Rajkumar, S. Vincent

Abstract Background: SWOG S0777, a randomized phase III trial, compared bortezomib, lenalidomide and dexamethasone (VRd) with lenalidomide and dexamethasone (Rd). The primary end point was progression-free survival (PFS) using a pre-specified one-sided stratified log rank test at a significance level of 0.02. The stratification factors were International Staging System (ISS) stage (I, II or III) and intent to transplant (yes or no), among a total of 6 strata. Overall response rate (ORR), overall survival (OS) and safety were secondary end points. Results of the primary analysis of this trial were published in Lancet (2016, Volume 389, Issue 10068, 519 - 527). Methods: This updated analysis includes 460 patients evaluable for survival endpoints: 225 eligible and analyzable patients were randomized to Rd and 235 patients to VRd. Rd patients received lenalidomide 25 mg/day on days 1-21 and dexamethasone 40 mg/day on days 1, 8, 15 and 22 of a 28-day cycle. VRd patients received lenalidomide 25 mg/day on days 1-14 and dexamethasone 20/mg/day on days 1, 2, 4, 5, 8, 9, 11 and 12 plus bortezomib 1.3 mg/m2 IV push on days 1, 4, 8 and 11 of a 21-day cycle. All patients received aspirin 325 mg/day and VRd patients received VZV prophylaxis per institutional standard. The 6-month induction was six 28-day cycles of Rd and eight 21-day cycles of VRd followed by Rd maintenance for all patients until progression, unacceptable toxicity or withdrawal of consent. Results: Between 2008 and 2012, 525 patients from 48 institutions were randomized. Patient data have been rigorously updated for this analysis based upon a May 15, 2018 datalock. The median follow up is now 84 months (7 years). The median PFS is 41 months for VRd and 29 months for Rd: stratified hazard ratio (96% Wald Confidence Interval) was 0.742 (0.594, 0.928) and one-sided stratified log-rank P-value 0.003 (see Figure 1). The median OS for VRd is still not reached with median OS for Rd being 69 months: stratified hazard ratio (96% Wald Confidence Interval) was 0.709 (0.543, 0.926) and stratified two-sided P-value was 0.0114 (see Figure 2). The impact of age was assessed in several ways including using 3 cutoffs (<65 years; 65-75 years; >75 years) and multivariate cox proportional hazards regression analyses adjusted for age. As in prior analyses, both PFS and OS were improved with VRd versus Rd adjusting for age (P-values: 0.013 [PFS]; 0.033 [OS])). Depth of response was assessed incorporating new serial data and additional bone marrow results. The CR plus VGPR was 74.9% for VRd versus CR plus VGPR of 53.7% for Rd (P-value 0.006 for response differences using a stratified Cochran-Mantel- Haenszel analysis). The median duration of lenalidomide plus dexamethasone maintenance was 17.4 months. The number of second cancers was 19/235 (8%) with VRd and 16/225 (7%) with Rd. Conclusion: The addition of bortezomib to lenalidomide dexamethasone for induction therapy in previously untreated myeloma results in a statistically significant and clinically meaningful improvement in PFS as well as better OS with follow up of 7 years. VRd had an acceptable safety and tolerability profile and continues to represent an appropriate standard of care irrespective of age. Disclosures Durie: Takeda: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Johnson & Johnson: Consultancy. Abidi:Millenium Takeda: Research Funding. Epstein:University of Arkansas for Medical Sciences: Employment. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Reu:Bristol Myers Squibb: Employment; Millenium Takeda: Consultancy; Novartis: Consultancy, Research Funding; Celgene: Research Funding. Orlowski:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millenium Pharmaceuticals: Consultancy, Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioTheryX, Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees; Genentech: Consultancy; Janssen Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Poseida: Research Funding; Bristol Myers Squibb: Consultancy. Barlogie:Dana Farber Cancer Institute: Other: travel stipend; Celgene: Consultancy, Research Funding; International Workshop on Waldenström's Macroglobulinemia: Other: travel stipend; Multiple Myeloma Research Foundation: Other: travel stipend; European School of Haematology- International Conference on Multiple Myeloma: Other: travel stipend; Myeloma Health, LLC: Patents & Royalties: : Co-inventor of patents and patent applications related to use of GEP in cancer medicine licensed to Myeloma Health, LLC; ComtecMed- World Congress on Controversies in Hematology: Other: travel stipend; Millenium: Consultancy, Research Funding.

Abstract Background: Limited data exist regarding histological transformation in patients with Waldenström macroglobulinemia (WM). In this study, we present the disease characteristics, outcomes and risk factors for histological transformation in WM. Methods: Patients with WM seen at Mayo Clinic, Rochester, MN between January 1996 and December 2017 were included. Patients with aggressive non-Hodgkin lymphoma in the setting of WM were considered to have transformation. Univariate analysis for comparing baseline characteristics of transformed versus non-transformed WM was performed using Wilcoxon, Fisher's exact and Chi square tests, as appropriate. Multivariate analysis was performed using logistic regression analysis. Cox proportional hazard method was used to assess the impact on time-to-transformation. All time-to-event analyses were calculated by the Kaplan-Meier method. Results: Of 1014 patients with WM, 42 patients (4.1%) developed histological transformation. The median follow-up for the entire cohort was 9.5 years (95% CI: 8.8-10.5 years). The cumulative probability of transformation was 2.3% at 5 years, 5.3% at 10 years and 8.5% at 15 years from diagnosis of WM, respectively. There was no difference in the 5-year cumulative probability of transformation in patients with WM diagnosed between 1996-2000 (2.1%), 2001-2005 (2.9%), 2006-2010 (2.7%) and 2011-2015 (3.8%), p=0.61.The disease characteristics, laboratory parameters and histology at transformation are outlined in Table 1. In patients with DLBCL histology (n=39), Revised-International Prognostic Index was calculable in 28 patients, with 50% (n=14), 46% (n=13) and 4% (n=1) of DLBCL belonging to poor, good and very good risk groups, respectively. For DLBCL histology, 18 patients were classifiable using Hans algorithm into germinal center B-cell (GCB) type (n=3, 17%) and non-GCB type histology (n=15, 83%). The median lines of therapy received prior to transformation for the entire cohort was 2 (range 0-9), with 5 (11%) patients not having received any therapy for WM before transformation. Number of lines of alkylator-based therapy used prior to transformation [median 1 line (range 0-4)] was comparable to that used in patients in whom WM did not occur [median 1, (range 0-6); p=0.78]. The median time-to-transformation from diagnosis of WM was 4.8 years (95% CI: 2.6- 6.8 years). Overall survival (OS) from transformed disease was 3.2 years (95% CI 1.1-3.9 years). The 10-year OS of patients with WM who transformed was lower (46%) compared to patients without transformation (60%) with a trend towards statistical significance (p=0.08), Figure 1. The MYD88L265P mutation status was available in 333 patients in the entire cohort (22/42 pts in the transformed cohort and 311/972 in the non-transformed cohort. Of the 22 patients in the transformed WM cohort, 13 (59%) exhibited MYD88WT genotype and 9 (41%) exhibited MYD88L265P genotype. The risk of transformation was higher in patients with MYD88WT status [Odds ratio 6.3 (95% CI: 2.6-15.5); p<0.0001]. Additionally, serum lactate dehydrogenase (LDH) was higher at diagnosis of WM in patients who transformed, Table 2. On multivariate analysis, MYD88WT status remained an independent predictor of disease transformation [p=0.003; odds ratio 10 (95% CI: 2.1-48)]. On univariate Cox proportional hazard analysis for identifying predictors of time-to-transformation, only MYD88WT mutational status was associated with shorter time-to-transformation with a 5-year transformation rate of 15.5 % for MYD88WT versus 2.6 % with MYDL265P mutated patients [risk ratio 6.2 (95% CI: 2.5-16.4); p<0.0001]. Treatment-related details in the transformed cases were available for 37 (90%) patients; R-CHOP was the most common (41%) frontline therapy for transformation; 33% patients underwent autologous stem cell transplantation for transformed disease during their disease course. Conclusion: Histological transformation is an uncommon event in WM but confers poorer survival. MYD88WT genotype is independently associated with histological transformation a shorter time-to- transformation in patients with WM. Disclosures Ansell: Trillium: Research Funding; Pfizer: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Takeda: Research Funding; Celldex: Research Funding; Regeneron: Research Funding; Merck & Co: Research Funding; Bristol-Myers Squibb: Research Funding. Gertz:Apellis: Consultancy; Alnylam: Honoraria; spectrum: Consultancy, Honoraria; janssen: Consultancy; annexon: Consultancy; Prothena: Honoraria; Abbvie: Consultancy; Amgen: Consultancy; celgene: Consultancy; Teva: Consultancy; Medscape: Consultancy; Ionis: Honoraria; Research to Practice: Consultancy; Physicians Education Resource: Consultancy. 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.. 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: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; 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; 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; Janssen: 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; Takeda: Membership on an entity's Board of Directors or advisory committees; Novartis: 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. Kapoor:Takeda: Research Funding; Celgene: Research Funding.

Abstract Introduction Multiple myeloma (MM) is a result of a malignant transformation of plasma cells that is preceded by the presence of an asymptomatic clonal plasma cell expansion, a condition referred to as monoclonal gammopathy of undetermined significance (MGUS). We and others have shown familial aggregation of MM and MGUS. Evidence from epidemiologic, family and genome-wide association studies (GWAS) suggests a genetic component underlying MM etiology. GWAS have successfully established 17 common genetic risk loci for MM to date and recently, rare inherited susceptibility variants in the LSD1 / KDM1A and USP45 genes were identified in familial MM / MGUS kindreds. Family-based approaches may be used to elucidate genetic variation contributing to familial MM. Genetic linkage analysis has historically been used to detect the chromosomal location of disease genes. The objective of this study was to conduct a linkage analysis of MM / MGUS families to identify genomic regions for MM / MGUS. Methods Linkage analysis was performed on whole exome sequencing (WES) data generated from germline DNA extracted from peripheral blood from MM / MGUS families ascertained at four sites, of which 79 were selected with 2 or more affected members with any combination of MM or MGUS. Whole exome capture was performed using Agilent SureSelect 38 Mb paired end sequencing and ran on Illumina HiSeq 2000s/2500s; standard analyses for alignment (GRCh37) and quality control were conducted. The Genome Analysis Toolkit's (GATK) HaplotypeCaller in per-sample mode was used to jointly call all the samples together. Quality control included removing variants that had <75% call rate, <8x coverage, or minor allele frequency <0.01 (1KGenomes). The jointly called WES data from the 79 families consisted of 230 individuals, including 119 MM, 93 MGUS and 18 unaffected relatives. Additional early onset (defined as age <60) MM cases (n=400), sporadic MM cases (n=879) and controls (n=2389) were also included in the joint calling to be used for follow-up of linkage regions. We included independent variants defined as linkage disequilibrium (LD) r2 <0.05 using both PLINK 1.07's LD based variant pruner and also MERLIN's pairwise r2 cluster marker-marker modeling to ensure variant independence. After quality control and LD filtering: 12,946 variants remained. We conducted multipoint linkage analysis using MERLIN (Multipoint Engine for Rapid Likelihood Inference using the Lander-Green approach) and considered both non-parametric and parametric (dominant and recessive) models to test for co-segregation of chromosomal regions with MM / MGUS. A logarithm of the odds (LOD) score greater than 3.3 was significant evidence for linkage. Within the same families, we interrogated any suggestive regions by performing gene-level association tests using the PEDGENE R package to calculate burden and kernel statistics, accounting for family relationships. Follow-up of these genes in the early onset and sporadic MM cases and controls and interrogation of single variants driving the associations of these genes is ongoing. Results Among the 79 families, 28 consisted of two or more MM, 41 had two or more MM and MGUS cases and 10 had two or more MGUS. Analyses of the 79 MM / MGUS families identified chromosome 6 at 123420001-149070000 BP region, with evidence for linkage by the non-parametric model (LOD score=3.3) and supportive evidence for linkage by the dominant parametric model (LOD=2.5) (Figure). The chromosome 6 region, which is outside the HLA-region, contains a total of 72 genes. Using gene-level association tests, we identified four genes within the region (MOXD1, TRDN, ADAT2, LTV1) that were associated within MM / MGUS in the family cases (p<0.05). Discussion We found evidence for a locus on chromosome 6 linked to MM / MGUS. Four genes in this region may be associated with MM / MGUS in these families. Follow-up of these genes/variants in high-risk individuals (early-onset / age <60), sporadic cases and controls will help elucidate genetic mechanisms contributing to familial MM / MGUS. In addition, we demonstrate the benefit of applying a linkage analysis framework to familial WES data for discovery of genomic regions influencing MM / MGUS. Disclosures Dumontet: Roche: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; Sanofi: Honoraria. Kumar: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; 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; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; 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; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Roche: 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 Background: Cardiac involvement is integral in staging and prognosis of immunoglobulin light chain (AL) amyloidosis. The N-terminal prohormone of brain natriuretic peptide (NT proBNP) is a cardiac biomarker used in screening for cardiac involvement and staging the disease. Transthoracic echocardiogram (TTE) and cardiac magnetic resonance (CMR) are the imaging modalities recommended to determine cardiac involvement and function. Methods: We conducted a retrospective review of all patients with biopsy proven systemic AL amyloidosis seen at the mayo clinic between Jan 1, 2006 and Dec 30, 2015. The aim of the study is to identify the nature of abnormalities in cardiac biomarkers and echocardiographic features in patients with AL amyloidosis and the ability of these investigations to diagnose cardiac involvement. We first identified all patients with AL amyloidosis that underwent endomyocardial biopsy for suspicion of cardiac involvement (Cohort 1). We then analyzed a cohort (Cohort 2) which consisted of patients who had serum NT proBNP and a comprehensive echocardiographic evaluation at time of diagnosis. Results: 179 patients with AL amyloidosis underwent endomyocardial biopsy (Cohort 1) of whom 173 had evidence of amyloid deposition. In this cohort, 159 patients had NT proBNP performed at the time of the procedure. The NT proBNP was elevated (>300) in all 159 patients with a median NT proBNP of 4917 (range 355-69541). The median left ventricular ejection fraction (LVEF), interventricular septal (IVS) thickness and strain rate were 54 (range 10-77), 15 (range 8-30) and -9 (range -21 to 0) respectively. CMR findings were consistent or suggestive of light chain amyloidosis in 38/42 patients, yielding a sensitivity of 90 percent. The LVEF, IVS thickness and strain rate were abnormal in 89/168 (53%), 102/64 (61%) and 92/95 (97%) respectively. 95 patients with biopsy proven cardiac amyloidosis had complete echocardiogram data available on LVEF, IVS thickness and strain rate, with 97% (n=92) presenting with an abnormality in at least one of these variables . CMR findings were consistent or suggestive of light chain amyloidosis in 38/42 patients, yielding a sensitivity of 90 percent. Patients with a normal NT proBNP and normal echocardiogram were considered disease free (true negative), based on our initial analysis of these investigations in Cohort 1. Cohort 2 consisted of 342 consecutive patients. The median NT pro BNP was 1878 (25-48214). The median LVEF, IVS thickness and strain rate were 63 (22-90), 14 (6-25) and -13 (-25 to -3) respectively. 259 (76%) patients had a positive NT proBNP (above 300), of whom 237 (92%) had an abnormality detected on TTE. 83 patients had a negative NT proBNP, of whom 27 (33%) had an abnormality in either LVEF, IVS thickness or strain rate. 19 of these 27 patients had a borderline reduced strain rate between -17 and -18, whilst the remaining 8 patients had a strain between -14 and -15. Only 6/27 patients were considered to have possible early cardiac involvement and none have any other diagnostic or classical features of amyloidosis on TTE. Conclusion: The combination of NT proBNP and comprehensive echocardiographic evaluation provides substantial information to diagnose cardiac amyloidosis in a significant portion of patients negating the need for endomyocardial biopsy. A negative NT proBNP rules out clinically meaningful cardiac involvement and may obviate the routine use of TTE in patients with a low clinical suspicion of cardiac amyloidosis. Disclosures Dispenzieri: Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Gertz:Research to Practice: Consultancy; Physicians Education Resource: Consultancy; Ionis: Honoraria; celgene: Consultancy; spectrum: Consultancy, Honoraria; Teva: Consultancy; Amgen: Consultancy; Medscape: Consultancy; janssen: Consultancy; Alnylam: Honoraria; Abbvie: Consultancy; annexon: Consultancy; Apellis: Consultancy; Prothena: Honoraria. 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:Takeda: Research Funding; Celgene: Research Funding. Kumar:AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Roche: Research Funding; Celgene: 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; 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; 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; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding.

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.

Abstract Background: Peripheral blood biomarkers of tumor microenvironment and immune surveillance such as absolute lymphocyte (ALC) and monocyte (AMC) counts are independent prognostic factors in several hematologic malignancies including multiple myeloma. The timing and prognostic impact of immune reconstitution has been studied after autologous hematopoietic stem cell transplantation, less is known about its significance in newly diagnosed multiple myeloma prior to transplantation. Methods: We studied 771 patients with newly diagnosed multiple myeloma who were treated with novel agents at Mayo Clinic between 01/2004 and 12/2015. Peripheral blood absolute lymphocyte and monocyte counts were measured at the time of treatment initiation and one month thereafter in all patients (including data obtained between 14 and 42 days after treatment initiation). The outcome of interest was overall survival. The peripheral blood parameters of interest were abnormal ALC (reference range 800-2400/µL) and AMC (reference range 500-1500/µL) at baseline and at one month. Immune dysregulation was defined as both abnormal ALC and AMC. Immune reconstitution was defined as recovery of both normal ALC and AMC. The Wilcoxon signed-rank test was used to compare the peripheral blood parameters before and after the first month of treatment. Multivariable-adjusted proportional hazards regression models were used to assess the associations between changes in peripheral blood parameters and overall survival. P-values below 0.05 were considered statistically significant. Results: The median age at diagnosis was 65 years (27 - 90) and 459 patients were male (60%). The three most common first-line regimens were lenalidomide + dexamethasone, bortezomib + cyclophosphamide + dexamethasone, and bortezomib + lenalidomide + dexamethasone. Two hundred and eighty patients (36%) went on to undergo autologous hematopoietic stem cell transplantation as part of their first-line therapy. The median ALC decreased from 1100/µL (range 60 - 5590) at baseline to 850/µL (range 60 - 5590) at one month (p < 0.001). The median AMC increased from 330/µL (range 0 - 1840) at baseline to 420/µL (range 0 - 1840) at one month (p < 0.001). The median time between re-assessment of ALC and AMC was 25 days (range 15 - 42). Two hundred and thirty-four patients (31%) had evidence of immune dysregulation at baseline (both abnormal ALC and AMC). Eighty-seven of these 234 patients (37%) recovered normal ALC and AMC at one month (early immune reconstitution). One hundred and thirty-seven of the 537 patients with normal ALC and AMC at baseline (26%) developed new immune dysregulation at one month. The absence of immune dysregulation at baseline (compared to the presence thereof) was associated with better overall survival (HR 0.77, 95% CI 0.61 - 0.97, p = 0.025, n = 771). The absence of immune dysregulation at one month (compared to the persistence or development thereof) was associated with better overall survival (HR 0.63, 95% CI 0.50 - 0.80, p < 0.001, n = 771). Early immune reconstitution (compared to the persistence or development of immune dysregulation) was associated with better overall survival (HR 0.62, 95% CI 0.43 - 0.92, p = 0.016, n = 771). Both associations remained statistically significant after adjusting for age at diagnosis, sex, International Staging System stage, and eligibility for transplantation: HR 0.70 (95% CI 0.54 - 0.90, p = 0.006, n = 612) and HR 0.59 (95% CI 0.39 - 0.90, p = 0.014, n = 612), respectively. Conclusions: Peripheral blood biomarkers of immune dysregulation vary over time and have prognostic significance both at baseline and during follow-up. The presence or development of immune dysregulation in newly diagnosed multiple myeloma is an independent risk factor. The favorable impact of early immune reconstitution suggests that immune dysregulation is a potentially modifiable risk factor that may be exploited for therapeutic benefit. Figure. Figure. Disclosures Lacy: Celgene: Research Funding. Gertz:celgene: Consultancy; Medscape: Consultancy; janssen: Consultancy; Prothena: Honoraria; Apellis: Consultancy; Ionis: Honoraria; annexon: Consultancy; spectrum: Consultancy, Honoraria; Amgen: Consultancy; Physicians Education Resource: Consultancy; Abbvie: Consultancy; Research to Practice: Consultancy; Teva: Consultancy; Alnylam: Honoraria. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Russell:Vyriad: Equity Ownership. Kapoor:Takeda: Research Funding; Celgene: Research Funding. Kumar: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; 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.

Abstract Background: The combination of a proteasome inhibitor (PI), an immunomodulatory drug (IMiD), and dexamethasone is the current standard induction therapy for myeloma. Daratumumab, a monoclonal antibody directed against CD38, is highly effective in treating myeloma and improves response rates and progression free survival (PFS) when added to PI or IMiD. Ixazomib, lenalidomide and dexamethasone (IRd) is an effective, all oral, induction regimen that has been studied in phase 2 and 3 trials. We designed this trial to examine the feasibility and efficacy of adding daratumumab to the IRd regimen. Patients and Methods: Patients with previously untreated MM, with measurable disease and adequate organ function were enrolled irrespective of their transplant eligibility. The primary objective was to determine the rate of complete response to the IRD-Dara combination in patients with NDMM. Treatment consisted of Ixazomib 4mg days 1, 8, 15; lenalidomide 25 mg days 1-21, dexamethasone 40 mg, weekly and daratumumab 16 mg/kg, weekly for two cycles, every other week during cycles 3-6 and then every 4 weeks after that. Overall, 40 patients were accrued; data on 38 patients were available for analysis as of July 02, 2018 (Table 1). Results: The median age was 62 (41-81); 52.6% female. All patients were alive and progression free at last assessment with a median follow up of 5.2 (2.0-12.9) months (median 5 cycles, range 2-13). One patient had gone off for alternate therapy. Responses were rapid with 90% partial response or better (32% VGPR) after 2 cycles, and 100% PR or better (50% VGPR) for 32 patients who have completed 4 cycles. The overall best confirmed response rate among the 38 patients was 95% including 11% CR and 47% VGPR. Overall, 231 cycles have been administered across the study, with dose modifications/ hold required for ixazomib, lenalidomide, daratumumab and dexamethasone in 3 (8%), 11 (29%), 2 (5%), and 8 (21%) patients respectively, the most common reasons being hematologic and skin rash. A grade 3 or higher adverse event at least possibly attributed to the study drugs was seen in 42% of patients, hematologic in 37% and non-hematologic in 11% (Figure). 11 patients have so far proceeded to stem cell collection, all have collected adequate numbers of stem cells for one or two intended transplants(median CD34+ collected 8.4 million/kg; range 3.8-12.3). Updated results with additional 6 months of follow up and MRD testing will be presented at the meeting. Conclusion: This represents the first reported results of this combination for treatment of newly diagnosed myeloma. The early results from the use of IRd-Dara in newly diagnosed myeloma suggests excellent efficacy with rapid responses that deepen quickly over the initial cycles of therapy. The regimen was well tolerated with limited dose modifications and no discontinuation for toxicity and no influence on the ability to collect stem cells. Figure. Figure. Disclosures Kumar: 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; 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. Kapoor:Takeda: Research Funding; 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. Lacy:Celgene: Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Gertz:Prothena: Honoraria; Amgen: Consultancy; Abbvie: Consultancy; Teva: Consultancy; annexon: Consultancy; janssen: Consultancy; celgene: Consultancy; Alnylam: Honoraria; Medscape: Consultancy; Apellis: Consultancy; spectrum: Consultancy, Honoraria; Physicians Education Resource: Consultancy; Ionis: Honoraria; Research to Practice: Consultancy.

Abstract Premalignant states are known to precede malignancy in many different cancers, including multiple myeloma (MM). Each year, 1% of Monoclonal Gammopathy of Undetermined Significance (MGUS) patients and 10% of Smoldering Multiple Myeloma (SMM) patients transition to symptomatic MM, which remains an incurable disease. By identifying patients at imminent risk (within 2 years) of progression to MM, treatment could begin early and potentially prevent full blown MM and associated morbidity and mortality. Multiple risk-factor models are currently utilized to identify patients at high-risk of developing MM. Commonly cited risk factors include percentage of bone marrow plasma cells, free light chain ratio, serum levels of M-protein, IgG subtype and levels of circulating plasma cells. These tests have individual and combined merit but there remains no consensus for measuring imminent risk of MM progression. To determine whether serum proteomics could help predict progression or provide information on relevant pathways involved in progression to MM, we evaluated 200 MGUS and SMM (187 non-IgM) patient samples on the Myriad DiscoveryMAP(r) platform (250+ serum proteins), supplemented by demographic and clinical information. Of the 187 non-IgM patients, 100 progressed to MM within 2 years (high-risk), and 87 did not progress to MM within 5 years (low-risk). We performed different subset analyses to screen for proteins that were informative and predictive of disease progression from MGUS/SMM to MM. First, a univariate Wilcoxon rank sum test was performed. The top 10 proteins that were found to be differential between high-risk/low-risk for all MGUS and SMM patients were IgM, Progesterone, MCP-2, Kallikrein-5, FGF4, EPO, MCP-4, MIP-1β, MCP-1, and TF. Interestingly, when analyzing MGUS and SMM patients separately, additional proteins that were important in distinguishing high-risk/low-risk patients included IgM, EN-RAGE, BAFF, and several others previously shown to be relevant in MM, as well as a handful of novel proteins with unidentified roles in MM. Second, to determine whether specific combinations of proteins could be utilized together to define high/low-risk, a classification tree was assembled. The combination of 8 features (IgM, Progesterone, Aldose Reductase, E-Selectin, Fas Ligand, Hemoglobin, Age and Creatine kinase-MB) appropriately classified 86% of the 187 patients into high/low-risk. Future analyses will include examining this high/low risk classifier in contrast to current risk factor models, and application to two additional sets of similar patient samples that serve as an independent validation set. Disclosures: No relevant conflicts of interest to declare.