Abstract: Background: CTCs may be responsible for MM spreading and accordingly, their numbers in peripheral blood (PB) could be a potential surrogate marker for the rate of dissemination and overall tumor burden in bone marrow (BM). In such case, CTCs may be a powerful biomarker of malignant transformation and disease aggressiveness. Aim: To investigate the clinical significance of CTCs in patients with smoldering (SMM), newly diagnosed (NDMM) and relapsed/refractory MM (RRMM), and to compare the transcriptional profile of CTCs across the disease spectrum. Methods: Next-generation flow (NGF) cytometry was used to assess the percentage of CTCs in PB of 1,157 patients: 316 with SMM, 650 with NDMM and 191 with RRMM. In each disease setting, patients were sub-classified into three groups with undetectable, low and high percentage of CTCs. Cutoffs were defined using maximally selected rank statistics adjusted for time to progression (TTP) in SMM and progression free survival (PFS) in NDMM/RRMM. A subset of SMM patients (n=86) was enrolled in GEM-CESAR. Transplant eligible (n=374) and ineligible (n=276) NDMM, as well as RRMM patients, were homogenously treated according to the GEM2012MENOS65, GEM-CLARIDEX and GEM-KYCYDEX clinical trials, respectively. In 40 patients (2 SMM, 33 NDMM and 5 RRMM) paired CTCs and BM tumor cells were FACSorted and their transcriptional profile was analyzed using RNAseq. Differentially expressed genes were investigated using DESeq2. Results: CTCs were detected in 248/316 (78%), 597/650 (92%) and 170/192 (89%) of SMM, NDMM and RRMM patients. Median CTC frequencies were: 0.001% (0.05 CTCs/µL), 0.01% (0.64 CTCs/µL) and 0.005% (0.22 CTCs/µL), respectively. There were 79 genes differentially expressed between patient-matched CTCs and BM tumor cells (e.g., FLNA, EMP3, LGALS9, MUC1). These were functionally related with TNFα signaling and inflammatory response (enriched in CTCs), as well as to cell cycle and MYC targets (enriched in BM tumor cells). Interestingly, the enrichment of these signatures in CTCs and BM tumor cells was progressively more pronounced from SMM to NDMM and RRMM. Altogether, these data suggest that the CTC-based dissemination potential peaks at the stage of NDMM, which could be related to greater inflammation in BM and cell cycle arrest driving tumor cell egression into PB. There were significant associations between the percentage of CTCs and the 2/20/20 IMWG risk model in SMM, the ISS in NDMM, and high-risk cytogenetics in all three-disease settings. Untreated SMM patients (n=230) with high CTC levels (≥0.02%) showed ultra-high risk of transformation vs those with low and undetectable CTCs (median TTP of 11 months vs not reached [NR] in both; P & lt; .0001). Notably, SMM patients with ≥0.02% CTCs enrolled in GEM-CESAR have not reached a median TTP; thus, early intervention abrogated the poor prognosis of high CTC levels. Transplant-eligible NDMM patients stratified by undetectable, low and high (≥0.2%) CTC levels showed median PFS of NR, 78 and 47 months, respectively (P & lt; .0001). Significant risk stratification was further observed in transplant ineligible NDMM (median PFS: NR, 31 and 14 months, respectively, P = .002) and RRMM (median PFS: NR, 24 and 7 months, respectively, P = .004). In untreated SMM, multivariate analysis of TTP including CTCs, serum M-component ( & gt;2 g/dL), sFLC ratio ( & gt;20) and BM plasma cells ( & gt;20%) selected CTCs as an independent prognostic factor (hazard ratio [HR]: 1.61, P = .015) together with the M-component and sFLC ratio. In NDMM, multivariate analysis of PFS including CTCs, BM plasma cells counts by morphology and flow cytometry, ISS, LDH, cytogenetics and transplant eligibility showed that high CTC levels had independent prognostic value (HR: 1.43, P = .003). Only the achievement of undetectable measurable residual disease (MRD) abrogated the poor prognosis of high CTC levels. Conclusions: This is the largest study investigating the role of CTCs in smoldering and active MM. Our results show that tumor cells are continuously trafficking in PB, possibly through a dynamic mechanism of egression that peaks in NDMM. Evaluation of CTCs in PB outperformed quantification of BM tumor burden in SMM and NDMM, and showed prognostic value in all three-disease stages. Thus, CTC assessment should be part of the diagnostic workup of MM. Early intervention in high risk SMM and undetectable MRD in NDMM may abrogate dismal outcomes associated with high CTC levels. Disclosures Puig: Amgen, Celgene, Janssen, Takeda: Consultancy; Celgene: Speakers Bureau; Celgene, Janssen, Amgen, Takeda: Research Funding; Amgen, Celgene, Janssen, Takeda and The Binding Site: Honoraria. Cedena: Janssen, Celgene and Abbvie: Honoraria. Oriol: GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, 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; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Sureda: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite, a Gilead Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; GSK: Consultancy, Honoraria, Speakers Bureau; Roche: Other: Support for attending meetings and/or travel; Bluebird: Membership on an entity's Board of Directors or advisory committees; Mundipharma: Consultancy; MSD: Consultancy, Honoraria, Speakers Bureau; BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support for attending meetings and/or travel, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support for attending meetings and/or travel, Research Funding, Speakers Bureau. De Arriba: Amgen: Consultancy, Honoraria; Glaxo Smith Kline: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; BMS-Celgene: Consultancy, Honoraria, Speakers Bureau. Moraleda: Pfizer: Other: Educational Grants, Research Funding; Sanofi: Other: Educational Grants, Research Funding; MSD: Other: Educational Grants, Research Funding; ROCHE: Consultancy, Honoraria, Other: Educational Grants, Research Funding; Takeda: Consultancy, Honoraria, Other: Educational Grants, Research Funding; Sandoz: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Other: Educational Grants, Research Funding; Gilead: Consultancy, Honoraria, Other: Educational Grants, Research Funding; Jazz Pharmaceuticals: Consultancy, Honoraria, Other: Educational Grants, Research Funding; NovoNordisk: Other: Educational Grants, Research Funding; Janssen: Other: Educational Grants, Research Funding; Celgene: Other: Educational Grants, Research Funding; Amgen: Other: Educational Grants, Research Funding. Terpos: GSK: Honoraria, Research Funding; Genesis: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Novartis: Honoraria; Janssen-Cilag: Consultancy, Honoraria, Research Funding; BMS: Honoraria; Amgen: Consultancy, Honoraria, Research Funding. Goldschmidt: Incyte: Research Funding; Adaptive Biotechnology: Consultancy; BMS: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Celgene: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Chugai: Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; GSK: Honoraria; Novartis: Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Johns Hopkins University: Other: Grant; Molecular Partners: Research Funding; MSD: Research Funding; Mundipharma: Research Funding; Dietmar-Hopp-Foundation: Other: Grant; Sanofi: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Takeda: Consultancy, Research Funding; Amgen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding. Avet-Loiseau: Adaptive Biotechnologies: 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; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: 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; 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, Membership on an entity's Board of Directors or advisory committees. Roccaro: AstraZeneca,: Research Funding; Amgen, Celgene, Janssen, Takeda: Membership on an entity's Board of Directors or advisory committees; Associazione Italiana per la Ricerca sul Cancro (AIRC): Research Funding; European Hematology Association: Research Funding; Fondazione Regionale per la Ricerca Biomedica (FRRB), Transcan-2 ERA-NET: Research Funding. Martinez-Lopez: Novartis: 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; Roche: 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; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: 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: 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; 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. Lahuerta: Celgene: Other: Travel accomodations and expenses; Celgene, Takeda, Amgen, Janssen and Sanofi: Consultancy. Ocio: Amgen: Consultancy, Honoraria; Bristol-Myers Squibb/Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria, Speakers Bureau; Sanofi: Consultancy, Honoraria; Karyopharm: Consultancy; MSD: Honoraria; Oncopeptides: Consultancy, Honoraria; Pfizer: Consultancy; Secura-Bio: Consultancy. Rosinol: Janssen, Celgene, Amgen and Takeda: Honoraria. Bladé Creixenti: Janssen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. Mateos: AbbVie: Honoraria; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bluebird bio: Honoraria; Takeda: 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; 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; Amgen: 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; Celgene - Bristol Myers Squibb: 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; Oncopeptides: Honoraria; Sea-Gen: Honoraria, Membership on an entity's Board of Directors or advisory committees. San-Miguel: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Karyopharm, Merck Sharpe & Dohme, Novartis, Regeneron, Roche, Sanofi, SecuraBio, and Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees. Paiva: Adaptive, Amgen, Bristol-Myers Squibb-Celgene, Janssen, Kite Pharma, Sanofi and Takeda: Honoraria; Bristol-Myers Squibb-Celgene, Janssen, and Sanofi: Consultancy; Celgene, EngMab, Roche, Sanofi, Takeda: Research Funding.

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: Patients with multiple myeloma (MM) carrying standard- or high-risk cytogenetic abnormalities (CAs) achieve similar complete response (CR) rates, but the later have inferior progression-free survival (PFS). This questions the legitimacy of CR as a treatment endpoint and represents a biological conundrum regarding the nature of tumor reservoirs that persist after therapy in high-risk MM. We used next-generation flow (NGF) cytometry to evaluate measurable residual disease (MRD) in MM patients with standard- vs high-risk CAs (n = 300 and 90, respectively) enrolled in the PETHEMA/GEM2012MENOS65 trial, and to identify mechanisms that determine MRD resistance in both patient subgroups (n = 40). The 36-month PFS rates were higher than 90% in patients with standard- or high-risk CAs achieving undetectable MRD. Persistent MRD resulted in a median PFS of ∼3 and 2 years in patients with standard- and high-risk CAs, respectively. Further use of NGF to isolate MRD, followed by whole-exome sequencing of paired diagnostic and MRD tumor cells, revealed greater clonal selection in patients with standard-risk CAs, higher genomic instability with acquisition of new mutations in high-risk MM, and no unifying genetic event driving MRD resistance. Conversely, RNA sequencing of diagnostic and MRD tumor cells uncovered the selection of MRD clones with singular transcriptional programs and reactive oxygen species–mediated MRD resistance in high-risk MM. Our study supports undetectable MRD as a treatment endpoint for patients with MM who have high-risk CAs and proposes characterizing MRD clones to understand and overcome MRD resistance. This trial is registered at www.clinicaltrials.gov as #NCT01916252.

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: 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: INTRODUCTION: There is expectation of using biomarkers to personalize treatment in MM. Yet, a successful treatment selection cannot be confirmed before 5 or 10 years of progression-free survival (PFS). Treatment individualization based on the probability of an individual patient to achieve undetectable MRD with a singular regimen, could represent a new model towards personalized treatment with fast assessment of its success. This idea has not been investigated previously. AIM: Develop a machine learning model to predict undetectable MRD in newly-diagnosed transplant-eligible MM patients, treated with a standard of care. METHODS: This study included a total of 278 newly-diagnosed and transplant-eligible MM patients treated with proteasome inhibitors, immunomodulatory drugs and corticosteroids. The training (n=152) and internal validation cohort (n=60) consisted of 212 active MM patients enrolled in the GEM2012MENOS65 trial. The external validation cohort was defined by 66 high-risk smoldering MM patients enrolled in the GEM-CESAR trial, which treatment differed only by the substitution of bortezomib by carfilzomib during induction and consolidation. RESULTS: We started by investigating patients' MRD status after VRD induction, HDT/ASCT and VRD consolidation according to their ISS and R-ISS, LDH levels, and cytogenetic alterations. Surprisingly, neither the ISS nor the R-ISS predicted significantly different MRD outcomes. Indeed, high LDH levels and del(17p13) were the only parameters associated with lower rates of undetectable MRD. Because these two features are relatively infrequent at diagnosis, we next aimed to evaluate other disease features and develop integrative, weighted and more effective models based on machine learning algorithms. Of 37 clinical and biological parameters evaluated, 17 were associated with MRD outcomes. These were subsequently modeled using logistic regression for machine learning classification, where the sum of the weighted coefficients multiplied by its input variable, is transformed into a probability outcome that ranges from 0 to 1 using a logit sigmoid function. The most effective model resulted from integrating cytogenetic [t(4;14) and/or del(17p13)], tumor burden (plasma cell [PC] clonality in bone marrow and CTCs in blood) and immune related (myeloid precursors, mature B cells, intermediate neutrophils, eosinophils, CD27 negCD38 pos T cells and CD56 brightCD27 neg NK cells) biomarkers. Of note, immune biomarkers displayed the highest coefficient weights and were determinant to predict patients' MRD status in this model. Data obtained for an individual patient can be substituted into our formula, which results in a numerical probability of achieving undetectable ( & gt;0.5) vs persistent ( & lt;0.5) MRD after treatment. If probability outcomes are & gt;0.685 or & lt;0.365 (observed in 102/212 patients), MRD outcomes are respectively predicted with higher confidence. Standard-confidence, high-confidence, and external validation predictions were accurate in 152/212 (71.7%), 85/102 (83.3%), and 48/66 (72.7%) patients respectively. Similarly, the external validation set exhibited a similar receiver operating characteristic (ROC) curve as the internal test set (AUC of 0.73 and 0.77 respectively). Patients predicted to achieve undetectable MRD using standard and high-confidence values showed longer PFS and overall survival (OS) than those with probability of persistent MRD. In fact, patients with & gt;0.687 probability of achieving undetectable MRD showed 86% PFS and 94% OS at five years, whereas those in whom persistent MRD was predicted ( & lt;0.365), median PFS was 44 months, and 69% OS was observed at five years. These data indicate that the combination of cytogenetics, tumor burden in bone marrow plus peripheral blood, and immune profiling, may also be explored to identify a subset of patients that have a singular disease biology and long-term survival. CONCLUSION: We demonstrated that it is possible to predict patients' MRD status with significant accuracy, using an integrative, weighted model based on machine learning algorithms. Although immune biomarkers are not commonly used, the raw data from which these can be developed is generally obtained in diagnostic laboratories using flow cytometry to screen for PC clonality. Furthermore, we made the model available to facilitate its use in clinical practice at www.MRDpredictor.com. Disclosures Puig: Celgene, Janssen, Amgen, Takeda: Research Funding; Celgene: Speakers Bureau; Amgen, Celgene, Janssen, Takeda: Consultancy; Amgen, Celgene, Janssen, Takeda and The Binding Site: Honoraria. Cedena: Janssen, Celgene and Abbvie: Honoraria. Oriol: Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, 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; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. De Arriba: Amgen: Consultancy, Honoraria; Glaxo Smith Kline: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; BMS-Celgene: Consultancy, Honoraria, Speakers Bureau. Martínez-López: Janssen, BMS, Novartis, Incyte, Roche, GSK, Pfizer: Consultancy; Roche, Novartis, Incyte, Astellas, BMS: Research Funding. Lahuerta: Celgene: Other: Travel accomodations and expenses; Celgene, Takeda, Amgen, Janssen and Sanofi: Consultancy. Rosinol: Janssen, Celgene, Amgen and Takeda: Honoraria. Bladé Creixenti: Janssen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. Mateos: Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria; Bluebird bio: Honoraria; GSK: Honoraria; Sanofi: 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; 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; Adaptive Biotechnologies: 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; Oncopeptides: 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; Oncopeptides: Honoraria; Janssen: 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. San-Miguel: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Karyopharm, Merck Sharpe & Dohme, Novartis, Regeneron, Roche, Sanofi, SecuraBio, and Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees. 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.

Abstract: Infections remain a common complication in patients with multiple myeloma (MM) and are associated with morbidity and mortality. A risk score to predict the probability of early severe infection could help to identify the patients that would benefit from preventive measures. We undertook a post hoc analysis of infections in four clinical trials from the Spanish Myeloma Group, involving a total of 1347 patients (847 transplant candidates). Regarding the GEM2010  〉  65 trial, antibiotic prophylaxis was mandatory, so we excluded it from the final analysis. The incidence of severe infection episodes within the first 6 months was 13.8%, and majority of the patients experiencing the first episode before 4 months (11.1%). 1.2% of patients died because of infections within the first 6 months (1% before 4 months). Variables associated with increased risk of severe infection in the first 4 months included serum albumin ≤30 g/L, ECOG  〉  1, male sex, and non-IgA type MM. A simple risk score with these variables facilitated the identification of three risk groups with different probabilities of severe infection within the first 4 months: low-risk (score 0–2) 8.2%; intermediate-risk (score 3) 19.2%; and high-risk (score 4) 28.3%. Patients with intermediate/high risk could be candidates for prophylactic antibiotic therapies.

Abstract: Assessing measurable residual disease (MRD) has become standard with many tumors, but the clinical meaning of MRD in multiple myeloma (MM) remains uncertain, particularly when assessed by next-generation flow (NGF) cytometry. Thus, we aimed to determine the applicability and sensitivity of the flow MRD-negative criterion defined by the International Myeloma Working Group (IMWG). PATIENTS AND METHODS In the PETHEMA/GEM2012MENOS65 trial, 458 patients with newly diagnosed MM had longitudinal assessment of MRD after six induction cycles with bortezomib, lenalidomide, and dexamethasone (VRD), autologous transplantation, and two consolidation courses with VRD. MRD was assessed in 1,100 bone marrow samples from 397 patients; the 61 patients without MRD data discontinued treatment during induction and were considered MRD positive for intent-to-treat analysis. The median limit of detection achieved by NGF was 2.9 × 10 −6 . Patients received maintenance (lenalidomide ± ixazomib) according to the companion PETHEMA/GEM2014MAIN trial. RESULTS Overall, 205 (45%) of 458 patients had undetectable MRD after consolidation, and only 14 of them (7%) have experienced progression thus far; seven of these 14 displayed extraosseous plasmacytomas at diagnosis and/or relapse. Using time-dependent analysis, patients with undetectable MRD had an 82% reduction in the risk of progression or death (hazard ratio, 0.18; 95% CI, 0.11 to 0.30; P 〈 .001) and an 88% reduction in the risk of death (hazard ratio, 0.12; 95% CI, 0.05 to 0.29; P 〈 .001). Timing of undetectable MRD (after induction v intensification) had no impact on patient survival. Attaining undetectable MRD overcame poor prognostic features at diagnosis, including high-risk cytogenetics. By contrast, patients with Revised International Staging System III status and positive MRD had dismal progression-free and overall survivals (median, 14 and 17 months, respectively). Maintenance increased the rate of undetectable MRD by 17%. CONCLUSION The IMWG flow MRD-negative response criterion is highly applicable and sensitive to evaluate treatment efficacy in MM.