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[Background]: Smoldering multiple myeloma (SMM) is a heterogeneous disease in terms of progression to myeloma (MM), but its standard of care continues to be observation. [Methods]: The QuiRedex phase 3 trial initiated in 2007 included 119 high-risk patients with SMM randomized to treatment or observation. Treatment consisted of nine 4-week induction cycles (lenalidomide [Rd], 25 mg on days 1–21 plus dexamethasone, 20 mg on days 1–4 and 12–15), followed by maintenance (R, 10 mg on days 1–21) for up to 2 years. The primary end-point was time to progression (TTP) to myeloma based on per protocol population. Secondary end-points were overall survival (OS), response rate, and safety. An update of the trial after a long-term follow-up is presented here. This trial was registered with ClinicalTrials.gov (NCT00480363). [Findings]: After a median follow-up time of 12.5 years (range: 10.4–13.6), the median TTP to MM was 2.1 years in the observation arm and 9.5 years in the Rd arm (HR: 0.28, 95% CI: 0.18–0.44, p < 0.0001). The median OS was 8.5 years in the abstention arm and not reached in the Rd group (HR: 0.57, 95% CI: 0.34–0.95, p = 0.032). Patients who progressed received optimized treatments according to the standards of care, and the OS from progression was comparable in both arms (p = 0.96). [Interpretation]: This analysis confirms that early treatment with Rd for high-risk SMM translates into a sustained benefit in both TTP and OS., This study was also supported by the Cooperative Research Thematic Network grant RD12/0036/0058 and RD12/0036/0046 and Instituto de Salud Carlos III/Subdirección General de Investigación Sanitaria, Spain. (FIS:PI12/02311/01761/01569).

Monoclonal gammopathies (MGs) are a wide range of diseases that may evolve or progress over time. Comorbidity plays a critical role in this setting. The co-occurrence of two MGs is not a rare event. The evidence on the association of systemic light chain (AL) amyloidosis and multiple myeloma (MM) is scarce and controversial. Herein we aim to address this topic in a large series of patients of a referral center. All consecutive AL amyloidosis patients treated at our center from January 2005 to April 2023 were prospectively enrolled in a clinical and epidemiological registry. 141 patients diagnosed with AL amyloidosis were included, of which 7 (5%) had localized whereas 134 presented with systemic disease. The heart was the most frequently affected organ (90.3%). 25 patients (18.7%) fulfilled the IMWG diagnostic criteria of MM (AL/MM). Time-dependent association between AL and MM showed that the synchronous pattern is more frequent than the appearance of a second primary malignancy. The diagnostic delay was six months (m). Patients with AL/MM had a poorer median overall survival (OS) than AL-only patients (35.5 m, CI 95% 0–88.9, vs. 52.6 m, CI 95% 16.7–88.5), but this difference was not statistically significant. The prognosis in AL is dominated by the heart involvement, which is massive in this series. In our Cox regression model, only three prognostic variables remain as independent prognostic factors: age, N-terminal pro-brain natriuretic peptide (≥8500 ng/L), and undergoing an autologous stem cell transplant, whereas left ventricular ejection fraction shows a marginal effect. More and large studies focusing on the AL/MM association are needed to uncover the characteristics and prognostic impact of this association.

In this randomized phase 2 study (GEM-KyCyDex), the combination of weekly carfilzomib 70 mg/m2, cyclophosphamide and dexamethasone was compared to carfilzomib and dexamethasone (Kd) in relapsed/refractory multiple myeloma (RRMM) after 1-3 prior lines (PLs). 197 patients were included and randomized 1:1 to receive KCd (97 patients) or Kd (100 patients) in 28-day cycles until progressive disease or unacceptable toxicity occurred. Patient median age was 70 years, and the median number of PLs was 1 (1-3). More than 90% of patients had previously been exposed to proteasome inhibitors, ≈70% to immunomodulators, and ≈50% were refractory to their last line (mainly lenalidomide) in both groups. After a median follow-up of 37 months, median progression-free survival (PFS) was 19.1 and 16.6 months in KCd and Kd, respectively (P=0.577). Of note, in the post hoc analysis of the lenalidomiderefractory population, the addition of cyclophosphamide to Kd resulted in a significant benefit in terms of PFS: 18.4 vs. 11.3 months (Hazard ratio 1.7 [1.1-2.7]; P=0.043). The overall response rate and the percentage of patients who achieved complete response was around 70% and 20% in both groups. The addition of cyclophosphamide to Kd did not result in any safety signal, except for severe infections (7% vs. 2%). In conclusion, the combination of cyclophosphamide with Kd 70 mg/m2 weekly does not improve outcomes as compared with Kd alone in RRMM after 1-3 PLs, but a significant benefit in PFS was observed with the triplet in the lenalidomide-refractory population. The administration of weekly carfilzomib 70 mg/m2 was safe and convenient, and, overall, the toxicity was manageable in both arms.

Purpose: Multiple myeloma remains an incurable disease. New approaches to develop better tools for improving patient prognostication and monitoring treatment efficacy are very much needed. In this study, we aimed to evaluate the potential of metabolomics by 1H-NMR to provide information on metabolic profiles that could be useful in the management of multiple myeloma.Experimental Design: Serum samples were collected from multiple myeloma patients at the time of diagnosis and after achieving complete remission. A matched control set of samples was also included in the study. The 1H-NMR measurements used to obtain the metabolic profile for each patient were followed by the application of univariate and multivariate statistical analyses to determine significant differences.Results: Metabolic profiles of multiple myeloma patients at diagnosis exhibited higher levels of isoleucine, arginine, acetate, phenylalanine, and tyrosine, and decreased levels of 3-hydroxybutyrate, lysine, glutamine, and some lipids compared with the control set. A similar analysis conducted in multiple myeloma patients after achieving complete remission indicated that some of the metabolic changes (i.e., glutamine, cholesterol, lysine) observed at diagnosis displayed a variation in the opposite direction upon responding to treatment, thus contributing to multiple myeloma patients having a closer metabolic profile to those of healthy individuals after the disappearance of major disease manifestations.Conclusions: The results highlight the potential of metabolic profiles obtained by 1H-NMR in identifying multiple myeloma biomarkers that may be useful to objectively discriminate individuals with and without multiple myeloma, and monitor response to treatment. Clin Cancer Res; 19(17); 4770–9. ©2013 AACR.

Online Supplement - PDF file 58K, NMR-based metabolomics

Supplementary Figure from A Machine Learning Model Based on Tumor and Immune Biomarkers to Predict Undetectable MRD and Survival Outcomes in Multiple Myeloma

Figure S1 - PDF file 47K, Principal Component Analyses (PCA) of 1H-NMR spectra corresponding to all the samples included in the study colored according to (A) gender (full triangles: male, empty triangles: female) and (B) age (full triangles: >70 years, empty triangles: 60-70 years, full squares: 50-60 years, empty squares

Purpose:Undetectable measurable residual disease (MRD) is a surrogate of prolonged survival in multiple myeloma. Thus, treatment individualization based on the probability of a patient achieving undetectable MRD with a singular regimen could represent a new concept toward personalized treatment, with fast assessment of its success. This has never been investigated; therefore, we sought to define a machine learning model to predict undetectable MRD at the onset of multiple myeloma.Experimental Design:This study included 487 newly diagnosed patients with multiple myeloma. The training (n = 152) and internal validation cohorts (n = 149) consisted of 301 transplant-eligible patients with active multiple myeloma enrolled in the GEM2012MENOS65 trial. Two external validation cohorts were defined by 76 high-risk transplant-eligible patients with smoldering multiple myeloma enrolled in the Grupo Español de Mieloma(GEM)-CESAR trial, and 110 transplant-ineligible elderly patients enrolled in the GEM-CLARIDEX trial.Results:The most effective model to predict MRD status resulted from integrating cytogenetic [t(4;14) and/or del(17p13)], tumor burden (bone marrow plasma cell clonality and circulating tumor cells), and immune-related biomarkers. Accurate predictions of MRD outcomes were achieved in 71% of cases in the GEM2012MENOS65 trial (n = 214/301) and 72% in the external validation cohorts (n = 134/186). The model also predicted sustained MRD negativity from consolidation onto 2 years maintenance (GEM2014MAIN). High-confidence prediction of undetectable MRD at diagnosis identified a subgroup of patients with active multiple myeloma with 80% and 93% progression-free and overall survival rates at 5 years.Conclusions:It is possible to accurately predict MRD outcomes using an integrative, weighted model defined by machine learning algorithms. This is a new concept toward individualized treatment in multiple myeloma.See related commentary by Pawlyn and Davies, p. 2482

Supplementary Data from A Machine Learning Model Based on Tumor and Immune Biomarkers to Predict Undetectable MRD and Survival Outcomes in Multiple Myeloma

Table S1 - PDF file 103K, Relative amounts of most significant metabolites in the OPLS-DA model from the control group and the MM patients at the time of diagnosis

Loss and/or mutation of the TP53 gene are associated with short survival in multiple myeloma, but the p53 landscape goes far beyond. At least 12 p53 protein isoforms have been identified as a result of a combination of alternative splicing, alternative promoters and/or alternative transcription site starts, which are grouped as α, β, γ, from transactivation domain (TA), long, and short isoforms. Nowadays, there are no studies evaluating the expression of p53 isoforms and its clinical relevance in multiple myeloma (MM). We used capillary nanoimmunoassay to quantify the expression of p53 protein isoforms in CD138-purified samples from 156 patients with newly diagnosed MM who were treated as part of the PETHEMA/GEM2012 clinical trial and investigated their prognostic impact. Quantitative real-time polymerase chain reaction was used to corroborate the results at RNA levels. Low and high levels of expression of short and TAp53β/γ isoforms, respectively, were associated with adverse prognosis in MM patients. Multivariate Cox models identified high levels of TAp53β/γ (hazard ratio [HR], 4.49; p, The Instituto de Salud Carlos III, European Union FEDER funds, Grant Numbers: PI16/01074 and PI19/00674; The Asociación Española Contra el Cáncer, Grant Number: AECC, PROYE20047GUTI; National Science Centre, Poland, Grant Number: UMO-2019/35/B/NZ5/02824; The Consejería de Educación de Castilla y León and FEDER funds; AECC, Grant Number: CLJUN18010DERA.

El rescate de los dibujos escolares de un Antonio Gaudí estudiante es una llave para abrir esta conversación. A partir de ellos se indaga en el mito del genio centrado en la figura de este arquitecto catalán. A través del recorrido que se propone en la entrevista se develan otros mitos relacionados con los cambios de paradigma en la enseñanza de la arquitectura y el diseño y que figuras como las de Gaudí contribuyen por una vía a alimentar y, por otra, a desandar volviendo a mirar los documentos de archivo.

Monoclonal gammopathies of clinical significance (MGCSs) represent a group of diseases featuring the association of a nonmalignant B cells or plasma cells clone, the production of an M-protein, and singularly, the existence of organ damage. They present a current framework that is difficult to approach from a practical clinical perspective. Several points should be addressed in order to move further toward a better understanding. Overall, these entities are only partially included in the international classifications of diseases. Its definition and classification remain ambiguous. Remarkably, its real incidence is unknown, provided that a diagnostic biopsy is mandatory in most cases. In fact, amyloidosis AL is the final diagnosis in a large percentage of patients with renal significance. On the other hand, many of these young entities are syndromes that are based on a dynamic set of diagnostic criteria, challenging a timely diagnosis. Moreover, a specific risk score for progression is lacking. Despite the key role of the clinical laboratory in the diagnosis and prognosis of these patients, information about laboratory biomarkers is limited. Besides, the evidence accumulated for many of these entities is scarce. Hence, national and international registries are stimulated. In particular, IgM MGCS deserves special attention. Until now, therapy is far from being standardized, and it should be planned on a risk and patient-adapted basis. Finally, a comprehensive and coordinated multidisciplinary approach is needed, and specific clinical trials are encouraged.

PURPOSE Patients with newly diagnosed multiple myeloma (NDMM) show heterogeneous outcomes, and approximately 60% of them are at intermediate-risk according to the Revised International Staging system (R-ISS), the standard-of-care risk stratification model. Moreover, chromosome 1q gain/amplification (1q+) recently proved to be a poor prognostic factor. In this study, we revised the R-ISS by analyzing the additive value of each single risk feature, including 1q+. PATIENTS AND METHODS The European Myeloma Network, within the HARMONY project, collected individual data from 10,843 patients with NDMM enrolled in 16 clinical trials. An additive scoring system on the basis of top features predicting progression-free survival (PFS) and overall survival (OS) was developed and validated. RESULTS In the training set (N = 7,072), at a median follow-up of 75 months, ISS, del(17p), lactate dehydrogenase, t(4;14), and 1q+ had the highest impact on PFS and OS. These variables were all simultaneously present in 2,226 patients. A value was assigned to each risk feature according to their OS impact (ISS-III 1.5, ISS-II 1, del(17p) 1, high lactate dehydrogenase 1, t(4;14) 1, and 1q+ 0.5 points). Patients were stratified into four risk groups according to the total additive score: low (Second Revision of the International Staging System [R2-ISS]-I, 19.2%, 0 points), low-intermediate (II, 30.8%, 0.5-1 points), intermediate-high (III, 41.2%, 1.5-2.5 points), high (IV, 8.8%, 3-5 points). Median OS was not reached versus 109.2 versus 68.5 versus 37.9 months, and median PFS was 68 versus 45.5 versus 30.2 versus 19.9 months, respectively. The score was validated in an independent validation set (N = 3,771, of whom 1,214 were with complete data to calculate R2-ISS) maintaining its prognostic value. CONCLUSION The R2-ISS is a simple prognostic staging system allowing a better stratification of patients with intermediate-risk NDMM. The additive nature of this score fosters its future implementation with new prognostic variables.

Background. The Revised International Staging system (R-ISS) is the standard risk stratification model used for newly diagnosed (ND) multiple myeloma (MM) (Palumbo et al. JCO 2015). R-ISS identifies 3 groups of patients (pts) with different PFS and OS. However, 60% of pts are considered as intermediate-risk (R-ISS II), possibly including pts with different risk of progression/death. Recently, 1q copy number alterations (CNAs), which were not included in the R-ISS, proved to be a poor prognostic factor in NDMM pts. The European Myeloma Network (EMN), under the umbrella of the HARMONY project, collected more than 7000 patient data from European clinical trials. The aim of this analysis is to revise the R-ISS risk stratification model, by analyzing the prognostic value of each single baseline risk feature, including 1q CNAs, to improve prognostication in NDMM pts. Methods. Data from 15 European clinical trials enrolling NDMM pts from 2005 to 2014 were collected through EMN and registered in HARMONY platform. HARMONY is a European public-private partnership focusing on hematologic malignancies with unmet medical needs, including MM. OMOP Common Data Model was used to harmonize data. All pts received an immunomodulatory agent (IMiD) and/or a proteasome inhibitor (PI) upfront. In a multivariate Cox regression analysis adjusted for age, sex and therapy, we evaluated the impact of each risk feature on overall survival (OS) and progression-free survival (PFS). The hazard of death conferred by the most significant variables was used to create an additive risk score. Results. 7077 NDMM pts were registered in the HARMONY platform and included in the analysis. Data were mature with a median follow-up of 75 months; median age was 62 years. The majority of pts were transplant-eligible (65%). 40% of the pts received IMiDs only, 15% PIs only, 46% both drug classes during their first-line treatment. In a multivariate Cox model, ISS (II vs I HR 1.55 p These prognostic variables were simultaneously present in 2227 pts and the most frequent reason of exclusion of the remaining pts was 1q CNAs that was missing in some of the trials. We exploited the OS impact of these risk features in pts with complete data to create an additive scoring system (Table 1). Pts were then stratified into 4 groups: Low [(n=429 (19.3%), score 0)], Low-Intermediate [(n=686 (30.8%), score 0.5-1], Intermediate-High [(n=917 (41.2%), score 1.5-2.5] and High [(n=195 (8.8%), score 3-5]. Each group showed significantly different OS (Figure 1A) and PFS (Figure 1B). Median OS was not reached vs 109.2 vs 68.5 vs 37.9 months and median PFS was 68 vs 45.5 vs 30.2 vs 19.9 months in the above 4 risk groups, respectively. With this new stratification model, R-ISS stage II pts (n=1372) were better distributed into Low-Intermediate (n=517), Intermediate-High (n=811) and High risk (n=44) groups, confirming that this wide group included heterogeneous pts with a different risk of progression and/or death. This new risk stratification maintained its prognostic value in subgroup analysis of transplant-eligible and transplant-ineligible pts and in pts receiving IMiDs, PIs or both. Conclusion. This analysis on a large number of patient data collected thanks to a well-established European collaboration demonstrated that the existing R-ISS stratification model may be improved. This additive scoring system based on the impact of single risk features could be the future risk stratification model for NDMM, so called "R2-ISS". About half of the pts can be classified as Low or Low-Intermediate risk and about half of the pts can be classified as Intermediate-High or High risk, representing an opportunity to design risk-adapted approaches in a meaningful number of pts. Moreover, such additive risk score easily allows the inclusion of new prognostic variables in the future as they continue to emerge. The inclusion of new patient data is ongoing, and validation in an independent cohort is planned. Disclosures D'Agostino: GSK: Membership on an entity's Board of Directors or advisory committees. Waage:Janssen: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy; Shire: Honoraria. Zamagni:Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Speakers Bureau; Takeda: Honoraria, Other: Travel, Accommodations, Expenses, Speakers Bureau; Celgene Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Speakers Bureau; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Speakers Bureau. Mateos:Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen-Cilag: Consultancy, Honoraria; PharmaMar-Zeltia: Consultancy; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie/Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Consultancy; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Larocca:Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria. van de Donk:Takeda: Other: Ad Board; Genentech: Other: Ad Board; Bayer: Other: Ad Board; BMS: Other: Ad Board, Research Funding; Amgen: Other: Ad Board, Research Funding; Celgene: Other: Ad Board, Research Funding; Novartis: Other: Ad Board; Janssen: Other: Ad Board, Research Funding. Cairns:Celgene, Amgen, Merck: Research Funding; Celgene: Other: Travel Support. Salwender:Takeda: Honoraria; Bristol-Myers Squibb/Celgene: Honoraria; Janssen-Cilag: Honoraria; Amgen: Honoraria; Oncopeptides: Honoraria; Sanofi: Honoraria; GlaxoSmithKline: Honoraria; AbbVie: Honoraria. Blade Creixenti:Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Dürig:Janssen: Consultancy; AbbVie: Consultancy; Celgene: Consultancy. Bringhen:Karyopharm: Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Zweegman:Sanofi: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Cavo:AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel accomodations, Speakers Bureau; GlaxoSmithKline: Honoraria, Speakers Bureau; Karyopharm: Honoraria; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel accomodations, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Goldschmidt:Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; Dietmar-Hopp-Foundation: Other: Grants and/or provision of Investigational Medicinal Product:; Molecular Partners: Research Funding; Merck Sharp and Dohme (MSD): Research Funding; Novartis: Honoraria, Research Funding; Johns Hopkins University: Other: Grants and/or provision of Investigational Medicinal Product; Chugai: Honoraria, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; Incyte: Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product:, Research Funding; University Hospital Heidelberg, Internal Medicine V and National Center for Tumor Diseases (NCT), Heidelberg, Germany: Current Employment; GlaxoSmithKline (GSK): Honoraria; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Grants and/or provision of Investigational Medicinal Product, Research Funding; Mundipharma GmbH: Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding. Cook:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; IQVIA: Research Funding; Sanofi: Consultancy; Amgen: Consultancy; Roche: Consultancy; Karyopharm: Consultancy. San-Miguel:Amgen, BMS, Celgene, Janssen, MSD, Novartis, Takeda, Sanofi, Roche, Abbvie, GlaxoSmithKline and Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees. Boccadoro:Sanofi: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; AbbVie: Honoraria; Mundipharma: Research Funding; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees. Sonneveld:Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Skyline Dx: Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy. OffLabel Disclosure: The presentation includes discussion of off-label use of a drug or drugs for the treatment of multiple myeloma.