Zeldenrust, Steven R.

Abstract Introduction: Melphalan based chemotherapy is commonly used for treatment of light chain amyloidosis (AL). Patients with AL often receive chemotherapy before autologous stem cell transplantation (ASCT) if they have high plasma cell burden or while awaiting ASCT. Melphalan is an alkylator and can affect bone marrow stem cells. Limited data is available on the effect of melphalan on stem cell mobilization in patients with amyloidosis. This study aims to identify the impact of melphalan therapy on collection of stem cells and ASCT in amyloidosis. Methods: All patients with AL seen at our institution within 90 days of diagnosis over a 10-year period (2006 to 2015) who underwent stem cell harvest were identified from an institutional database. Data pertaining to demographics, diagnosis, treatment, stem cell harvest and ASCT was extracted from the electronic medical records. Analysis was carried out by chi-square and Fisher's exact test for categorical variables and Kruskal-Wallis and Wilcoxon rank sum test for ordinal and continuous variables. Results: Three hundred and seventy two patients with AL who met the inclusion criteria were identified, of whom 10% (n=38) received melphalan based chemotherapy prior to harvesting, 28.5% (n=106) received non-melphalan based chemotherapy and 61.3% (n=228) received no chemotherapy prior to stem cell collection. Bortezomib based regimens were the most common (78%, n=83) non-melphalan based chemotherapy. All three groups were similar in terms of median age at diagnosis (59.1 years), median age at collection (59.4 years), gender distribution (59% males, n=221) and type of involved free light chain (FLC), with lambda being more common (72.2%, n=268). Patients who received melphalan-based chemotherapy had more cardiac (73.8% vs. 45.2% vs. 46.4%, p=0.005) and renal (84.2% vs. 50.9% vs. 68%, p=0.0002) involvement compared to other chemotherapy and no chemotherapy groups, respectively. In contrast, patients who received non-melphalan based chemotherapy had higher plasma cell burden (15% vs. 6% vs. 10%, p< 0.0001) and greater difference between involved and uninvolved FLC (44.2 mg/dL vs. 13.3 mg/dL vs. 13.2 mg/dL, p< 0.0001) compared to melphalan and no chemotherapy, respectively. Median duration of melphalan based chemotherapy was shorter at 54 days (34.5 to 79.5) or estimated 2 cycles compared to 101 days (60 to 135.5) or estimated 4 cycles (p=0.0019). Despite shorter duration of chemotherapy, total stem cell yield (million CD34/kg) was lower in patients who received melphalan based chemotherapy (5.54) compared to non-melphalan based chemotherapy (8.14) or no prior chemotherapy (7.94); p<0.0001. Similarly, day one stem cell yield (million CD34/kg) was the lowest in the melphalan group (2.71), followed by other chemotherapy group (3.63) and highest in no chemotherapy group (4.84); p<0.0001. This trend persisted for average stem cell yield per collection as illustrated in table 1. Filgrastrim (GCSF) alone was the most common mobilizing agent. However, patients with any chemotherapy prior to harvesting had higher utilization of plerixafor; 26.3% (n=10) in the melphalan group and 39.6% (n=42) in the non-melphalan group compared to 11.6% (n=27) if no prior chemotherapy (p<0.0001). However, no statistically significant difference was seen for melphalan vs. non-melphalan chemotherapy groups (p=0.44). In patients who underwent ASCT (85%, n=315), median stem cell dose (million CD34/kg) was different in the melphalan (3.66), non-melphalan (4.2) and no chemotherapy groups (4.44) (p=0.047), though the difference was not statistically significant amongst the 2 chemotherapy groups (p=0.34). There was also no difference in time to engraftment (table 1). Conclusions: Melphalan based chemotherapy, even if used for a short duration of time, significantly decreases both total stem cell yield and the yield on day one. It therefore has the potential to add to resource utilization with more collections needed. As much as possible, limited cycles of melphalan based chemotherapy or non-melphalan based treatment should be utilized in patients who are transplant eligible. Disclosures Dispenzieri: GSK: Membership on an entity's Board of Directors or advisory committees; Alnylam: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; Jannsen: Research Funding; Celgene: Research Funding; pfizer: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kapoor:Amgen: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Kumar:Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Research Funding; Glycomimetics: Consultancy; BMS: Consultancy; Sanofi: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Kesios: Consultancy.

Abstract Introduction: Chemotherapeutic options for patients with systemic light chain amyloidosis (AL) who are not transplant candidates include bortezomib based therapy, melphalan with dexamethasone, and less commonly, immunomodulatory drugs (IMiDs). However, prospective clinical trial data comparing these regimens are lacking. This study aims to compare efficacy of bortezomib-based treatment to other therapies. Methods: All patients with AL seen within 90 days of diagnosis at our institution over a 10-year period (2006 to 2015) who did not undergo a stem cell transplant were identified from our institutional database. Data pertaining to demographics, diagnosis, treatment and follow-up were extracted from electronic medical records. Analyses were carried out by chi-square and Fisher's exact test for categorical variables and Kruskal-Wallis and Wilcoxon rank sum test for ordinal and continuous variables. Progression free survival (PFS) is defined as time to death, progression requiring treatment change or relapse requiring re-institution of treatment. PFS and overall survival was analyzed via the Kaplan-Meier method. Results: Seven hundred and twenty five patients met the inclusion criteria, of which 38% (n=275) received bortezomib containing regimens and 62% (n=450) received non-bortezomib based therapies. Bortezomib was used with dexamethasone in 24% (n=67) patients; and with other drugs, most commonly cyclophosphamide, in 76% (n=208) patients. Non-bortezomib treatment regimens included melphalan-based treatment in the majority (92%, n=414) followed by IMiDs with steroids and other drugs (8%, n=36). Baseline variables similar in both groups and their distribution in the entire cohort was as follows: gender distribution (63.3% males, n=459), median age of diagnosis (66.3 years, range 32.2 to 93.6), type of involved free light chain (FLC) (lambda 73%, n=523) and median plasma cell burden (10%, range 0 to 91). Median difference between the involved and uninvolved free light chain (dFLC) was higher in the bortezomib group (29 mg/dL vs. 23 mg/dL; p=0.017). There was no difference in organ involvement. In the bortezomib group, organ involvement was as follows: cardiac (81%, n=219), renal (62%, n=168) and hepatic (18%, n=48). In the non-bortezomib group, the rates of organ involvement were similar: cardiac (78%, n=346), renal (57%, n=247) and hepatic (19%, n=85). Median duration of first line treatment was similar in the 2 groups, with 178 days in the bortezomib cohort and 187 days in the non-bortezomib cohort. Response rates are illustrated in Table 1. Rates of very good partial response (VGPR) or better response were higher in the bortezomib group (64 % vs. 54%, p=0.0002). Patients treated with bortezomib achieved VGPR faster with higher rates of VGPR or better response seen at 3 months (48% vs. 27%, p <0.0001) and 6 months (57% vs. 34%, p < 0.0001) after initiation of therapy compared to non-bortezomib treatment. Rates of organ response were similar amongst the 2 groups as shown in Table 1. However, median time taken to achieve a cardiac response was shorter in the bortezomib group (23 vs. 38 weeks, p=0.0026). In a multivariable model, bortezomib-based treatment and dFLC at diagnosis were predictors of VGPR. Relapse or progression requiring change in therapy was more common in patients treated with non-bortezomib based therapy (38%, n=143/372) compared to bortezomib-based treatment (28%, n=67/236); p =0.01). However, no difference in overall survival was observed in patients treated with bortezomib (2.2 years; 95% confidence interval (CI): 1.7 to 3.3) vs. non-bortezomib therapies (1.7 years; 95% CI: 1.3 to 2.5). Conclusion: Treatment with bortezomib-based regimens results in a deeper response including higher rates of early VGPR at 3 and 6 months from starting therapy. Moreover, these patients achieve cardiac response faster and have lower rate of relapse. However, no difference in overall survival was seen, which may be explained by subsequent use of bortezomib-based therapies in this population. Disclosures Dispenzieri: Celgene: Research Funding; Alnylam: Research Funding; pfizer: Research Funding; Jannsen: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Membership on an entity's Board of Directors or advisory committees; Prothena: Membership on an entity's Board of Directors or advisory committees. Kumar:Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; AbbVie: Research Funding; Janssen: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; BMS: Consultancy; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Array BioPharma: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Kesios: Consultancy; Glycomimetics: Consultancy.

Abstract AL amyloidosis is a systemic disease with profound effects on organ function. However, despite the broad array of disease manifestations, the effect of AL amyloidosis on thyroid function is underreported. We explored the frequency of thyroid function abnormalities in 961 untreated AL amyloidosis patients seen in our clinic between 8/2005-8/2015, with emphasis on association with other organ involvement and tumor burden. Thyroid function was assessed using the thyroid stimulating hormone assay (TSH, normal range 0.3-5 mIU/L). If TSH was abnormal, measurement of free thyroxine (FT4) and thyroid peroxidase (TPO) antibodies was routinely performed. Patients' median age was 62 [interquartile range (IQR) 56-69], 62% were male (Table). The median number of organs involved was 2 (IQR 1-3), 29% of patients had more than 2 involved organs. Seventy-seven percent of patients had cardiac involvement, 61% renal, 23% peripheral/autonomic neuropathy, 19% hepatic and 15% gastro-intestinal (GI) involvement. The median difference between involved and uninvolved light chains (dFLC) was 24.4 [interquartile range 10.6-65.2 mg/dL]. The median TSH was 3 mIU/L (range 0.1-50.1); 22% had levels above the normal range and 8% of patients had TSH greater than 7.5 mIU/L. Baseline characteristics by TSH ≤5 mIU/L and TSH >5 mIU/L subgroups can be viewed in Table. Patients with renal or hepatic involvement had higher TSH values compared to no renal or no hepatic involvement (3.2 vs 2.6 and 2.8 vs 3.8, respectively; P<0.001 for both comparisons). There was a borderline significance for higher TSH in patients with >2 organ involvement compared to 1-2 affected organs (3.3 vs 2.8; P=0.05), with a strong trend for higher TSH for dFLC ≥18 mg/dL compared to dFLC<18 mg/dL (P=0.07). In patients with renal involvement, presence of proteinuria > 2 grams/day was associated with a higher likelihood of TSH >7.5 mIU/L (13% vs 5%; P=0.003). Free thyroxine (FT4) measurements were performed in 214 (22%) of patients with a median value of 1.1 ng/dL(range 0.3-72), 6% had levels below the lower limit (0.8 ng/dL). One-hundred and sixty five patients (17%) were screened for TPO antibodies, of which 16% (n=27) had an elevated titer. L-thyroxine (median dose 100 mcg/d, range 25-350 mcg/d) was already prescribed to 157 of the patients (16%) at their first visit, but duration of treatment prior to AL amyloidosis diagnosis could not be determined. Seventeen patients (1.5%) were prescribed amiodarone (median dose 200mg/d, range 100-400 mg/d), and although numbers were low, patients with amiodarone treatment had a TSH twice as high as patients without this treatment (6 vs 2.9 mIU/L, P=0.006). In conclusion, thyroid function abnormalities are frequent at the time of AL amyloidosis diagnosis and are influenced by type of organ involvement as well as disease burden assessed by dFLC and/or number of affected organs. Amiodarone, although infrequently used in this disease, can cause a profound disturbance in thyroid function among these patients. Disclosures Dispenzieri: Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; pfizer: Research Funding; Celgene: Research Funding; Alnylam: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Jannsen: Research Funding. Kumar:AbbVie: Research Funding; Array BioPharma: Consultancy, Research Funding; Glycomimetics: Consultancy; Celgene: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Millennium: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; Kesios: Consultancy; BMS: Consultancy; Sanofi: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Abstract Introduction: Hematologic response criteria for light chain amyloidosis (AL) requires that difference in involved and uninvolved free light chains (dFLC) be at least 5 mg/dL (or 50 mg/L). However, many patients do not meet these criteria and are often excluded from clinical trials. These patients are challenging to follow clinically as organ response takes much longer and therefore response to treatment is difficult to evaluate in the first few cycles. This study aims to evaluate patients who had non-evaluable FLC (dFLC< 5 mg/dL) at diagnosis and compare them to those who had evaluable FLC (dFLC≥ 5 mg/dL). Methods: All patients with newly diagnosed AL seen within 90 days of diagnosis at our institution over a 10-year period (2006-2015) were identified from an institutional database. Data pertaining to demographics, diagnosis, treatment and follow-up was extracted from electronic medical records. Analysis was carried out by chi-square and Fisher's exact test for categorical variables and Kruskal-Wallis and Wilcoxon rank sum test for ordinal and continuous variables. Progression free survival (PFS) is defined as time to progression requiring treatment change or relapse requiring re-institution of treatment or death. PFS and overall survival (OS) were analyzed via the Kaplan-Meier method. Results: Of 1336 patients meeting inclusion criteria, dFLC at diagnosis was known in 1290. 85.4% (n=1101) had dFLC ≥ 5 mg/dL, while 14.6% (n=189) had non-evaluable FLC. Median age at diagnosis (65.2 vs. 63.9 years), gender distribution (males 56.1% vs.64.8%) and involved FLC (lambda: 72.2% vs. 72.9%) was similar in FLC < 5 mg/dL and FLC ≥ 5 mg/dL group. Cardiac (38.1 vs. 76.3%, p <0.0001) and liver (10.2% vs. 16.3%, p=0.03) organ involvement were less common in patients with non-evaluable FLC (table 1). NT-ProBNP was significantly lower in the group with dFLC < 5 mg/dL in patients with and without cardiac involvement, as was Mayo cardiac stage (table 1). A trend towards less gastrointestinal (GI) involvement (17.1% vs. 24%, p=0.09) was also seen with dFLC < 5 mg/dL. In contrast, a trend towards higher renal involvement was seen in patients with dFLC < 5 mg/dL (64.6% vs. 55.9%, p=0.08), though this was not statistically significant. Median 24 hour urine protein was significantly higher in all patients (with and without renal involvement) with dFLC < 5 mg/dL compared to dFLC ≥ 5 mg/dL group (table 1). Treatment details are listed in Table 1. ASCT (autologous stem cell transplant) was utilized more commonly in patients with dFLC < 5 mg/dL compared to patients with dFLC ≥ 5 mg/dL(43.2% vs. 26.1%, p <0.0001), including ASCT alone without chemotherapy (35.4% vs. 15.3%, p <0.0001).Rates of cardiac response (53.3% vs. 50.3%, p=0.88), and time to response (27.7 weeks vs. 35.6 weeks, p=0.67), were similar in both groups. Similarly, there was no difference in rates of renal and liver response and time taken to achieve a response (table 1). In patients with evaluable FLC, hematologic response was complete response (27.3%, n=245), very good partial response (21%, n=189), partial response (18%, n=160), no response (8%, n=74), progression (2%, n=15) and not known in 26.1% (n=216). In patients who had follow up data available, 30.6% (44/144) with dFLC < 5mg/dL experienced a relapse/progression with median PFS of 4.1 years (95% confidence interval (CI): 3 to 5.7), while 34.7% (304/875) with FLC ≥ 5 mg/dL experienced a relapse/progression with median PFS of 1.3 years (95% CI 1.1 to 1.5); p<0.0001. Median OS was higher in patients with dFLC < 5 mg/dL at diagnosis at 8.3 years compared to 2.4 years in patients with dFLC ≥ 5 mg/dL (p < 0.0001) as depicted in Figure 1. Conclusions: Patients with non-evaluable FLC at diagnosis have significant differences in organ involvement and survival compared to those with FLC ≥ 5 mg/dL at diagnosis. They have less cardiac and liver involvement and a trend towards less GI involvement, which may be secondary to low serum FLC burden and consequent less organ deposition. However, a trend towards higher renal involvement was seen in dFLC < 5 mg/dL group, with significantly higher urinary protein excretion. Loss of FLC in urine may result in lower serum FLC levels in this group. Survival was significantly better in patients with dFLC < 5 mg/dL, which may be explained by less cardiac involvement, lower cardiac stage and lower median FLC at diagnosis. Disclosures Dispenzieri: GSK: Membership on an entity's Board of Directors or advisory committees; Prothena: Membership on an entity's Board of Directors or advisory committees; pfizer: Research Funding; Celgene: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Alnylam: Research Funding; Jannsen: Research Funding. Kapoor:Amgen: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Skyline: Consultancy, Honoraria; BMS: Consultancy; AbbVie: Research Funding; Noxxon: Consultancy, Honoraria; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding.

Abstract Background: Renal impairment is a common feature of multiple myeloma (MM) seen in over a quarter of newly diagnosed patients (pts). Studies have confirmed the presence of renal impairment (RI) as a strong predictor of inferior survival in MM. Some studies have also indicated that reversibility of RI is associated with improved survival. However, it is not clear if normalization of renal function improves the outcome to that expected for MM pts without RI at diagnosis. Methods: We evaluated 1,135 consecutive pts with newly diagnosed MM seen at the Mayo Clinic, Rochester between December 2002 and January 2011. Renal function was assessed by the estimated creatinine clearance (CrCl) which was calculated by the modified MDRD formula. We examined these pts for improvement in renal function based on their CrCl at diagnosis and their highest CrCl during their disease course. RI was defined as having a CrCl of < 60. Pts were categorized based on their renal function at diagnosis and response to therapy: Group 1- CrCl >60 at diagnosis, Group 2- CrCl <60 at diagnosis but improved to >60 after therapy and Group 3- CrCl <60 at diagnosis and remained <60 after therapy. The degree of restoration of renal function was evaluated according to the IMWG criteria. Survival analysis was performed by the Kaplan-Meier method and differences assessed using the log rank test. Results: The median age at diagnosis was 65 years (range; 22 - 93) and 682 (60%) were male. The median follow up for the entire group from diagnosis was 73 mos (95% CI; 69 - 77). At diagnosis, 123 (11%) pts had a CrCl < 30, 322 (28%) had a CrCl of 30-59 and 690 (61%) had a CrCl >60. Most pts (N=754, 67%) received novel agent induction (NAI) therapy. The median PCLI was 0.7 (range: 0 – 22) and 91 (21%) pts had high-risk cytogenetics by FISH. The median OS for the pts with CrCl at diagnosis of < 30, 30-59 and >60 were 41 mos, 60 mos and not reached respectively (P < 0.001). Of the 445 patients with RI, the median absolute creatinine and CrCl at diagnosis were 1.6 mg/dL (range: 1 – 11) and 44 (range: 4 – 59) respectively. Among pts with RI, any improvement in CrCl was seen in 295 (66%) with median time to highest CrCl of 5 months and 228 (51%) had complete reversal of their RI. The median OS for pts with RI at diagnosis receiving and not receiving NAI therapy was not reached (NR) vs. 46 mos (P < 0.001). The median OS for Groups 1, 2 and 3 were NR, 60 and 49 mos respectively (Figure 1, P < 0.001). At a 6 month landmark analysis, the median OS for Groups 1, 2 and 3 were NR, 67 and 62 mos respectively (P < 0.001). The complete renal response and no renal response rates for pts with RI at diagnosis receiving and not receiving NAI induction therapy was (57% vs. 44%, P=0.004) and (29% vs. 39%, P=0.04) respectively. In a univariable analysis, presence of RI at diagnosis, no NAI therapy, older age, ISS stage 3, high-risk FISH, elevated PCLI, diagnosis prior to 2007 and increased LDH were found to predict for worse OS; however only older age (P<0.001), high-risk FISH (P=0.037) and lack of NAI therapy (P=0.023) retained their negative prognostic significance in a multivariable analysis. Conclusion: MM pts with RI treated with novel agent induction therapy demonstrate improved responses in their renal function and OS. The results also demonstrate improved outcome for pts with improvement in renal function, but it remains inferior to pts with normal renal function at diagnosis. These results have implications for early treatment strategies for pts at risk of developing renal insufficiency. Figure 1: OS based on improvement in CrCl upon receiving treatment Figure 1:. OS based on improvement in CrCl upon receiving treatment Figure 2 Figure 2. Disclosures No relevant conflicts of interest to declare.

Background: Primary Systemic Amyloidosis (AL) is a fatal disorder characterized by uncontrolled deposition of light chain derived amyloid with variable survival dependent on extent of organ involvement and degree of individual organ dysfunction. We previously demonstrated that troponin T (cTnT) and N-terminal fragment of brain natriuretic peptide (NT-ProBNP) together can allow prognostic stratification in AL. Uric acid (UA) is a marker of increased mortality in congestive heart failure and we examined its prognostic value in AL. Methods: A cohort 1977 patients with AL seen at our institution and 293 patients with AL undergoing stem cell transplant (PBSCT) were studied retrospectively to examine the value of serum UA. Results: The median OS for those with UA>8mg/dL was 9 months from diagnosis (95% CI; 7.4, 10.6) compared to 20.3 months for those with UA<=8mg/dL (95% CI; 17.8, 22.7), P<0.001 (Figure 1). As previously demonstrated both cTnT≥0.035μg/L and NT-ProBNP≥332ng/L were prognostic for OS. The median OS for patients (n=617) with a cTnT>0.035g/L was 6.7 months (95% CI; 5.0, 8.4) compared to 35.2months (95% CI; 29.4, 41.0) for those with cTnT<=0.035μg/L, P<0.0001. Similarly, the median OS for patients with NT-ProBNP > 332ng/L was 11.8 months (95% CI; 9.4, 14.2) compared to 36.2 months (95% CI; 26.7, 45.8) for those with NT-ProBNP <=332ng/L; P<0.0001. The prognostic value of UA was independent of cTnT and NT-ProBNP and together with these allowed a novel prognostic classification. Patients with none (Stage-I), 1 (Stage-II), 2 (Stage-III) or 3 (Stage-IV) of these risk factors (UA>8mg/dl, cTnT>0.035μg/L and NT-ProBNP>332ng/L) had a median OS of 36.6, 29.2, 11.1, and 3.6 months respectively (P<0.0001) (Figure 2). We also explored various predictors of OS in this large cohort of patients. The parameters that were significant for a shorter median OS included septal thickness>15mm, ejection fraction<50%, alkaline phosphatase>upper limit of normal, serum creatinine>2.0mg/dL, serum albumin<3.0gm/dl, 24-hour urine albumin>5gm, UA>8 mg/dL, cTnT>0.035μg/L and NT-ProBNP>332ng/L. We then performed a multivariate analysis with all these variables and those predicting for shorter OS were cTnT>0.035μg/L, serum uric acid>8mg/dL, and ejection fraction<50%. The stage determined at the time of PBSCT also predicted outcome with a median OS from PBSCT not reached in stages 1 and 2, 55 months for stage 3 and 16 months for stage 4 patients. Interpretation: The data confirms the prognostic value of serum UA in AL and allows development of a novel and simple but powerful, reproducible staging system with applicability at all stages of AL. Figure Figure Figure Figure

Abstract Background: Prior studies suggest that the presence of >5% polyclonal plasma cells (pPCs) among total plasma cells (PCs) within the bone marrow (BM) is associated with a longer progression-free survival, higher response rates, and lower frequency of high-risk cytogenetic abnormalities in patients with newly diagnosed multiple myeloma (MM). However, the incidence and prognostic utility of this factor in patients with relapsed and/or refractory MM has not been previously evaluated. Thus, we evaluated the prognostic value of quantifying the percentage of pPCs among the total PCs in the BM of patients with actively relapsing MM. Methods: We evaluated all MM patients with actively relapsing disease (biochemical and/or symptomatic) seen at the Mayo Clinic, Rochester, from 2012 to 2013, who had BM samples evaluated by seven-color multiparametric flow cytometry. All patients had at least 24 months of follow-up from the date of flow evaluation. Cell surface antigens were assessed by direct immunofluorescence antibodies for CD45, CD19, CD38, CD138, cytoplasmic Kappa and Lambda Ig light chains, and DAPI nuclear stain. The flow cytometry data was collected using the Becton Dickinson FACSCanto II instruments that analyzed 150,000 events (cells); this data was then analyzed by multi-parameter analysis using the BD FACS DIVA Software. PCs were selectively analyzed through combinatorial gating using light scatter properties and CD38, CD138, CD19, and CD45. Clonal PCs were separated from pPCs based on the differential expression of CD45, CD19, DAPI (in non-diploid cases), and immunoglobulin light chains. The percentage of pPCs was calculated in total PCs detected. Survival analysis was performed by the Kaplan-Meier method and differences were assessed using the log rank test. Results: There were 180 consecutive patients with actively relapsing MM who had BM biopsies analyzed via flow cytometry as part of their routine clinical evaluation. The median age of this group was 65 years (range: 40 - 87); 52% were male. At the time of this analysis, 104 patients had died, and the 2-year overall survival (OS) rate for the cohort was 58%. The median number of therapies received was 4 (range: 1 - 15). Of these patients, 61% received a prior ASCT, and almost all (99%) received prior regimens containing either immunomodulators or proteasome inhibitors. There were 55 (30%) patients with >5% pPCs among the total PCs in their BM. The median percentage of pPCs among total PCs in these 55 patients was 33% (range: 5 - 99). The median OS for those with >5% pPCs was not reached compared with 22 months for those with <5% pPCs (P = 0.028; Figure 1). Patients with <5% pPCs PCs had a higher likelihood of high-risk FISH cytogenetics compared with the rest of the patients. In a univariate analysis, increasing number of pPCs was associated with an improved OS, while higher labeling index, number of prior therapies, and the presence of high-risk FISH cytogenetics were associated with a worse OS. In a multivariate analysis, only the increasing number of pPCs (P = 0.006), higher labeling index (P = 0.0002) and number of prior therapies (P = 0.003) retained statistical significance. Conclusion: Quantitative estimation of the percentage of pPCs among the total PCs in the BM of patients with actively relapsing MM was determined to be a predictor of worse OS. As such, this parameter is able to identify a group of patients with MM with actively relapsing disease who have a particularly poor outcome. Further studies evaluating its biological significance are warranted. Figure 1 Kaplan-Meier curve comparing OS between patients with ≥5% pPCs and <5% pPCs among the total PCs in their BM. Figure 1. Kaplan-Meier curve comparing OS between patients with ≥5% pPCs and <5% pPCs among the total PCs in their BM. Disclosures Kapoor: Celgene: Research Funding; Amgen: Research Funding; Takeda: Research Funding. Gertz:Prothena Therapeutics: Research Funding; Novartis: Research Funding; Alnylam Pharmaceuticals: Research Funding; Research to Practice: Honoraria, Speakers Bureau; Med Learning Group: Honoraria, Speakers Bureau; Celgene: Honoraria; NCI Frederick: Honoraria; Sandoz Inc: Honoraria; GSK: Honoraria; Ionis: Research Funding; Annexon Biosciences: Research Funding. Kumar:AbbVie: Research Funding; Noxxon Pharma: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Millennium: Consultancy, Research Funding; Kesios: Consultancy; Glycomimetics: Consultancy; BMS: Consultancy.

Abstract The impact of fluorescence in-situ hybridization (FISH) on outcome in AL amyloidosis remains uncertain. We analyzed the response and overall survival (OS) of 692 AL amyloidosis patients with available FISH testing at diagnosis. First line treatment was categorized as autologous stem cell transplant or three non-transplant regimens (melphalan-based; bortezomib-based, and immunomodulatory drug (IMiD)-based). Forty-nine percent of patients had t(11;14), 37% del 13q/monosomy 13 and 19% had trisomy/tetrasomy. Analysis by abnormality type was restricted to t(11;14) and trisomy/tetrasomy sub-groups as chromosome 13 abnormalities were commonly associated with the other abnormalities. Patients with t(11;14) had lower rate of very good partial response or better (≥VGPR) compared to those lacking t(11;14) (56% vs 70%, P=0.001). By regimen stratification, this difference was maintained for bortezomib-based (52% vs 77%; P=0.004) and IMiD-based therapy (13% vs 54%; P=0.04) (Figure 1). Patients with trisomy/tetrasomy had no difference in the rate of ≥VGPR compared to those who did not (66% vs 63%, P=0.62), with no difference within regimen types. OS was similar between t(11;14)-positive and negative patients (median 43 vs 57 months; P=0.58). However, sub-analysis by regimen type showed a significantly inferior OS among t(11;14)-positive bortezomib-treated patients (median 15 vs 27 months; P=0.05) and t(11;14)-positive IMiD-treated patients (median 12 vs 32 months; P=0.05) (Figure 2). Among t(11;14)-positive bortezomib-treated patients, the OS difference was maintained among favorable-prognosis patients, but was absent for poor-prognosis sub-groups (Table). Trisomy/tetrasomy was associated with inferior OS (median 29 vs 69 months; P=0.001), a difference that was maintained for melphalan (median 15 vs 32 months; P=0.01) and borderline significance for bortezomib (median 14 vs 38 months; P=0.09). Multivariate analysis confirmed an independent effect on OS for trisomy/tetrasomy in the study cohort and for t(11;14) among bortezomib-treated patients. FISH analysis is essential in newly diagnosed AL amyloidosis, as it provides prognostic information among treatment groups and may influence the selection of induction treatment. Patients with t(11;14) should be considered for ASCT at diagnosis. Disclosures Dispenzieri: Celgene: Research Funding; Alnylam: Research Funding; pfizer: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jannsen: Research Funding. Kumar:Glycomimetics: Consultancy; AbbVie: Research Funding; Array BioPharma: Consultancy, Research Funding; Kesios: Consultancy; Onyx: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; BMS: Consultancy; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Kapoor:Amgen: Research Funding; Takeda: Research Funding; Celgene: Research Funding.

Abstract Background: Cytogenetic evaluation using fluorescence in situ hybridization (FISH) at the time of diagnosis is essential for initial risk stratification in multiple myeloma. Despite the absence of cytogenetic high-risk abnormalities a subset of patients does experience poor overall survival comparable high-risk disease (i.e. median overall survival less than three years after diagnosis). We aimed to identify demographic, clinical, and cytogenetic characteristics predicting poor three-year overall survival in patients with standard-risk cytogenetics. Methods: We studied 428 patients who were diagnosed with multiple myeloma between July 2004 and July 2014 at Mayo Clinic Rochester, underwent FISH evaluation within six months of diagnosis, and received treatment with novel agents (immunomodulator, proteasome-inhibitor, or a combination thereof). Patients with high- and intermediate-risk cytogenetics as well as patients lost to follow-up within three years were excluded. High-risk cytogenetics were defined as del(17p), t(14;16), and t(14;20). Intermediate-risk cytogenetics were defined as t(4;14) and gain(1q). Bone marrow aspirates were evaluated for deletions, monosomies, trisomies, and tetrasomies using chromosome- or centromere-specific FISH probes. IGH rearrangements were evaluated using an IGH break-apart probe and evaluating up to five potential partners (FGFR3, CCND1, CCND3, MAF, and MAFB). A multivariable-adjusted logistic regression model was used to assess the associations between the parameters of interest and three-year overall survival. Discrimination and calibration of the model were evaluated using the c-statistic and the Hosmer-Lemeshow test, respectively. The odds ratios of the identified predictors were rounded up to the next integer and assigned as points in a scoring system. Receiver operating characteristic analysis was used to determine the optimal cut-point and associated test performance characteristics. P-values below 0.05 were considered statistically significant. Results: The median age at diagnosis was 65 years (31 - 95), 259 (61%) of the patients were male. The median overall survival was 7.4 years (6.1 - 8.6) for the entire cohort (n = 428), 10.5 years (8.3 - NR) for those who survived at least three years (n = 327, 76%), and 1.6 years (1.2 - 1.7) for those who did not survive three years after diagnosis (n = 101, 24%). The factors associated with poor three-year overall survival and the derived scoring system are summarized in Table 1. Conclusions: Patients with multiple myeloma and standard-risk cytogenetics are a heterogeneous group. One fourth of the patients are experiencing less than three years of overall survival after diagnosis. Stage, age, extent of bone marrow involvement, karyotype, and platelet count at the time of diagnosis were helpful in identifying patients at risk for poor three-year overall survival. These findings emphasize the importance of further risk stratification in this patient population and warrant external validation. Disclosures Dispenzieri: Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jannsen: Research Funding; pfizer: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Alnylam: Research Funding. Kapoor:Takeda: Research Funding; Amgen: Research Funding; Celgene: Research Funding. Kumar:AbbVie: Research Funding; BMS: Consultancy; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Noxxon: Consultancy, Honoraria; Janssen: Research Funding; Skyline: Consultancy, Honoraria.

Abstract Introduction: AL amyloidosis is a very heterogeneous disease. Prognosis is a function of organ tropism, extent of organ damage, and ability of tissues to heal, the last of which relates both to hematologic response and intrinsic toxicity of the light chain. Using mass spectroscopy (MS) technology, we are able to distinguish immunoglobulin light chain variable gene family (IGVL) usage on clinical samples. The goal of this study was to evaluate if IGVL usage impacts patient outcomes in patients with light chain amyloidosis (AL). Methods: IGVL usage was determined by mass spectroscopy (MS) of amyloid in clinical tissue specimens of Mayo Clinic patients. Specimens were from fat pad (n=257), bone marrow (n=172), myocardium (n=113), gastrointestinal (n=58), kidney (n=20), lung (n=15), and nerve (n=5). For those cases for which the IGVL could not be identified--not otherwise specified (NOS)—but constant region could be identified as lambda or kappa, we assume that the amyloid consisted primarily of immunoglobulin light chain gene constant regions or variable genes with somatic mutations making them uninterpretable to our matching algorithms. The medical records from these 700 patients were abstracted for relevant clinical and laboratory data. Results: The baseline characteristics of patients are shown in table 1. Three hundred and thirty-two patients have died with a median follow-up of surviving patients of 38 months. The estimated median survival for the entire population is 59 months. Out of 700 patients, 214 (31%) achieved a CR or a VGPR, 432 (62%) were not evaluable (NE) for hematologic or organ response, and 54 (8%) achieved a PR or did not respond (NR). The distribution of IGVL cases is shown in table 2. Overall survival (OS) for the whole group was not different across different IGVLs on univariate analysis, but when corrected for hematologic response, outcomes differed significantly based on IGVL. Patients could be further assembled into two groups, based on risk for death on univariate analyses: an IGVL high risk, which included KV1, LV1, LV2, LV3, and LV6; and low risk, which included all other cases (Figure). In a multivariate model that included level of hematologic response (CR/VGPR versus PR/NR/NE) and IGVL, IGVL family was independently associated with overall survival (RR=1.5 (95% CI 1.2-1.9, p=0.008). The risk ratio for CR/VGPR was 0.28 (95% CI 0.20-0.38, p<0.0001). This effect persisted when either the Mayo 2006 or the 2012 staging system was included in the multivariate. Conclusion: IGVL usage appears to have prognostic significance in patients who have not achieved VGPR or better to initial chemotherapy. Table 1. Baseline characteristics of patients N= 700 Age 63 (32-94) Male, (%) 447 (64%) Biopsy site Solid organ/Soft tissue 271 (39%) Fat pad 257 (37%) Bone Marrow 172 (25%) Organ involvement Cardiac 432 (62%) Renal 346 (49%) Gastrointestinal 168 (24%) Liver 56 (8%) Nerve 107 (15%) Lung 42 (6%) Soft Tissue 92 (13%) Organs involved 1 321 (46%) 2 228 (33%) ≥3 151 (22%) Laboratory characteristics NTBNP, pg/ml 2547 (11.3-70000) Troponin, ng/ml 0.03 (0.001-0.84) dFLC, mg/dl 26 (0.04-2330) Cardiac Stage 1 59 (18%) 2 125 (38%) 3 144 (44%) Table 2. Variable region family distribution. Light Chain N=700 N (%) KV1 107 (15%) KV2 3 (0.4%) KV3 17 (2%) KV4 25 (4%) KV6 1 (0.1%) LV1 85 (12%) LV2 64 (9%) LV3 118 (17%) LV4 3 (0.4%) LV6 97 (14%) LV8 1 (0.1%) LV9 1 (0.1%) Kappa NOS1 34 (4%) Lambda NOS1 140 (19%) Heavy chain amyloidosis 4 (0.6%) 1 No IGVL family could be identified Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.