scholarly journals Identification of patients with smouldering multiple myeloma at ultra‐high risk of progression using serum parameters: the Czech Myeloma Group model

2020 ◽  
Vol 190 (2) ◽  
pp. 189-197
Author(s):  
Roman Hájek ◽  
Viera Sandecka ◽  
Ivan Špička ◽  
Marc Raab ◽  
Hartmut Goldschmidt ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Group Model ◽  
Serum Parameters ◽  
Ultra High Risk ◽  
Risk Of Progression ◽  
Smouldering Multiple Myeloma

scholarly journals Prognostic value of involved/uninvolved free light chain ratio determined by Freelite and N Latex FLC assays for identification of high-risk smoldering myeloma patients

2019 ◽  
Vol 57 (9) ◽  
pp. 1397-1405 ◽  
Author(s):  
Basile Henriot ◽  
Emmanuel Rouger ◽  
Chloé Rousseau ◽  
Martine Escoffre ◽  
Martine Sébillot ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Light Chain ◽  
Laboratory Data ◽  
Independent Study ◽  
Free Light Chain ◽  
Accurate Identification ◽  
Serum Free Light Chain ◽  
Ultra High Risk ◽  
Risk Of Progression

Abstract Background Smoldering multiple myeloma (SMM) is an asymptomatic plasma cell disorder with a high risk of progression to symptomatic multiple myeloma (MM). The serum free light chain (sFLC) ratio is a powerful prognostic factor for SMM: an sFLC ratio ≥8 has been reported to be associated with a high risk of progression to MM, and an sFLC ratio ≥100 has been described as a criterion for ultra-high-risk SMM, and has been integrated into the definition criteria for MM since 2014. However, all recommendations were based on sFLC measured using the first commercialized assay, Freelite™, while other assays are now available. We aimed to evaluate the safety and accuracy of N-Latex sFLC to identify high-risk and ultra-high-risk SMM. Methods The sFLC ratio was measured at diagnosis with both Freelite and N-Latex assays in a cohort of 176 SMM patients on a BN Prospec nephelometer. Demographic, clinical, therapeutic and laboratory data were collected at the time of diagnosis and at follow-up. Results Sixty-two patients (35.2%) progressed to MM within 2 years. Compared to Freelite™ sFLC, N Latex sFLC ratios ≥8 and ≥100 provided similar performances for the identification of high-risk and ultra-high risk SMM patients. Conclusions Our results evidenced that the N-Latex assay could be used for SMM monitoring, like Freelite. However, an N-Latex sFLC ratio ≥70 appears to provide similar performances to a Freelite sFLC ratio ≥100, with a slightly better positive predictive value. Both assays provided accurate identification of high-risk and ultra-high risk SMM patients. These results should be confirmed in an independent study.

Depth of response and minimal residual disease status in ultra high-risk multiple myeloma and plasma cell leukemia treated with daratumumab, bortezomib, lenalidomide, cyclophosphamide and dexamethasone (Dara-CVRd): Results of the UK optimum/MUKnine trial.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 8001-8001
Author(s):  
Martin F. Kaiser ◽  
Andrew Hall ◽  
Katrina Walker ◽  
Ruth De Tute ◽  
Sadie Roberts ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Minimal Residual Disease ◽  
Plasma Cell ◽  
Residual Disease ◽  
Cell Leukemia ◽  
Ultra High Risk ◽  
Grade 3 ◽  
Minimal Residual

8001 Background: Patients with ultra high-risk (UHiR) newly diagnosed multiple myeloma (NDMM) and patients with plasma cell leukemia (PCL) continue to have dismal outcomes and are underrepresented in clinical trials. Recently, improved responses with anti-CD38 monoclonal antibody combination therapy have been reported for NDMM patients. We report here outcomes for NDMM UHiR and PCL patients treated in the OPTIMUM/MUKnine (NCT03188172) trial with daratumumab, cyclophosphamide, bortezomib, lenalidomide, dexamethasone (Dara-CVRd) induction, augmented high-dose melphalan (HDMEL) and ASCT. With final analysis follow-up surpassed in Feb 2021, we report here early protocol defined endpoints from induction to day 100 post ASCT. Methods: Between Sep 2017 and Jul 2019, 107 patients with UHiR NDMM by central trial genetic (≥2 high risk lesions: t(4;14), t(14;16), t(14;20), gain(1q), del(1p), del(17p)) or gene expression SKY92 (SkylineDx) profiling, or with PCL (circulating plasmablasts > 20%) were included in OPTIMUM across 39 UK hospitals. Patients received up to 6 cycles of Dara-CVRd induction, HDMEL and ASCT augmented with bortezomib, followed by Dara-VR(d) consolidation for 18 cycles and Dara-R maintenance. Primary trial endpoints are minimal residual disease (MRD) status post ASCT and progression-free survival. Secondary endpoints include response, safety and quality of life. Data is complete but subject to further data cleaning prior to conference. Results: Median follow-up for the 107 patients in the safety population was 22.2 months (95% CI: 20.6 – 23.9). Two patients died during induction due to infection. Bone marrow aspirates suitable for MRD assessment by flow cytometry (10-5 sensitivity) were available for 81% of patients at end of induction and 78% at D100 post ASCT. Responses in the intention to treat population at end of induction were 94% ORR with 22% CR, 58% VGPR, 15% PR, 1% PD, 5% timepoint not reached (TNR; withdrew, became ineligible or died) and at D100 post ASCT 83% ORR with 47% CR, 32% VGPR, 5% PR, 7% PD, 10% TNR. MRD status was 41% MRDneg, 40% MRDpos and 19% not evaluable post induction and 64% MRDneg, 14% MRDpos and 22% not evaluable at D100 post ASCT. Responses at D100 post ASCT were lower in PCL with 22% CR, 22% VGPR, 22% PR, 22% PD, 12% TNR. Most frequent grade 3/4 AEs during induction were neutropenia (21%), thrombocytopenia (12%) and infection (12%). Grade 3 neuropathy rate was 3.7%. Conclusions: This is to our knowledge the first report on a trial for UHiR NDMM and PCL investigating Dara-CVRd induction and augmented ASCT. Response rates were high in this difficult-to-treat patient population, with toxicity comparable to other induction regimens. However, some early progressions highlight the need for innovative approaches to UHiR NDMM. Clinical trial information: NCT03188172.

Lenalidomide plus dexamethasone versus observation in patients with high-risk smouldering multiple myeloma (QuiRedex): long-term follow-up of a randomised, controlled, phase 3 trial

2016 ◽  
Vol 17 (8) ◽  
pp. 1127-1136 ◽  
Author(s):  
María-Victoria Mateos ◽  
Miguel-Teodoro Hernández ◽  
Pilar Giraldo ◽  
Javier de la Rubia ◽  
Felipe de Arriba ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Phase 3 ◽  
Long Term Follow Up ◽  
Smouldering Multiple Myeloma ◽  
Randomised Controlled

scholarly journals Genomic Profiling of Smoldering Multiple Myeloma Classifies Molecular Groups with Distinct Pathogenic Phenotypes and Clinical Outcomes

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 723-723
Author(s):  
Shankara Anand ◽  
Mark Bustoros ◽  
Romanos Sklavenitis-Pistofidis ◽  
Robert A. Redd ◽  
Eileen M Boyle ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Molecular Classification ◽  
Intermediate Risk ◽  
Advisory Committees ◽  
Increased Risk ◽  
Risk Of Progression ◽  
Over Time

Abstract Introduction: Multiple Myeloma (MM) is an incurable plasma cell malignancy commonly preceded by the asymptomatic stage smoldering multiple myeloma (SMM). MM is characterized with significant genomic heterogeneity of chromosomal gains and losses (CNVs), translocations, and point mutations (SNVs); alterations that are also observed in SMM patients. However, current SMM risk models rely solely on clinical markers and do not accurately capture progression risk. While incorporating some genomic biomarkers improves prediction, using all MM genomic features to comprehensively stratify patients may increase risk stratification precision in SMM. Methods: We obtained a total of 214 patient samples at SMM diagnosis. We performed whole-exome sequencing on 166 tumors; of these, RNA sequencing was performed on 100. Targeted capture was done on 48 additional tumors. Upon binarization of DNA features, we performed consensus non-negative matrix factorization to identify distinct molecular clusters. We then trained a random forest classifier on translocations, SNVs, and CNVs. The predicted clinical outcomes for the molecular subtypes were further validated in an independent SMM cohort of 74 patients. Results: We identified six genomic subtypes, four with hyperdiploidy (>48 chromosomes, HMC, HKR, HNT, HNF) and two with IgH translocations (FMD, CND) (Table 1). In multivariate analysis accounting for IMWG (20-2-20) clinical risk stages, high-risk (HMC, FMD, HKR) and intermediate-risk (HNT, HNF) genetic subtypes were independent predictors of progression (Hazards ratio [HR]: 3.8 and 5.5, P = 0.016 and 0.001, respectively). The low-risk, CND subtype harboring translocation (11;14) was enriched for the previously defined CD-2 MM signature defined by the B cell markers CD20 and CD79A (FDR = 0.003 ), showed upregulation of CCND1, E2F1, and E2F7 (FDR = 0.01, 0.0004, 0.08), and was enriched for G2M checkpoint, heme metabolism, and monocyte cell signature (FDR = 0.003, 0.003, 0.003, respectively). The FMD subtype with IgH translocations (4;14) and (14;16) was enriched for P53, mTORC1, unfolded protein signaling pathways and plasmacytoid dendritic cell signatures (FDR = 0.01, 0.005, 0.008, respectively). The HKR tumors were enriched for inflammatory cytokine signaling, MYC target genes, T regulatory cell signature, and the MM proliferative (PR) signatures (FDR = 0.02, 0.03, 0.007, 0.02, respectively). The APOBEC mutational signature was enriched in HMC and FMD tumors (P = 0.005), while there was no statistical difference across subtypes in the AID signature. The median follow-up for the primary cohort is 7.1 years. Median TTP for patients in HMC, FMD, and HKR was 3.8, 2.6, and 2.2 years, respectively; TTP for HNT and HNF was 4.3 and 5.2, respectively, while it was 11 years in CND patients (P = 0.007). Moreover, by analyzing the changes in MM clinical biomarkers over time, we found that patients from high-risk subgroups had higher odds of developing evolving hemoglobin and monoclonal protein levels over time (P = 0.01 and 0.002, respectively); Moreover, the absolute increase in M-protein was significantly higher in patients from the high-risk genetic subtypes at one, two, and five years from diagnosis (P = 0.001, 0.03, and 0,01, respectively). Applying the classifier to the external cohort replicated our findings where intermediate and high-risk genetic subgroups conferred increased risk of progression to MM in multivariate analysis after accounting for IMWG staging (HR: 5.5 and 9.8, P = 0.04 and 0.005, respectively). Interestingly, within the intermediate-risk clinical group in the primary cohort, patients in the high-risk genetic subgroups had increased risk of progression (HR: 5.2, 95% CI 1.5 - 17.3, P = 0.007). In the validation cohort, these patients also had an increased risk of progression to MM (HR: 6.7, 95% CI 1.2 - 38.3, P = 0.03), indicating that molecular classification improves the clinical risk-stratification models. Conclusion: We identified and validated in an independent dataset six SMM molecular subgroups with distinct DNA alterations, transcriptional profiles, dysregulated pathways, and risks of progression to active MM. Our results underscore the importance of molecular classification in addition to clinical evaluation in better identifying high-risk SMM patients. Moreover, these subgroups may be used to identify tumor vulnerabilities and target them with precision medicine efforts. Figure 1 Figure 1. Disclosures Bustoros: Janssen, Bristol Myers Squibb: Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria. Casneuf: Janssen: Current Employment. Kastritis: Amgen: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Consultancy, Honoraria, Research Funding; Genesis Pharma: Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Walker: Bristol Myers Squibb: Research Funding; Sanofi: Speakers Bureau. Davies: Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Dimopoulos: Amgen: Honoraria; BMS: Honoraria; Takeda: Honoraria; Beigene: Honoraria; Janssen: Honoraria. Bergsagel: Genetech: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; GSK: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Yong: BMS: Research Funding; Autolus: Research Funding; Takeda: Honoraria; Janssen: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; GSK: Honoraria; Amgen: Honoraria. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees. Getz: IBM, Pharmacyclics: Research Funding; Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy.

scholarly journals Identifying Ultra-High Risk Smoldering Multiple Myeloma

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3192-3192 ◽  
Author(s):  
Theresia Akhlaghi ◽  
Even H Rustad ◽  
Venkata D Yellapantula ◽  
Neha Korde ◽  
Sham Mailankody ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Advisory Committees ◽  
Ultra High Risk ◽  
Risk Of Progression ◽  
Equity Ownership ◽  
M Spike ◽  
Risk Biomarkers

Abstract Introduction Smoldering multiple myeloma (SMM) is an asymptomatic precursor stage to active multiple myeloma (MM), comprised by a heterogenous group of patients with varying rates of progression. While the overall yearly progression rate is 10% the first 5 years, some patients progress at a considerably higher rate. A study from the Mayo Clinic showed that in a subset of 21 patients defined by ≥60% monoclonal bone marrow plasma cells (BMPC), 95% progressed within 2 years. It was subsequently concluded by the International Myeloma Working Group (IMWG) that patients with biomarkers predictive of a 2-year progression rate at 80%, and a median time to progression at 12 months were at ultra-high risk of progression and should be considered to have MM requiring treatment despite being asymptomatic. In 2014, ultra-high risk biomarkers were incorporated in the definition of MM, including BMPC ≥60%, free light chain (FLC) ratio ≥100 and ≥2 focal lesions on magnetic resonance imaging (MRI). While the updated myeloma definition changed the diagnosis of some patients with ultra-high risk SMM to MM, there remain patients classified as SMM progressing at a very high rate. In the present study, we aimed at further identifying ultra-high risk biomarkers predictive of a high rate of progression to active MM. Methods Patients with SMM presenting to Memorial Sloan Kettering Cancer Center between the years 2000 and 2017 were identified and included in the study. Diagnosis of SMM and progression to MM requiring therapy was defined according to the IMWG criteria at the time of diagnosis. Baseline patient and disease characteristics were collected at date of diagnosis with SMM, including pathology reports, laboratory results and imaging data. Time to progression (TTP) was assessed using the Kaplan-Meier method with log-rank test for comparisons. Optimal cut-off values for continuous variables were assessed with receiver operating characteristics (ROC) curve. Patients who had not progressed by the end of study or were lost to follow up were censored at the date of last visit. Univariate Cox regression was used to estimate risk factors for TTP with hazard ratios (HR) and 95% confidence intervals (CI). Significant univariate risk factors were selected for multivariate Cox regression. Results A total of 444 patients were included in the study. Median follow-up time was 78 months. During the study period, 215 (48%) patients progressed to active MM, with a median TTP of 72 months. Cut-off points for BMPC, M-spike, and FLC ratio were determined with ROC curves to be 20%, 2 g/dL, and 18, respectively, for predicting high risk of progression. The following factors were associated with significantly increased risk of progression to active MM: BMPC >20%, M-spike >2g/dL, FLC ratio >18, immunoparesis with depression of 1 and 2 uninvolved immunoglobulins respectively, elevated lactate dehydrogenase, elevated beta-2-microglobulin, and low albumin (Table 1). In the multivariate model, BMPC >20% (HR 2.5, 95% CI 1.6-3.9), M-spike >2g/dL (HR 3.2, CI 1.9-5.5), FLC ratio >18 (HR 1.8, CI 1.1-3.0), albumin <3.5 g/dL (HR 3.9, CI 1.5-10.0), and immunoparesis with 2 uninvolved immunoglobulins (HR 2.3, CI 1.2-4.3), predicted a decreased TTP (Table 1). A total of 12 patients had 4 or 5 of the risk factors from the multivariate model, 8 of these did not meet the 2014 IMWG criteria for MM. These patients had a significantly shorter TTP than patients with less than 4 risk factors (median TTP 11 vs 74 months, p<0.0001, Figure 1). At 16 months, 82% of these patients had progressed, and within 2 years, 91% of the patients progressed. Only one patient remained progression free after 2 years, progressing at 31 months. Of patients with less than 4 risk factors, 19% progressed within the first 2 years. Conclusion In addition to baseline BMPC >20%, M-spike >2g/dL, FLC-ratio >18, we found that albumin <3.5g/dL and immunoparesis of both uninvolved immunoglobulins at the time of diagnosis with SMM were highly predictive of a decreased TTP to MM requiring therapy. These biomarkers are readily available and routinely assessed in clinic. Patients with 4 or 5 of these risk factors represent a new ultra-high risk group that progress to active disease within 2 years, further expanding on the definition of ultra-high risk SMM. In accordance with the rationale on ultra-high risk biomarkers as criteria established by the IMWG in 2014, such patients should be considered to have MM requiring therapy. Disclosures Korde: Amgen: Research Funding. Mailankody:Janssen: Research Funding; Takeda: Research Funding; Juno: Research Funding; Physician Education Resource: Honoraria. Lesokhin:Squibb: Consultancy, Honoraria; Serametrix, inc.: Patents & Royalties: Royalties; Takeda: Consultancy, Honoraria; Genentech: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Janssen: Research Funding. Hassoun:Oncopeptides AB: Research Funding. Smith:Celgene: Consultancy, Patents & Royalties: CAR T cell therapies for MM, Research Funding. Shah:Amgen: Research Funding; Janssen: Research Funding. Mezzi:Amgen: Employment, Equity Ownership. Khurana:Amgen: Employment, Equity Ownership. Braunlin:Amgen: Employment. Werther:Amgen: Employment, Equity Ownership. Landgren:Takeda: 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; Karyopharm: Consultancy; Merck: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Research Funding; Pfizer: Consultancy; Celgene: Consultancy, Research Funding.

scholarly journals Evolving diagnostic criteria for multiple myeloma

Hematology ◽  
2015 ◽  
Vol 2015 (1) ◽  
pp. 272-278 ◽  
Author(s):  
S. Vincent Rajkumar
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Diagnostic Criteria ◽  
Organ Damage ◽  
Bone Lesions ◽  
End Organ Damage ◽  
Positron Emission ◽  
Disease Definition ◽  
Risk Of Progression ◽  
Asymptomatic Phase

Abstract Multiple myeloma (MM) is a plasma cell malignancy historically defined by the presence of end-organ damage, specifically, hypercalcemia, renal failure, anemia, and bone lesions (CRAB features) that can be attributed to the neoplastic process. In 2014, the International Myeloma Working Group (IMWG) updated the diagnostic criteria for MM to add specific biomarkers that can be used to make the diagnosis of the disease in patients who did not have CRAB features. In addition, the update allows modern imaging methods including computed tomography (CT) and positron emission tomography-CT to diagnose MM bone disease. These changes enable early diagnosis, and allow the initiation of effective therapy to prevent the development of end-organ damage in patients who are at the highest risk. This article reviews these and several other clarifications and revisions that were made to the diagnostic criteria for MM and related disorders. The updated disease definition for MM also automatically resulted in a revision to the diagnostic criteria for the asymptomatic phase of the disease termed smoldering MM (SMM). Thus the current diagnosis and risk-stratification of SMM is also reviewed in this article. Using specific prognostic factors, it is possible to identify a subset of patients with SMM who have a risk of progression to MM of 25% per year (high-risk SMM). An approach to the management of patients with low- and high-risk SMM is discussed.

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