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Background: Multiple myeloma (MM) is an incurable plasma cell malignancy and genetic abnormalities contribute to disease heterogeneity and outcome. Primary abnormalities, namely recurrent immunoglobulin (Ig) heavy chain translocations and hyperdiploidy, occur early in disease course. Secondary events, such as MYC abnormalities occur upon progression. Earlier studies showed MYC abnormalities detected by FISH or by capture sequencing were independently associated with poor outcome (Walker, et al., BCJ, 2014), while recent studies using WGS did not support this finding (excluding MYC/IGL) (Mikulasova, et al. Haematologica, 2020; Misund, et al. Leukemia, 2020). We hypothesize these discrepancies are due to differences in methods and sensitivities of detection of MYC abnormalities by FISH vs. WGS. Given that MYC abnormalities often display remarkable genomic heterogeneity with numerous gene partners, reduced detection of MYC abnormalities by FISH is not unexpected. This hypothesis is supported by lower frequencies of MYC abnormalities found by FISH (15%) vs. NGS (30-35%) consistent with ~50% false-negative rate of the MYC FISH probe (Smadbeck, et al. BCJ, 2019). To better understand the role of MYC in myeloma disease outcome, we compared the MYC abnormality subtype identified by FISH or NGS vs. MYC gene expression levels and overall survival. Methods: We performed a retrospective study of newly diagnosed MM patients seen at Mayo Clinic or enrolled in the MMRF CoMMpass trial. For Mayo cases, MYC FISH results (breakapart probe, Abbott) were obtained from the Mayo Clinic Genomics database (N=1342) and mate pair sequencing (MPseq) was performed on 140 cases. For CoMMpass cases, we obtained tumor long-insert whole genome sequencing (WGS), RNA sequencing (RNAseq) for gene expression and clinical outcome data. Overall survival (OS) was defined as time from diagnosis to death from any cause or to last follow up. Survival curves were estimated using Kaplan Meier and compared using the Log-Rank test. Statistical analyses performed using SPSS and JMP with significance determined when P <0.05. Results: We first evaluated the impact of MYC abnormalities on OS when detected by FISH or NGS. In Mayo cases, OS was significantly shorter in patients with MYC abnormalities compared to patients without MYC abnormalities using FISH (5.3 vs. 8.0 years, P<0.001, N=1342). In contrast, there was no significant difference in OS between patients with or without MYC or abnormalities using MPseq or WGS in both the Mayo and CoMMpass cohorts (Mayo: 6.4 vs. and 6.9 years P=0.78, N=140; CoMMpass: 4.9 vs. and 5.1 years P=0.74, N=546). Since FISH-detected MYC abnormalities were associated with poor outcome, we evaluated differences in the types of MYC abnormalities identified FISH and genome sequencing; 270 of 658 CoMMpass cases had a MYC abnormality and 12 abnormality subgroups were identified. In the Mayo cases, FISH preferentially detected translocations and complex abnormalities and missed insertions with flanking duplicating sequences or terminal tandem duplications (TTD) that occur telomeric to MYC. Since the level of MYC expression should be a consequence of the various genomic abnormalities altering the MYC gene region, we compared MYC expression levels in relation to MYC abnormality subgroups. Highest expression was seen with MYC amplification, followed by Ig abnormalities, non-Ig abnormalities, complex deletion/duplications, proximal deletions, non-Ig insertions, terminal deletions, TTD, trisomy 8, no MYC structural variation, monosomy 8 and cases with MAX mutations had the lowest expression. Abnormalities identified by FISH had higher MYC expression (83.5 TPM) compared to cases predicted to be missed by FISH (63.2 TPM). We tested if high MYC expression, irrespective of MYC structural abnormality, was associated with differences in OS. Boxplot analysis was used to categorize MYC expression in 631 CoMMpass patients as top quartile/high MYC expression (Q4≥ 75 TPM, n=159) and bottom quartile/low MYC expression (Q1≤ 16.5 TPM, n= 158) (see Figure). OS was significantly shorter in patients with high MYC expression compared to patients with low MYC expression (4.6 vs. 5.3 years, P <0.038). Conclusion: We show that FISH detects only a subset of the MYC abnormalities detected by genome sequencing, and that FISH-detected MYC abnormalities are associated with higher MYC gene expression and decreased survival. Figure 1 Disclosures Kumar: Kite Pharma: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Dr. Reddy's Laboratories: Honoraria; Cellectar: Other; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Tenebio: Other, Research Funding; Carsgen: Other, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Genecentrix: Consultancy; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; MedImmune: Research Funding; Adaptive Biotechnologies: Consultancy.

Introduction: The utility of amyloidosis staging systems has been validated for newly diagnosed patients, but their role in restaging after starting treatment has not been explored. Given the high early mortality in this disease, restaging remote from the diagnosis may have clinical value. We designed this study to evaluate whether the currently used staging systems are prognostic when applied at 3 and 6 months from starting first-line treatment, and whether stage migration impacts survival. Methods: This is a retrospective study including patients with systemic light chain amyloidosis diagnosed between January, 1st 2006 and June, 30th 2019 and were seen in Mayo Clinic, Rochester, MN within 90 days of diagnosis; the analysis included 535 and 301 patients who had restaging data available for at least one of the staging systems at 3 and 6 months, respectively. Patients were grouped into 4 stages using the 2015 European modification of the Mayo 2004 staging system based on values of cardiac biomarkers (cardiac troponin T and NTproBNP), and using the Mayo 2012 staging system based on cardiac biomarkers and the difference in serum free light chain concentration (dFLC). Overall survival (OS) was calculated from the time of re-staging until death or last follow up. Results: Using the modified Mayo 2004 staging system at 3 months from starting first-line treatment, median OS was 11.8 [95%CI: 11.4-not reached (NR)], 10.8 (95%CI: 9.4-NR), 4.6 (95%CI: 2.8-6.7), and 1.1 (95%CI: 0.7-2.6) years in patients with stage I, II, IIIa, and IIIb, respectively. Using Mayo 2012 staging at 3 months, OS was 11.8 (95%CI: 10.9-NR), 9.0 (95%CI: 6.2-NR), 5.2 (95%CI: 3.3-6.1), and 0.8 (95%CI: 0.7-1.1) years in patients with stage I, II, III, and IV, respectively (Figure 1a &b). Using the modified Mayo 2004 staging system at 6 months from starting first-line treatment, median OS was NR (95%CI: NR-NR), 9.8 (95%CI: 6.2-NR), 5.4 (95%CI: 3.2-9.0) and 0.9 (95%CI: 0.6-3.7) years in patients with stage I, II, IIIa, and IIIb, respectively. Using Mayo 2012 staging at 6 months, OS was NR (95%CI: 8.4-NR), NR (95%CI: 7.9-NR), 4.6 (95%CI: 3.0-6.5), and 0.9 (95%CI: 0.2-1.8) years in patients with stage I, II, III, and IV, respectively (Figure 1c &d). On multivariate analysis, advanced (stage > 2) modified Mayo 2004 stage (HR: 1.6, P=0.004) and advanced (stage > 2) Mayo 2012 stage (HR: 2.4, P<0.001) at 3 months were associated with decreased survival independent of cardiac response, hematologic response, and transplantation status. Although advanced Mayo 2004 stage at 6 months was associated with decreased survival, it was not statistically significant (HR: 1.5, P=0.09). In contrast, advanced Mayo 2012 stage at 6 months was independently associated with decreased survival (HR: 2.1, P=0.02). For both systems, worsening stage at 3 months or at 6 months was associated with a worse survival than retaining the original stage. In contrast, improving stage as compared to remaining in same stage was not associated with better survival at 3 or 6 months (Table 1). When the analysis was restricted to patients who had an advanced stage at diagnosis, improving stage at 3 months was associated with longer survival compared to retaining the original stage, with both modified Mayo 2004 (10.8 vs. 3.3 years, P<0.001) and Mayo 2012 (8.1 vs. 2.6 years, P<0.001) staging systems. At 6 months, stage improvement was associated with longer survival than retaining the original stage when the modified Mayo 2004 staging system was used (NR vs. 5.0 years, P=0.02), but it was not statistically significant when the Mayo 2012 staging system was used (5.9 vs. 3.7 years, P=0.12). Conclusion: The modified Mayo 2004 and the Mayo 2012 staging systems have independent prognostic value when used for restaging after 3 and 6 months from initiation of first-line treatment. Migration to a higher stage from diagnosis predicts decreased survival, compared to retaining the same stage. Stage improvement is associated with a better OS in patients with advanced stage at diagnosis. Disclosures Dispenzieri: Alnylam, Intellia, Janssen, Takeda, Pfizer, Prothena, Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kapoor:GlaxoSmithKline: Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; Celgene: Honoraria; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Cellectar: Consultancy. Dingli:Rigel: Consultancy; Millenium: Consultancy; Sanofi-Genzyme: Consultancy; Bristol Myers Squibb: Research Funding; Karyopharm Therapeutics: Research Funding; Janssen: Consultancy; Alexion: Consultancy; Apellis: Consultancy. Lin:Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gamida Cells: Consultancy; Takeda: Research Funding; Merck: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Janssen: Consultancy, Research Funding; Vineti: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding. Gertz:Alnylam: Consultancy; NCI SPORE MM: Research Funding; Ionis/Akcea: Consultancy; Amyloidosis Foundation: Research Funding; Celgene: Consultancy; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Advisory Board for Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Advisory Board for Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Consultancy; Springer Publishing: Patents & Royalties; Prothena: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Data Safety Monitoring board from Abbvie: Membership on an entity's Board of Directors or advisory committees; International Waldenstrom Foundation: Research Funding. Kumar:Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Genecentrix: Consultancy; Cellectar: Other; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Kite Pharma: Consultancy, Research Funding; MedImmune: Research Funding; Carsgen: Other, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Karyopharm: Consultancy; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; BMS: Consultancy, Research Funding; Novartis: Research Funding; Adaptive Biotechnologies: Consultancy; Tenebio: Other, Research Funding; Dr. Reddy's Laboratories: Honoraria; Sanofi: Research Funding.

Abstract Purpose: Rearrangements involving the MYC protooncogene are common in newly diagnosed multiple myeloma, but their prognostic significance is still unclear. The purpose of this study was to assess the impact of MYC rearrangement on clinical characteristics, treatment response, and survival in patients with newly diagnosed multiple myeloma. Experimental Design: This is a retrospective study including 1,342 patients seen in Mayo Clinic in Rochester, MN, from January 2006 to January 2018, who had cytogenetic testing by FISH at diagnosis, including MYC testing using the break apart FISH probe (8q24.1). Results: A rearrangement involving MYC was found in 8% of patients and was associated with elevated β2-microglobulin, ≥50% bone marrow plasma cells, IgA multiple myeloma, and the cooccurrence of trisomies. There were no differences in overall response rates between patients with and without MYC rearrangement when induction chemotherapy was proteasome inhibitor (PI)-based, immunomodulatory drug (IMiD)-based or PI + IMiD-based. Overall survival was shorter in patients with MYC rearrangement compared with patients without MYC rearrangement (5.3 vs. 8.0 years, P < 0.001). MYC rearrangement was associated with increased risk of death on multivariate analysis when high-risk cytogenetic abnormalities, ISS stage III, and ≥70 years of age were included (risk ratio: 1.5; P = 0.007). Conclusions: MYC rearrangement is associated with high disease burden and is an independent adverse prognostic factor in patients with newly diagnosed multiple myeloma.

Abstract A gain in chromosome 1q (+1q) is among the most common cytogenetic abnormalities in multiple myeloma (MM). It is unclear whether +1q is independently associated with decreased overall survival (OS). The objective of this study was to evaluate the impact of +1q on clinical characteristics, treatment response, and survival outcomes. We included 1376 Mayo Clinic patients diagnosed with MM from 2005 to 2018 who underwent fluorescence in situ hybridization testing at diagnosis with a panel including the +1q probe. A gain in 1q was found in 391 patients (28%) and was associated with anemia, hypercalcemia, high tumor burden, International Staging System (ISS) stage 3, high-risk (HR) translocations, and chromosome 13 abnormalities. There was no difference in overall response or deeper responses to proteasome inhibitor (PI)–, immunomodulatory drug (iMiD)–, or PI plus IMiD–based induction. Time to next treatment was shorter in patients with +1q compared with those without +1q (19.9 vs 27.7 months; P < .001). On univariate analysis, +1q was associated with increased risk of death (risk ratio [RR], 1.9; P < .001), and decreased OS was seen in all treatment groups. +1q was independently associated with decreased OS on multivariate analysis when other HR cytogenetic abnormalities, ISS stage 3, and age ≥70 years were included (RR, 1.5; P < .001). Gain of >1 copy of 1q was not associated with worse OS compared with gain of 1 copy (4.9 vs 4.3 years; P = .21). +1q was associated with high tumor burden, advanced disease stage, and HR translocations. It is independently associated with decreased OS, even in the setting of novel therapy and transplant.

e20520 Background: Cytogenetic abnormalities detected by FISH are found in the majority of multiple myeloma (MM) patients. Although their prognostic value has been studied extensively, less is known about their association with disease characteristics and treatment response. Methods: To address these questions, we designed a retrospective study including 2031 Mayo Clinic patients diagnosed with MM from 2004 to 2018. We compared baseline characteristics and treatment outcomes between primary cytogenetic groups: t(11;14), t(4;14), t(14;16), (14;20), t(6;14), unknown IgH translocation/del and trisomy (without IgH translocation). These included 373, 177, 78, 20, 18, 228 and 791 patients respectively. Kruskal-Wallis and Fisher’s exact tests were used for categorical and continuous variables respectively. Time to next treatment (TTNT) was estimated using Kaplan-Meier method and compared using Log-Rank test. Results: t(4;14), t(14;16), t(6;14) and t(14;20) groups were associated with hemoglobin < 10 g/dL, beta2microglobulin > 5.5 µg/ml, ISS stage 3 and ≥50% bone marrow plasma cells. The latter 3 groups were also associated with renal dysfunction (Cr ≥2 mg/dL) and higher urinary monoclonal protein. t(4;14) was associated with IgA isotype, serum monoclonal protein ≥1g/dL and plasma cell labeling index ≥1%. Light chain myeloma was more prevalent in patients with t(11;14). Overall response rate (ORR) to proteasome inhibitor (PI) induction was higher for those with IgH translocations (any) compared to trisomies (85% vs 77% P = 0.02), while ORR was higher for those with trisomies with immunomodulatory drug (IMiD) induction (90% vs 78% P < 0.01). The rate of ≥ very good partial response was higher for patients with high risk IgH translocations [t(4;14), t(14;16) or t(14;20)] compared to standard risk with PI-IMiD combination treatment (88% vs 65% P < 0.01). Otherwise, response rates did not differ between these 2 groups. TTNT was longer in patients with trisomies compared to those with IgH translocation with IMiD or PI-IMiD treatments (32.2 vs 19 and 44 vs 27.4 months, respectively P < 0.01). For all cytogenetic groups, better treatment responses and longer TTNT were seen with PI-IMiD combinations compared to other treatments. Conclusions: t(4;14), t(14;16), t(6;14), and t(14;20) are associated with high risk disease characteristics. Patients with IgH translocations may have better response to PI induction compared to those with trisomies, while those with trisomies may have better response to IMiD treatment, with best outcomes for both seen with PI-IMiD combinations.

e13540 Background: The identification of pathogenic variants and variants of unknown significance (VUS) in multi-gene cancer predisposition testing raises new questions regarding cancer risk and management. We evaluated the personal and family cancer patterns and variation by race and ethnicity, among individuals positive for pathogenic variants in non-BRCA1/ 2 cancer predisposing genes. Methods: The Karmanos Cancer Institute (KCI) Cancer Genetics database was queried from May 13, 2013 through December 31, 2018. There were 3,544 unrelated individuals evaluated for hereditary cancer predisposition of whom 1,868 had 18-gene panel testing at 6 sites across Michigan. Data was collected on personal and family cancer history including ages at diagnosis utilizing a 3-generation pedigree, self-identified race and ethnicity and results of genetic testing. We describe the prevalence of pathogenic variants by proband cancer diagnosis, family history, race, and ethnicity. Results: The race/ethnic distribution of the tested cohort included 67.5% non-Hispanic White (NHW), 24.4% African American (AA), 2.1% Arab, 1.8% Ashkenazi Jewish (AJ), 1.0% Hispanic, and 3.4% other. The distribution of cancer diagnoses included 40.6% breast, 5.5% ovarian, 4.1% colon, 3.5% endometrial, 2.0% pancreas and 39.7% unaffected. Pathogenic variants were seen in 151 (8.1%) individuals and VUS in 309 (16.5%). The five most common pathogenic variants were CHEK2 (40), MUTYH (22), ATM (20), and PALB2 (18). The most common pathogenic variants by race and ethnicity were CHEK2 (NHW), RAD51C (AA), PALB2 (Arab), CHEK2, MSH6 (AJ), and none in Hispanics. Variants associated with the four most common cancer types were breast ( CHEK2 ), ovarian ( CHEK2, MUTYH, BRIP1), colon ( ATM), and endometrial ( MSH6, PALB2). Of 40 individuals with CHEK2 variants, 92.5% were NHW, and 34 (85%), 31 (78%), 10 (25%), 1 (2.5%) had family history of breast cancer, breast cancer before age 50, ovarian, and colon cancer, respectively. Of 20 with ATM variants, 95% were NHW, 13 had family history data and 10 (76.9%), 8 (61.5%), 2 (15.4%), 1 (7.7%) had family history of breast, breast cancer before age 50, ovarian, and colon cancer, respectively. Conclusions: Pathogenic variants seen using multigene panel testing differ by race, ethnicity and personal/family history of cancer. This data will inform genetic counseling strategies in regards to cancer risk and management. Data on additional genes updated through 2019 will be presented.

Key PointsPatients with an abnormal sFLC ratio because of LC suppression have outcomes similar to those with a normal ratio. sFLC ratio has prognostic value in patients achieving CR who have an absence of clonal BMPCs assessed by MFC.

The treatment of multiple myeloma has evolved markedly in the last decade, but mortality remains high, emphasizing the need for more effective therapies. Daratumumab, a fully human monoclonal antibody targeting CD38, has shown clinical efficacy in relapsed/refractory multiple myeloma both as monotherapy and in combination with other drugs, including novel agents. More recently, promising results have been reported in patients with untreated newly diagnosed multiple myeloma (NDMM). Clinical trials thus far have shown enhanced efficacy and tolerability of several daratumumab-based combinations in both transplant ineligible and eligible patients, without compromising transplant ability. However, benefit in high-risk subpopulations is still unclear. A subcutaneous formulation of daratumumab has been introduced to decrease the risk of infusion reactions, with preliminary results showing non-inferior efficacy. The antimyeloma activity of daratumumab is achieved through multiple mechanisms including direct, Fc-dependent, and immunomodulatory mechanisms. Enhanced efficacy of daratumumab in combination with immunomodulatory drugs and proteasome inhibitors is supported by preclinical data showing synergism. This review will focus on the role of daratumumab in untreated NDMM patients, highlighting the results of major clinical trials, and listing ongoing trials that are evaluating various daratumumab-based combinations in this setting.

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.