Diagnosis Of Smoldering Multiple Myeloma Research Articles

Real-world characteristics and outcomes of patients with high-risk and non-high-risk smoldering multiple myeloma using the Flatiron Health database

This study aimed to provide real-world evidence on progression risk in patients with high-risk smoldering multiple myeloma (SMM). This retrospective, observational study leveraged data from the Flatiron Health database. Eligible patients had SMM and relevant measures to apply Mayo 2018, International Myeloma Working Group (IMWG) 2020, and AQUILA trial risk criteria. Time to progression to active MM (TTP), progression or death (PFS), and death or progression on first-line MM therapy (PFS2) were evaluated using Kaplan–Meier methods and multivariate Cox regression models adjusted for age, Charlson Comorbidity Index, and time from SMM diagnosis to risk classification date. Across the three risk models (Mayo 2018, IMWG 2020, and AQUILA trial), high-risk patients with SMM had 3.0–4.0 times the risk of TTP, 2.1–3.5 times the risk of PFS, and 1.7–3.2 times the risk of PFS2 versus non-high-risk patients (p < 0.001 for all comparisons). Similar results were observed when patients with early treatment, early progression, and/or bone disease were excluded. This study demonstrates that high-risk patients with SMM have worse prognoses than non-high-risk patients, regardless of the criteria used, and highlights a need for early intervention testing.

Exploring the role of the combination of FDG-PET plus whole body MRI for staging patients with high-risk smoldering myeloma: A prospective trial.

7569 Background: According to IMWG criteria, Smoldering Multiple Myeloma (SMM) is an asymptomatic stage characterized by M-spike &lt; 3 g/dl serum and/or bone marrow plasma cells infiltration between 10-59% in absence of myeloma-defining events and organ damage. In SMM setting, it is really important to differntiate high risk SMM (HR-SMM), in which treatment could be available thanks to clinical trials. 2016 IMWG criteria state that detection of bone lesions is mandatory for diagnosis of multiple myeloma and essential for diagnosis of SMM. It is really important to clarify in SMM the best imaging analysis in order to perform a correct diagnosis, and particularly it is necessary to define if the combination of FDG-PET/TC and WB-MRI could improve the assessment of lytic lesions and so the discrimination between high risk SMM and symptomatic MM. Methods: In our Institution we conducted a prospective trial, based on integrated new generation imaging, aiming to improve patients’ stadiation and to define its prognostic implications. From January 2021 to January 2024, we performed a prospective trial enrolling 26 consecutive newly diagnosed high risk SMM, according to IMWG, in which WB-MRI was performed according to MY-RADS criteria in combination with FDG PET-CT (median age 56; range 36-85). Results: Our comparison between WB-MRI and FDG PET-CT, showed a discordance between the two imaging modalities in 4/26 (15%) cases. In particular, in 3/26 (12%) cases WB-MRI showed bone lesions that have lead to symptomatic MM diagnosis according to IMWG criteria, while PET-CT was negative. In one case, PET-CT showed a diffuse uptake, not diagnostic for MM, while WB-MRI was negative. WB-MRI showed a 100% of accuracy in detecting SMM and MM. Therefore, WB-MRI has lead to a modification of the prognosis and treatment approach (observation in SMM vs treatment in symptomatic MM) in 3/26 patients (11%) (i.e. Figure 1, with DWI of C2 lesion). Furthermore, in 5/23 (22%) cases of confirmed SMM WB-MRI showed a slight diffuse alteration pattern of bone marrow without any overt lytic bone lesion, which could be a potential prognostic evidence. Conclusions: Our results support a fundamental role of WB-MRI in combination with FDG PET/CT in the stadiation of patients with newly diagnosed high risk SMM, which could modify prognosis and treatment, improving the differentiation with symptomatic MM. In particular, combination of WB-MRI plus FDG PET/CT could be more accurate in the detection of bone lesions than FDG PET/CT alone, being able to anticipate symptomatic MM diagnosis and consequently its treatment. Moreover, a diffuse pattern of marrow involvement could be detected in some HR-SMM patients without any overt lytic lesions: it is questionable if this group of patients is associated with a rapid progression in lytic lesions and so in symptomatic MM diagnosis. Prospective data on evolution of these patients are pending.

Risk Stratification Models Overestimate Progression Risk in Contemporary Patients with Smoldering Multiple Myeloma (SMM)

Introduction: SMM is an asymptomatic precursor of multiple myeloma (MM), affecting ~1 in 200 people aged &amp;gt;40 years. Historically, risk of progression from SMM to MM was 10% per year in the first 5 years. However, since then, the definition and characteristics of the SMM patient population have changed substantially. First, IMWG diagnostic criteria for MM in 2014 changed to include biomarker-only myeloma (SLiM), reclassifying asymptomatic patients previously considered SMM. Second, incorporation of advanced imaging (CT, PET/CT, MRI) identified bone disease with greater sensitivity. Hence, we hypothesized that in the contemporary era, the risk of progression from SMM to MM would be markedly lower than historically. Methods: We performed a retrospective cohort study of consecutive patients with SMM at Columbia University Irving Medical Center from 2014-2022 and observed without therapeutic intervention. Our primary objective was to measure cumulative incidence of progression to MM and to characterize progression events. We also calculated predicted 2-year risk of progression by different risk-stratification models (Mayo 20/2/20, PANGEA, IMWG SMM model) in our cohort. Results: 102 consecutive patients with SMM were included. Median year of diagnosis was 2019 (range, 2014-2022). Baseline clinical and demographic characteristics of the cohort are shown in Table 1. The three most common scenarios that led to SMM diagnosis were workup of anemia/cytopenias(s) (n=22; 21.8%), incidental protein gap or elevated immunoglobulin level (n=20; 19.8%), and renal dysfunction (n=16; 15.8%). The racial/ethnic makeup of our study cohort was 38% Hispanic/Latino, 38% Non-Hispanic White, 19% Black/African-American, and 5% Asian. Bone disease was ruled out by advanced imaging (whole body CT, PET/CT, WB-MRI, and/or MRI spine+ pelvis) in 81.2% of patients. The most common abnormality on FISH was hyperdiploidy (39.2%), followed by t(11;14) (22.1%), with ≥1 high-risk cytogenetic abnormality (HRCA) in 35% of patients. Median follow-up was 45 months (95% CI, 34-52). 22/102 patients (21.6%) progressed to symptomatic plasma cell dyscrasia: CRAB myeloma in 18, SLiM myeloma in 1, systemic AL amyloidosis in 3 patients. The cumulative incidence of progression to MM (CRAB/SLiM) at 1, 2, 3, and 4 years from SMM diagnosis was 3.1% (95% CI, 0.99-9.1), 7.7% (95% CI, 3.7-15.3), 13.9% (95% CI, 8.1-23.1), and 17.1% (95% CI, 10.3-27.1) respectively [Figure 1]. Notably, presence of HRCA by FISH had a dose-dependent increase in risk of progression, with the 2-year risk being 75% (95% CI, 24-97%) in patients with ≥2 HRCA vs 13.0% (95% CI, 5.9-26.3) in those with 0-1 HRCA respectively ( p=0.0049). Among 18 patients who progressed to CRAB myeloma, the myeloma-defining event/s (MDEs) were anemia in 11, anemia + bone disease in 4, and bone disease in 3 patients. Among patients with a bone disease MDE, 4/7 had &amp;gt;1 lytic lesions on imaging and 3 had vertebral compression fracture(s). No patient had renal insufficiency or hypercalcemia as MDE. The sole patient with SLiM had a serum free light chain ratio&amp;gt;100 as the only MDE. 13/102 patients (12.75%) died, with 4/13 deaths attributed to myeloma after disease progression. The predicted median 2-year risk of progression to MM with different risk-stratification models were as follows: PANGEA with Bone Marrow (BM): 5.75% (range, 1.2-42); PANGEA without BM: 4.6% (0.7-26.6); Mayo 20/2/20: 9.7% (9.7-47.4); IMWG SMM: 26% (3.8-73). Figure 2 shows Sankey diagram of predicted risk tertiles for patients at SMM diagnosis by different models. Notably, a substantial proportion of high-risk patients by 20/2/20, who are currently considered for therapeutic intervention, were re-assigned to intermediate risk (2-year risk of progression 8.1-20%) by PANGEA-BM. Conclusion: The risk of progression to MM among this cohort of contemporary patients with SMM is &amp;lt;5% per year for the 1 st 4 years, which is substantially lower than the historical rate of 10% per year. Morbid progression such as renal failure or fractures are very infrequent, with anemia being the most common MDE. Prospective studies testing active surveillance strategies are needed in contemporary SMM cohorts to determine the optimal approach to these patients and ensure balancing of potential risks and benefits of treatment.

Clinical characteristics and outcomes in risk-stratified patients with smoldering multiple myeloma: data from the Czech Republic Registry of Monoclonal Gammopathies

Smoldering multiple myeloma (SMM) is an asymptomatic precursor to active multiple myeloma (MM). The aim of this study was to report clinical characteristics and outcomes of patients with SMM stratified based on their risk of progression to MM using the Mayo 20/2/20 criteria. Data were leveraged from the Czech Myeloma Group Registry of Monoclonal Gammopathies (RMG). Key outcomes included progression-free survival from SMM diagnosis to active MM diagnosis or death (PFS), progression-free survival from SMM diagnosis to progression on first line (1 L) MM treatment or death (PFS2), and overall survival (OS). Of 498 patients, 174 (34.9%) were classified as high risk and 324 (65.1%) as non–high risk. Median follow-up was approximately 65 months. During follow-up, more patients in the high-risk vs non–high-risk group received 1 L MM treatment (76.4% vs 46.6%, p < 0.001). PFS, PFS2, and OS were significantly shorter in high-risk vs non–high-risk patients (13.2 vs 56.6 months, p < 0.001; 49.9 vs 84.9 months, p < 0.001; 93.2 vs 131.1 months, p = 0.012, respectively). The results of this study add to the growing body of evidence that patients with high-risk vs non–high-risk SMM have significantly worse outcomes, including OS.

Presence of hyperdiploidy and history of tobacco use in African American patients with SMM.

8062 Background: Smoldering multiple myeloma (SMM) has a clinically variable course in progression to active myeloma (MM). Accurate risk stratification is essential in identifying which patients may benefit from early therapeutic intervention. Current models do not account for the potential impact of race on risk of progression to SMM. Here, we seek to identify independent risk factors for progression in African American (AA) versus white patients in a real-world single institutional database of SMM patients. Methods: We retrospectively identified 224 patients (pts) with untreated SMM from 2007 to 2021 treated at our institution. Patient demographics and disease characteristics were obtained from our IRB-approved myeloma database. TTP was defined as the time from diagnosis of SMM to diagnosis of active MM, estimated by Kaplan-Meier and compared by log-rank test. Univariate analyses were performed using Cox proportional hazard models for TTP. Results: A total of 224 pts (AA 35%, white 47%, other/unknown 17%) were identified with median age 62y (range 32-82). Median follow-up was 4.3y in Whites and 5y in AA pts. Notable characteristics include M/F 45%/54%, IgG/IgA/FLC 76%/17%/6%, 30% current/past smoker (median 15 pack-years), 12% alcohol use (≥10 drinks/wk), 45% with BMI &gt; 30. Multiple cytogenetic abnormalities were defined as presence of ≥2 of the following: t(4;14), t(14;16), gain(1q21), del(1p), del(13), or del(17p). The median TTP (mTTP) was 6.8 [95% CI (3.7, 8.2)] years in whites and 5.6 [95% CI (4.6, 11.8)] years in AA. On univariate analysis, M-spike &gt; 1.5, involved K/L ratio &gt; 12, and bone marrow PC &gt; 20% were associated with increased risk of progression for both AA and whites (all p &lt; 0.05). As expected, gain of 1q21 was associated with increased risk of progression for both groups, though more pronounced in AA (HR 2.94, p = 0.025) versus whites (HR 2.33, p = 0.013). Hyperdiploidy was associated with shorter mTTP in AA (HR 3.03, p = 0.004) compared to whites (HR 1.39, p = 0.3). Multiple cytogenetic abnormalities was associated with shorter mTTP in whites (HR 2.63, p = 0.004) but was not statistically significant in AA (HR 2.63, p = 0.104). Interestingly, tobacco use was associated with shorter mTTP in Blacks (HR 2.94, p = 0.005) but not in whites (HR 0.96, p = 0.85). Conclusions: Understanding the potential impact of racial background on progression from SMM to MM is critical in the appropriate management of all patients with SMM. In this database, with a large proportion of AA patients, hyperdiploidy and +1q portend high risk of progression in AA patients. Further study is needed to better classify these potential differences to ensure risk stratification models are applicable to all patients.

Evolving Pattern Improves the IMWG 2/20/20 Classification for Patients with Smoldering Multiple Myeloma

Introduction: Smoldering multiple myeloma (SMM) is a monoclonal gammopathy defined by the presence of an M-protein in serum ≥30 g/L and/or ≥500 mg/24h in urine and/or ≥10% of plasma cells in bone marrow, in the absence of CRAB symptoms or very high-risk criteria (SLiM). Multiple scales are available to stratify the risk of SMM progression. In clinical practice, the most used are the PETHEMA model and the 2/20/20 model established by the Mayo Clinic and validated by the International Myeloma Working Group (IMWG). These scales, in addition to providing prognostic information, allow us to guide patient follow-up and could support the start of treatment in high-risk patients. On the other hand, SMM can develop an evolving pattern, characterized by a progressive increase of the M-protein that is associated with a higher risk of progression to symptomatic multiple myeloma (MM). The objective of this study is to explore whether the incorporation of the evolving pattern to the IMWG score allows for a more accurate identification, particularly of high-risk patients. Materials and methods: Clinical records of patients diagnosed with SMM between 2011 and 2020 in a single hospital center, excluding those who met SLiM criteria, were reviewed. Progression to symptomatic MM was established according to the IMWG criteria. The evolving pattern was defined as the progressive increase of at least 10% or 25% in the M-protein size within the first 12 months from diagnosis when baseline M-protein was ≥30 g/L or <30 g/L, respectively (Ravi et al, Blood Cancer J 2016, Fernandez de Larrea et al, Leukemia 2018). The evolving type was analyzed as a time-dependent covariate. Results: Ninety three patients were initially included in the study; however, 10 patients were finally excluded: 9 for presenting SLiM criteria (1 with >60% bone marrow plasma cells, 9 with a free light chain ratio >100) and 1 for missing data. Median follow-up was 3.2 years (IQR 2-5) with a rate of progression (RP) at 2 and 4 years of 20% (95%CI 12-30) and 33.7% (95%CI 23-46), respectively. Using IMWG risk stratification model, the 2-year RP was 3.3% (95%CI 0.5-21) in low-risk patients, 9.3% (95%CI 2-32) in intermediate-risk patients, and 54 % (95%CI 35-75) in high-risk patients. Regarding the evolving pattern, it was recognized in 25% of patients. Median time from SMM diagnosis and recognition of evolving type was 9 months (IQR 6-12). The RP at 2 and 4 years was 48% (95%CI 29-71) and 65% (95%CI 44-85) for evolving type. After adding the evolving classification to IMWG model, we created a new prognostic classification system that divides patients into three risk groups: low (IMWG low or intermediate risk and non-evolving pattern), intermediate (IMWG low or intermediate risk and evolving pattern, or high risk and non-evolving pattern) and high (IMWG high risk and evolving pattern), with a 2-year RP of 2.4% (95%CI 0.3-15), 20% (95%CI 9-43) and 88.9% (95%CI 61-99), respectively. The cumulative incidence of progression to MM for the three risk groups using the IMWG and the new Evolving-2/20/20 system is represented in Figure 1A, whereas in Figure 1B the reclassification of patients with the new Evolving-2/20/20 system is shown. Regarding the validation of this score, the area under the curve (AUC) of the new score was greater than that of the IMWG and that of the evolving score independently (2y-AUC PETHEMA 0.65, IMWG 0.83, Evolving 0.77, Evolving-2/20/20 0.89; P=0.02). In addition, concordance was superior with the new score Evolving-2/20/20 (C-index 0.93) compared with PETHEMA (0.73), IMWG (0.86) and evolving (0.85) by themselves. The specificity and the positive predictive value for detecting high-risk patients at 2 years with the new model was very high (98% and 88%, respectively) compared to the other risk stratification models (PETHEMA 59% and 27%; IMWG 83 and 52%; Evolving 83% and 49%, respectively). Decision curve analysis indicated that the score was clinically useful. Conclusions: The dynamic addition of the evolving pattern to the IMWG classification (Evolving-2/20/20 system) in patients with SMM, allows more precise risk stratification and the detection of those with very high risk of progression. These patients could benefit from more intensive follow-up and may be eligible for early treatment strategies. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

African American Race Is a Potential Favorable Biologic Factor That Impacts Clinical Outcome for Patients with Multiple Myeloma

Multiple myeloma (MM) remains an incurable malignancy characterized by plasma cells that are nurtured and proliferate within the permissive bone marrow milieu. It has a greater incidence in African Americans (AA) compared to whites (13.8 vs. 6.5/100,000). The five-year age adjusted mortality rate, according to SEER database, is greater in AA compared to white Pts (5.8 vs. 2.9/100,000), which is likely explained by a greater incidence in the AA population. However, recent reports have also shown that AAs with equal access to care have an even better survival than their white counterparts [Fiala et al. Cancer. 2017]. Conversely, results from the CoMMpass registry database showed that OS was shorter for AA compared with Whites (age-adjusted hazard ratio (HR) 1.7, 95% confidence interval 1.2-2.4, P = 0.003) [Derman et al. Blood Cancer J. 2020]. Here, we report the interplay of race and other dimensions of MM care using the National Cancer Database (NCDB). Methods: NCDB is the largest cancer database in the US including >70% of all newly diagnosed cancer patients. The International Classification of Diseases for Oncology (ICD-O) code of 9732 was used. OS was calculated from the date of MM diagnosis. Given that Smoldering MM (SMM) does not have specific ICD code, we defined patients who did not receive any treatment within 3 months after the diagnosis as SMM, similar to other authors (Ravindran et al. Blood Cancer J. 2016). Initiation of systemic treatment was considered as a surrogate of progression to symptomatic MM. Overall survival (OS) of SMM patients was calculated from initiation of systemic treatment after they progressed to MM, estimated by the Kaplan-Meier method, and compared with the log-rank test. Cumulative incidence of progression from SM to MM was calculated with death as a competing risk and compared with the Gray's test. Multivariable Cox and logistic regression analysis were performed to identify independent predictors of OS and progression to MM, respectively. Results: We identified 56,021 patients with MM and 11,485 with SMM between 2010 to 2014 in this database. Among MM patients, 42,836 (76%) were white and 11,255 (20%) self-identified as AA. For AA patients, there was a lower proportion of Medicare (46 vs. 56%), and private insurance (35 vs. 36%) and a higher percentage of Medicaid (11 vs. 5%) and uninsured Pts (6 vs. 3%) compared to Pts that self-identified as white. A larger proportion of AAs had a Charlson score ≥1 (30 vs. 24%, p<0.001). The percentage of Pts who underwent radiation was higher among whites compared to AA (23 vs 8%). However, unadjusted OS was greater for AA compared to white Pts, 55 vs. 48 months, respectively (P < 0.0001). Among SMM patients, 8,324 (72%) were white and 2,756 (24%) were AA. SMM was diagnosed in AA patients at a median of 3.7 years younger than in white patients. Similar socioeconomic disparities were observed in SMM as in MM cohort. The time from diagnosis of SMM to first therapy which is indicative of progression from SMM to MM is the same among AA and white (median time in days 136 vs 135 days, p=0.672) with comparable OS. Multivariable Cox and logistic regression analysis showed that lower age, AA race, Female gender, ASCT, living in a higher income area and having Medicare or Private insurance compared to no insurance were independent predictors for better OS in MM. Although other predictive factors persisted for patients with SMM, race did not reach statistical significance. Conclusion: Taken together, our results utilizing one of the largest available datasets in the US, reflect a similar outcome for AA and white patients with MM despite a clear disparity in healthcare access and SES. This finding might suggest a more favorable biology of the disease among AA Pts. The lower rate of radiation among AA is also an indirect measure of bone complications. AA enjoy less bone loss and fractures under physiologic and pathologic conditions. Further studies to elucidate the role of bony compartment of the MM microenvironment at the cellular and molecular levels might be able to explain this disparity and help advance a more personalized treatment options to improve outcomes. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

MM-219 Smoldering Multiple Myeloma: A Demographic and Survival Analysis of a Retrospective Cohort Study in a University Hospital of Buenos Aires

Smoldering multiple myeloma (SMM) is a heterogeneous asymptomatic precursor to multiple myeloma (MM). It is the intermediate stage between monoclonal gammopathy of undetermined significance (MGUS) and MM, where there is a subset of patients with an indolent disease and a subset with progressive disease. The Mayo Clinic published a risk stratification model to help to differentiate these patients into 3 groups. To describe the demographic features of patients with SMM treated at the Italian Hospital of Buenos Aires. Retrospective cohort study, between 01/2005 and 05/2022. Consecutive patients with a confirmed diagnosis of SMM were included. Patients were followed from diagnosis until death, progression or loss to follow-up. Thirty-nine patients with SMM were included, of whom 16 (41%) were men. The median age at diagnosis was 69 years (95% CI: 55-77). 25 (64%) had a previous MGUS; the median time to progression (TTP) from MGUS to SMM was 6.4 months. 19 (49%) of patients had progression to MM. Eight (20%) of patients died, 3 (37%) secondary to myeloma. The most common type of band was IgG kappa with 55%. The median of monoclonal band was 1.5 (CI: 1.2-2), the median of plasma cells in bone marrow biopsy was 15% (CI: 12-20), 29 patients (74.36%) presented evaluation of lytic lesions, 6 patients (15%) presented risk assessment by FISH, of which 2 were positive for del(17p). The median follow-up of the cohort was 92 months (95% CI: 72.4-127.2). The estimated median TTP for the entire cohort was 71 months (95% CI, 55-94). Eight (21%) patients presented a high risk of progression according to the Mayo clinic score. The median TTP according to the Mayo Clinic score was 44 months (CI: 27-62) for high-risk patients, 86.5 months (CI: 69-94) for intermediate-risk patients, and 75 months for low risk. Of the patients who presented del(17p) all progressed to myeloma during follow-up with a median TTP of 49 months (CI: 35-64). 1 patient entered the research protocol. Our cohort demonstrated characteristics similar to those published. Patients with high-risk Mayo score and del(17p) by FISH showed faster progression, which emphasizes the need to include them in research protocols.

S177: EVALUATING SERUM FREE LIGHT CHAIN RATIO AS A BIOMARKER FOR MULTIPLE MYELOMA

Background: In 2014, the definition of multiple myeloma (MM) was updated to include serum free light chain (FLC) ratio ≥100 as a myeloma defining biomarker, based on retrospective data indicating a 2-year progression rate of 80% and a median time to progression (TTP) of 12 months associated with this marker. As a result, patients previously diagnosed as smoldering MM (SMM), were considered to have MM requiring treatment if they had a FLC ratio ≥100. However, two recent studies have reported lower 2-year progression rates, 30-44%, and a longer median TTP of 40 months in patients with FLC ratio ≥100, raising concern about the FLC criteria. Aims: To assess the risk of progression in patients with SMM and a FLC ratio ≥100. Methods: We performed a retrospective analysis of patients diagnosed with SMM at Memorial Sloan Kettering Cancer Center between January 2000 and December 2017. Diagnosis of SMM and progression to active MM requiring therapy was defined according to the International Myeloma Working Group (IMWG) criteria at the time of diagnosis. Kaplan-Meier method was used to assess TTP and generate survival curves, with log-rank test for comparison between groups. Results: A total of 438 patients were included in the study, with a median follow-up time of 52 months. While all patients with FLC ≥100 (n=66) had elevated involved FLC levels, 35 (53%) had an involved FLC concentration >100 mg/L. Per current diagnostic criteria, we only included patients with an involved FLC concentration >100 mg/L in the FLC ratio ≥100 group and found a median TTP of 31 months (95% confidence interval [CI] 16-59 months) and a 2-year progression rate of 49% (CI 28-63%). In a sensitivity analysis including all 66 cases with FLC ratio ≥100 (independent of involved FLC concentration), we found the median TTP to be 41 months (CI 30-72 months), compared to 101 months for those with a FLC ratio <100 (CI 78-127 months; p<0.0001). Furthermore, the risk of progression within 2 years was 35% (CI 22-46%) compared to 18% (CI 14-23%; p<0.0001) for those with a FLC ratio <100. Of note, 22 patients with a FLC ratio ≥100 were monitored expectantly for >4 years, among whom 12 patients had involved FLC levels >100 mg/L. Ten patients (7 with involved FLC level >100 mg/L) were followed over a period ranging from 4 to 8.5 years before eventually progressing, and 12 patients (5 with an involved FLC level >100 mg/L) were followed between 4 and 8 years and did not progress during the study period. Image:Summary/Conclusion: While FLC ratio ≥100 is associated with a high risk of progression in patients with SMM, it does not infer an imminent risk of progression, defined by the IMWG as median TTP of 12 months and 2-year progression rate of at least 80%. On the contrary, select patients with FLC ratio ≥100 can be followed for many years without progressing and some may never progress despite long-term follow-up. These findings suggest that in patients where FLC ratio ≥100 is the only myeloma-defining event, other high-risk features as well as the evolution of FLCs over time should be considered in the decision to start a patient on treatment.

Subcutaneous daratumumab (DARA SC) versus active monitoring in patients (pts) with high-risk smoldering multiple myeloma (SMM): Randomized, open-label, phase 3 AQUILA study.

TPS8075 Background: Standard of care for SMM includes active monitoring until progression to multiple myeloma (MM); however, recent evidence suggests pts with high-risk features may benefit from early treatment. DARA is a human IgGκ monoclonal antibody targeting CD38 that is approved as monotherapy for relapsed/refractory MM (RRMM) or in combination with standard of care for RRMM or newly diagnosed MM. Results from the phase 3 COLUMBA study showed that DARA SC demonstrated similar efficacy to intravenous (IV) DARA but with a lower rate of infusion-related reactions and shorter administration time. Based on the promising single-agent activity observed with IV DARA in intermediate- or high-risk SMM pts during the phase 2 CENTAURUS study, we hypothesized that DARA SC may delay progression to MM versus active monitoring in pts with high-risk SMM. Methods: AQUILA is an ongoing, randomized, open-label, multicenter phase 3 study of DARA SC versus active monitoring in pts with high-risk SMM. DARA SC (DARA 1,800 mg + recombinant human hyaluronidase PH20 [rHuPH20; 2,000 U/mL; Halozyme]) is administered by manual injection over approximately 5 minutes at alternating locations on the abdomen weekly in Cycles 1 and 2, every 2 weeks in Cycles 3-6, and every 4 weeks thereafter until 39 cycles (28 days/cycle), up to 36 months, or until disease progression. Eligibility criteria include confirmed diagnosis of SMM for ≤5 years, factors indicating high risk of progression to MM (clonal bone marrow plasma cells [BMPCs] ≥10% and ≥1 of the following: serum M protein ≥30 g/L, IgA SMM, immunoparesis with reduction of 2 uninvolved Ig isotypes, serum involved:uninvolved free light chain ratio ≥8 to &lt; 100, or clonal BMPCs &gt; 50% to &lt; 60% with measurable disease), and ECOG performance status ≤1. The primary endpoint is progression-free survival (PFS), assessed by an independent review committee, with disease progression defined according to International Myeloma Working Group diagnostic criteria for MM. Secondary endpoints include time to biochemical or diagnostic (SLiM-CRAB) progression, overall response rate, complete response rate, duration of response, time to response, time to first-line treatment for MM, PFS on first-line treatment for MM (PFS2), overall survival, and incidence of MM with adverse prognostic features. The study completed enrollment on May 6, 2019; 390 pts have been randomly assigned to DARA SC or active monitoring. The primary efficacy analysis will be performed after approximately 165 PFS events have been observed. Clinical trial information: NCT03301220.

Smoldering multiple myeloma progression to multiple myeloma in a community-based population.

e20015 Background: Few studies have characterized patients with smoldering multiple myeloma (SMM) in ethnically diverse settings and data regarding progression to multiple myeloma (MM) in real-world clinical populations is limited. Using data from a large healthcare system, we examined a contemporary cohort of adults with confirmed SMM and their progression to MM. Methods: We conducted a retrospective cohort study of SMM cases from 2010-2017 in Kaiser Permanente Northern California (KPNC). We used the KPNC SEER-based Cancer Registry to identify potential SMM cases by ascertaining MM cases with either: 1) “asymptomatic, evolving, or smoldering myeloma” status in the Cancer Registry or 2) mention of “smoldering” in clinical records. Chart review was conducted for potential SMM cases and confirmed SMM status was assigned using the 2014 IMWG criteria. SMM cases were followed for progression to MM and myeloma-directed therapy, excluding those with KPNC membership &lt;1 year after diagnosis. Time to MM progression (or treatment) was examined. SMM cases were classified during follow-up as: a) SMM, no progression to MM (and no receipt of myeloma-directed therapy); b) SMM, progression to MM (and receipt of myeloma-directed therapy); and c) SMM, receipt of myeloma-directed therapy without frank progression to MM (follow-up was censored at treatment). Results: During 2010-2017, we identified 152 adults with confirmed SMM. The median age at diagnosis was 71 years (IQR, 62-78), 56% were male, and 55% were non-Hispanic White, 17% Black, 9% Hispanic, and 18% Asian. During follow-up, 28% of patients progressed to MM, with a median time to progression of 1.2 years (IQR 0.8-2.0). Over half (58%) did not progress during a median follow-up time of 3.4 years, and an additional 14% received treatment before a MM-defining event. Progression data by demographic group is shown in Table. Conclusions: This is one of the first studies to examine SMM progression in an ethnically diverse cohort using the 2014 IMWG criteria. Although follow-up time was limited, we found that over half of the identified SMM cases did not progress to MM. However, patients who did progress to MM generally required treatment within 2 years of SMM diagnosis. These findings support efforts to identify high-risk patients with SMM who may benefit from early initiation of therapy. [Table: see text]

Assessing the Prognostic Utility of the Mayo 2018 and IMWG 2020 Smoldering Multiple Myeloma Risk Stratification Scores When Applied Post Diagnosis

Assessing the Prognostic Utility of the Mayo 2018 and IMWG 2020 Smoldering Multiple Myeloma Risk Stratification Scores When Applied Post Diagnosis

OAB-037: Assessing the prognostic utility of the Mayo 2018 and IMWG 2020 smoldering multiple myeloma risk stratification scores applied post diagnosis

<h3>Background</h3> Smoldering multiple myeloma (SMM) prognostication models routinely used in clinical practice were developed for use at diagnosis. However, retrospective studies in SMM patients have shown that 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 markers. <h3>Methods</h3> We retrospective 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 re-applied the Mayo 2018 and IMWG 2020 SMM risk stratification models at annual landmark timepoints up to 4 years post SMM diagnosis. Survival analyses were performed using the Kaplan-Meier method. Time to progression was defined as time from diagnosis or landmark timepoint to treatment initiation for MM or systemic AL amyloidosis. <h3>Results</h3> 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; 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. Patients evolving to a higher Mayo 2018 or IMWG 2020 risk category during follow up consistently had an increased risk of progression compared to patients with a stable/decreased risk categorization. We showed that 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). <h3>Conclusion</h3> 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, suggesting that patients evolving to a high-risk score during follow-up should be considered for early intervention treatment approaches.

Abstract 2240: Genomic profiling of smoldering multiple myeloma classifies distinct molecular groups

Abstract Background: Multiple Myeloma (MM) is an incurable plasma cell malignancy with significant genomic heterogeneity. It is usually preceded by the asymptomatic stage known as smoldering multiple myeloma (SMM). SMM patients have a 10% annual risk of progression to MM. Genomic alterations that are observed in SMM patients include chromosomal gains and losses, translocations, and point mutations. However, current SMM risk models rely solely on clinical markers that do not accurately capture the progression risk. While incorporating some genomic biomarkers improves prediction, using all MM genomic features to comprehensively stratify patients may increase the precision of risk models. Methods: We obtained a total of 214 patients' samples at SMM diagnosis in the US and Europe. We performed whole exome sequencing on 166 tumors; of these, RNA sequencing was performed on 100. Targeted capture with a MM gene panel was done on an additional 48 tumors. We identified subgroups using binarized DNA features and performing consensus binary non-negative matrix factorization. Results: We identified six clusters (C1-C6) with the following features: four with a hyperdiploidy (HD) (&amp;gt;48 chromosomes) and two with IgH translocations. These subgroups have unique transcriptomic profiles overlapping with known MM signatures and biological pathways. One of the clusters harboring translocation (11;14), which we call C4-CCND1, was enriched with the previously defined CD-2 MM signature that uniquely expresses B cell markers CD20 and CD79A; shows upregulation of CCND1 and E2F7; and is enriched with pathways like DNA replication, heme metabolism, and NFkB signaling. The C3-MS_MF cluster with the IgH translocations (4;14) and (14;16) shows downregulation of ribosomal genes, TRAF2, and DUSP2. The MYC oncogene was highly expressed in the four HD clusters: C1-HD_NRAS, C2-HD_MAFB, C5-HD_KRAS, and C6-HD_1q (BH-P = 0.037). The clusters also showed different outcomes in terms of time to progression (TTP) to active MM (P = 0.005). Median TTP for patients in C2-HD_MAFB, C3-MS_MF, and C5-HD_KRAS was 3.7, 2.6, and 2.2 years, respectively; TTP for C1-HD_NRAS, C4-CCND1, and C6-HD_1q was 4.3, 11, and not reached, respectively. In multivariate analysis, C2-HD_MAFB, C3-MS_MF, and C5-HD_KRAS were independent predictors of progression after accounting for the clinical risk stage. Moreover, the odds of having evolving hemoglobin and monoclonal protein levels in these three clusters were 3.5 and 12.3 times higher than the other clusters, respectively (P = 0.01 and 0.002). Conclusion: We identified six distinct SMM molecular groups with corresponding transcription profiles and dysregulated pathways. These groups have different progression risks to active MM, with three groups being independent predictors of progression. Our results underscore the importance of molecular classification in MM to better understand and target various tumor vulnerabilities. Citation Format: Shankara Anand, Mark Bustoros, François Aguet, Romanos Sklavenitis-Pistofidis, Robert Redd, Benny Zhitomirsky, Andrew J. Dunford, Yu-Tzu Tai, Selina J. Chavda, Cody Boehner, Carl J. Neuse, Tineke Casneuf, Lorenzo Trippa, Chip Stewart, Kwee Yong, Irene Ghobrial, Gad Getz. Genomic profiling of smoldering multiple myeloma classifies distinct molecular groups [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2240.

Validation of Dynamic Biomarker-Based Risk Progression Model for Smoldering Multiple Myeloma

Validation of Dynamic Biomarker-Based Risk Progression Model for Smoldering Multiple Myeloma

Risk Stratification of Smoldering Multiple Myeloma in the Light of the Revised IMWG Diagnostic Criteria

Introduction: The 2014 revised International Myeloma Working Group (IMWG) definition of multiple myeloma (MM) and smoldering MM (SMM), reclassified high risk patients with SMM who had one or more of bone marrow plasma cell percentage (BMPC) ≥ 60%, involved to uninvolved free light chain ratio (FLCr)≥100 and >1 focal lesion on magnetic resonance imaging as MM. A previous model developed at our institution to predict progression of SMM to MM or systemic amyloidosis included serum-M spike ≥3 g/dL, BMPC≥10% and FLCr >8 as predictors and was devised before 2014 (Dispenzieri et al. Blood; 2008). We aimed to devise a simple scoring system, using routinely used parameters, to risk stratify patients with SMM as defined by the current diagnostic criteria.Methods: We retrospectively reviewed electronic medical records to identify patients who satisfied the 2014 revised IMWG criteria for SMM, who were seen at our institution between 2001 and 2015. We collected data regarding baseline characteristics, date of progression, myeloma defining event, and first treatment. Time to progression (TTP) was defined as time duration from diagnosis of SMM to initiation of therapy for MM/amyloidosis. Patients were censored in TTP analysis if they did not progress at last follow-up, started cancer chemotherapy or steroids for other indications, or if they enrolled in a treatment trial of SMM. We used receiver operating characteristics (ROC) analysis to identify best cut-offs for continuous variables like serum M-spike, BMPC and FLCr in predicting progression at 3 years from diagnosis of SMM. We used Cox proportional hazards model to identify the effect of predictors on TTP and estimate their hazard ratios (HRs). TTP was estimated using Kaplan Meier method.Results: We included 433 patients in the final analysis. The estimated median follow-up duration was 6.0 years (95%CI, 5.4-6.8). Using ROC curve analysis, we identified M-spike of 2g/dL, BMPC of 20%, and FLCr of 20 as cut-offs to predict progression at 3 years. Apart from the above variables, we also included immunoglobulin isotype (IgG vs non-IgG) and presence of immunoparesis in the univariate analysis. The results of univariate analysis are shown in Table 1 . M-spike >2 g/dL, BMPC>20%, and FLCr>20 were significant in the univariate model and were included in the multivariate Cox proportional hazards model which included 419 patients. M-spike [HR: 1.67 (CI, 1.18-2.38); p=0.003], BMPC [HR: 2.02 (CI, 1.44-2.84); p<0.0001] and FLCr [HR: 1.88 (CI, 1.37-2.57); p=0.0001] predicted reduced TTP in the multivariate model. Depending on the presence of M-spike>2 g/dL, BMPC>20% and FLCr>20, we divided patients into three groups- low risk (none of the three risk factors; n=143), intermediate risk (one of the three risk factors; n=121) and high risk (two or more of the risk factors; n=155). The estimated median TTP for the low, intermediate and high risk groups were 9.1 years (CI, 5.4-not reached), 3.7 years (CI, 2.8-6.9) and 1.6 years (CI, 1.1-2.5) respectively (p<0.0001; Figure 1). There was no difference in TTP between patients who had two or three of the above risk factors at diagnosis. The 5-year estimated risk of progression in the low, intermediate and high risk groups were 26.5%, 57.1% and 81.0% respectively.Conclusions: M-spike >2 g/dL, BMPC>20% and FLCr>20 at diagnosis are routinely measured parameters which can be used to risk stratify patients meeting current diagnostic criteria for SMM. Presence of 2 or more of these risk factors identifies a high risk group with shorter TTP. These patients might benefit from clinical trials of early intervention to prevent/ delay progression to MM/amyloidosis. [Display omitted] DisclosuresDispenzieri:Celgene, Millenium, Pfizer, Janssen: Research Funding. Gertz:Millennium: Consultancy, Honoraria; Celgene, Novartis, Smith-Kline, Prothena, Ionis, Amgen: Honoraria. Dingli:Karyopharm Therapeutics: Research Funding; Millenium: Consultancy; Takeda: Consultancy; Janssen: Consultancy; Alexion Pharmaceuticals: Consultancy. Russell:Imanis Life Sciences: Equity Ownership; Vyriad: Equity Ownership. Kapoor:Takeda, Celgene and Amgen: Research Funding. Kumar:Celgene, Millennium, BMS, Onyx, Janssen, Noxxon, AbbVie, Amgen, Merck, Oncopeptides, Skyline Diagnostics, Takeda: Consultancy; Celgene, Millennium/Takeda, Onyx, AbbVie, Janssen, Sanofi, Novartis, Amgen, Genentech, Merck, Oncopeptides, Roche, Skyline Diagnostics: Research Funding; Skyline: Honoraria.

Genomic Profiling of Smoldering Multiple Myeloma Identifies Patients at a High Risk of Disease Progression.

Smoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with a 10% annual risk of progression. Various prognostic models exist for risk stratification; however, those are based on solely clinical metrics. The discovery of genomic alterations that underlie disease progression to MM could improve current risk models. We used next-generation sequencing to study 214 patients with SMM. We performed whole-exome sequencing on 166 tumors, including 5 with serial samples, and deep targeted sequencing on 48 tumors. We observed that most of the genetic alterations necessary for progression have already been acquired by the diagnosis of SMM. Particularly, we found that alterations of the mitogen-activated protein kinase pathway (KRAS and NRAS single nucleotide variants [SNVs]), the DNA repair pathway (deletion 17p, TP53, and ATM SNVs), and MYC (translocations or copy number variations) were all independent risk factors of progression after accounting for clinical risk staging. We validated these findings in an external SMM cohort by showing that patients who have any of these three features have a higher risk of progressing to MM. Moreover, APOBEC associated mutations were enriched in patients who progressed and were associated with a shorter time to progression in our cohort. SMM is a genetically mature entity whereby most driver genetic alterations have already occurred, which suggests the existence of a right-skewed model of genetic evolution from monoclonal gammopathy of undetermined significance to MM. We identified and externally validated genomic predictors of progression that could distinguish patients at high risk of progression to MM and, thus, improve on the precision of current clinical models.

Diagnostic performance of skeletal survey versus 18F-FDG-PET/CT for detecting lytic lesions in smoldering multiple myeloma.

8532 Background: Per NCCN Guidelines for smoldering multiple myeloma (SMM), whole body radiography, i.e. skeletal survey (SS), should be used to rule out osteolytic bone lesions. If negative, more sensitive imaging techniques such as whole body 18F-FDG-PET/CT(PET/CT), MRI, or low dose CT should be used to differentiate between SMM and multiple myeloma (MM). The false-negative rate of SS is high (30-70%). The frequency of false-positive SS in SMM is less well known but important because of its common use in community practice. We examine the specificity of SS in patients with a presumed diagnosis of SMM and question if SS is still warranted prior to modern imaging techniques to confirm a diagnosis of SMM. Methods: Records of patients sequentially referred from the community and evaluated for a presumed diagnosis of SMM at the National Institutes of Health Myeloma Program between April 2010 to January 2020 were reviewed. Patients with a SS and PET/CT performed within 30 days were included. Positive findings on PET/CT were defined per the 2014 IMWG criteria as one or more sites of osteolytic bone destruction seen on CT. The sensitivity and specificity of SS were calculated using PET/CT as the reference test. Results: Charts from 144 patients with presumed SMM were reviewed. A total of 76 SMM patients had both a SS and PET/CT performed within 30 days of each other. Sixty-four patients (84.2%) showed concordant results. Twelve (15.8%) patients had discordant imaging results. SS was falsely negative in 3 (4.7% (95% CI: 1.2%-14.2%)) patients and falsely positive in 9 (69.2% (95% CI: 38.9%-89.6%)) patients. SS had a sensitivity of 57.1% (95% CI: 20.2%-88.2%) and a specificity of 86.9% (95% CI: 76.2-93.5). Conclusions: In patients presumed to have SMM, disease burden is low thus highly sensitive imaging modalities are needed to rule out bone disease. This study confirms the low sensitivity of SS in the SMM population. It more importantly points out the low specificity of SS in SMM. The IMWG no longer recommends conventional SS prior to whole body CT (or PET/CT) as first imaging choice in SMM. While the argument may be made that SS should still be used upfront due to low cost and widespread availability, this study shows the risk of overestimating disease. Over 10% of patients in this series had false positive disease on SS and thus at risk of receiving unnecessary treatment. Not only concerning for patient toxicity but more so financial toxicity. If SS is used, it is important to review positive findings directly with a radiologist and consider follow-up confirmatory imaging.

The role of bone marrow biopsy in patients with plasma cell disorders: should all patients with a monoclonal protein be biopsied?

We conducted a retrospective review of multiple myeloma (MM), smoldering multiple myeloma (SMM), and monoclonal gammopathy of undetermined significance (MGUS) patients seen at Mayo Clinic to determine whether a bone marrow biopsy (BM) is necessary in all patients diagnosed with a monoclonal protein. A total of 2254 MM, 397 SMM, and 5836 MGUS patients were included in the study. A total of 29 (1.3%) MM patients “without CRAB/FLC” were identified where BM or advanced imaging was critical for diagnosis, 8 (0.3% MM cohort) of whom were diagnosed with MM solely on BM findings (plasma cells > 60%). Without BM or advanced imaging none of these patients would be classified low-risk MGUS. A total of 314 (79%) MGUS-like SMM patients were identified where classification of SMM was based on BM findings. Without BM 97 would be classified as low/low-intermediate-risk MGUS and 151 intermediate or high-risk MGUS; 66 had missing information precluding classification. Only three (<1% SMM cohort) were low-risk MGUS without abnormalities in hemoglobin, calcium, and renal function. In patients presenting with low-risk MGUS and normal hemoglobin, calcium, and renal function, the risk of missing a diagnosis of SMM and MM by omitting BM is <1%. BM should be deferred in these patients in preference to clinical and laboratory monitoring.

Using Current Clinical Markers to Define High Risk Smoldering Multiple Myeloma: Agree to Disagree

Using Current Clinical Markers to Define High Risk Smoldering Multiple Myeloma: Agree to Disagree