Go, Ronald S.

Background: The past two decades have seen an explosion in the development of new drugs for the treatment of myeloma, and previous studies have shown that these advances have translated into improved survival. It is unclear if we have continued to maintain the pace of improvement in the recent years. We designed this study to examine the patterns of survival in patients with newly diagnosed MM, specifically examining the impact on patient subgroups by age and disease risk. Patients and Methods: We included patients with newly diagnosed MM, who were seen at Mayo Clinic, Rochester between 2004 and 2018. We grouped them into three 5-year groups: group 1 (2004-2008), group 2 (2009-2013) and group 3 (2014-2018) to assess the trends over time. Only those who were seen within 6 months of diagnosis were included in the current cohort. Fluorescence in situ hybridization (FISH) was performed using clg based approach as previously described and high risk (HR) was defined as those with t(4;14), t(14;16), t(14;20) and del17p. Survival was estimated using the Kaplan-Meier method and curves were compared using the log rank test. The Cox proportional hazards model was used to examine the prognostic impact of various clinical and laboratory factors. Results: The study cohort had 3783 patients: 61% were male, median age was 64 years (range 22-96), 47% were ≥65 and 14% ≥75 years. There was no change over time in the median age or the gender distribution. No clear trends were evident across the groups in terms of the disease characteristics including high risk status. The patients in the cohort were divided into three 5 year groups: Group 1(2004-2008; n=1045), Group 2(2009-2013; n=1237) and Group 3(2014-2018; n=1501). The initial treatment regimen changed over time to include proteasome inhibitors (PI) and immunomodulatory drug (IMiD) based regimens with a PI-IMiD combination being 2%, 18% and 55% respectively in groups 1, 2 and 3 (Figure 1). The median follow-up for the entire cohort was 6.8 years (95% CI; 6.5,6.9), and for groups 1, 2 and 3 were 13 years, 8 years and 3.2 years respectively. The median OS for the entire group was 6.8 years (95% CI; 6.4, 7.2). The median OS from diagnosis has improved over time with the groups 1, 2, and 3 having a median OS (95% CI) of 5.5 years (5.1, 6.1), 7.3 years (6.7, 8.0) and NR respectively(P=0.0001) (Figure 2). We specifically looked at the 1, 2 and 3-year survival over the years and found a steady trend for improvement (Figure 3). When examining trends by age, those under 65 years had improvement in survival from group 1 to 2; median OS was 7.3 years, 10 years and NR for groups 1, 2 and 3 respectively (P=0.0001) . Those above 65 had major improvement from group 2 to 3; median OS was 4.4 years, 5.2 years and NR for groups 1,2 and 3 respectively (P=0.0001). When examined by FISH risk status, improvement in OS was seen among with Standard Risk (SR) status, especially during the last 5-year period. The median OS for patients with HR status was 3.5 years, 4.5 years and NR (P=0.07); and 7.6 years, 8.6 years and NR in patients with SR status (P=0.0012) for groups 1, 2 and 3 respectively. Conclusion: In a large cohort of patients with newly diagnosed MM, we have been able to demonstrate sustained improvement in OS over the years, likely driven by introduction of new drugs and continued use of transplant. The impact of newer generation of drugs, especially monoclonal antibodies is not reflected in this analysis and will likely become obvious over the next five years. The data will help identify the areas that require focus for continued improvements in order to derive the maximum impact on outcomes. Disclosures Kapoor: Celgene: Honoraria; Amgen: Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; Cellectar: Consultancy; GlaxoSmithKline: Research Funding; Takeda: Honoraria, Research Funding. Gertz:Alnylam: Other: personal fee; Prothena: Other: personal fee; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Proclara: Other; Aurora Bio: Other; Springer Publishing: Patents & Royalties; Sanofi: Other; Research to Practice: Other; Celgene: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Ionis/Akcea: Other: personal fee; Abbvie: Other. Dispenzieri:Intellia: Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Janssen: Research Funding; Celgene: Research Funding. Dingli:Rigel: Consultancy; Bristol Myers Squibb: Research Funding; Apellis: Consultancy; Alexion: Consultancy; Sanofi-Genzyme: Consultancy; Karyopharm Therapeutics: Research Funding; Millenium: Consultancy; Janssen: Consultancy. Russell:Imanis: Other: Equity Ownership. Lin:Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Takeda: Research Funding; Legend BioTech: Consultancy; Merck: Research Funding; Vineti: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gamida Cells: Consultancy. Kumar:Carsgen: Other, Research Funding; Adaptive Biotechnologies: Consultancy; Tenebio: Other, Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Cellectar: Other; Genecentrix: Consultancy; Dr. Reddy's Laboratories: Honoraria; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; MedImmune: Research Funding; Sanofi: Research Funding; Karyopharm: Consultancy; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; BMS: Consultancy, Research Funding; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Merck: Consultancy, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments.

Background: Within the heterogeneous genomic landscape of multiple myeloma (MM), clonal evolution including the acquisition of risk-defining mutations and chromosomal abnormalities is a recurrent event and can be detected by fluorescence in situ hybridization (FISH). The effects of acquired abnormalities on clinical outcomes have not been well defined. We previously reported that patients who acquired 17p deletion [del(17p)] during the course of their disease had a significantly reduced overall survival (OS) by 38 months compared to patients who did not acquire del17p (Lakshman et al 2019). Similarly, while de novo gain of the long arm of chromosome 1 (1q22 gain) is a known high-risk aberration associated with significantly shorter OS and progression-free survival (PFS) in MM, the prognostic significance of acquired 1q22 gain has not been described. The primary objective of this study was to analyze factors predictive for acquired 1q22 gain and determine its impact on survival. Methods: We identified MM patients from the Mayo Clinic Dysproteinemia Database who had at least one follow up FISH performed ≥6 months from diagnosis. The clinical characteristics, concomitant cytogenetic abnormalities, first line treatments administered, and OS were compared between patients with acquired 1q22 gain and patients who did not acquire this abnormality. The Mayo Clinic IRB approved this study. Results: A total of 1041 MM patients met the inclusion criteria. Of these, 63 patients (6.1%) had acquired 1q22 gain, defined as being negative for 1q22 gain on initial FISH at diagnosis and having this abnormality detected on subsequent FISH. Median age at diagnosis was 59 years and 56% were male. Median time to acquisition of 1q22 gain was 60 months (range 8-140 months). We identified one control patient for each case who was diagnosed within one year of the case and had a subsequent FISH performed at a similar duration from diagnosis. Patients with acquired 1q22 gain had similar baseline characteristics except for a higher proportion of high-risk (HR) FISH at diagnosis [t(4;14), t(14;16), t(14;20), and del(17p13)] when compared to controls (27% HR FISH versus 6% HR FISH; P<0.01). 1q22 gain was concomitantly present with trisomies in 33 patients (54%), monosomy 13 in 24 patients (39%), t(4;14) in 8 patients (13%), and del(17p13) in 7 patients (12%). All patients received treatment prior to acquisition of 1q22 gain. Of the 63 patients, first line induction therapy consisted of proteasome inhibitor (PI) with steroid in 43%, immunomodulatory drugs (IMiD) with steroid in 40%, and PI + IMiD with steroid in 17% of patients. 54 patients (85%) received upfront stem cell transplant (SCT) (median 5.9 months to SCT), compared to 50 patients (79%) in the control group who received SCT. The median follow up of all 126 patients was 6.8 years. There was a statistically significant reduction in median OS from diagnosis in patients with acquired 1q22 gain compared to the control group (10.8 years versus 13.0 years; P = 0.02; Figure 1). Predictors of acquisition of 1q22 gain were identified using a case-control method. Age ≥70 at diagnosis and presence of HR FISH at baseline appeared to increase the risk of acquiring 1q22 gain. Conclusion: Acquisition of 1q22 gain is a relatively uncommon occurrence, but notably reduced OS by 2.2 years compared to patients who did not acquire 1q22 during the course of their disease (P = 0.02). Older age and the presence of HR FISH at diagnosis increased the risk of acquisition of 1q22 gain. The presence of high-risk translocations at baseline suggests that acquisition of 1q22 gain occurs in the context of more aggressive disease biology. Disclosures Kapoor: Cellectar: Consultancy; Celgene: Honoraria; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding. Dispenzieri:Alnylam: Research Funding; Pfizer: Research Funding; Celgene: Research Funding; Takeda: Research Funding; Intellia: Research Funding; Janssen: Research Funding. Gertz:Prothena: Consultancy; 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; Amyloidosis Foundation: Research Funding; International Waldenstrom Foundation: Research Funding; NCI SPORE MM: Research Funding; Ionis/Akcea: Consultancy; Physicians Education Resource: Consultancy; Medscape: Consultancy, Speakers Bureau; Amgen: Consultancy; Appellis: Consultancy; Annexon: Consultancy; Spectrum: Consultancy, Research Funding; Janssen: Consultancy; Sanofi: Consultancy; Data Safety Monitoring board from Abbvie: Membership on an entity's Board of Directors or advisory committees; Alnylam: Consultancy. Dingli:Apellis: Consultancy; Rigel: Consultancy; Millenium: Consultancy; Bristol Myers Squibb: Research Funding; Karyopharm Therapeutics: Research Funding; Sanofi-Genzyme: Consultancy; Alexion: Consultancy; Janssen: Consultancy. Lin:Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy; Legend BioTech: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding. Kumar:Cellectar: Other; Genecentrix: Consultancy; Dr. Reddy's Laboratories: Honoraria; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; BMS: Consultancy, Research Funding; Sanofi: Research Funding; Karyopharm: Consultancy; MedImmune: Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; 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; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Adaptive Biotechnologies: Consultancy; 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; Carsgen: Other, Research Funding; Tenebio: Other, Research Funding.

Introduction: Since 2018, immunoenrichment-based matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), termed MASS-FIX, has replaced immunofixation for the detection and isotyping of serum monoclonal proteins at Mayo Clinic. MASS-FIX has advantages including increased sensitivity, specificity, and the ability to distinguish therapeutic monoclonal antibodies. Herein, we report the laboratory characteristics and distribution of diagnoses of patients tested clinically at Mayo Clinic. Methods: MASS-FIX was performed on patient samples as previously described (Kohlhagen et. al. Clin Chem Lab 2020). Demographics and laboratory data, including quantitative M-spike, serum free light chains (FLC), and quantitative immunoglobulins at the time of MASS-FIX were recorded. For patients with multiple samples during the study period, only the initial MASS-FIX was evaluated. We identified 9195 unique patients with MASS-FIX performed between 7/24/2018 and 3/6/2020. Seven-thousand nine hundred and forty-six patients provided consent for study enrollment, and 7689 had data available on index diagnosis. Given considerable variability in the interpretation of diagnostic criteria for light chain (LC) MGUS, patients with this diagnosis (1360, 18%) were excluded. Patients were considered to have negative results (2211 in total) on MASS-FIX if: 1) no monoclonal protein was identified (1081, 49%); 2) the interpretation was "cannot rule out monoclonal protein" (945, 43%); 3) multiple, nonspecific spectral peaks were identified consistent with immune reconstitution (29, 1%); or 4) the only monoclonal protein identified was consistent with a therapeutic monoclonal antibody (156, 7%). Results: The final cohort consisted of 4118 patients with a positive MASS-FIX and 2211 patients with a negative MASS-FIX, all in the setting of underlying PCDs. Figure 1 illustrates the numbers and percentages of patients who are MASS-FIX positive versus MASS-FIX negative by diagnosis. MGUS and multiple myeloma (MM) were the most common diagnoses overall, and both were more common in the MASS-FIX positive cohort. More than 90% of patients with Waldenstrom's macroglobulinemia (WM), smoldering WM, smoldering MM, and cold agglutinin disease were positive by MASS-FIX. For MASS-FIX positive patients, IgG isotype was identified in 2575 patients (63%), IgA in 703 (17%) and IgM in 710 (17%). Bence Jones proteinemia was identified in 283 patients (7%) with lambda restriction being the most common (57%). 3625 patients (88%) had a monoclonal pattern, 228 patients (6%) had a bi-clonal pattern, and 7 (<1%) had a tri-clonal pattern. The majority of patients (58%) were kappa LC restricted by MASS-FIX, 222 (5%) had N-glycosylated LC, and 2 patients (<1%) had a heavy chain with no light chain. Conclusions: This single institution experience illustrates the practicality of MASS-FIX in detecting and following monoclonal proteins for a wide range of PCDs in a tertiary center. In this cohort, the percentage of patients who were MASS-FIX positive varied by diagnosis, reflecting cross sectional sampling of patients throughout their disease course. Disclosures Gertz: Research to Practice: Other; Springer Publishing: Patents & Royalties; Aurora Bio: Other; Johnson and Johnson: Speakers Bureau; Sanofi: Other; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Prothena: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee; Proclara: Other; DAVA oncology: Speakers Bureau; Celgene: Other; Teva: Speakers Bureau; Abbvie: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau. Kumar:AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Karyopharm: Consultancy; Merck: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Genecentrix: Consultancy; Adaptive Biotechnologies: Consultancy; Novartis: Research Funding; MedImmune: Research Funding; Sanofi: Research Funding; Tenebio: Other, Research Funding; 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. Kapoor:Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Cellectar: Consultancy; Janssen: Research Funding; Celgene: Honoraria. Dingli:Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Rigel: Consultancy; Alexion: Consultancy; Sanofi-Genzyme: Consultancy; Janssen: Consultancy; Apellis: Consultancy; Millenium: Consultancy. Lin:Merck: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Gamida Cells: Consultancy; Takeda: Research Funding; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy. Murray:The Binding Site: Patents & Royalties: Patent Use of Mass Spec to identify monoclonal proteins licensed to The Binding Site. Dispenzieri:Alnylam, Intellia, Janssen, Takeda, Pfizer, Prothena, Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Background: Lytic bone lesions are one of the most common clinical characteristics of patients with multiple myeloma (MM) and identification of bone lesions help distinguish between patients with smoldering multiple MM and active MM. Given this, the most recent update of the diagnostic criteria for MM incorporates advanced imaging approaches for distinguishing between the two entities. Several small retrospective studies have compared conventional skeletal survey (SS) with whole-body low dose computed tomography (WBLDCT) scan or the CT portion of a positron emission tomography (PET) scan. Conducting prospective studies comparing these two modalities side by side is limited by the radiation exposure. We undertook this study to provide a comparison between these two imaging modalities in terms of their ability to recognize lytic bone lesions in patients with MM. Patients and methods: This was a retrospective study of consecutive patients with the diagnosis of MM treated at Mayo Cinic Hospital during 2004- 2018. Patients were included if they had a conventional skeletal survey no more than 3 months before MM diagnosis or any time after diagnosis and also had a WBLDCT or PET-CT within a 12-month period following the skeletal survey. We chose this approach since it is unlikely that a patient would have had both modalities done at the same time as part of standard of care (SOC). This approach was also facilitated by a gradual change in our SOC for skeletal imaging from conventional skeletal survey to WBLDCT. To measure the robustness of our findings, we performed a sensitivity analysis in patients who had the exam ≤6 months apart. Proportions were compared using a chi-square test and survival estimates were calculated using the Kaplan- Meier methodology and compared using log rank test. Results: The overall study cohort had 1040 patients, median age was 62 years at diagnosis (range, 24-94), 61% were male and 39% were female. The median time to the skeletal survey was 8 months from diagnosis (range, 0-160) and the median time to WBLDCT or PET-CT from SS was 2 months (0-12). A PET-CT was available in 789 (76%) of patients and WBLDCT in 251 (24%) of patients. Among the 300 patients with no lesions identified by SS, 188 (63%) had lytic lesions identified by CT, while in 60/740 (8%) patients with a positive SS did not have lytic lesions observed on the CT (p<0.0001). Overall, CT identified lytic lesions in 868 (84%) patients compared with 740 (71%) patients with lytic lesions seen on SS. Although the proportion of lytic lesions was slightly higher with PET compared to WBLDCT, the analysis did not reach statistical significance (65% vs. 56%; p = 0.17; Table 1a). After restricting the analysis to those with ≤6 months gap between low dose CT and SS (n=737), the result did not change (Table 1b). Further examination demonstrated that presence of lytic lesions by SS had no impact on OS from diagnosis, detection of lesions on the CT exam was associated with an inferior survival (112 vs. 81 months, p<0.0001). (Figure 1) Conclusion: Skeletal survey has been the screening technique of choice for evaluation of bone involvement in MM for decades. However, CT based approaches have higher sensitivity with lytic lesions identified in a higher proportion of patients. The prognostic value of lytic disease is evident with CT based detection, again suggesting that this provides a more accurate estimate of the skeletal disease burden. Low dose CT rather than conventional radiographs should be the modality of choice for monitoring disease-progression and diagnosing active multiple myeloma. Disclosures Kapoor: Cellectar: Consultancy; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria. Gertz:Abbvie: Other; Celgene: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Janssen: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Johnson and Johnson: Speakers Bureau; Teva: Speakers Bureau; Annexon: Other: personal fee; Research to Practice: Other; Sanofi: Other; Proclara: Other; DAVA oncology: Speakers Bureau; Springer Publishing: Patents & Royalties; Appellis: Other: personal fee; Amgen: Other: personal fee; Prothena: Other: personal fee; Aurora Bio: Other; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee. Dispenzieri:Takeda: Research Funding; Pfizer: Research Funding; Janssen: Research Funding; Intellia: Research Funding; Alnylam: Research Funding; Celgene: Research Funding. Dingli:Alexion: Consultancy; Janssen: Consultancy; Sanofi-Genzyme: Consultancy; Millenium: Consultancy; Bristol Myers Squibb: Research Funding; Rigel: Consultancy; Apellis: Consultancy; Karyopharm Therapeutics: Research Funding. Lin:Merck: Research Funding; Takeda: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Vineti: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gamida Cells: Consultancy. Kumar:Dr. Reddy's Laboratories: Honoraria; AbbVie: 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; Sanofi: Research Funding; Novartis: Research Funding; Janssen Oncology: 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; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Carsgen: Other, Research Funding; Cellectar: Other; MedImmune: Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Tenebio: Other, Research Funding; Genecentrix: Consultancy; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding.

Background: Patients with newly diagnosed MM can be quite symptomatic as a result of end organ damage related to MM as well as presence of other comorbidities in this relatively older patient population. Prior studies have shown that the performance score as well as other quality of life (QOL), frailty and comorbidities scores can have prognostic value in these patients. However, many of these questionnaires are lengthy and complex, and not practical in a busy outpatient practice. We implemented a three question symptom assessment score in 2010 in our outpatient practice. Here we present the results of the analysis looking at the impact of this measurement in patients with newly diagnosed MM. Patients and Methods: Patients seen in the outpatient Hematology practice at Mayo Clinic, Rochester MN, were asked to grade the symptoms of fatigue, pain, and QOL on a 0 to 10 scale during the past 7 days, with 10 being the worst and the QOL on a similar scale but with 10 being the best. For the purpose of the current analysis the QOL score was reversed.These three scores were added for a total score. We looked at the impact of the baseline score as well as the score after four cycles of therapy, at the time of best response, and at the time of the first progression, wherever they were available. Survival curves were generated by the Kaplan-Meier method and compared using the log rank test. The Cox proportional hazards model was used for assessment of the impact of different prognostic variables. Results: Data from 735 patients with newly diagnosed MM seen at Mayo Clinic between 2011 and 2018 were available from baseline. The median total score was 10 (0-30), and for fatigue, pain and QOL were 4, 3 and 7 respectively, all with range of 0-10. Based on the baseline scores, patients were grouped into tertiles (Group 1 with score < 8, group 2 with score 8 to 14 and group 3 with a score ≥ 15). There were 256 (34%), 272 (37%) and 207 (28%) patients in groups 1, 2 and 3 respectively. The median overall survival (OS) (95% CI) from diagnosis was NR (7.9, NR), 7.7 (6.2, NR) and 5.4 (4.2, 6.9), respectively for groups 1, 2 and 3 (P < 0.0001) (Figure 1a). The prognostic value of the score was independent of age, FISH based risk status and the ISS stage. When evaluated after 4 cycles (n=325), the OS was significantly different for the 3 groups (P<0.01) (figure 1b). We then examined the impact of the score at best response to initial therapy (n=446) on OS from that timepoint and saw similar trend, but the results were not statistically significant (P=0.09) (Figure 1c). When evaluated at the time of first disease progression, the score again identified three groups with different OS from progression (P<0.001) (Figure 1d). Conclusions:Patient-reported outcomes are associated with survival in patients with MM. This simple, easy to complete patient-reported outcome 3-item scale can be easily completed in a busy practice and is a clinically useful tool to assess potential outcomes of patients at various disease stages, including at diagnosis and at relapse. Disclosures Kumar: Adaptive Biotechnologies: Consultancy; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; AbbVie: 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; Kite Pharma: Consultancy, Research Funding; Novartis: Research Funding; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Cellectar: Other; Genecentrix: Consultancy; Merck: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria. Kapoor:Janssen: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria. Gertz:Proclara: Other; Springer Publishing: Patents & Royalties; Abbvie: Other; Celgene: Other; Aurora Bio: Other; Medscape: Other: personal fee, Speakers Bureau; Sanofi: Other; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Prothena: Other: personal fee; Physicians Education Resource: Other: personal fee; Research to Practice: Other; Ionis/Akcea: Other: personal fee; Alnylam: Other: personal fee. Dispenzieri:Alnylam: Research Funding; Intellia: Research Funding; Janssen: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Pfizer: Research Funding. Dingli:Rigel: Consultancy; Millenium: Consultancy; Alexion: Consultancy; Janssen: Consultancy; Apellis: Consultancy; Sanofi-Genzyme: Consultancy; Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding. Lin:Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy; Legend BioTech: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding.

Introduction: Since 2018, immunoenrichment-based matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), termed MASS-FIX, has replaced standard gel-based immunofixation for the detection and isotyping of serum monoclonal proteins at Mayo Clinic. MASS-FIX can readily identify N-glycosylation of involved light chains (LC N-glycosylation) by its unique, polytypic spectral pattern. LC N-glycosylation is identified more commonly in light chain amyloidosis (AL) than other plasma cell disorders (PCDs), and is associated with an increased risk of progression from MGUS to both AL and other PCDs (Dispenzieri et. al. Leukemia 2020). Herein, we report the mass spectral characteristics and distribution of diagnoses among 222 patients with LC N-glycosylation detected during a 20 month period in our clinical lab. Methods: MASS-FIX was performed on patient samples as previously described (Kohlhagen et. al. Clin Chem Lab 2020). Demographics and laboratory data, including quantitative M-spike, serum free light chains (FLC), and quantitative immunoglobulins at the time of MASS-FIX were recorded. For patients with multiple samples during the study period, only the initial MASS-FIX was evaluated. 9195 unique patients had MASS-FIX performed from 7/24/2018 to 03/06/2020. Inclusion criteria for this retrospective study included: 1) consent for record review; 2) a monoclonal protein identified on MASS-FIX; 3) an underlying PCD. Patients were considered to have negative results (2211 in total) on MASS-FIX if: 1) no monoclonal protein was identified (1081, 49%); 2) the interpretation was "cannot rule out monoclonal protein" (945, 43%); 3) multiple, nonspecific spectral peaks were identified consistent with immune reconstitution (29, 1%); or 4) the only monoclonal protein identified was consistent with a therapeutic monoclonal antibody (156, 7%). The final positive cohort consisted of 4118 patients with definitive monoclonal proteins on MASS-FIX. Results: Two-hundred and twenty-two (5%) of the 4118 patients with a positive MASS-FIX had LC N-glycosylation. 202 patients (91%) had FLC assays performed. Of these, 110 (54%) were kappa LC restricted, 22 (11%) were lambda restricted, and 70 (35%) were normal. A quantifiable M-spike was identified in 110 patients (85%) of 129 patients who had serum protein electrophoresis performed. By MASS-FIX, 139 patients (63%) had an IgG isotype, 18 (8%) an IgA, and 55 (25%) an IgM. Two of these patients had a bi-clonal pattern in which both IgG kappa and IgM kappa LCs were N-glycosylated. 12 patients (5%) had monoclonal light chains with no corresponding heavy chain. Overall, 173 (78%) of 222 patients were kappa LC restricted and 44 (22%) were lambda. 189 patients (85%) had a monoclonal pattern, 18 (8%) had a bi-clonal pattern, and 3 (1%) had a tri-clonal pattern. The most common PCD diagnoses for the 222 patients with LC N-glycosylation were MGUS (45%), multiple myeloma (MM) (31%), and immunoglobulin light chain amyloidosis (AL) (8%). The percentage of MASS-FIX positive patients with LC N-glycosylation by diagnosis, stratified by kappa and lambda LC restriction, is illustrated in Figure 1. Cold agglutinin disease (CAD) had the highest relative percentage of patients with LC N-glycosylation, regardless of LC restriction. Eighteen AL patients (5%) had LC N-glycosylation; the percentage was higher in kappa restricted (13%) than lambda restricted AL patients (2%). Of note, LC N-glycosylation was not detected in patients with plasma cell leukemia, non-AL amyloidosis with associated MGUS, POEMS Syndrome or Castleman's Disease in this cross sectional sampling of patients. Conclusions: This retrospective study demonstrates that 5% of patients in a routine clinical setting with positive MASS-FIX have glycosylated LCs. Consistent with prior observations, CAD had the highest relative percentage of LC N-glycosylated patients. The percentage of AL patients with LC N-glycosylation in this cohort is lower than previously reported for newly diagnosed AL patients (Kumar et. al. Leukemia 2019), which is not surprising given that the current cohort study is a cross sectional evaluation of patients at various stages of diagnosis and treatment rather than a prevalence study. Further study will be done to exclude the presence of latent AL in patients with N-glycosylated LC and diagnoses of MGUS, SMM, MM, and Waldenstrom's macroglobulinemia. Disclosures Gertz: Springer Publishing: Patents & Royalties; Proclara: Other; DAVA oncology: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Teva: Speakers Bureau; Sanofi: Other; Research to Practice: Other; Celgene: Other; Abbvie: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Prothena: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee; Aurora Bio: Other. Kumar:Adaptive Biotechnologies: Consultancy; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Carsgen: Other, Research Funding; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Merck: Consultancy, Research Funding; Janssen Oncology: 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; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; MedImmune: Research Funding; Genecentrix: Consultancy; Tenebio: Other, Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Cellectar: Other. Kapoor:Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria; Cellectar: Consultancy. Dingli:Alexion: Consultancy; Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Janssen: Consultancy; Sanofi-Genzyme: Consultancy; Apellis: Consultancy; Rigel: Consultancy; Millenium: Consultancy. Lin:Janssen: Consultancy, Research Funding; Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy; Legend BioTech: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding. Murray:The Binding Site: Patents & Royalties: Patent Use of Mass Spec to identify monoclonal proteins licensed to The Binding Site. Dispenzieri:Intellia: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Alnylam: Research Funding.

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.

Background: Chronic myelomonocytic leukemia (CMML) is a rare chronic myeloid malignancy with a poor prognosis. There are few epidemiologic studies on CMML. We studied population-based outcomes in CMML using the Surveillance, Epidemiology, and End Results (SEER) and the National Cancer Database (NCDB). Methods: The SEER 18 registries and NCDB Participant User File were used to identify patients with ICD-O-3 diagnosis code 9945/3 from 2004-2015. Incidence was identified using SEER and age-adjusted to the U.S. 2000 standard population. Causes of death were obtained and CMML-related death was defined as death from any myeloid disorder (CMML, acute monocytic leukemia, acute myeloid leukemia [AML], chronic myeloid leukemia, other myeloid/monocytic leukemia, and aleukemic, subleukemic, and NOS) to avoid misattribution. Relative survival (RS) was defined as the ratio of the proportion of observed survivors in a cohort of CMML patients to the proportion of expected survivors in a comparable set of individuals that did not have CMML, adjusting for the general survival of the US population for race, sex, age, and time when the diagnosis was established. Time to AML was calculated using the left-truncated life tables session and a 3 month latency period was used to prevent misattribution. Per the NCDB's system on classifying treatment, hydroxyurea, decitabine, and azacitidine are considered chemotherapy. The Kaplan-Meier method was used to calculate overall survival (OS), and Cox regression model was used to identify predictors of survival. Variables significant in univariate analysis (age, Charlson Deyo score [CDS], insurance type, and treatment facility type) were included in a multivariate analysis. Statistical analyses were performed using SAS version 9.0. Results: In the SEER database (n=4437), the median age at diagnosis was 76 years (interquartile range [IQR] 68-83) and 2,783 patients (63%) were male. Incidence rates (1 case/1,000,000 individuals) were as follows: overall 4.4, male 6.6, female 2.9, Non-Hispanic White 4.9, and Non-Hispanic Black 3.3. The incidence did not significantly change from 2004 to 2015. With a median follow up of 5.8 years (95% CI: 5.5-6.3), the median OS was 1.3 years (95% CI: 1.3-1.4). 3635 patients (82%) died. Among those who died, 2016 patients (55%) deaths were CMML-related. When comparing CMML patients to the US general population, 3,156 patients were matched to the expected survival tables. In the general U.S. population, the expected survival for 12, 24, 36, 48 and 60 months was 95.6%, 91.3%, 87.1%, 83.1%, and 79.2%, respectively. In contrast, the RS for patients with CMML at the same time points was 63.6%, 46.2%, 35.2%, 28.8%, and 23.1% (Figure 1). 229 patients (5.2%) progressed to AML. The median time to AML was 1.2 years (IQR 0.6-2.3). In NCDB (n=6403), the median age at diagnosis was 74 years (IQR 66-82). With the median follow up of 6 years (95% CI 3.5-9), the median OS was 1.3 years (95% CI 0.4-3.3). The distribution of CDS score 0, 1, and >1 was 4518 (71%), 1193 (18%), and 692 (11%) respectively. 4687 (77%) had government insurance, while 1399 (23%) had private insurance. 3750 (60%) were treated at a non-academic center. The year of diagnosis was associated with improved OS (HR 0.99, 95% CI: 0.98-0.99). Patients who were diagnosed in 2012-2015 had improved OS compared to patients diagnosed in 2004-2007 (HR 0.89, 95% CI 0.83-0.95) with OS at 1- and 5- years being 60% and 16% (2012-2015) vs. 56% and 17% (2008-2011) vs. 53% and 15% (2004-2007) respectively. 3029 (48%) patients received chemotherapy, while 270 (4%) patients received stem cell transplant as the first-line therapy. The median time to chemotherapy from diagnosis was 19 days (IQR 6-43). OS at 1-, 5-, and 10-years was 57%, 18%, and 4% (no chemotherapy), 56%, 14%, and 7% (received chemotherapy), 79%, 44%, and 38% (received stem cell transplant), and 56%, 15%, 5% (no stem cell transplant). OS curves are shown in Figure 2. Factors independently predicting inferior OS were age ≥ 65 years at the time of diagnosis (p<0.001), CDS ≥ 1 (p<0.001), government insurance (p<0.001), and treatment at a non-academic center (p<0.001) (Table). Conclusion: Despite an improvement in survival over the years, CMML continues to be a cause of significant morbidity and mortality. Older age, CDS ≥ 1, government insurance, and treatment at non-academic facilities were predictive of inferior survival. Disclosures Shah: Dren Bio: Consultancy.

Background: Patients with Waldenström Macroglobulinemia (WM) tend to present at an older age. Frailty, resulting from comorbidities and reduced organ function, poses unique challenges to the management of WM in the elderly. Age above 65 years, is an established unfavorable prognostic factor in WM. However, data specifically pertaining to the very elderly patient population are scant. The impact of advanced age (≥75 years at diagnosis) on the clinical features and outcomes of patients with symptomatic/active WM were studied. Methods: Patients with active WM, evaluated at Mayo Clinic, Rochester between January 1996 and December 2018 were included in the study. The characteristics and laboratory parameters at presentation of the cohort of patients with the age ≥75 years were compared to those of the younger (age <75 years) cohort. The median follow-up and overall survival (OS) were assessed from active disease to last follow-up or death using the Kaplan Meier method. Because older age is a confounding factor for deaths from unrelated causes, the cause-specific survival (CSS) was calculated. Deaths were deemed WM-related if patients died from progressive disease, transformation with antecedent WM, concomitant light chain (AL) amyloidosis, infection associated with WM or anti-WM therapy related toxicity, while patients who died from other causes were considered to have a WM-unrelated death. The patients who died from causes unrelated to WM were censored at death for CSS analysis. The OS of the cohort of the very elderly patients was compared to that of a cohort of the general US population, matched for age, sex as well as follow-up from the calendar-year of diagnosis, to assess the degree to which WM impacts survival. Results: Among 949 consecutive patients, with a median follow-up of 8.4 years [95% Confidence Interval (CI): 7.7-9.3 years] from active disease, the median age at diagnosis was 65 years (range: 31-93 years). Of 177 patients (19%) who were ≥75 years of age at the onset of active WM, 173 (98%) received anti-WM therapy. The baseline characteristics of the 2 cohorts (patients ≥75 years of age versus <75 years) are outlined in Table 1. The patients in the age ≥75 years cohort were noted to have lower IgM levels and serum albumin, and higher serum LDH and serum β-2 microglobulin compared to the age <75 years cohort. A higher proportion of patients in the age <75 years cohort had coexisting AL amyloidosis at diagnosis. The frequency of MYD88L265P mutation was similar between the 2 cohorts (p=0.2). During the 23-year period, there was an increase in the proportion of patients ≥75 years who were diagnosed with active WM (12% during the 1996-2003 period, 18% during 2004-2010, 25% during 2011-2018; P<0.0001). In the elderly WM cohort, the most frequently used frontline treatment was rituximab monotherapy (36%), followed by rituximab-alkylating agent-based regimen (31%). Of 177 patients with age ≥75 years, 89 (50%) patients were deceased at the time of last follow-up and 58% (52/89) of all deaths in age ≥75 years were attributable to WM. By contrast, 303 (39%) out of the 772 patients in the age <75 years cohort were deceased at last follow-up, with 73% (224/303) deaths attributable to WM. The CSS for patients with age ≥75 years was 10.9 years (95% CI: 7.3-11.7 years) versus 14.7 years (95% CI: 13.2-15.7 years) for age <75 years [Risk ratio 2.1(95% CI: 1.5-2.8); p<0.0001]. At the 1 and 2 year follow-up, WM-related mortality was 6.8% and 11.9%, respectively, for patients with age ≥75 years versus 2.6% and 4.9%, respectively, for the younger cohort. The median OS of patients with age ≥75 years from the diagnosis of active WM was 5.9 years (95% CI: 4.2-7.3 years) compared to the OS of 8.3 years for an age, sex and calendar-year-matched cohort, derived from the general US population (p<0.001), Figure 1. Conclusion: Patients who are ≥75 years of age at the time of diagnosis of active WM present with certain poor prognostic features, including higher serum LDH and β-2 microglobulin and lower serum albumin compared to their younger counterparts. The impact of advanced age is underscored by a poorer WM-specific survival for the subset of patients with the age ≥75 years compared to the younger cohort. Furthermore, although active/symptomatic WM is typically an indolent malignancy, it adversely affects OS of the very elderly patients as suggested by the comparison with an age, sex and calendar-year matched cohort of the general US population. Disclosures Ansell: Bristol Myers Squibb: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; ADC Therapeutics: Research Funding; Seattle Genetics: Research Funding; AI Therapeutics: Research Funding; Takeda: Research Funding. Gertz:Ionis/Akcea: Other: personal fee; Alnylam: Other: personal fee; Prothena: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Annexon: Other: personal fee; Appellis: Other: personal fee; Amgen: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Physicians Education Resource: Other: personal fee; Abbvie: Other; Celgene: Other; Research to Practice: Other; Sanofi: Other; Teva: Speakers Bureau; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Proclara: Other; Springer Publishing: Patents & Royalties; Aurora Bio: Other; Janssen: Other: personal fee. Nowakowski:NanoString: Research Funding; Seattle Genetics: Consultancy; Curis: Consultancy; Kymera: Consultancy; Kite: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees; MorphoSys: Consultancy, Research Funding; Celgene/BMS: Consultancy, Research Funding. Witzig:Spectrum: Consultancy; Immune Design: Research Funding; Karyopharm Therapeutics: Research Funding; Acerta: Research Funding; Incyte: Consultancy; MorphSys: Consultancy; AbbVie: Consultancy; Celgene: Consultancy, Research Funding. Dispenzieri:Pfizer: Research Funding; Janssen: Research Funding; Intellia: Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Dingli:Sanofi-Genzyme: Consultancy; Janssen: Consultancy; Bristol Myers Squibb: Research Funding; Rigel: Consultancy; Apellis: Consultancy; Karyopharm Therapeutics: Research Funding; Alexion: Consultancy; Millenium: Consultancy. Kumar:Sanofi: Research Funding; Kite Pharma: Consultancy, Research Funding; Cellectar: Other; Genecentrix: Consultancy; Novartis: Research Funding; Karyopharm: Consultancy; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; AbbVie: 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; Carsgen: Other, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Merck: Consultancy, Research Funding; MedImmune: Research Funding; Adaptive Biotechnologies: Consultancy; Tenebio: Other, Research Funding; Dr. Reddy's Laboratories: Honoraria; BMS: Consultancy, Research Funding; Janssen Oncology: 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. Kapoor:Cellectar: Consultancy; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria.

In 2013, the American Society of Hematology (ASH) published recommendations with Choosing Wisely to limit surveillance imaging in aggressive lymphoma. We studied surveillance imaging practice patterns for diffuse large B-cell lymphoma (DLBCL) before and after the ASH Choosing Wisely campaign. We used OptumLabs Data Warehouse, a national insurance claims database, to retrospectively study imaging frequency in survivors of DLBCL from 2008 to 2016. Three time periods were defined: Period 1 (2008 to 2010), Period 2 (2011 to 2013), and Period 3 (2014 to 2016). One thousand four hundred seventy-two patients were included. Median follow up was approximately 2 years. During the first and second years of surveillance, imaging remained stable between Period 1 (years 1 and 2: 199 [91%] and 137 [83%], respectively) and Period 2 (years 1 and 2: 257 [88%] and 172 [77%], respectively; P = .38), but decreased in Period 3 (years 1 and 2: 315 [78%] and 83 [61%], respectively; P < .01). In a multivariable logistic regression, year after 2012 was a significant predictor of decreased overuse (more than two scans per year in the first year of surveillance; [odds ratio, 0.49 for 2013 v 2008; P = .02]). Our study demonstrated the rate of surveillance scans—both computed tomography and positron emission tomography imaging—in DLBCL decreased after the ASH Choosing Wisely campaign. Multiple factors, such as changes in recommendations, reimbursement, and provider knowledge base, may have all contributed and should be studied further.