFC was performed on peripheral blood mononuclear cells by isolated by Ficoll gradient, and stained with antibodies to CD45, CD19, CD38, CD138 and cytoplasmic Kappa and Lambda immunoglobulin light chains. The data was collected using Becton Dickinson FacsCanto II instruments collecting 150,000 events and analyzed using the BDFacs DIVA Software. The gating strategy employed first used the expression of CD38, CD138, and cytoplasmic immunoglobulin light chains to identify all plasma cells in the specimen. The cPCs were then discriminated from polyclonal/normal plasma cells based on differential CD19 and CD45 expression. The cPCs detected were reported as the number of clonal events/150,000 collected total events and converted to the absolute number of cPCs/microliter using their absolute lymphocyte count and monocyte count determined at the time of the blood draw for cPC MFC assessment. A receiver operator curve (ROC) was performed to determine the absolute cPCs/microliter by MFC that best identified those patients with >5% cPC on their peripheral blood smear. Survival analysis was performed by the Kaplan-Meier method and differences assessed using the log rank test. RESULTS: A total of 591 patients were included in this analysis of which 59% were male and the median age was 66 years (range: 27 - 95) with 22% being 75 years of age or older. From this cohort, 133 (24%) patients had high risk FISH cytogenetics, 172 (30%) were classified as ISS 3 at diagnosis, 83 (15%) had an elevated LDH level and 61 (17%) had a plasma cell labeling index (PCLI) of 2% or greater. There were 65 (11%) patients with any amount of cPCs detectable by peripheral blood smear of which only 22 (4% of the total population) met criteria for pPCL with >5% cPCs. With MFC, 403 (68%) patients had detectable cPCs. The median number of cPCs per microliter was 0.81 (0 - 10,455) with 273 (46%) having >1 cPC/microliter. A ROC analysis determined that the presence of >50 cPCs/microliter by MFC was the optimal cutoff to identify patients with >5% cPCs by blood smear with approximately a specificity of 94% and a sensitivity of 86%. The presence of >50 cPCs/microliter by MFC was associated with higher presence of high risk FISH cytogenetics, ISS 3 classification, elevated LDH and PCLI > 2%. The median time to next treatment (TTNT) for patients with and without >5% cPCs by peripheral blood smear was 18 months vs. 30 months (P < 0.001). The median TTNT for patients with and without >50 cPCs/microliter by MFC was 19 months vs. 30 months (P < 0.01). The median overall survival (OS) for patients with and without >5% cPCs by peripheral blood smear was 25 months vs. 71 months (P < 0.001; Fig 1A). The median OS for patients with and without >50 cPCs/microliter by MFC was 38 months vs. 71 months (P < 0.01; Fig 1B). CONCLUSION: This is the largest study that attempts to identify an optimal cutoff of cPCs/microliter by MFC for diagnosing pPCL patients. The presence of >50 cPCs/microliter is an optimal cutoff by MFC that best predicts for the presence of >5% cPCs by peripheral blood smear. However, there remains discordance in the OS outcomes between the two cutoffs by different methodologies for pPCL. This could signify the presence of biological processes associated with the presence of >5% cPCs when detected by peripheral blood smear that are not captured by MFC. Disclosures Dispenzieri: Pfizer: Research Funding; Janssen: Consultancy; Intellia: Consultancy; Akcea: Consultancy; Alnylam: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Dingli:Karyopharm: Research Funding; Rigel: Consultancy; Millenium: Consultancy; Janssen: Consultancy; alexion: Consultancy. Lacy:Celgene: Research Funding. Kapoor:Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding; Sanofi: Consultancy, Research Funding; Cellectar: Consultancy; Janssen: Research Funding; Celgene: Honoraria. Leung:Aduro: Membership on an entity's Board of Directors or advisory committees; Omeros: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding. Russell:Imanis: Equity Ownership. Gertz:DAVA oncology: Speakers Bureau; Ionis/Akcea: Consultancy; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Research to Practice: Consultancy; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Other: Development of educational programs and materials; Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Introduction: Several patient and disease biology characteristics that impact overall survival (OS) outcomes of patients with newly diagnosed multiple myeloma (NDMM) have been well described. However, several prior population-based registry studies in the US such as SEER and NCDB databases have demonstrated the negative prognostic impact of socio-economic (SE) factors such as low median household income based on US national census bureau data for zip code of residence as well as absence of marital support on the OS of NDMM patients. Whether such SE factors are independent of established host and disease biology related factors remains unknown due to the absence of detailed patient-level data in population-based cancer registries. Thus, we evaluated whether such SE factors independently affected the OS of NDMM patients in our institution when accounting for patient and disease biology related factors. Methods: We analyzed a retrospective cohort of consecutive NDMM patients seen at the Mayo Clinic from January 2005 to December 2015. Median household income for each patient's area of residence was estimated by matching their home zip code at diagnosis with data available through the US National Census Bureau. Median household income < $63,000 for a zip code were used to classify patients as having low income based on the National Cancer Database classification of the bottom three quartiles. Absence of marital support was considered in patients divorced, single or widowed at the time of diagnosis. Survival estimates were calculated using the Kaplan-Meier method. Patient and disease biology related factors taken into consideration included age, FISH cytogenetics, ISS stage and LDH levels. Survival estimates were compared between groups using the log-rank test. Multivariable adjusted proportional hazards regression models were fit for the association between known prognostic factors and OS. Results: A total of 2,621 MM patients were analyzed from the Mayo Clinic cohort of which 60% were male and the median age was 64 (22 - 96) years with 14% being 75 years of age or older. In this cohort, 541 (33%) patients had ISS 3 disease and 370 (22%) had high risk cytogenetics by FISH. The median OS based on estimated average household income was 65 months for the group of patients with low household income (N = 32%) and 80 months for the remainder (P = 0.001) (Fig 1A). The median OS based on marital support was 59 months for those without marital support at diagnosis (N = 21%) versus 76 months for remainder (P = 0.003) (Fig 1B). However, in a multivariable analysis that included the aforementioned SE factors and patient and disease biology characteristics , only age of 75 years or older (p < 0.001), the presence of high-risk FISH cytogenetics (p < 0.001), presence of ISS 3 disease (p < 0.001) and elevated LDH (p = 0.005) retained independent statistical significance in predicting for worse OS. Lower household income (p = 0.264) and absence of marital support (p = 0.054) were not independent predictors of worse OS. Conclusions: With the caveat of patient selection bias in a tertiary academic center, SE factors such as estimated average household income and marital support at diagnosis do not appear to impact OS of NDMM patients when considered in the context of traditional host and disease biology risk factors. These findings are in contrast to those suggested by population based registry studies; nevertheless, similar patient-level assessments should be considered in patient cohorts from non-tertiary medical centers as these results may likely be different. Disclosures Dispenzieri: Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Lacy:Celgene: Research Funding. Kapoor:Amgen: Research Funding; Glaxo Smith Kline: Research Funding; Sanofi: Consultancy, Research Funding; Celgene: Honoraria; Janssen: Research Funding; Cellectar: Consultancy; Takeda: Honoraria, Research Funding. Leung:Prothena: Membership on an entity's Board of Directors or advisory committees; Aduro: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Omeros: Research Funding. Russell:Imanis: Equity Ownership. Gertz:Medscape: Consultancy, Speakers Bureau; Research to Practice: Consultancy; Springer Publishing: Patents & Royalties; Ionis/Akcea: Consultancy; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Other: Development of educational programs and materials; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Abstract INTRODUCTION: Our group has demonstrated that MASS-FIX is a quick, inexpensive, and accurate means to diagnose and monitor the serum and urine of patients with plasma cell disorders. Screening can be done with a MALDI-TOF MS and samples reflexed to microflow liquid chromatography coupled with electrospray ionization (ESI) and Q-TOF MS (microLC-ESI-Q-TOF MS). Because this technique provides a mass/charge (m/z) for a given patient's monoclonal protein, this method can provide greater sensitivity and specificity to monitor for complete response (CR), especially in patients receiving therapeutic monoclonal antibodies. Our goal was to assess the performance of miRAMM in patients with AL who have been classified as complete response using conventional means. METHODS: We identified 77 patients with AL who had both documented CR by immunofixation (Seibia) of the serum (SIFE), urine IFE (UIFE), and serum free light chain (FLC; The Binding Site) and paired serum samples to test by MALDI-TOF and ESI-TOF. No urine samples were available to test. Paired serum samples from baseline and approximately one year post-therapy were immunoaffinity purified using nanobodies targeting kappa, lambda, alpha, gamma and mu as previously described. For the MALDI-TOF (Bruker Microflex, LT), a range of 9,000 to 32,000 m/z was acquired. The m/z distribution was then visually inspected for the presence of a peak that was distinct from the polyclonal background in both the M+1 and M+2 light chain mass ranges. For the ESI-TOF, spectra were also collected on an TripleTOF 5600 quadrupole time-of-flight mass spectrometer (ABSciex, Vaughan ON, CA) in ESI positive mode with a Turbo V dual ion source with an automated calibrant delivery system. TOF MS scans were acquired from m/z 600−2500 with an acquisition time of 100 ms. RESULTS: Median age of the cohort was 58 (range 42, 81). Fifty-eight percent were male. No test was 100% sensitive at baseline with positive results as follows: abnormal FLC ratio, 82%; positive SIFE, 70%; 73% positive UIFE; positive serum MASS-FIX, 71%; and ESI-TOF, 79% . There was light chain isotype agreement in all cases, except for 2 patients for whom the SIFE and the FLCr disagreed. Of the 56 patients with baseline positive MASS-FIX, there was evidence of the original monoclonal protein in 5 patients (see figure for example of spectra illustrating same m/z before and after therapy). Of the 63 patients who had baseline positive ESI-TOF, there was evidence of the original monoclonal protein in 8 patients. Small unrelated monoclonal proteins were seen both by SIFE and by mass spectrometry techniques. With the spectrometry techniques, however, these transient oligoclonal bands could be distinguished from the original monoclonal protein when they shared the same isotype based on the difference in m/z. DISCUSSION: At baseline, the MALDI was able to identify the baseline monoclonal protein in a comparable number of patients as SIFE, UIFE, and FLC. Approximately 10% of patients thought to be in CR using routine screening tests were found to have persistence of their original clone by MALDI and by ESI-TOF. Small post-therapy unrelated monoclonal proteins were also seen both by IFE and by MALDI, but either the presence of a different isotype or in the case of MALDI, a different m/z, made it clear that the monoclonal protein was not related to the original clone. The sensitivity of the assay will improve significantly when we formalize the introduction of free light chain magnetic beads to capture the serum FLCs. Routine use of MASS-FIX of the urine will also increase performance characteristics. Figure. Figure. Disclosures Dispenzieri: Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Gertz:Prothena: Honoraria; celgene: Consultancy; spectrum: Consultancy, Honoraria; Teva: Consultancy; Physicians Education Resource: Consultancy; annexon: Consultancy; Apellis: Consultancy; Alnylam: Honoraria; Medscape: Consultancy; Amgen: Consultancy; janssen: Consultancy; Research to Practice: Consultancy; Abbvie: Consultancy; Ionis: Honoraria. Kumar:Novartis: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Dingli:Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Millennium Takeda: Research Funding; Millennium Takeda: Research Funding. Kapoor:Takeda: Research Funding; Celgene: Research Funding. Russell:Vyriad: Equity Ownership.

Abstract Background: Modern clinical practice places time restrictions on the amount of information and processing that can be done in a typical office visit. Meeting patient needs within the healthcare system is challenging, contributing to patient (pt) and clinician dissatisfaction and potential suboptimal outcomes. We developed an electronic point-of-care case management system for cancer patients. The system's goal is to obtain patient-reported quality of life (PROQOL) outcomes and provide clinicians with information regarding QOL issues to address. We tested this system in a prospective randomized study against usual care (UC). The primary objective was to determine if PROQOL system would improve mean QOL over time. Methods: Eligible pts were adults with multiple myeloma (MM) or light amyloidosis (AL), seen at Mayo Clinic. Pts were randomized 2:1 to PROQOL system or usual care. PROQOL system was offered prior to every visit. Pts select from various categories about their single biggest concern, and receive a printed list of actionable resources based on selected concern. Clinicians also receive the PROQOL results to review with pts. Providers and pts randomized to PROQOL completed a "was it worth it survey" (WIWI). An 8 item Linear Analogue Self-Assessment was used to assess QOL, the primary endpoint. Secondary endpoints included distribution of choices of most important concern and their relationship to demographic and clinical variables. The study was powered to detect a 0.5 standard deviation difference in QOL between groups. Results: There were 233 patients enrolled (171 MM, 62 AL) in this study between July 1, 2016 and April 17, 2018. Median age was 65 years (range 31-87), and 59% were male. Median time from diagnosis to study consent was 37 months (PROQOL 36.3 versus UC 39.6). Median follow up for all patients was 15 months (range: 0.7-22 months), and median follow up for PROQOL pts was 16 months and 14 months for UC pts (p=0.027). There were 25 pts that have died since enrollment and 208 alive. No statistical significant difference in QOL between PROQOL and UC (median QOL 7 vs 7, p=0.75). The most prevalent main concerns selected were Physical Health (37%) and Cancer and Diagnosis (27%), the pattern remained even when pts were given the option to pick a second major concern 26% and 20% respectively. No other concern was listed more than 8% at baseline. All category selections and percentages are shown in the Figure. The average time to complete the instrument was 6 minutes. Pts found the PROQOL system was worth their time (75%), they would choose it again (87%) and recommend it to others (82%). Eighty-two percent of clinicians did not think the PROQOL tool negatively impacted their practice and 75% believed they may see improvement in pt wellbeing. Discussion: The PROQOL system was well received by pts and clinicians but did not improve QOL relative to UC in this study. The PROQOL demonstrates that majority of patients strongly desire more information regarding ongoing therapy, clinical trials, prognosis and toxicity. Further investigation is needed to understand whether communication is limited by time or mechanism of information delivery, such as verbal or written, or whether it should be undertaken in a separate allied health care visit. Figure. Figure. Disclosures Gertz: spectrum: Consultancy, Honoraria; Abbvie: Consultancy; Research to Practice: Consultancy; annexon: Consultancy; Medscape: Consultancy; Physicians Education Resource: Consultancy; Amgen: Consultancy; janssen: Consultancy; Alnylam: Honoraria; Teva: Consultancy; Apellis: Consultancy; Ionis: Honoraria; celgene: Consultancy; Prothena: Honoraria. Kumar:Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding. Dingli:Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Millennium Takeda: Research Funding; Millennium Takeda: Research Funding; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.. Lacy:Celgene: Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding.

Abstract Abstract 448 Background: POEMS syndrome is a rare form of plasma cell dyscrasia that presents with polyneuropathy and various other systemic findings. Patients with 1–3 lesions and bone marrows without clonal plasma cells have been given targeted radiation as the initial and potentially definitive therapy. Outcomes of patients treated thus have not been systematically studied. Patients and Methods: One hundred and forty-six patients with POEMS syndrome were seen at the Mayo Clinic in Rochester, MN between January 1999 and September 2011. Charts of patients with research authorization were reviewed with IRB approval. Patients who had been given targeted radiation as their initial primary therapy were eligible for this study. Thirty-eight patients satisfied criteria and comprise the study population. Three patients had either short or poorly documented follow-up and were excluded from the response and time to next treatment analyses. Patients were categorized by systems that were involved at diagnosis, time of radiation, response after radiation, and the need for further therapy. Statistical analyses were performed using JMP statistical software (SAS, Carey, NC). Results: The median age was 50, with 76% of the population being male. Median time from diagnosis to radiation was 0.7 months, ranging from 0 to 9.4 months. 20, 14, 11 and 2 patients had immunosuppressive therapy with corticosteroids, IVIG, plasmapheresis, or rituximab, respectively, directed at a prior presumptive, but incorrect, diagnosis of CIDP. Five patients had one cycle or less of alkylator, lenalidomide, or bortezomib, prior to receiving what was hoped to be definitive radiation therapy. The median number of bone lesions was 1, range 1–6. In total 55 lesions of the possible 64 were irradiated being mostly found in the pelvic bones including the sacrum, ileum, ischium, and pubis. The median dose of radiation given was 45 Gy range 35 Gy to 54 Gy. Forty-nine percent had clinical improvement, 26% had a mixed clinical picture, 3% merely stabilized, and 23% had a clinical worsening. 29% had a complete hematologic response, 9% had a very good partial hematologic response, 9% had a partial hematologic response, 26% had no hematologic response, and the remaining were either non- or oligo-secretory or undocumented. 11% had a complete FDG-PET response, 11% had a partial FDG-PET response, 11% had no FDG-PET response, and the remaining had no documented FDG-PETs to analyze. 11% had a complete VEGF response, 3% had partial VEGF response, 14% had no VEGF response, and the rest were either not documented or unevaluable. The median follow up of living patients is 30 months, and the 4-year OS is 95%. Forty-eight percent of patients went on to receive additional therapy after their radiation (Figure). The median time to next therapy (TTNT) for these patients was 7.6 months (range 2.2 –73 months). Subsequent therapies included high dose chemotherapy with autologous hematopoietic stem cell transplant (n=10), low dose alkylator (n=2), thalidomide/lenalidomide (n=3), and more radiation (n=3). None of the baseline characteristics predicted for whether a patient would receive (or require) subsequent therapy, including the number of bone lesions at baseline. Conclusion: The results show that radiation is sufficient to produce clinical improvements and hematologic and radiographic responses approximately 50% of patients, even those with as many as 3 lesions. Disclosures: No relevant conflicts of interest to declare.

Abstract Introduction Del(17p) detected by fluorescence in situ hybridisation (FISH) of bone marrow plasma cells (BMPCs) is an adverse prognostic factor in patients with multiple myeloma (MM). While the natural history and prognostic factors in patients with del (17p) detected at diagnosis have been studied, the outcomes of patients who acquire del (17p) later in their course are not known. We aimed to define the outcomes of MM patients who acquire del(17p). Methods We reviewed the Dysproteinemia database at Mayo Clinic, MN to identify 80 patients with MM who had their first FISH test negative for del (17p), but acquired del(17p) later in the course of the disease. Sixty (75%) patients had their first FISH within 6 months (mo) of diagnosis; 20 (25%) patients had their first FISH more than 6 mo after diagnosis of MM. Del(17p) included del(17p13.1) and/or monosomy 17. We identified 2 control patients for each case, who were diagnosed during the same time period, but did not demonstrate del (17p) at any time during follow-up. Results Characteristics of patients at acquisition of del(17p) are shown in Table 1. Of these, 76 patients had relapsed and/or refractory MM; in 4 patients, del (17p) was detected after having attained a response to prior therapy. Seventy (87.5%) patients had del (17p13.1); 5 (6.3%) patients had monosomy 17; 1 (1.2%) patient had both del (17p13.1) and monosomy 17. Four (5.0%) patients had relative loss of 17p. High-risk translocations (HRT) [t(4;14), t(14;16) and t(14;20)] were present in 14 (17.5%) patients. The percentage of PCs with del(17p) were available in 75 patients. The median percentage of PCs with del(17p) was 76 (range, 9-100). Sixty two (77.5%) patients received exclusively chemotherapy as subsequent treatment; stem cell transplant (SCT) was part of the next treatment in 16 (20%) patients (allogeneic SCT in 1). Among 71 evaluable patients, ≥very good partial response and ≥partial response were attained in 24 (33.8%) and 35 (49.2%) patients respectively. The median progression free survival (PFS) from detection of del (17p) was 5.7 mo (95% CI, 3.5-7.8); overall survival (OS) was 18.2 mo (CI, 13.1-27.5). From a comparable time point, the OS for 160 controls was 56.2 mo (CI, 37.1-75.3) (P<0.001). The results were similar when patients were stratified based on variables at diagnosis such as age, presence of HRT, international staging system (ISS) stage, serum lactate dehydrogenase (LDH) and PC proliferative rate, and proteasome inhibitor (PI)-containing induction and SCT within a year of diagnosis and before acquisition of del(17p). Evaluating outcomes from initial diagnosis, PFS in the acquired del (17p) and control groups were 23.0 (CI, 20.2-25.8) and 30.2 (CI, 26.7-33.9) mo (P=0.028) and OS were 68.2 (CI, 50.8-74.8) and 111.6 (CI, 103.4-127.8) mo respectively (P<0.001). High LDH at baseline [OR- 4.31 (CI, 1.34-13.86)] predicted acquisition of del(17p) while presence of HRT showed borderline significance [OR- 2.02 (0.90-4.54)]. Age ≥65 yrs, ISS III vs. I/II stage, t(11;14), any trisomy, monosomy 13, BMPC%, initial therapy and SCT in first year and before acquiring del (17p) were not predictive. We performed univariable analysis with variables at detection of del(17p) such as age ≥65 vs. <65 years, serum creatinine >2 vs. ≤2 mg/dL, BMPC% ≥50 vs. <50%, ISS III vs. I/II stage, elevated vs. normal LDH, presence vs. absence of a HRT, presence vs. absence of monosomy 13, presence vs. absence of any trisomy, high vs. low PC proliferation rate, PI and immunomodulatory drug (IMiD)-refractoriness and percentage of PCs with del(17p) as independent variables to determine their association with PFS and OS. ISS stage III, high PC proliferative rate and PI and IMiD-refractoriness were selected after univariable analysis and included in the multivariable Cox proportional hazards model. A higher PC proliferative rate alone predicted shorter OS. None of the above factors were associated with shorter PFS. The median OS in those with high PC-proliferative rate from detection of del(17p) was 10.9 mo (CI, 6.0-17.1) vs. 37.2 mo (CI, 18.2-47.5) in those with low PC proliferative rate (P=0.005). Conclusion The prognosis of patients who acquire del (17p) is poor with OS of 6.5 years against 9 years from diagnosis in patients who do not acquire del (17p). This was valid across prognostic sub-groups. High PC proliferative rate was the only factor which impacted OS once patients acquired del(17p). Disclosures Kapoor: Celgene: Research Funding; Takeda: Research Funding. Gertz:Research to Practice: Consultancy; Teva: Consultancy; Ionis: Honoraria; annexon: Consultancy; Physicians Education Resource: Consultancy; Abbvie: Consultancy; spectrum: Consultancy, Honoraria; Prothena: Honoraria; Alnylam: Honoraria; Apellis: Consultancy; Medscape: Consultancy; Amgen: Consultancy; janssen: Consultancy; celgene: Consultancy. Lacy:Celgene: Research Funding. Dingli:Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Millennium Takeda: Research Funding; Millennium Takeda: Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Russell:Vyriad: Equity Ownership. Kumar:AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Background Limited data exist with respect to outcome and optimal therapeutic strategies in patients with central nervous system (CNS) involvement in multiple myeloma (MM). We present a single center experience of patients with myelomatous CNS involvement in newly diagnosed and relapsed / refractory MM. Methods Of 4060 patients with MM seen at Mayo Clinic, Rochester, MN between January, 1st 1998 and December, 31st 2012, 26 patients had identifiable CNS involvement confirmed by biopsy / presence of plasma cells in the cerebrospinal fluid (CSF) and/or identification of intraparenchymal or meningeal involvement by imaging (MRI/CT). Patients were risk stratified by mSMART (Mayo Stratification for Myeloma And Risk-adapted Therapy) criteria. Overall survival (OS) from diagnosis and the time of CNS involvement was calculated using the Kaplan-Meier method. Results Myelomatous CNS involvement occurred in 26 (0.6%) patients with MM of whom 3 were newly diagnosed. The median time to detection of CNS involvement was 24 months (range: 0-125) from diagnosis of MM. Median age at CNS myeloma diagnosis was 58 years (range 37-80) and 73% were male. Abnormally high LDH was observed in 11 out of 22 patients at the time of CNS involvement. Lumbar puncture was performed on 16 patients, 13 (81%) of whom had plasma cells in the CSF detected by cytology/flow-cytometry. Two patients, without evidence of plasma cells, had abnormally high CSF protein and 1 had normal CSF analysis. Of the 25 patients who underwent MRI, 16 (64%) had at least one of the following significant abnormalities; intraparenchymal disease (37%), leptomeningeal enhancement (68%) or direct extension of MM (31%). The neurological symptoms at or after diagnosis of CNS myeloma included headache (38%), cranial nerve palsy (38%), visual disturbance (38%), gait disturbance (35%), paresthesias (35%), limb weakness (31%), confusion (30%), nausea/vomiting (15%), dysarthria (12%), seizures (8%) and urinary incontinence (4%). Fluorescent in-situ hybridization (FISH n=7), cytogenetics (n=8) and/or plasma cell labeling index (PCLI n=12) were available in 18 patients prior to the diagnosis of CNS disease. Ten (56%) out of those 18 patients had high-risk features at least by one criterion. At the time of CNS involvement, six additional patients demonstrated high risk features [5 by PCLI (≥ 3%) and 1 by FISH]. Overall, 16 out of 26 (62%) patients were classified as high risk by mSMART criteria prior to or at the time of CNS involvement. Four (27%) out of 15 had a deletion p53 or monosomy 17 chromosomal abnormality. Median OS was 42 (95% CI, 19-55) months from the diagnosis of MM and 3 months (95% CI: 1-7.9) from the time of CNS involvement (Figure). OS of patients with high risk features was significantly worse (27 months) compared to standard risk disease (67 months, p=0.02) from diagnosis of MM. Eighteen patients received radiation therapy for CNS myeloma. Five of those patients also received intrathecal (MTX and ARA-C) therapy. One patient received intrathecal and systemic chemotherapy. Four patients did not receive any treatment. Novel agents, including bortezomib (23%), thalidomide (15%), and pomalidomide (4%) were administered to the patients post diagnosis of CNS disease. Six (23%) patients underwent autologous stem cell transplant post diagnosis of CNS disease with a median OS of 19 months (95% CI: 10-122 months) from the time of CNS involvement. Conclusion CNS involvement is a rare complication of MM that portends a poor survival outcome. It is likely that the rates in this study are an underestimate of the true incidence due the perceived futility of CNS directed therapy in this disease. Among those recognized, high-risk genetic and markers of increased proliferative activity, including deletion p53 / monosomy 17 and elevated PCLI (≥ 3%) appear to cluster in this cohort. Current therapeutic approaches are largely ineffective in managing this aggressive subset of myeloma patients. Disclosures: No relevant conflicts of interest to declare.

Abstract Introduction: Immunoglobulin light chain (AL) amyloidosis is associated with significant morbidity and mortality. Several models were developed to allow survival prediction, but head-to-head model comparison is lacking. Patients and Methods: Five prognostic models were compared: Mayo 2004; Mayo 2012; 2013 European modification of Mayo 2004 (where Mayo 2004 stage 3 is subdivided into 3 subgroups based on NT-proBNP at 8500 ng/L and systolic blood pressure at 100 mmHg); 2015 European modification of Mayo 2004 (where Mayo 2004 stage 3 is subdivided into 2 subgroups based on NT-proBNP at 8500 ng/L); and organ model (a model based on number of involved organs). All patients with available baseline data for the 5 models were included in this study (n=1005). Improvements in predictive accuracy of the various models were determined by calculating a net improvement in survival prediction for each pair of prognostic models. Net improvement was considered as the proportion where model A outperforms model B minus the proportion where model B outperforms model A. Results: For all models, there was increasing risk for death with increasing stage. The organ model was the least powerful system with a hazard ratio of 2.8 for ≥4 organs compared to 1 involved organ. The organ model was consistently outperformed by the other 4 systems. In the cohort as a whole, the biomarker models (Mayo 2004; Mayo 2012; European 2013; European 2015) were comparable in ability to predict survival (Figure). However, a slightly superior performance of the European 2013 modification of the Mayo 2004 system was seen over the Mayo 2004 system in the group as a whole (net improvement 4.1%, P=0.023) and when restricted to non-ASCT population (net improvement 6.3% P=0.014). The European 2015 modification performed slightly better than the Mayo 2004 system in the ASCT population (net improvement 3.4%, P=0.025). 1-year mortality was better predicted by the European models (net improvement 11-14%, P<0.05), while the Mayo 2012 had better survival prediction to all other biomarker models in 3-year landmark comparison (net improvement 7-9%, P<0.05). Conclusion: Using biomarker based staging is a clear improvement over the organ staging system. The different biomarker staging systems' abilities to predict for survival were relatively comparable, solidifying the importance of soluble cardiac biomarkers and free light chain measurement as prognosticators in AL amyloidosis. Mayo 2004-based models better predict for early death while Mayo 2012 model has a better prediction for long-term survival. Figure. Figure. Disclosures Gertz: Ionis: Honoraria; celgene: Consultancy; spectrum: Consultancy, Honoraria; janssen: Consultancy; Amgen: Consultancy; Abbvie: Consultancy; Medscape: Consultancy; annexon: Consultancy; Teva: Consultancy; Research to Practice: Consultancy; Apellis: Consultancy; Alnylam: Honoraria; Prothena: Honoraria; Physicians Education Resource: Consultancy. Lacy:Celgene: Research Funding. Dingli:Millennium Takeda: Research Funding; Millennium Takeda: Research Funding; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.. Kapoor:Celgene: Research Funding; Takeda: Research Funding. Russell:Vyriad: Equity Ownership. Kumar:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding.

Abstract Introduction: Light chain burden in light chain (AL) amyloidosis is often low, making accurate response assessment challenging. Methods: AL amyloidosis patients achieving very good partial or complete response to first line therapy and had serial sFLC studies during and after completion of therapy were included (n=396). Involved free light chain (iFLC), difference in involved-to-uninvolved free light chains (dFLC) and sFLC ratio (sFLCR) were assessed at the end of first line therapy and at nadir iFLC. Survival analysis was done using the Kaplan-Meier method. Hematological progression-free survival (hemPFS) was defined as the time from diagnosis until hematological progression or death, where patients known to be alive and progression-free at the end of follow-up were censored. Hematological progression was defined according to consensus criteria or upon initiation of second line therapy, whichever came first. Results: The median iFLC and dFLC at the end of therapy was 1.7 mg/dL and 0.5 mg/dL, respectively. sFLCR normalization occurred in 70% of patients. iFLC ≤2 mg/dL and dFLC ≤0.5 mg/dL were associated with a longer hemPFS compared to their counterparts (Figure). Only iFLC ≤2 mg/dL was associated with a significantly longer overall survival (Figure). sFLCR normalization did not predict hemPFS or overall survival. Organ response was predicted by iFLC ≤2 mg/dL and dFLC ≤0.5 mg/dL (Table), with best discrimination seen with iFLC ≤2 mg/dL. Organ response was not predicted by sFLC normalization (Table). The median nadir iFLC was 1.4 mg/dL and was reached 3.9 months from the end of therapy, longer in transplanted patients compared to patients treated with non-transplant regimens (7.3 vs 1.8 months, respectively; P<0.001). iFLC ≤2 mg/dL at the completion of therapy and nadir iFLC reached >12 months from the end of therapy were favorable predictors of hemPFS/OS in a multivariate analysis. Conclusion: iFLC at the end of first line therapy better predicts for organ response and survival than dFLC among deep responders. Normalization of sFLCR does not predict for organ response or survival and should not be used as measure of therapeutic efficacy. Figure. Figure. Disclosures Dispenzieri: Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Dingli:Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Millennium Takeda: Research Funding; Millennium Takeda: Research Funding. Kapoor:Celgene: Research Funding; Takeda: Research Funding. Russell:Vyriad: Equity Ownership. Kumar:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding. Gertz:Alnylam: Honoraria; celgene: Consultancy; Ionis: Honoraria; Abbvie: Consultancy; annexon: Consultancy; janssen: Consultancy; spectrum: Consultancy, Honoraria; Research to Practice: Consultancy; Medscape: Consultancy; Apellis: Consultancy; Teva: Consultancy; Amgen: Consultancy; Prothena: Honoraria; Physicians Education Resource: Consultancy.

Abstract ATTRwt (formerly known as senile) amyloidosis and plasma cell disorders share a common demographic of occurrence with increasing prevalence with age. We aimed to identify the prevalence of plasma cell disorders in patients diagnosed with ATTRwt. We retrospectively reviewed all patients seen at Mayo Clinic Rochester between 1st January 2009 and 31st of December 2017 who were diagnosed with ATTRwt. The start date of the study was chosen to coincide with routine clinical availability of laser microdissection mass spectrometry (LCMS) for subtyping of amyloidosis. 492 patients with ATTRwt were evaluated during the study period. Serum immunofixation electrophoresis (SIFE), urine immunofixation electrophoresis (UIFE) and serum free light chain (FLC) assay testing was performed in 74% (n=362), 53% (n=261) and 79% (n=386) respectively. Of the 492 ATTRwt seen during this period, 139 (28%) had abnormal monoclonal protein studies, the vast majority (92%, n=128) of which were monoclonal gammopathy of undetermined significance (MGUS). Monoclonal protein testing in this cohort included SIFE, UIFE and FLC in 96% (n=134), 71% (n=99) and 99% (n=137) respectively. The non-MGUS diagnoses included smoldering multiple myeloma in <1%% (n=2), multiple myeloma (MM) in 6% (n=8), AL amyloidosis in 2% (n=3), and lymphoplasmacytic lymphoma (LPL) in 3% (n=4). MM and LPL developed after progression from MGUS in 2 and 3 patients respectively. Two patients with MGUS also had a diagnosis of low grade non Hodgkin lymphoma (chronic lymphocytic leukemia in one and marginal zone lymphoma in the other). The abnormal monoclonal protein studies included SIFE in 55%, UIFE in 26% and an abnormal serum free light chain ratio (FLCr) in 73%. The organ biopsied for the diagnosis of ATTRwt was heart in 43% (n=60), bone marrow in 24% (n=33), fat in 9% (n=12) and other sites in 5% (n=8, 3 lung, 2 lip, 2 bladder and 1 small bowel). LCMS confirmed the subtype of amyloidosis as ATTRwt in all patients with a biopsy positive for amyloidosis by congo red staining. 19% (n=26) of patients were diagnosed with ATTRwt based on clinical features and a strongly positive PYP scan. PYP scan was positive for ATTR in 55/56 patients in whom the test was performed. The most common monoclonal protein isotypes detected were light chain (45%) and IgG (28%). Light chain subtype was kappa in the majority of patients (80%). Plasma cell disorders are not uncommon in patients with ATTRwt amyloidosis. The diagnosis of a plasma cell disorder and ATTRwt are not mutually exclusive, and their coexistence can confuse the diagnosis if amyloid typing is not performed. Patients with ATTRwt may be misclassified as AL amyloidosis due to the presence of amyloid and a clonal plasma cell disorder with significant prognostic and therapeutic implications. Disclosures Kumar: Novartis: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding. Lacy:Celgene: Research Funding. Dingli:Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Millennium Takeda: Research Funding; Millennium Takeda: Research Funding; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.. Kapoor:Takeda: Research Funding; Celgene: Research Funding. Gertz:Ionis: Honoraria; Research to Practice: Consultancy; Amgen: Consultancy; Prothena: Honoraria; Alnylam: Honoraria; Medscape: Consultancy; celgene: Consultancy; Teva: Consultancy; Abbvie: Consultancy; janssen: Consultancy; spectrum: Consultancy, Honoraria; annexon: Consultancy; Apellis: Consultancy; Physicians Education Resource: Consultancy. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding.