Abstract: The International Staging System (ISS) and the Revised International Staging System (R-ISS) are commonly used prognostic scores in multiple myeloma (MM). These methods have significant gaps, particularly among intermediate-risk groups. The aim of this study was to improve risk stratification in newly diagnosed MM patients using data from three different trials developed by the Spanish Myeloma Group. For this, we applied an unsupervised machine learning clusterization technique on a set of clinical, biochemical and cytogenetic variables, and we identified two novel clusters of patients with significantly different survival. The prognostic precision of this clusterization was superior to those of ISS and R-ISS scores, and appeared to be particularly useful to improve risk stratification among R-ISS 2 patients. Additionally, patients assigned to the low-risk cluster in the GEM05 over 65 years trial had a significant survival benefit when treated with VMP as compared with VTD. In conclusion, we describe a simple prognostic model for newly diagnosed MM whose predictions are independent of the ISS and R-ISS scores. Notably, the model is particularly useful in order to re-classify R-ISS score 2 patients in 2 different prognostic subgroups. The combination of ISS, R-ISS and unsupervised machine learning clusterization brings a promising approximation to improve MM risk stratification.

Abstract: Introduction: Carfilzomib dosed at 56 mg/m2 twice a week in combination with dexamethasone (Kd) is a standard of care for RRMM after 1-3 prior lines (PL) based on the ENDEAVOR study. Later, the ARROW study showed Kd dosed at 70 mg/m2 weekly to be superior to Kd dosed at 27 mg/m2 twice a week on RRMM patients (pts) after 2-3 PL. On the other side, Cyclophosphamide is an alkylating agent that has been widely combined with proteasome inhibitors and immunomodulatory drugs in MM, improving their efficacy with a good safety profile. In this phase 2 randomized study, we have compared Kd plus cyclophosphamide (KCyd) with Kd in RRMM after 1-3PL, both with K dosed weekly at 70 mg/m2. Patients and methods: RRMM after 1-3 PL of therapy were included in the trial. Consistently with the ENDEAVOR population, previous therapy with proteasome inhibitors was allowed but refractory patients were excluded. Pts were randomized 1:1 to receive K at a dose of 70 mg/m2 iv on days 1, 8 and 15 plus dexamethasone at a dose of 20 mg PO the day on and the day after K plus/minus KCyd at a dose of 300 mg/m2 IV on days 1, 8 and 15 of each 28 days-cycle, as continuous treatment until progressive disease or unacceptable toxicity. The primary endpoint was PFS and key secondary endpoints included response rates, safety profile, and OS. Results: Between January 2018 and February 2020, 198 RRMM pts were included. 97 pts were randomized to KCyd and 101 to Kd. The baseline characteristics of the patients were well balanced between both groups. The median age was 70 years, and 70% and 28% of pts were older than 65 and 75. The median number of PL was one; 61% of pts had received 1 prior line. 94% and 92% of patients had been exposed to bortezomib in the KCyd and Kd and all of them were sensitive. 72% and 67% of patients had been exposed to IMiD's and 51% and 55% of them were IMiD's-refractory in the KCyd and Kd. Only 4 and 6 patients in KCyd and Kd, had received anti-CD38 antibodies being all refractory. After a median f/u of 15.6 months, median PFS was 20.7 m and 15.2 m in KCyd and Kd (p=0.2). In pts after 1PL, median PFS has not been reached in any arm (p=0.4) and in patients after 2-3PL, KCyd resulted in a median PFS of 20.7 vs 11m for Kd (p=0.4). Of note, in the IMiD-refractory population, the addition of Cy to Kd resulted in a significant benefit in terms of PFS: 26.2 months vs 7.7 months in the Kd arm (p=0.01). OS is immature with 23 and 25 events so far in KCyd and Kd, respectively. The ORR was 78% for KCyd and 73% for Kd: 20% of patients in both arms achieved at least complete response, 33% and 28% very good partial response, respectively, and 25% partial response in both arms. The MRD-ve rate was 4% and 5%. As far as toxicity is concerned, neutropenia was the only hematological adverse event more frequently reported in KCyd compared with Kd, of any grade (24% vs 11%) and grade 3-4 (13% vs 7%). This did not translate into more infections and the rate was comparable in both arms (5% G3-4 in both arms). Thrombocytopenia of any grade and grade 3-4 occurred in 14%/1% and 18%/10% in KCyd/Kd. Cardiovascular events of any grade occurred in 22% and 30% of patients in KCyd and Kd. Nine pts in KCyd developed G3-4 cardiovascular events, these included atrial fibrillation (1pt), cardiac failure (2 pts), myocardial infarct (2 pts), and hypertension (4 pts). In the Kd arm, 11 patients developed G3-4 cardiovascular events and consisted of hypertension in most of them (9 pts). Conclusion: Cyclophosphamide added to Kd 70 mg/m2 weekly in RRMM pts after 1-3 PL prolonged the PFS as compared to Kd particularly in the lenalidomide-refractory population. The administration of K at a dose of 70 mg/m2 weekly was safe and more convenient and overall, the toxicity profile was manageable in both arms. Disclosures Mateos: Abbvie/Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; 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; Janssen-Cilag: Consultancy, Honoraria; PharmaMar-Zeltia: Consultancy; Sanofi: 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; 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; 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; Adaptive Biotechnologies: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Ocio:Janssen: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria; Asofarma: Honoraria; Sanofi: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Honoraria; GSK: Consultancy; MDS: Honoraria; Secura-Bio: Consultancy; Oncopeptides: Consultancy. Sureda Balari:Novartis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Roche: Honoraria; Takeda: Consultancy, Honoraria, Speakers Bureau; Sanofi: Consultancy, Honoraria; Merck Sharpe and Dohme: Consultancy, Honoraria, Speakers Bureau; Celgene/Bristol-Myers Squibb: Consultancy, Honoraria; BMS: Speakers Bureau; Incyte: Consultancy; Celgene: Consultancy, Honoraria; Gilead/Kite: Consultancy, Honoraria. Oriol:Celgene/Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees. Rosinol Dachs:Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria; Takeda: Honoraria; Sanofi: Honoraria. Blade Creixenti:Takeda: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. 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.

Abstract: In this randomized phase II study (GEM-KyCyDex, clinicaltrials gov. Identifier: NCT03336073), the combination of weekly carfilzomib 70 mg/m2, cyclophosphamide and dexamethasone (KCd) was compared to carfilzomib and dexamethasone (Kd) in relapsed/refractory multiple myeloma (RRMM) after 1-3 prior lines (PL). One hundred and ninety-seven 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 PL was one (range, 1-3). More than 90% of patients had previously been exposed to proteasome inhibitors, approximetely 70% to immunomodulators, and approximetely 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 lenalidomide-refractory population, the addition of cyclophosphamide to Kd resulted in a significant benefit in terms of PFS: 18.4 versus 11.3 months (hazard ratio =1.7, 95% confidence interval: 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 PL, but a significant benefit in PFS was observed with the triplet combination 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.

Abstract: 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

Abstract: VRD was effective and well tolerated before ASCT; 33.4% complete response/28.8% minimal residual disease–negative after 6 induction cycles. Responses deepened with VRD throughout induction and over the course of treatment with few discontinuations due to toxicity.

Abstract: Introduction: The GEM-CESAR trial is a potentially curative strategy for high-risk smoldering multiple myeloma (HRsMM) patients in which the primary endpoint is the assessment of bone marrow minimal residual disease negativity by next generation flow (NGF). However, alternative methods of tumor burden evaluation in serum, like Quantitative Immunoprecipitation Mass Spectrometry (QIP-MS), a polyclonal antibody-based technology to identify intact immunoglobulins, have been also evaluated. Patients and Methods: Ninety HRsMM patients included in the GEM-CESAR trial received six 4-weeks cycles of carfilzomib, lenalidomide and dexamethasone followed by high dose melphalan and ASCT and 2 further cycles of consolidation with the same regimen. All patients received maintenance with lenalidomide up to 2 years. SPEP and IFE were performed using standard procedures and MRD was analyzed by flow cytometry following EuroFlow recommendations. QIP-MS assessment has been previously described (1) and allowed us the characterization of the isotype of each Ig trough immunoprecipitation with paramagnetic beads as well as the measurement of the molecular mass of each Ig for each specific patient, with enough precision and accuracy to establish clonality. Standard response assignment was carried out as per the IMWG guidelines. Results: First, we confirmed the higher sensitivity of QIP-MS to identify the presence of a serum M-spike as compared to conventional protein immunofixation electrophoresis methods. Amongst patients in CR, QIP-MS identified the M-spike in 18/30 (60%) post-induction, 18/47(38%) post-ASCT and 25/58(43%) post-consolidation. Interestingly, similar results were obtained with MRD-NGF post-induction [17/30(57%)] and post-ASCT [15/47(32%)] although the positive rate post-consolidation [15/58(26%)] was higher with QIP-MS. Then, we analyzed the overall concordance between the results obtained with QIP-MS and MRD-NGF at the three timepoints of disease evaluation, finding an overall concordance of 81% post-induction (n=76), 70% post-transplant (n=76) and 68% post-consolidation (n=77). Thus, when compared to the results of MRD-NGF, QIP-MS demonstrated sensitivities of 100%, 79% and 77% post-induction, post-ASCT and post-consolidation, and negative predictive values (NPV) of 100%, 79% and 82% at each respective time-point. (P & lt; 0,0001; P = 0,0004; P = =,0012) Evaluation of discrepant cases showed 14 out of 22 MRD-NGF-negative patients post-induction for whom QIP-MS identified a M-spike; in some cases (i.e. IgG MM isotype) this may be related to a longer immunoglobulin half-life. There were no cases with detectable disease by NGF but QIP-MS negative. By contrast, post-ASCT, QIP-MS was negative in seven MRD-positive patients, two of whom became MRD-NGF-negative after consolidation; at last follow-up, none of them have progressed. On the other hand, sixteen patients with negative MRD-NGF after ASCT had a detectable M-spike by mass spectrometry. Of note, the M-spike became undetectable after consolidation in six out of these 16 patients. Post-consolidation, there were 7 patients in which MRD-NGF was positive but QIP-MS negative: MRD evaluation during maintenance is pending but none of them have so far progressed. By contrast, there were 18 patients with the M-spike detectable by QIP-MS but MRD-NGF negative: follow-up of these patients will address their outcome but, the only patient that has progressed so far had MRD-NGF negative post-induction, becoming positive post-transplant and consolidation, but the M-spike was detectable by QIP-MS throughout. Conclusions: M-spike monitoring by QIP-MS shows a moderate concordance with the MRD assessment by NGF in this group of HRsMM homogeneously treated. Longer follow-up will allow us to unravel the outcome of discordant cases and to define the specificity of QIP-MS and its complementary value to NGF. North S, Barnidge D, Brusseau S, Patel R, Haselton M, Du Chateau B, et al. QIP-MS: A specific, sensitive, accurate, and quantitative alternative to electrophoresis that can identify endogenous m-proteins and distinguish them from therapeutic monoclonal antibodies in patients being treated for multiple myeloma. Clinica Chimica Acta 2019;493:S433. Disclosures Puig: Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding; The Binding Site: Honoraria; Takeda, Amgen: Consultancy, Honoraria. Mateos:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria; GSK: Membership on an entity's Board of Directors or advisory committees; Pharmamar: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; EDO: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Paiva:Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, Novartis, Roche, and Sanofi; unrestricted grants from Celgene, EngMab, Sanofi, and Takeda; and consultancy for Celgene, Janssen, and Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau. Rodriguez Otero:Takeda: Consultancy; Kite Pharma: Consultancy; BMS: Honoraria; Celgene Corporation: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria. Oriol:Celgene, Amgen, Takeda, Jansse: Consultancy, Speakers Bureau. Rios:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Alegre:Celgene, Amgen, Janssen, Takeda: Membership on an entity's Board of Directors or advisory committees. de la Rubia:AbbVie: Consultancy; Janssen: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Takeda: Consultancy. De Arriba:Amgen: Consultancy, Honoraria; Takeda: Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Ocio:Mundipharma: Research Funding; Pharmamar: Consultancy; Amgen: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; AbbVie: Consultancy; Takeda: Consultancy, Honoraria; Array Pharmaceuticals: Research Funding; Sanofi: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy; Novartis: Consultancy, Honoraria; BMS: Honoraria. Bladé:Janssen, Celgene, Amgen, Takeda: Membership on an entity's Board of Directors or advisory committees; Irctures: Honoraria. Lahuerta:Takeda, Amgen, Celgene and Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract: The existence of patients with multiple myeloma (MM) and light-chain (AL) amyloidosis who present with a monoclonal gammopathy of undetermined significance (MGUS)–like phenotype has been hypothesized, but methods to identify this subgroup are not standardized and its clinical significance is not properly validated. PATIENTS AND METHODS An algorithm to identify patients having MGUS-like phenotype was developed on the basis of the percentages of total bone marrow (BM) plasma cells (PC) and of clonal PC within the BM PC compartment, determined at diagnosis using flow cytometry in 548 patients with MGUS and 2,011 patients with active MM. The clinical significance of the algorithm was tested and validated in 488 patients with smoldering MM, 3,870 patients with active MM and 211 patients with AL amyloidosis. RESULTS Patients with smoldering MM with MGUS-like phenotype showed significantly lower rates of disease progression (4.5% and 0% at 2 years in two independent series). There were no statistically significant differences in time to progression between treatment versus observation in these patients. In active newly diagnosed MM, MGUS-like phenotype retained independent prognostic value in multivariate analyses of progression-free survival (PFS; hazard ratio [HR], 0.49; P = .001) and overall survival (OS; HR, 0.56; P = .039), together with International Staging System, lactate dehydrogenase, cytogenetic risk, transplant eligibility, and complete remission status. Transplant-eligible patients with active MM with MGUS-like phenotype showed PFS and OS rates at 5 years of 79% and 96%, respectively. In this subgroup, there were no differences in PFS and OS according to complete remission and measurable residual disease status. Application of the algorithm in two independent series of patients with AL predicted for different survival. CONCLUSION We developed an open-access algorithm for the identification of MGUS-like patients with distinct clinical outcomes. This phenotypic classification could become part of the diagnostic workup of MM and AL amyloidosis.

Abstract: Background: Within the spectrum of monoclonal gammopathies, there are various subgroups with unique biological and clinical profiles. Namely, the presence of multiple myeloma (MM) and light-chain amyloidosis (AL) pts with MGUS-like phenotype has been hypothesized, but the criteria to identify this subgroup are poorly defined and lack clinical validation. Aim: Develop an algorithm based on a large flow cytometry dataset across the spectrum of monoclonal gammopathies, for automated identification of MM and AL pts with MGUS-like phenotype. Methods: This study included 5,114 pts with monoclonal gammopathies and available flow cytometry data on the frequency of bone marrow (BM) plasma cells (PC) and the percentages of normal and clonal PC within the BM PC compartment, at diagnosis. An algorithm to classify pts with MGUS-like phenotype was developed based on these three parameters, obtained from 548 MGUS, 393 smoldering MM (SMM) and 2,011 MM pts. Newly diagnosed MM pts were homogeneously treated according to the GEM2000 (n = 486), GEM2005MENOS65 (n = 330), GEM2005MAS65 (n = 239), GEM2010MAS65 (n = 230), GEM2012MENOS65 (n = 450) and CLARIDEX (n = 276) protocols. The prognostic value of the MGUS-like phenotype was validated in 96 SMM pts studied in Arkansas and 1,859 MM pts treated outside clinical trials in Czech Republic. The clinical significance of the algorithm was investigated in two independent series of Spanish (n = 102) and Italian (n = 105) AL pts. Results: The frequency of BM PC and of normal and clonal PC within the BM PC compartment were used to plot MGUS, SMM and MM pts in a principal component analysis (PCA). Lines defining 1.5 standard deviations of MGUS and MM pts were used as reference to classify each of the 5,114 cases. Once plotted against the dataset, individual pts were classified as MGUS-, intermediate- or MM-like, if their location in the PCA fell inside the MGUS, the overlapping or the MM reference lines, respectively. In the training SMM series, patient classification into MGUS-, intermediate- and MM-like phenotype resulted in significantly different rates of disease progression (0%, 54% and 66% at 5y, respectively; P & lt; .001). These results were validated in the Arkansas series (8%, 27% and 71% at 5y, respectively; P & lt; .001). Only 5% of SMM pts with high-risk disease according to Mayo or PETHEMA criteria had an MGUS-like phenotype, and these had virtually no risk of progression at 5y. In the training MM series, pts with MGUS-like phenotype showed significantly longer progression free (PFS) and overall survival (OS) vs the remaining pts. Median PFS was 10y vs 3y (hazard ratio [HR]: 0.46, P & lt; .001) and median OS was not reached (NR) vs 6.5y (HR: 0.48, P & lt; .001), respectively. These results were validated in the Czech Republic series with significant differences in PFS (HR: 0.45, P & lt; .001) and OS (HR: 0.38, P & lt; .001) between MGUS-like vs other MM pts. MGUS-like classification in the training MM series retained independent prognostic value in multivariate analyses of PFS (HR: 0.48, P & lt; .001) and OS (HR: 0.54, P = .033), together with ISS, LDH, cytogenetics, induction regimen, transplant-eligibility and complete remission (CR). MGUS-like pts showed similar PFS (P = .932) and OS (P = .285) regardless of having standard vs high risk cytogenetics. Notably, MGUS-like transplant-eligible MM pts treated with proteasome inhibitors, immunomodulatory drugs and corticoids during induction showed PFS and OS rates at 5y of 86% and 96%, respectively. Differences in PFS among MGUS-like MM pts achieving ≥CR vs & lt;CR were not significant (median of 13y vs 9y, respectively; P = .122), which suggests that attaining CR is not mandatory to reach long-term survival in this subgroup of pts, treated with fixed-duration regimens. Classification of AL pts into the MGUS-, intermediate- and MM-like phenotype resulted in significantly different PFS in the Spanish (median of 28, 20 and 1 months, respectively; P = .001) and Italian (median 32, 11 and 3 months, respectively; P & lt; .001) cohorts. Conclusions: We developed an algorithm that can be readily installed in clinical flow cytometry software, and requires three parameters that are routinely assessed at screening. Patient' automated classification using the algorithm was validated in large series across the spectrum of monoclonal gammopathies. Because pts with MGUS-like phenotype have a distinct clinical behavior, their identification could become part of the diagnostic workup in SMM, MM and AL. Disclosures Cedena: Janssen, Celgene and Abbvie: Honoraria. Milani: Celgene: Other: Travel support; Janssen-Cilag: Honoraria. Cordon: Cytognos SL: Research Funding. Oriol: Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy. de la Rubia: Amgen, Bristol Myers Squibb,: Honoraria, Speakers Bureau; Celgene, Takeda, Janssen, Sanofi: Honoraria; Ablynx/Sanofi: Consultancy; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; AbbVie: Consultancy; Bristol Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Accommodations; GSK: Consultancy; Takeda: Consultancy; Sanofi: Membership on an entity's Board of Directors or advisory committees. De Arriba: Amgen: Consultancy, Honoraria; Glaxo Smith Kline: Consultancy, Honoraria; BMS-Celgene: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau. Cabañas: Janssen: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Sanofi: Honoraria. Gonzalez De La Calle: Celgene-BMS, Janssen, Amgen: Honoraria. Rodríguez-Otero: Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Membership on an entity's Board of Directors or advisory committees; Abbvie: 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; Kite: 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; GlaxoSmithKline: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel and other expenses. Hajek: Pharma MAR: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Jimenez-Zepeda: BMS, Amgen, Takeda, Janssen: Honoraria. Palladini: Janssen Global Services: Honoraria, Other: advisory board fees; Pfizer: Honoraria; Siemens: Honoraria. Rosinol: Janssen, Celgene, Amgen and Takeda: Honoraria. Bladé Creixenti: Janssen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. Martínez-López: Janssen, BMS, Novartis, Incyte, Roche, GSK, Pfizer: Consultancy; Roche, Novartis, Incyte, Astellas, BMS: Research Funding. Mateos: Roche: 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; Regeneron: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene - Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sea-Gen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bluebird bio: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria; Oncopeptides: Honoraria. San-Miguel: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Karyopharm, Merck Sharpe & Dohme, Novartis, Regeneron, Roche, Sanofi, SecuraBio, Takeda: Consultancy, Other: Advisory board. Paiva: Bristol-Myers Squibb-Celgene, Janssen, and Sanofi: Consultancy; Adaptive, Amgen, Bristol-Myers Squibb-Celgene, Janssen, Kite Pharma, Sanofi and Takeda: Honoraria; Celgene, EngMab, Roche, Sanofi, Takeda: Research Funding.