Visram, Alissa

Abstract Multiple myeloma (MM) bone disease is a significant cause of morbidity but there is a paucity of data on the impact of malignant plasma cells on adjacent trabecular bone within the BM. Here, we characterize the proteome of trabecular bone tissue from BM biopsies of 56 patients with monoclonal gammopathy of undetermined significance (MGUS), smoldering (SMM), newly diagnosed (NDMM), relapsed MM (RMM), and normal controls. Proteins involved in extracellular matrix (ECM) formation and immunity pathways were decreased in SMM and active MM. Among the proteins most decreased were immunoglobulins, type IV collagen, and TIMP3, suggesting increased immunoparesis and decreased ECM remodelling within trabecular bone. Proteins most increased in SMM/MM were APP (enhances osteoclast activity), ENPP1 (enhances bone mineralization), and MZB1 (required for normal plasmablast differentiation). Pathway analyses showed that proteins involved in gamma -carboxylation, a pathway implicated in osteocalcin function, osteoblast differentiation, and normal hematopoiesis, were also overexpressed in SMM/MM. This study is the first comprehensive proteomic atlas of the BM bone proteome in dysproteinemias. We identify new key proteins and pathways for MM bone disease and potentially impaired hematopoiesis, and show for the first time that gamma -carboxylation pathways are increased in the bone tissue of SMM/MM.

Abstract The treatment landscape for relapsed multiple myeloma (MM) has increased. In this study we aimed to characterize 2nd (n = 1439) and 3rd (n = 1104) line regimens and compare the results between subgroups based on the year of treatment initiation (2nd line: 2003–2008, 2009–2015, 2016–2021; 3rd line: 2004–2009, 2010–2015, and 2016–2021). In both 2nd and 3rd line we observed increasing use of novel agents (from 78–95% and from 77–95%, respectively) and triplet regimens (from 15–69% and from 21–71%, respectively). Most frequently used regimens in the last studied periods included lenalidomide-dexamethasone (RD; 14%), carfilzomib-RD (12%) and daratumumab-RD (10%) for 2nd line, and daratumumab-pomalidomide-dexamethasone (11%) and daratumumab-RD (10%) for 3rd line. Median time to next treatment from 2nd line therapy has improved from 10.4 months (95% CI 8.4–12.4) to 16.6 months (95% CI 13.3–20.3; p < 0.001). The median overall survival from 1st relapse increased from 30.9 months (95% CI 26.8–183.0) to 65.8 months (95% CI 50.7–72.8; p < 0.001). Over the last two decades more patients were treated with newer agents and triplets for relapsed MM. The landscape of regimens has become more diverse, and the survival after 1st relapse is continually improving.

Abstract Almost all patients with multiple myeloma (MM) eventually relapse, either asymptomatically or with end-organ damage. However, it remains unclear whether initiating therapy at the time of biochemical progression (BP) improves the outcomes compared with initiating therapy at the clinical progression (CP) stage. Here, we retrospectively assessed 1347 patients with relapsed MM. Most progressions were BP (60.4%); 39.6% had CP. The most prevalent symptoms at relapse were new or evolving bone disease (80.9%), anemia (38.0%), and renal failure (12.7%). Patients with BP had longer median time from second-line treatment to the next treatment compared with patients who had CP (17.0 vs 9.6 months; P &lt; .001) as well as longer median overall survival from first relapse (59.4 vs 26.2 months; P &lt; .001). Male sex (odds ratio [OR], 1.49; 95% confidence interval [CI], 1.02-2.18; P = .04), plasma cell labeling index ≥2% (OR, 1.58; 95% CI, 1.02-2.45; P = .04), and extramedullary disease at diagnosis (OR, 1.84; 95% CI, 1.08-3.13; P = .03) were associated with higher risk of CP, whereas very good partial remission or better had decreased risk of CP (OR, 0.62; 95% CI, 0.43-0.91; P = .02). To conclude, patients with CP have inferior postprogression outcomes compared with patients who have BP. Patients with deeper response to first-line therapy are less likely to develop CP. The presence of a specific CRAB (C, hypercalcemia; R, renal failure; A, anemia; B, bone disease) symptom at diagnosis predicts for the development of similar CRAB symptoms at relapse.

Abstract Mass-spectrometry (MS) assays detect lower levels of monoclonal proteins and result in earlier detection of monoclonal gammopathy of undetermined significance (MGUS). We examined heavy chain MGUS prevalence using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS among 3 risk groups, ages 50 or older: 327 African Americans (AA) and 1223 European Americans (EA) from a clinical biobank and 1093 unaffected first-degree relatives (FDR) of patients with hematologic disorders. Age- and sex-adjusted prevalence rates were directly standardized to 2010 United States population. Prevalence ratios were estimated for comparisons of AA and FDR to the EA group using the Poisson distribution. Results were also compared with population-based prevalence using conventional gel-based methods. Risk groups had similar sex and age distributions. MALDI-TOF MGUS prevalence was higher in the AA (16.5% [95% confidence interval (CI), 12.2%, 20.8%]) and FDR (18.3% [95% CI, 16.6%, 21.6%]) than in EA (10.8% [95% CI, 8.8%, 12.7%]), translating to prevalence ratios of 1.73 (95% CI, 1.31, 2.29) and 1.90 (95% CI, 1.55, 2.34), respectively. MALDI-TOF EA prevalence was over threefold higher than conventional estimates but showed similar age trends. Thus, the MALDI-TOF assay found greater numbers with MGUS but similar relative differences by race, family history, and age as prior studies.

Abstract The adage for smoldering myeloma (SMM) has been to observe without treatment, until criteria for active multiple myeloma were satisfied. Definitions and risk stratification models have become more sophisticated, with prognostication tailored to include high-risk cytogenetics as per the most recent International Myeloma Working Group 2020 risk model. Moreover, progress in defining genomic evolution and changes in the bone marrow microenvironment through the monoclonal continuum have given insight into the complexities underlying the different patterns of progression observed in SMM. Given recent data showing improved progression-free survival with early intervention in high-risk SMM, the current dilemma is focused on how these patients should be treated. This case-based article maps the significant advancements made in the diagnosis and risk stratification of SMM. Data from landmark clinical trials will also be discussed, and ongoing trials are summarized. Ultimately, we outline our approach to SMM and hope to impart to the reader a sound concept of the current clinical management of SMM.

Abstract INTRODUCTION POEMS syndrome is a paraneoplastic disorder that results in multi-organ disease, and Vascular endothelial growth factor (VEGF) is associated with disease activity. There is evidence that the cytokine Interleukin- 6 (IL-6) stimulates VEGF production in several cancer cell lines. It has also been suggested that patients with POEMS syndrome experience symptoms improvement when IL-6 levels are low. Our study aims to understand the role of IL-6 and whether it is a contributor to disease activity in POEMS syndrome. METHODS We conducted a retrospective study of patients (pts) seen at Mayo Clinic within 1 year of diagnosis for POEMS syndrome with an IL-6 level within 3 months of diagnosis between 01/01/2011-05/31/2021 were included. Our database comprised 358 pts,7 were excluded because did not have official diagnosis of POEMS syndrome. Two hundred and ninety-nine pts did not have IL-6 testing within 90 days of diagnosis and were excluded. Clinical data was abstracted from our electronic medical record. Descriptive statistics were used for IL-6 levels. The majority of IL-6 laboratory testing for pts utilized the same reference range. A minority of pts had alternate reference ranges; thus, all IL-6 values and reference ranges were fold-corrected to have a unified reference to determine elevation in IL-6. High IL-6 was considered any value above the normal range, also analyzed pts in quartiles and deciles. Hematologic, VEGF and PET response criteria were utilized to group pts into responders or non-responders. Time to progression (TTP) and overall survival (OS) was calculated using the Kaplan Meier method. Differences between curves were by log rank. Statistical analysis was conducted via JMP software package (SAS, Cary, NC, USA). Univariate analysis was done to determine the prognostic value of IL-6. Statistical significance is considered with p-values &lt;0.05. RESULTS 52 patients from among 352 met criteria and were included for analysis. Twenty-one patients (40%) had elevated IL-6 levels (IQR 5.67, 22.6) at the time of diagnosis. The fold elevation about normal was typically not very high, with a median of 3.1-fold elevation (IQR 1.3, 4.4; and range 1.0, 8.3). The percentage of males in the high IL-6 versus the normal Il-6 group were 90% versus 65%, p=0.03. Compared to normal IL-6, those with elevated IL-6 values had more instances of hepatomegaly (43% vs 16%, p=0.03), ascites (28% vs 6%, p=0 .04), abnormal DLCO (26% vs 3%, p=0.03), mixed bone lesions (57% vs 29%, p= 0.04), and lower serum albumin (range 2.3-3.5 vs 2.5-4.5 g/dL, p=0.0008).There was a trend for lower VEGF values among the high IL-6 group, but this did not meet statistical significance (median 250 vs 438 pg/mL). There was no significant difference in the time to progression between pts with high versus normal IL-6 levels (HR 1.36; p=0.456). Overall survival was significantly longer in pts with normal IL-6 compared to pts with high IL-6 levels (Median OS 67.4 vs 47.8 months, p=0.02). Forty-two pts were evaluated for VEGF response after treatment; there was a significant improvement in time to progression (85.5 vs 14.9 months, p=0.03) in pts who were VEGF responders. Among pts evaluable for a hematologic response (n=15), time to progression in pts with baseline high IL6 was longer in hematologic responders compared to non-responders (p=0.02). Conclusion Although OS was longer for pts with normal IL-6, elevated IL-6 at the time of diagnosis does not prevent pts from achieving disease remission. The study demonstrates that response to treatment rather than interleukin-6 levels in pts with POEMS syndrome is more prognostic. This study is an important initial step into understanding the utility of IL-6 in POEMS syndrome. Figure 1 Figure 1. Disclosures Gertz: Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Aurora Biopharma: Other: Stock option; Ionis Pharmaceuticals: Other: Advisory Board; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria. Kumar: Oncopeptides: Consultancy; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Merck: Research Funding; Antengene: Consultancy, Honoraria; Tenebio: Research Funding; Novartis: Research Funding; Roche-Genentech: Consultancy, Research Funding; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Dingli: GSK: Consultancy; Novartis: Research Funding; Janssen: Consultancy; Sanofi: Consultancy; Apellis: Consultancy; Alexion: Consultancy. Lin: Janssen: Consultancy, Research Funding; Merck: Research Funding; Novartis: Consultancy; Legend: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Vineti: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding; Sorrento: Consultancy; Gamida Cell: Consultancy; Takeda: Research Funding. Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Dispenzieri: Pfizer: Research Funding; Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Alnylam: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding.

Abstract Introduction: Smoldering multiple myeloma (SMM) prognostication models routinely used in clinical practice were developed for use at diagnosis. However, retrospective studies have shown that in SMM patients the risk of progression to multiple myeloma (MM) decreases over time. Therefore, this study assessed whether the Mayo 2018 and IMWG 2020 scores could be used dynamically to risk stratify patients post-diagnosis, and whether they could identify SMM patients with evolving disease. Methods: We retrospectively studied 704 SMM patients diagnosed between January 2000 to January 2020. Patients with a baseline FLCr ≥100 and involved FLC ≥10 mg/dL or baseline bone marrow plasma cells ≥60% were excluded. We collected serial laboratory data and available pathology data and re-applied the Mayo 2018 and IMWG 2020 SMM risk stratification models at annual landmark timepoints up to 5 years post SMM diagnosis. Survival analyses were performed using the Kaplan-Meier method. Time to progression (TTP) was defined as time from diagnosis or landmark timepoint to treatment initiation for MM or systemic AL amyloidosis. Cox proportional hazards models were used to estimate hazard ratios. A two-sided p-value &lt;0.05 was considered statistically significant. Results: At SMM diagnosis, 271 (38%) patients were low risk, 228 (32%) were intermediate risk, and 205 (29%) were high risk per the Mayo 2018 score. Applying the IMWG 2020 score at diagnosis, 90 (34%) of patients were low risk, 111 (42%) were low-intermediate risk, 54 (21%) were intermediate risk, and 9 (3%) were high risk. The Mayo 2018 and IMWG 2020 risk scores was re-assessed annually post-diagnosis in patients without progression (respective sample sizes: n=430 and n=197 at year 1 landmark, n=326 and n=143 at year 2 landmark, n=260 and n=106 at year 3 landmark, n=203 and n=73 patients at year 4 landmark). The Mayo 2018 and IMWG 2020 models reliably stratified patients based on progression risk post diagnosis (as shown in Figure 1 and Figure 2, respectively). As shown in Figure 1, if only diagnostic values were used in risk categorization with the Mayo 2018 model, the TTP between risk categories became less distinct over time. However, when follow-up laboratory values were used to re-stratify patients, the TTP between risk categories was more consistent over time. The respective 2-year progression risk in Mayo 2018 high-risk versus IMWG 2020 intermediate-high risk patients was 51% versus 62% at the 1-year landmark, 60% versus 65% at the 2-year landmark, 47% versus 62% at the 3-year landmark, and 47% versus 45% at the 4-year landmark. To assess the prognostic significance of an increase in SMM risk category, we stratified patients based on whether the SMM risk category at follow-up had increased versus was stable or decreased compared to the baseline SMM risk stratification. We found that patients evolving to a risk category during follow up consistently had an increased risk of progression compared to patients with a stable/decreased risk categorization using both the Mayo 2018 (HR 3.34, 95% CI 2.04-5.48, p&lt;0.001 at 2-year landmark; HR 3.41, 95% CI 2.05-5.68, p&lt;0.001 at 3-year landmark; HR 2.69, 95% CI 1.34-5.38, p=0.005 at 4-year landmark) and IMWG 2020 (HR 2.32, 95% CI 1.42-3.77, p&lt;0.001 at 1-year landmark; HR 3.10, 95% CI 1.69-5.70, p&lt;0.001 at 2-year landmark; HR 2.50, 95% CI 1.30-4.78, p=0.004 at 3-year landmark; HR 2.26, 95% CI 0.91-5.60, p=0.072 at 4-year landmark) risk models. However, patients categorized as Mayo 2018 high-risk at follow-up had a similar risk of progression regardless of whether the baseline risk categorization was low-intermediate versus high-risk (HR 0.87, 95% CI 0.51-1.48, p=0.606 at 2-year landmark; HR 1.01, 95% CI 0.59-1.73, p=0.972 at 3-year landmark; HR 0.75, 95% CI 0.34-1.65, p=0.467 at 4-year landmark). Conclusions: Our findings support the use of the Mayo 2018 and IMWG 2020 scores post-diagnosis. We showed that patients migrating to a higher risk category have an increased risk of progression. This suggests that if patients evolve to a high-risk score during follow-up, they should be considered for an early intervention treatment approach. Figure 1 Figure 1. Disclosures Kapoor: Sanofi: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Karyopharm: Consultancy; Cellectar: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Dispenzieri: Pfizer: Research Funding; Janssen: Consultancy, Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy. Gertz: Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Ionis Pharmaceuticals: Other: Advisory Board. Dingli: Janssen: Consultancy; Sanofi: Consultancy; Apellis: Consultancy; Novartis: Research Funding; Alexion: Consultancy; GSK: Consultancy. Kumar: Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Novartis: Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Bluebird Bio: Consultancy; Roche-Genentech: Consultancy, Research Funding; Merck: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Antengene: Consultancy, Honoraria; Oncopeptides: Consultancy; Beigene: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Abstract Background Multiple Myeloma (MM) remains incurable with current approaches and eventually relapses in nearly all patients. At relapse, patients may present with increasing serum and/or urine monoclonal (M) protein or with clinical features suggestive of progression. The outcomes of different progression patterns need to be better understood to provide insight about the optimal time to intervene with salvage therapy. This study aimed to describe the prevalence and outcome of biochemical (BP) versus clinical progression (CP) in a real-world setting. Methods We retrospectively assessed 1347 relapsed MM patients seen at Mayo Clinic between February 2001 and December 2018. CP was defined as per IMWG criteria (increase ≥50% in size or new plasmacytomas/bone lesions, hypercalcemia ≥11.5 mg/dl, decrease in hemoglobin ≥2 g/dl or to ≤10 g/dl, rise in serum creatinine ≥2g/dl, hyperviscosity), while BP was defined as increase in serum or urine M protein leading to initiation of a new line of therapy without meeting criteria for CP. Aggressive relapse was defined as new extramedullary disease (EMD), plasma cell leukemia or hyperviscosity requiring plasmapheresis. The overall survival (OS) was defined as the time from 1 st relapse to last follow-up or death. Time to next treatment (TTNT) was defined as the time between initiation of 2 nd and 3 rd line therapy. Results Prevalence of different patterns of relapse is presented in Table 1. The majority of progressions were BP (60.4%); among the CP (39.6%), the most common presentation was a new bone lesion. Similar proportions of BP and CP patients were diagnosed before 2013 (70% and 73%; p=0.2). The median time from diagnosis to 1 st relapse was 22.8 months (range, 0.4-154.7) and was shorter in the CP group in comparison to BP (20.8 [range, 1.0-152.1] vs 23.7 [range, 0.4-154.7] months, p=0.001). With the exception of ISS stage, patients in the CP group had higher risk features at MM diagnosis including: high-risk (HR) FISH ([4;14], t[14;16], t[14;20], deletion 17p or p53 mutation; 29% vs 20%, p=0.01); elevated LDH (23% vs 17%, p=0.03); and EMD (19% vs 10%, p&lt;0.001). CP patients more often had non-secretory disease at baseline (6% vs 2%, p&lt;0.001). At 1 st line, patients with eventual CP were less likely to have received novel agents (78% vs 85%, p&lt;0.001), upfront autologous stem cell transplantation (ASCT, 43% vs 51%, p=0.004), and lenalidomide-based maintenance (11% vs 16%, p=0.01). While patients in the CP group were less likely to have achieved very good partial remission (VGPR) or better to the 1 st line therapy (53% vs 60%, p=0.01), the percentage of patients who achieved CR was similar between the groups (22% vs 24%, p=0.4). Relapse while on primary treatment/maintenance was more prevalent in the CP (46% vs 40%, p=0.04). On multivariable logistic regression model male sex, plasma cell labeling index (PCLI) ≥2% and EMD at diagnosis were associated with higher risk of CP, whereas achieving VGPR or better after 1 st line treatment was associated with decreased risk of CP. Patients with CP had shorter median TTNT from 2 nd line therapy compared to BP (9.6 vs 17.0 months, p&lt;0.001) as well as shorter median OS from 1 st relapse (26.2 vs 59.4 months, p&lt;0.001; Figure 1). Amongst patients with CP, those presenting with typical "aggressive" versus "CRAB" features at relapse had a significantly shorter median TTNT (6.0 vs 11.0 months, p&lt;0.001) and OS (17.2 vs 28.1 months, p&lt;0.001). Using a multivariable Cox proportional hazard model, CP (vs BP) was a predictor of shorter TTNT from 2 nd line therapy (HR 1.40, 95% CI 1.20-1.62, p&lt;0.001), along with ISS stage III, HR FISH at diagnosis and relapse while on primary treatment/maintenance, whereas the use of upfront ASCT was a predictor of longer TTNT from 2 nd line therapy. CP was also a predictor of shorter OS from 1 st relapse (HR 1.53, 95% CI 1.29-1.81, p&lt;0.001) along with age &gt;65 years, male sex, ISS stage III, HR FISH at diagnosis, EMD at diagnosis and relapse while on primary treatment/maintenance. Conclusions Patients with clinical features at relapse have a worse prognosis after 1 st relapse than patients who relapsed solely biochemically. Approximately half of CP presented while on active treatment, which suggests that even patients monitored closely may develop CRAB features at relapse. Factors that help predict the occurrence of CP include male sex, PCLI ≥2% and EMD at diagnosis. Patients with deeper response to 1 st line treatment are less likely to develop CP. Figure 1 Figure 1. Disclosures Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Dispenzieri: Sorrento Therapeutics: Consultancy; Pfizer: Research Funding; Oncopeptides: Consultancy; Janssen: Consultancy, Research Funding; Takeda: Research Funding; Alnylam: Research Funding. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Aurora Biopharma: Other: Stock option; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy. Dingli: Apellis: Consultancy; Sanofi: Consultancy; GSK: Consultancy; Novartis: Research Funding; Alexion: Consultancy; Janssen: Consultancy. Kumar: Antengene: Consultancy, Honoraria; Sanofi: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Tenebio: Research Funding; Beigene: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Carsgen: Research Funding; Oncopeptides: Consultancy; Roche-Genentech: Consultancy, Research Funding; Novartis: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding.

Abstract Background Multiple myeloma (MM) is an incurable disease, and its prognosis is largely influenced by clinicopathological features, response to therapy, and relapse characteristics. Despite novel agents and the attempts to individualize treatment strategies based on baseline risk stratification, significant variations in progression-free survivals (PFS) and overall survivals (OS) are observed between patients. We examined the outcomes of MM patients stratified according to timing of first relapse into early (&lt;2 years) and late (&gt;5 years). Methods We retrospectively assessed 1441 MM patients seen at Mayo Clinic between 2003 and 2018. Patients were 18 years or older and had at least one disease relapse that required an additional line of treatment. The study cohort was divided into three groups based on time of first relapse: early relapse (&lt;2 years from diagnosis), relapse between 2 to 5 years from diagnosis, and late relapse (&gt;5 years from diagnosis). The independent predictors of early/late relapse were identified using a forward stepwise multivariate logistic regression. Odds ratios in multivariate models were adjusted for age and sex. Results Early relapse has been recognized in 758 patients (52.6%), relapse between 2-5 years in 561 patients (38.9%), late relapse in 122 patients (8.5%). Six patients had a PFS &gt;10 years. In comparison to patients with late relapse, patients with early relapse were older (median 63 vs 61 years, p=0.04), more frequently ISS stage III (40% vs 20%, p&lt;0.001) had higher bone marrow plasma cell infiltration (median 60% vs 40%, p&lt;0.001), and were more likely to have high-risk (HR) FISH (defined as translocation t[4;14], t[14;16], t[14;20], deletion 17p or p53 mutation; 28% vs 11%, p&lt;0.001). At diagnosis, early relapse group more often presented with anemia (35% vs 21%, p=0.004), hypercalcemia (15% vs 5%, p&lt;0.001), renal insufficiency (19% vs 5%, p&lt;0.001) and higher serum beta-2-microglobulin (median 4.4 vs 3.4 mg/l, p&lt;0.001). In terms of first line treatment, novel agents use was higher in early relapse group in comparison to late relapse group (82% vs 72%, p=0.007). Early relapse patients more often received PI-based therapy (30% vs 10%, p&lt;0.001) or PI+IMID-based therapy (22% vs 12%, p=0.01), whereas late relapse patients received more often IMID-based therapy (63% vs 37%, p&lt;0.001). No differences in the maintenance therapy were observed. Early relapse patients were less frequently treated with upfront autologous stem cell transplantation (ASCT, 35% vs 60%, p&lt;0.001). Progression on active treatment/maintenance was observed more often in the early relapse group (55% vs 18%, p&lt;0.001). On multivariable logistic regression model early relapse (vs all remaining patients) was predicted by HR cytogenetic features (odds ratio [OR] 3.06, 95% confidence interval [CI] 1.71-5.46, p&lt;0.001), non-IgG isotype disease (OR 2.17, 95% CI 1.33-3.54, p=0.02), a non-ASCT pathway (OR 2.78, 95% CI 1.71-4.52, p&lt;0.01), and by achieving less than a very good partial remission (VGPR; OR 3.23, 95% CI 1.96-5.35, p&lt;0.01). The only factor associated with decreased chances of late relapse (vs all remaining patients) on multivariate logistic regression model was the presence of HR FISH features (OR 0.18, 95% CI 0.04-0.82, p=0.03). Median PFS from first relapse for the whole population was 13.9 months (95% CI 12.9-15.1), median OS from first relapse - 44.6 months (95% CI 41.7-183.0). Early relapse group exhibited worse median PFS and OS from first relapse (median PFS 9.1 months; median OS 26.6 months) than patients who relapsed 2-5 years after diagnosis (median PFS 18.5 months; OS 71.9 months), or late relapse group (median PFS 31.6 months; median OS 87.8 months; p&lt;0.001) (Figure 1). Conclusions Early relapse (&lt;2 years) is an indicator for shorter duration of response to subsequent treatments, and worse OS. Treatment with upfront ASCT and achieving VGPR or better after first line therapy lower the risk of early relapse. The only parameter that is predictive for both early and late relapse is HR FISH features. Although factors that predict worse survival in MM are well defined, further studies are needed to identify predictors of a more indolent disease course so that future therapeutic approaches can be tailored to each individual. Figure 1 Figure 1. Disclosures Kapoor: AbbVie: Research Funding; Glaxo SmithKline: Research Funding; Takeda: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding. Dispenzieri: Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Pfizer: Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Gertz: Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Ionis Pharmaceuticals: Other: Advisory Board; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria. Dingli: Alexion: Consultancy; Janssen: Consultancy; Novartis: Research Funding; GSK: Consultancy; Sanofi: Consultancy; Apellis: Consultancy. Kumar: Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Tenebio: Research Funding; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; Oncopeptides: Consultancy; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Antengene: Consultancy, Honoraria; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.