Search

Since the publication of the Revised European-American Classification of Lymphoid Neoplasms in 1994, subsequent updates of the classification of lymphoid neoplasms have been generated through iterative international efforts to achieve broad consensus among hematopathologists, geneticists, molecular scientists, and clinicians. Significant progress has recently been made in the characterization of malignancies of the immune system, with many new insights provided by genomic studies. They have led to this proposal. We have followed the same process that was successfully used for the third and fourth editions of the World Health Organization Classification of Hematologic Neoplasms. The definition, recommended studies, and criteria for the diagnosis of many entities have been extensively refined. Some categories considered provisional have now been upgraded to definite entities. Terminology for some diseases has been revised to adapt nomenclature to the current knowledge of their biology, but these modifications have been restricted to well-justified situations. Major findings from recent genomic studies have impacted the conceptual framework and diagnostic criteria for many disease entities. These changes will have an impact on optimal clinical management. The conclusions of this work are summarized in this report as the proposed International Consensus Classification of mature lymphoid, histiocytic, and dendritic cell tumors.

The panel would like to acknowledge the work of Klizia Marinoni and Delanie Young, from the Scientific and Medical Division at ESMO, for the project coordination and editorial assistance. None declared. CB reports honoraria from Roche/Genentech, Janssen, BeiGene, Novartis, Pfizer, Incyte, AbbVie, Gilead Sciences, Celltrion, MorphoSys, Regeneron; he reports consulting or advisory role: Gilead Sciences, Janssen, Roche, Pfizer, BeiGene, Celltrion, AbbVie, Incyte, Regeneron, MorphoSys, Novartis; he reports speaker's engagement: Roche, Janssen, BeiGene, Celltrion, AbbVie, Pfizer, Gilead Sciences; he reports research funding: Roche/Genentech, Janssen, Celltrion, Merck Sharp & Dohme (MSD), Pfizer, Amgen. MD reports honoraria as Advisory Board Member of AstraZeneca, Bayer, BeiGene, Celgene, Genmab, Gilead, Incyte, Janssen, Lilly, MorphoSys, Novartis, Roche; he reports honoraria for speaker's engagement from Amgen, AstraZeneca, Bayer, Celgene, Gilead, Janssen, Novartis, Roche; he reports institutional research grants from AbbVie, Bayer, Gilead, Celgene, Janssen, Roche. AA-L has declared no conflicts of interest. JA reports personal financial interests as advisory board and invited speaker from Incyte, advisory board from Mallinckrodt, advisory board and invited speaker from Novartis, advisory board and invited speaker from Pfizer; she reports non-financial interests as principal investigator from Incyte, principal investigator from Novartis. LA received advisory honoraria from Roche, Celgene, Janssen-Cilag, Verastem, Eusa Pharma, Incyte, ADC Therapeutics and Gilead; research support from Gilead, and travel expenses from Roche, Celgene, Janssen-Cilag, and Eusa Pharma; speakers bureau from Novartis. CB has declared no conflicts of interest. LB reports Advisory Committee activities for AbbVie, Amgen, Astellas, Bristol Myers Squibb (BMS), Celgene, Daiichi Sankyo, Gilead, Hexal, Janssen, Jazz Pharmaceuticals, Menarini, Novartis, Pfizer, Sanofi, Seattle Genetics and has research support from Bayer and Jazz Pharmaceuticals. PC has declared no conflicts of interest. MGDP has declared no conflicts of interest. MD reports personal fees from Amgen, personal fees from Takeda, personal fees from Janssen, personal fees from BeiGene, personal fees from BMS, outside the submitted work. SD reports personal financial interests as advisory board, invited speaker, fellow funding, and coordinating PI from BeiGene, writing engagement from Karger, advisory board and coordinating PI from Sanofi, funding, and other from Janssen; she reports non-financial interests as advisory role at British Society for Haematology Lymphoma Special Interest Group, advisory role at Lymphoma Action, member of board of directors at WMUK Charity. HTE has declared no conflicts of interest. RF reports honoraria for advisory boards and/or speaker bureau from Janssen, Gilead, AbbVie, Amgen, Novartis, Roche, Incyte, Pfizer, all outside the submitted work. PG reports grants and personal fees from AbbVie, grants and personal fees from Acerta/AstraZeneca, personal fees from BeiGene, personal fees from Celgene/Juno/BMS, grants and personal fees from Janssen, personal fees from Lilly/Loxo, personal fees from MEI, personal fees from Roche, personal fees from Sanofi, personal fees from ArQule/MSD, outside the submitted work;, MGdS reports grants, personal fees, non-financial support and other from Gilead Sciences, grants from AstraZeneca, personal fees, non-financial support, and other from Janssen Cilag, personal fees and non-financial support from Roche, non-financial support from AbbVie, personal fees and non-financial support from BMS, personal fees and non-financial support from MSD, personal fees and non-financial support from Takeda, personal fees from Novartis, personal fees from ADC Therapeutics, outside the submitted work. JG reports personal fees from AbbVie, grants and personal fees from AstraZeneca, grants and personal fees from BMS/Celgene, grants and personal fees from Janssen, personal fees from Kite/Gilead, personal fees from MorphoSys, personal fees from Novartis, personal fees from TG Therapeutics, outside the submitted work. RH has had a consultant or advisory relationship with Janssen, Amgen, Celgene, AbbVie, BMS, Novartis, PharmaMar, and Takeda; has received honoraria from Janssen, Amgen, Celgene, BMS, PharmaMar, and Takeda; has received research funding from Janssen, Amgen, Celgene, BMS, Novartis, and Takeda. CH reports grants and personal fees from Novartis, grants and personal fees from BMS, personal fees from Sierra Oncology, personal fees from CTI pharmaceuticals, personal fees from Jannsen, personal fees from Geron, grants and personal fees from AOP Orphan Pharma, personal fees from Galecto, grants, personal fees and other from Constellation, outside the submitted work. MH reports personal fees from Novartis, personal fees from Pfizer, personal fees from Roche, personal fees from AbbVie, personal fees from Daiichi Sankyo, personal fees from Bayer Pharma AG, personal fees from Jazz Pharmaceuticals, personal fees from BMS, personal fees from Tolremo, outside the submitted work. BK has received honoraria for lectures from Ipsen, Novartis and MSD (all outside of the submitted work). J-JK reports consulting fees and honoraria from Novartis, consulting fees from AbbVie, honoraria from AOP Orphan Pharma, participation on a monitoring board or advisory board from BMS/Celgene, participation on a monitoring board or advisory board from Incyte. NK reports grants and honoraria from Neovii, honoraria from Sanofi, grants and honoraria from Jazz, grants and honoraria from Celgene, grants and honoraria from Riemser, honoraria from Gilead/Kite, honorarium from AOP Oprhan Pharma, grants and honorarium from Novartis, honorarium from Amgen. PM reports personal fees from Celgene, Amgen, Janssen, AbbVie, Sanofi, outside the submitted work. JP has declared no conflicts of interest. FP has declared no conflicts of interest. DR received honoraria from Incyte, Novartis Pharma, Pfizer; clinical trial steering committee membership: Novartis; membership on advisory boards: Incyte, Novartis Pharma, Pfizer. J-MR reports grants and honoraria from Novartis, Amgen, Pfizer, Takeda, Incyte, and Servier. TR has declared no conflicts of interest. JF-M reports consulting and advisory boards honoraria (received by CUN) from AbbVie, Amgen, BMS, Celgene, Janssen, GlaxoSmithKline, Karyopharm, MSD, Novartis, Takeda, Sanofi, SecuraBio, Regeneron, Roche, outside the submitted work. VS has declared no conflicts of interest. GFS reports personal fees and other from AbbVie, other from Amgen, other from Astellas, other from Boehringer-Ingelheim, grants, personal fees and other from Celgene, other from Helsinn Healthcare, grants, personal fees, and other from Janssen-Cilag, grants and other from Novartis, other from Onconova, grants, personal fees and other from Roche, and other from Takeda, outside the submitted work. PS reports honoraria from Amgen, Celgene, Janssen, Karyopharm, SkylineDx, Takeda, and research support from Celgene, Janssen, Amgen, Takeda, BMS, SkylineDx, Karyopharm, all outside the submitted work. MvL-T has received travel grants and honoraria from Celgene, Gilead, Chugai, Janssen, Novartis, Amgen, Takeda, BMS, Medac, Oncopeptides, Merck, CDDF, Pfizer, Medac, Thermo Fisher, AstraZeneca; is a consultant for Celgene, Gilead, Oncopeptides, MSD, 4D Pharma, Janssen, Shionogi and received research funding from BMBF, Deutsche Jose Carreras Leukämie-Stiftung, IZKF Jena, Novartis, Gilead, Deutsche Krebshilfe, Celgene, Oncopeptides, Deutsche Forschungsgemeinschaft (DFG). CW has declared no conflicts of interest. GP reports grants from Amgen, grants, personal fees and non-financial support from Merck, grants and non-financial support from AstraZeneca, grants and personal fees from Roche, grants and personal fees from BMS, grants from Lilly, grants and personal fees from MSD, grants and personal fees from Novartis, outside the submitted work. FP reports grants from Novartis, Celgene, BMS, Abbvie, Karyopharma, Janssen. GP reports grants from Amgen, grants, personal fees and non-financial support from Merck, grants and non-financial support from AstraZeneca, grants and personal fees from Roche, grants and personal fees from BMS, grants from Lilly, grants and personal fees from MSD, grants and personal fees from Novartis, outside the submitted work. Background: The COVID-19 pandemic has created enormous challenges for the clinical management of patients with hematological malignancies (HMs), raising questions about the optimal care of this patient group. Methods: This consensus manuscript aims at discussing clinical evidence and providing expert advice on statements related to the management of HMs in the COVID-19 pandemic. For this purpose, an international consortium was established including a steering committee, which prepared six working packages addressing significant clinical questions from the COVID-19 diagnosis, treatment, and mitigation strategies to specific HMs management in the pandemic. During a virtual consensus meeting, including global experts and lead by the European Society for Medical Oncology and the European Hematology Association, statements were discussed and voted upon. When a consensus could not be reached, the panel revised statements to develop consensual clinical guidance. Results and conclusion: The expert panel agreed on 33 statements, reflecting a consensus, which will guide clinical decision making for patients with hematological neoplasms during the COVID-19 pandemic.

Granulocytic myeloid-derived suppressor cells (G-MDSCs) promote tumor growth and immunosuppression in multiple myeloma (MM). However, their phenotype is not well established for accurate monitoring or clinical translation. We aimed to provide the phenotypic profile of G-MDSCs based on their prognostic significance in MM, immunosuppressive potential, and molecular program. The preestablished phenotype of G-MDSCs was evaluated in bone marrow samples from controls and MM patients using multidimensional flow cytometry; surprisingly, we found that CD11b+CD14−CD15+CD33+HLADR− cells overlapped with common eosinophils and neutrophils, which were not expanded in MM patients. Therefore, we relied on automated clustering to unbiasedly identify all granulocytic subsets in the tumor microenvironment: basophils, eosinophils, and immature, intermediate, and mature neutrophils. In a series of 267 newly diagnosed MM patients (GEM2012MENOS65 trial), only the frequency of mature neutrophils at diagnosis was significantly associated with patient outcome, and a high mature neutrophil/T-cell ratio resulted in inferior progression-free survival (P < .001). Upon fluorescence-activated cell sorting of each neutrophil subset, T-cell proliferation decreased in the presence of mature neutrophils (0.5-fold; P = .016), and the cytotoxic potential of T cells engaged by a BCMA×CD3-bispecific antibody increased notably with the depletion of mature neutrophils (fourfold; P = .0007). Most interestingly, RNA sequencing of the 3 subsets revealed that G-MDSC–related genes were specifically upregulated in mature neutrophils from MM patients vs controls because of differential chromatin accessibility. Taken together, our results establish a correlation between the clinical significance, immunosuppressive potential, and transcriptional network of well-defined neutrophil subsets, providing for the first time a set of optimal markers (CD11b/CD13/CD16) for accurate monitoring of G-MDSCs in MM.

In patients with transplant-ineligible newly diagnosed multiple myeloma (NDMM), daratumumab reduced the risk of disease progression or death by 44% in MAIA (daratumumab/lenalidomide/dexamethasone [D-Rd]) and 58% in ALCYONE (daratumumab/bortezomib/melphalan/prednisone [D-VMP]). Minimal residual disease (MRD) is a sensitive measure of disease and response to therapy. MRD-negativity status and durability were assessed in MAIA and ALCYONE. MRD assessments using next-generation sequencing (10−5) occurred for patients achieving complete response (CR) or better and after at least CR at 12, 18, 24, and 30 months from the first dose. Progression-free survival (PFS) by MRD status and sustained MRD negativity lasting ≥6 and ≥12 months were analyzed in the intent-to-treat population and among patients achieving at least CR. In MAIA (D-Rd, n = 368; lenalidomide and dexamethasone [Rd], n = 369) and ALCYONE (D-VMP, n = 350; bortezomib/melphalan/prednisone [VMP], n = 356), the median duration of follow-up was 36.4 and 40.1 months, respectively. MRD-negative status and sustained MRD negativity lasting ≥6 and ≥12 months were associated with improved PFS, regardless of treatment group. However, daratumumab-based therapy improved rates of MRD negativity lasting ≥6 months (D-Rd, 14.9% vs Rd, 4.3%; D-VMP, 15.7% vs VMP, 4.5%) and ≥12 months (D-Rd, 10.9% vs Rd, 2.4%; D-VMP, 14.0% vs VMP, 2.8%), both of which translated to improved PFS vs control groups. In a pooled analysis, patients who were MRD negative had improved PFS vs patients who were MRD positive. Patients with NDMM who achieved MRD-negative status or sustained MRD negativity had deep remission and improved clinical outcomes. These trials were registered at www.clinicaltrials.gov as #NCT02252172 (MAIA) and #NCT02195479 (ALCYONE). © 2022 American Society of Hematology

Response kinetics is not well-established as a prognostic marker in multiple myeloma (MM). We developed a mathematical model to assess the prognostic value of serum monoclonal component (MC) response kinetics during 6 induction cycles in 373 newly diagnosed MM patients. The model calculated a resistance parameter that reflects the stagnation in the response after an initial descent, dividing the patients into two kinetics categories with significantly different progression-free survival (PFS). Introduction: Response kinetics is a well-established prognostic marker in acute lymphoblastic leukemia. The situation is not clear in multiple myeloma (MM) despite having a biomarker for response monitoring (monoclonal component [MC]). Materials and Methods: We developed a mathematical model to assess the prognostic value of serum MC response kinetics during 6 induction cycles, in 373 NDMM transplanted patients treated in the GEM2012Menos65 clinical trial. The model calculated a resistance parameter that reflects the stagnation in the response after an initial descent. Results: Two patient subgroups were defined based on low and high resistance, that respectively captured sensitive and refractory kinetics, with progression-free survival (PFS) at 5 years of 72% and 59% (HR 0.64, 95% CI 0.44-0.93; P =.02). Resistance significantly correlated with depth of response measured after consolidation (80.9% CR and 68.4% minimal residual disease negativity in patients with sensitive vs. 31% and 20% in those with refractory kinetics). Furthermore, it modulated the impact of reaching CR after consolidation; thus, within CR patients those with refractory kinetics had significantly shorter PFS than those with sensitive kinetics (median 54 months vs. NR; P =.02). Minimal residual disease negativity abrogated this effect. Our study also questions the benefit of rapid responders compared to late responders (5-year PFS 59.7% vs. 76.5%, respectively [P

We explored minimal residual disease (MRD) in relapsed/refractory multiple myeloma (RRMM) and transplant-ineligible (TIE) newly diagnosed multiple myeloma (NDMM) using data from 4 phase 3 studies (POLLUX, CASTOR, ALCYONE, and MAIA). Each study previously demonstrated that daratumumab-based therapies improved MRD negativity rates and reduced the risk of disease progression or death by approximately half vs standards of care. We conducted a large-scale pooled analysis for associations between patients achieving complete response or better (≥CR) with MRD-negative status and progression-free survival (PFS). MRD was assessed via next-generation sequencing (10−5 sensitivity threshold). Patient-level data were pooled from all 4 studies and for patients with TIE NDMM and patients with RRMM who received ≤2 prior lines of therapy (≤2 PL). PFS was evaluated by response and MRD status. Median follow-up (months) was 54.8 for POLLUX, 50.2 for CASTOR, 40.1 for ALCYONE, and 36.4 for MAIA. Patients who achieved ≥CR and MRD negativity had improved PFS vs those who failed to reach CR or were MRD positive (TIE NDMM and RRMM hazard ratio [HR] 0.20, P

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 endpoint 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. Funding: Pethema (Spanish Program for the Treatment of Hematologic Diseases), Spain. 2022 Elsevier Ltd. All rights reserved.

Introduction: Many treatment regimens have been evaluated in transplant-ineligible (TIE) patients with newly diagnosed multiple myeloma (NDMM). The objective of this study was to compare the efficacy of relevant therapies for the treatment of TIE patients with NDMM. Methods: Progression-free survival (PFS) and overall survival (OS) from large randomised controlled trials (RCTs) evaluating different treatment options for TIE patients with NDMM were compared in a network meta-analysis (NMA). The NMA includes recent primary and long-term OS readouts from SWOG S0777, ENDURANCE, MAIA, and ALCYONE. Relevant trials were identified through a systematic literature review. Relative efficacy measures (i.e., hazard ratios [HRs] for PFS and OS) were extracted and synthesised in random-effects NMAs. Results: A total of 122 publications describing 45 unique RCTs was identified. Continuous lenalidomide/dexamethasone (Rd) was selected as the referent comparator. Daratumumab-containing treatments (daratumumab/lenalidomide/dexamethasone [D-Rd], daratumumab/bortezomib/melphalan/prednisone [D-VMP]) and bortezomib/lenalidomide/dexamethasone (VRd) had the highest probabilities of being more effective than Rd continuous for PFS (HR: D-Rd, 0.53; D-VMP, 0.57, VRd, 0.77) and OS (HR: D-Rd, 0.68; VRd, 0.77, D-VMP, 0.78). D-Rd had the highest chance of being ranked as the most effective treatment with respect to PFS and OS. Results using a smaller network focusing on only those regimens that are relevant in Europe were consistent with the primary analysis. Conclusions: These comparative effectiveness data may help inform treatment selection in TIE patients with NDMM. © 2022, The Author(s).