Kapoor, Prashant

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.

Background: Based on results from the phase 3 trials, maintenance therapy after autologous stem cell transplantation has become the standard of care. While lenalidomide is typically used as the maintenance agent, patients with high risk MM are often maintained on proteasome inhibitor-based maintenance treatment. We examined the trends in maintenance use and outcomes in a large group of patients transplanted at a single institution over two decades spanning the years when maintenance gradually became standard of care. Methods: We included patients who underwent their first autologous stem cell transplantation between 2000 and 2016 in the current study. Patients who received an allogeneic SCT or a planned tandem SCT were excluded. Clinical data was extracted from the medical records or from a prospectively maintained database. Early transplant was defined as SCT within 12 months of diagnosis. High risk (HR) myeloma was defined as per IMWG criteria, based on presence of high-risk FISH abnormalities. Progression free survival and overall survival were estimated from either diagnosis as well as from the date of SCT. Results: We included 1961 patients with MM who were transplanted between January 2000 and August 2016 in the current analysis. Majority (n=1496; 76%) had an early SCT while the remaining patients were transplanted beyond 12 mos from diagnosis. Maintenance was employed in 31% of the patients, 33% of the early SCT and 23% of the delayed SCT. Proportion of patients receiving maintenance increased over the years: <1% in 2000 to 85% in 2016. The most common maintenance approach was an IMiD (56%), followed by a PI (33%) and a PI+IMiD (8%). FISH risk was available in 875 patients, all assessed within 6 months of diagnosis, and 22% were HR. Overall, maintenance was more commonly used in HR patients (64% vs. 36%), and a PI containing maintenance was more commonly used in HR (42% vs. 12%). The PFS was superior for those receiving a maintenance therapy (70 vs. 23 mos, P<0.001); NR vs. 27 mos for early SCT and 25 vs. 16 mos for delayed SCT. The impact of maintenance therapy was more evident in the HR group HR vs SR risk ratio was 2.3 without maintenance, and 1.5 with maintenance. Among the HR patients, PI based maintenance had a trend towards better outcome, while the PFS was better with non-PI maintenance among the SR patients. OS from diagnosis was also better among the early SCT group who received maintenance (99 vs. 88 mos; p=0.01); however, the OS advantage appeared most evident among the HR patients. Conclusions: The experience with maintenance therapy post autologous SCT for myeloma in a non-clinical trial setting appear to confirm the findings from the phase 3 trials. Maintenance provided benefit in patients who had a delayed SCT in our experience. The benefit appear to be particularly relevant for high risk patients, who appear to benefit from PI based regimens. In contrast, SR patients appear to benefit primarily from IMiD based regimen. Disclosures Gertz: Spectrum: Consultancy, Research Funding; Johnson and Johnson: Speakers Bureau; Amgen: Consultancy; Ionis/Akcea: Consultancy; Research to Practice: Consultancy; Appellis: Consultancy; Celgene: Consultancy; Teva: Speakers Bureau; Alnylam: Consultancy; Janssen: Consultancy; Annexon: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Medscape: Consultancy, Speakers Bureau; Prothena Biosciences Inc: Consultancy; Physicians Education Resource: Consultancy. Lacy:Celgene: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Dingli:Millenium: Consultancy; Rigel: Consultancy; Janssen: Consultancy; alexion: Consultancy; Karyopharm: Research Funding. Kapoor:Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding; Celgene: Honoraria; Janssen: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy, Research Funding. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Background: The treatment of Multiple Myeloma (MM) has evolved significantly in the past decade with the introduction of novel agents and drug combinations, thus enhancing treatment efficacy and allowing more patients to achieve complete response (CR). This has created a need to identify surrogates for depth of treatment response. Serum free light chain (sFLC) ratio normalization has been shown to be prognostic for progression free survival as well as overall survival in patients achieving a complete response to therapy. Consequently, it has been incorporated as a defining feature for stringent CR, along with lack of clonal plasma cells by immunohistochemistry (IHC) or low sensitivity flow cytometry. The routine use of multiparametric flow cytometry with higher sensitivity to detect residual disease than IHC or the older 4-color flow cytometry, has raised the question as to whether sFLC ratio is still a valid indicator of response depth. Moreover, in nearly half of the patients with an abnormal sFLC ratio after treatment, the abnormality is secondary to suppression of one or both serum light chains. Therefore, we designed a retrospective study to address these issues. Patients and Methods: This is a retrospective study using the Multiple Myeloma Database at Mayo Clinic, Rochester. We included patients who, after any line of therapy, had negative serum and urine immunofixation and absence of clonal bone marrow plasma cells by flow cytometry (PC-PRO), which has a sensitivity of >10-4. Simultaneous sFLC data was also extracted. Patients were grouped into three categories based on their sFLC ratios: 1) normal ratio (normal), 2) abnormal ratio due to suppression of the uninvolved light chain (LC), involved LC, or both (Abn-suppressed) and 3) abnormal ratio due to elevation of the involved LC (Abn-inv elevated). The primary endpoint was the median time to next treatment (TTNT), defined as the time from sample collection to the time of initiation of the subsequent therapy or time of last follow up if a subsequent line of treatment was not initiated. Results: The cohort consisted of 510 patients. 285 (56%) were males and 225 (44%) females. Median age was 61 years (IQR: 55-67). Median Follow-up was 41 months. The last treatments administered prior to data collection included stem cell transplant (SCT) (with or without maintenance) in 290 (57%) patients, and non-SCT regimens in the others. The sFLC ratio was normal in 337 (66%) and abnormal in 173 (34%) patients. Among the patients with abnormal sFLC ratios, 81 had elevated involved LC, 25 had suppression of the involved LC, 45 had suppression of the uninvolved LC and 22 had suppression of both LCs. We first examined the TTNT for the three groups and found that the TTNT was identical for those with a normal ratio and those with an abnormal ratio due to suppression of one or both light chains (Figure 1). So, we combined these two groups (Normal-Abn suppressed) and compared their outcomes to the patients with abnormal sFLC ratio due to elevated involved LC. The Abn-inv elevated group had a shorter TTNT as shown in Figure 2 (log-rank 0.06, Wilcoxon <0.01). The Abn-inv elevated group also had decreased overall survival compared to the other group (log-rank: 0.05, Wilcoxon: 0.01) (Figure 3). Conclusion: This study provides 2 important observations. First, patients with an abnormal ratio due to suppression of one or both LCs have outcomes similar to those with a normal ratio, suggesting a need to clarify the current definition of stringent CR. Second, the study suggests an important prognostic value for an abnormal sFLC ratio due to elevated involved LC, suggesting this as an important surrogate for depth of response. Disclosures Kapoor: Janssen: Research Funding; Takeda: Honoraria, Research Funding; Cellectar: Consultancy; Celgene: Honoraria; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Glaxo Smith Kline: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Gertz:Ionis: Honoraria; Alnylam: Honoraria; Prothena: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Spectrum: Honoraria, Research Funding. Lacy:Celgene: Research Funding. Dingli:Karyopharm: Research Funding; Rigel: Consultancy; Millenium: Consultancy; Janssen: Consultancy; alexion: Consultancy. Leung:Takeda: 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; Omeros: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: 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.

Background: Lenalidomide maintenance therapy post-autologous stem cell transplantation (ASCT) is associated with improved progression-free survival (PFS) and possibly overall survival in multiple myeloma (MM). However, almost all patients do relapse as a result of residual multiple myeloma cells that remain after the high-dose chemotherapy. In the myeloma setting it has been found that the hedgehog (Hh) pathway is essential for maintaining a subset of tumor causing stem cells. LDE 225 (Sonidegib) is a potent selective oral bioavailable antagonist of Smoothened (SMO), a component of the Hh signaling pathway. In in vitro experiments, LDE225 treatment of myeloma cell lines resulted in a modest inhibition of cell proliferation at increasing doses. When LDE225 was combined with lenalidomide, a more than additive effect was observed in terms of cell proliferation, an effect that was more pronounced in the context of myeloma cell lines growing in co-culture with marrow derived stromal cells. These findings form the basis of evaluation of LDE 225 as a strategy to enhance the activity of lenalidomide in the post-transplant maintenance setting. The minimal residual state post SCT provides the most optimal situation for evaluation of a drug that is likely to work by inhibiting the tumor cells that escaped high dose therapy. Methods: Multiple myeloma patients without evidence of progression, who were 60 - 120 days after a single autologous stem cell transplant (SCT), performed within 1 year of diagnosis were eligible for the study. Maintenance therapy was started approximately 3 months after SCT. Treatment consisted of lenalidomide 10 mg days 1-21 and LDE225 400 mg days 1-28 in 28-day cycles for a total of 18 cycles. The goal of the study was to assess toxicity of this combination, complete response rate (CR) progression free survival (PFS) at 1 and 2 year and overall survival (OS). CR and PFS were estimated using an exact binomial distribution and Kaplan Meier curves respectively. Results: A total of 28 patients were accrued from Jan 2014 to Aug 2016, 1 patient canceled prior to treatment and 1 patient was deemed ineligible resulting in 26 evaluable pts for CR and PFS. The median age of all pts (n=26) was 60 years (range 43-69) and 50% were males. Seventy-three percent of patients reported one treatment regimen prior to SCT, while 27% reported 2 or more prior regimens. The other characteristics of the patient are summarized in Table 1. Twenty seven pts received at least one cycle of treatment and are evaluable for toxicities (AE). Patients were treated for a median of 12.5 (range 1-18) cycles. While 10 pts (38.5%) completed protocol treatment (18 cycles), the remaining 16 pts went off treatment due to AEs (6, 23%), disease progression (3, 11.5%), refusal of further treatment (3, 11.5%) and other reasons (4, 15.4%). A grade 3 or higher AE at least possibly attributed to either drug was seen in 63%. Grade 3+ hematologic toxicities were noted in 30%, with 7% neutropenia and 4% thrombocytopenia. Notable grade 2+ non-hematologic toxicities with more than 5% incidence were dysgeusia 22%, alopecia 11%, and anorexia 7%. Grade 3+ non-hematologic toxicities were fatigue, myalgia and arthralgia each at 7%. The CR rate in evaluable patients was 46% (5 CRs and 7 sCRs) with a 95% CI of 27% - 66%. CR rate improved from 31% to 46%. VGPR or better improved from 42% to 85%. The 24-month PFS (time from SCT to progression or death due to any cause) was 73% (95% CI: 57.9 - 92.3%) with a median time to censoring of 38 months. Conclusion: Lenalidomide in combination with LDE225 as posttransplant maintenance therapy was associated with some toxicity but manageable. The combination improved the depth of response after autologous stem cell transplant. Long-term follow-up is needed to determine overall survival. Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Celgene: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Janssen: Consultancy; Intellia: Consultancy; Akcea: Consultancy; Alnylam: Research Funding. Gertz:Ionis: Honoraria; Alnylam: Honoraria; Prothena: Honoraria; Celgene: Honoraria; Spectrum: Honoraria, Research Funding; Janssen: Honoraria. Kapoor:Glaxo Smith Kline: Research Funding; Amgen: Research Funding; Janssen: Research Funding; Cellectar: Consultancy; Takeda: Honoraria, Research Funding; Celgene: Honoraria; Sanofi: Consultancy, Research Funding. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Russell:Imanis: Equity Ownership. Kumar:Janssen: Consultancy, Research Funding; Takeda: Research Funding; Celgene: Consultancy, Research Funding. OffLabel Disclosure: Sonidegib (LDE 225) is a selective oral bioavailable antagonist of Smoothened (SMO), a component of the hedgehog signaling pathway.

AbstractRisk stratification of multiple myeloma (MM) at diagnosis is critical. We examined the ability of hematopoietic indices including mean corpuscular volume (MCV), hemoglobin (Hgb), and platelet (Plt) to predict outcomes. This was a retrospective study of patients treated at Mayo Clinic between January 2004 and April 2018. We incorporated three variables (Hgb < 10 g/dL, Plt < 150 × 109/L, and MCV > 96 fL), assigning a score of 1 to each. We identified 1540 newly diagnosed MM patients, of whom 707 (46%) had a score of 0, 513 (33%) had a score of 1, 260 (17%) had a score of 2, and 60 (4%) had a score of 3. The score risk stratified patients into four groups with differing survivals. The median PFS was 32.3 months for score 0, 24.8 months for score 1, 21.7 months for score 2, and 18.3 months for score 3, for P < .001. The median OS was 80.7 months for score 0, 59.9 months for score 1, 51.7 months for score 2, and 31.3 months for score 3, P < .0001. Predictors of OS on the multivariable analysis were age ≥ 65 (HR, 1.93; P < .0001), R‐ISS stage (1‐2 vs 3) (HR, 0.48; P < .0001), and hematopoietic score (0‐2 vs 3) (HR, 0.51; P = .006). A hematopoietic score can predict survival in newly diagnosed myeloma patients.

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: Waldenström macroglobulinemia (WM) is an indolent B-cell lymphoma with a heterogeneous disease course. For nearly a decade, the International Prognostic Scoring system (IPSS), requiring 5 variables (platelet count, hemoglobin, age, Beta 2 microglobulin and immunoglobulin M size) has been used to prognosticate patients with active WM. In this study, we attempt to propose a simplified prognostic model for patients with active/symptomatic WM. Methods: All patients with active WM diagnosed between 01/01/1996 and 12/31/2017 and evaluated consecutively at Mayo Clinic, Rochester were included in the study after Institutional Review Board approval. Active WM was defined as ≥10% marrow infiltration with lymphoplasmacytic cells plus monoclonal IgM of any size requiring systemic therapy. The follow up and overall survival (OS) were calculated from the time of active WM until date of last follow up or death. Baseline parameters at active disease were used to assess prognostic factors for OS using a univariate followed by a multivariate (MV) Cox regression analysis. Independent variables on the MV analysis were given a score proportional to their risk ratios (RR). All time-to-event analyses were performed using the Kaplan-Meier method and the survival curves were compared using log-rank test. Discriminatory ability of the IPSS and the currently proposed prognostic system was assessed using Harrell's concordance index wherein a higher c-statistic is associated with a better discriminatory ability. Results: We identified 889 patients with active WM. The median follow up was 8.2 years (95% CI: 7.5-9 years). The baseline characteristics of the patients are shown in Table 1. At the time of diagnosis of WM, 16% of patients had previously documented MGUS and 16% patients had smoldering (asymptomatic) WM. The course of WM was complicated by systemic amyloidosis in 8% (n=69), transformation to high-grade lymphoma in 4% (n=38), symptomatic hyperviscosity in 13% (n=118), myelodysplastic syndrome in 2% (n=17) and Bing-Neel syndrome in 1.4% (n=12) of patients. Of the patients tested, cryoglobulinemia was present in 17% (n=48), cold agglutinin disease in 34% (n=43) and Coombs positive hemolytic anemia in 9% (n=34) patients. The median OS was 10.6 years (95% CI: 9.7-11.4 years). The factors affecting OS are shown in Table 2. While the patients' MYD88L265P mutation status was not found to be prognostic for OS, age >65 years [RR 1.8 (95% CI: 1.2-2.8); p=0.01], LDH > upper limit of normal [RR 2.5 (95% CI: 1.3-4.6); p=0.003] and serum albumin <3.5 g/dL [RR 1.6 (95% CI: 1.1-2.5); p=0.02] were independently prognostic. Owing to comparable RRs, each of these were assigned a score of 1 point and a prognostic model with a minimum score of 0 and maximum score of 3 was constructed. A score of 0 was considered as low risk WM and 1 as intermediate risk WM. The patients with scores of 2 and 3 were analyzed together to form the high risk cohort due to comparable OS for these two groups. The patient outcomes based on this prognostic model are depicted in Figure 1. Using the new prognostic model (n-=341), the median OS for the low risk group (n=71, 21%) was 14.6 years (95% CI: 9 years- not reached) compared to 11 years (95% CI: 8.1-14.7 years) for intermediate risk (n=140, 41% ) and 7.2 years (95 % CI: 5.4-10 years) for the high risk group (n=130, 38%), p<0.0001. The data for the IPSS-WM were available in 319 patients in the entire cohort. The OS for low risk IPSS (n=56) was 14.6 years (95% CI: 12.1 years-NR), 15.6 years (95% CI: 8.3-18.5 years) for intermediate risk IPSS (n=131) and 9.1 years (95% CI: 6.8-11.2 yeas) for the high risk IPSS group (n=132; p=0.009). Among the 220 patients having data for IPSS-WM as well as our proposed model, the current three variable model held its prognostic significance (p=0.0004). The Harrell's c-index was 0.647 (95% CI 0.592-0.702) for our prognostic model and 0.58 (95%CI: 0.521-0.638) for IPSS-WM. Common frontline treatment comprised of rituximab monotherapy (n=277, 33%), rituximab with alkylator or purine analog combination (n=255, 30.5%) and other therapies, including alkylators/purine analog monotherapy, ibrutinib, proteasome inhibitors, etc., in 37% patients. Conclusion: A simpler, clinically useful, risk stratification model based on age, serum albumin and serum LDH with a potentially higher discriminatory value than IPSS-WM may be used to prognosticate patients with WM. This model requires external validation. Disclosures Ansell: Pfizer: Research Funding; Affimed: Research Funding; Celldex: Research Funding; Bristol-Myers Squibb: Research Funding; Takeda: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Merck & Co: Research Funding; Regeneron: Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Gertz:Abbvie: Consultancy; Prothena: Honoraria; Medscape: Consultancy; annexon: Consultancy; Amgen: Consultancy; Alnylam: Honoraria; Teva: Consultancy; janssen: Consultancy; Physicians Education Resource: Consultancy; Ionis: Honoraria; spectrum: Consultancy, Honoraria; celgene: Consultancy; Research to Practice: Consultancy; Apellis: Consultancy. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Lacy:Celgene: Research Funding. Dingli: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.; Millennium Takeda: Research Funding. Kumar:Takeda: Membership on an entity's Board of Directors or advisory committees; Merck: 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; 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; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: 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; Roche: Research Funding; KITE: 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. Kapoor:Takeda: Research Funding; Celgene: Research Funding.

Abstract Introduction Waldenstrom macroglobulinemia (WM) is a rare disease accounting for only 1-2% of all hematologic malignancies and with an overall annual, age-adjusted incidence of approximately 3.5 to 5.5 cases per million-person years. With approximately 13,000 active hematologist/oncologists in the US, most of who are in the community oncology setting, it's estimated that a hematologist/oncologist will only diagnose a WM case approximately every 8 years. Therefore, the clinical experience of a general hematologist/oncologist in the management of WM is likely very limited compared to more prevalent malignances. Previous studies in the setting of rare cancers suggest a correlation between higher volume of care and improved outcomes. Therefore, we explored the volume-outcome relationship in WM using the National Cancer Data Base (NCDB). Methods Patient-level data from the NCDB, a nationwide, facility-based, database covering approximately 70% of all newly diagnosed cancer cases in the US, was queried for all new WM cases diagnosed between 2004 and 2014. Only patients requiring treatment were included. Treatment facilities were divided into quartiles based on the average annual volume of newly diagnosed cases of WM seen. Cox regression was used to analyze the association between facility WM volume and survival, adjusted by demographics (sex, age, race), socioeconomic status (income, education, insurance type), geography (area of residence, treatment facility type, travel distance), comorbidity factors (Charlson-Deyo score), and year of diagnosis. Time-to-event analysis was calculated from frontline therapy initiation date using the Kaplan-Meier method and the log-rank test. Results A total of 3,732 patients with WM treated in 831 facilities were included. The median age at diagnosis was 70 years and 75% of the patients were treated within 20 miles from their residency zip code. Patient characteristics per treatment facility volume quartile are shown in table 1. The median annual facility volume was 1 new WM patient/year (range 0.1 to 21). The median follow-up from frontline treatment was 5 years. The unadjusted median OS by facility volume was: Q1: 6.5 years (95% CI: 5.7-7.4), Q2: 7 years (95% CI: 6.3-8.2), Q3: 8.2 years (95% CI: 7.1-8.9), and Q4: NR (95% CI: 8.5-NR), p<0.0001 (figure 1). The estimated 5-year OS by facility volume was: Q1: 56%, Q2: 61%, Q3: 64%, Q4: 71%, p<0.0001. Multivariate analysis including all variables showed in Table 1 demonstrated that facility volume was independently associated with all-cause mortality. Compared to patients treated at Q4 facilities, patients treated at lower-quartiles facilities had a higher incremental risk of death (Q3 hazard ratio [HR], 1.07 [95% CI: 0.88 to 1.29] p=0.46; Q2 HR, 1.34 [95% CI: 1.11 to 1.63] p=0.002; Q1 HR, 1.52 [95% CI: 1.23 to 1.88] p=<0.0001). Conclusion Our results suggest that a volume-outcome relationship exits in WM as patients treated initially at higher-volume facilities had a lower risk of mortality. Although differences in the underlying disease biology, referral patterns after initial therapy, or cumulative treating-physician experience could not be assessed, these potential biases would only underestimate the magnitude of the volume-outcome relationship reported. Disclosures Ansell: Celldex: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Pfizer: Research Funding; Affimed: Research Funding; Merck & Co: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding. Gertz:Medscape: Consultancy; janssen: Consultancy; Alnylam: Honoraria; Ionis: Honoraria; Physicians Education Resource: Consultancy; Prothena: Honoraria; Teva: Consultancy; Research to Practice: Consultancy; spectrum: Consultancy, Honoraria; celgene: Consultancy; Amgen: Consultancy; Abbvie: Consultancy; annexon: Consultancy; Apellis: Consultancy. Kapoor:Takeda: Research Funding; Celgene: Research Funding. Ailawadhi:Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Research Funding; Celgene: Consultancy; Takeda: Consultancy. Reeder:Affimed: Research Funding. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Lacy:Celgene: Research Funding. Kumar: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; 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.

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.