Since the publication in 2021 of the European Hematology Association (EHA) Clinical Practice Guidelines for the treatment of patients with smouldering multiple myeloma (SMM) and multiple myeloma (MM), developed in collaboration with the European Society for Medical Oncology, a novel international staging system (R2-ISS) has been developed, several prognostic factors are entering clinical practice (such as minimal residual disease, circulating plasma cells and monoclonal protein assessed by mass spectrometry) and, at the time of writing, 14 novel regimens have been approved by the EMA and/or the FDA for the treatment of patients with MM. A multidisciplinary group of experts from the EHA and European Myeloma Network, based in various institutions mostly located in Europe, have updated the previous guidelines and produced algorithms for everyday clinical practice that incorporate levels of evidence and grades of recommendation based on the aforementioned new data. In these Evidence-Based Guidelines, we provide key treatment recommendations for both patients with newly diagnosed MM and those with relapsed and/or refractory MM, including guidance for the use of established drugs as well as contemporary immunotherapies. Novel approaches for the management of patients with SMM focus on those who might require early intervention. Finally, we provide recommendations for myeloma-related complications and adverse events, such as bone disease, renal impairment and infections, as well as for those associated with T cell-mobilizing therapies, such as cytokine-release syndrome and immune effector cell-associated neurotoxicity syndrome.

• MeSH
• Humans MeSH
• Evidence-Based Medicine MeSH
• Multiple Myeloma * diagnosis   therapy   MeSH
• Practice Guidelines as Topic * MeSH
• Neoplasm Staging MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Review MeSH

Smoldering multiple myeloma (SMM) is an asymptomatic precursor to active multiple myeloma (MM). The aim of this study was to report clinical characteristics and outcomes of patients with SMM stratified based on their risk of progression to MM using the Mayo 20/2/20 criteria. Data were leveraged from the Czech Myeloma Group Registry of Monoclonal Gammopathies (RMG). Key outcomes included progression-free survival from SMM diagnosis to active MM diagnosis or death (PFS), progression-free survival from SMM diagnosis to progression on first line (1 L) MM treatment or death (PFS2), and overall survival (OS). Of 498 patients, 174 (34.9%) were classified as high risk and 324 (65.1%) as non-high risk. Median follow-up was approximately 65 months. During follow-up, more patients in the high-risk vs non-high-risk group received 1 L MM treatment (76.4% vs 46.6%, p < 0.001). PFS, PFS2, and OS were significantly shorter in high-risk vs non-high-risk patients (13.2 vs 56.6 months, p < 0.001; 49.9 vs 84.9 months, p < 0.001; 93.2 vs 131.1 months, p = 0.012, respectively). The results of this study add to the growing body of evidence that patients with high-risk vs non-high-risk SMM have significantly worse outcomes, including OS.

• MeSH
• Progression-Free Survival MeSH
• Smoldering Multiple Myeloma * diagnosis   epidemiology   therapy   MeSH
• Humans MeSH
• Multiple Myeloma * diagnosis   epidemiology   therapy   MeSH
• Registries MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Czech Republic epidemiology   MeSH

BACKGROUND: Patients with precursors to multiple myeloma are dichotomised as having monoclonal gammopathy of undetermined significance or smouldering multiple myeloma on the basis of monoclonal protein concentrations or bone marrow plasma cell percentage. Current risk stratifications use laboratory measurements at diagnosis and do not incorporate time-varying biomarkers. Our goal was to develop a monoclonal gammopathy of undetermined significance and smouldering multiple myeloma stratification algorithm that utilised accessible, time-varying biomarkers to model risk of progression to multiple myeloma. METHODS: In this retrospective, multicohort study, we included patients who were 18 years or older with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma. We evaluated several modelling approaches for predicting disease progression to multiple myeloma using a training cohort (with patients at Dana-Farber Cancer Institute, Boston, MA, USA; annotated from Nov, 13, 2019, to April, 13, 2022). We created the PANGEA models, which used data on biomarkers (monoclonal protein concentration, free light chain ratio, age, creatinine concentration, and bone marrow plasma cell percentage) and haemoglobin trajectories from medical records to predict progression from precursor disease to multiple myeloma. The models were validated in two independent validation cohorts from National and Kapodistrian University of Athens (Athens, Greece; from Jan 26, 2020, to Feb 7, 2022; validation cohort 1), University College London (London, UK; from June 9, 2020, to April 10, 2022; validation cohort 1), and Registry of Monoclonal Gammopathies (Czech Republic, Czech Republic; Jan 5, 2004, to March 10, 2022; validation cohort 2). We compared the PANGEA models (with bone marrow [BM] data and without bone marrow [no BM] data) to current criteria (International Myeloma Working Group [IMWG] monoclonal gammopathy of undetermined significance and 20/2/20 smouldering multiple myeloma risk criteria). FINDINGS: We included 6441 patients, 4931 (77%) with monoclonal gammopathy of undetermined significance and 1510 (23%) with smouldering multiple myeloma. 3430 (53%) of 6441 participants were female. The PANGEA model (BM) improved prediction of progression from smouldering multiple myeloma to multiple myeloma compared with the 20/2/20 model, with a C-statistic increase from 0·533 (0·480-0·709) to 0·756 (0·629-0·785) at patient visit 1 to the clinic, 0·613 (0·504-0·704) to 0·720 (0·592-0·775) at visit 2, and 0·637 (0·386-0·841) to 0·756 (0·547-0·830) at visit three in validation cohort 1. The PANGEA model (no BM) improved prediction of smouldering multiple myeloma progression to multiple myeloma compared with the 20/2/20 model with a C-statistic increase from 0·534 (0·501-0·672) to 0·692 (0·614-0·736) at visit 1, 0·573 (0·518-0·647) to 0·693 (0·605-0·734) at visit 2, and 0·560 (0·497-0·645) to 0·692 (0·570-0·708) at visit 3 in validation cohort 1. The PANGEA models improved prediction of monoclonal gammopathy of undetermined significance progression to multiple myeloma compared with the IMWG rolling model at visit 1 in validation cohort 2, with C-statistics increases from 0·640 (0·518-0·718) to 0·729 (0·643-0·941) for the PANGEA model (BM) and 0·670 (0·523-0·729) to 0·879 (0·586-0·938) for the PANGEA model (no BM). INTERPRETATION: Use of the PANGEA models in clinical practice will allow patients with precursor disease to receive more accurate measures of their risk of progression to multiple myeloma, thus prompting for more appropriate treatment strategies. FUNDING: SU2C Dream Team and Cancer Research UK.

• MeSH
• Algorithms MeSH
• Creatinine MeSH
• Humans MeSH
• Multiple Myeloma * MeSH
• Monoclonal Gammopathy of Undetermined Significance * MeSH
• Retrospective Studies MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Creatinine MeSH

Monoclonal gammopathy of renal significance (MGRS) is a recognized clinical entity. Literature regarding treatment and its outcomes in MGRS is sparse due to the rarity and misdiagnosis of MGRS. We retrospectively analyzed 280 adults with an MGRS diagnosis from 2003 to 2020 across 19 clinical centers from 12 countries. All cases required renal biopsy for the pathological diagnosis of MGRS. Amyloidosis-related to MGRS (MGRS-A) was present in 180 patients; nonamyloidosis MGRS (MGRS-NA), including a broad spectrum of renal pathologies, was diagnosed in 100 patients. The median overall survival in the studied cohort was 121.0 months (95% CI: 105.0-121.0). Patients with MGRS-A had a shorter overall survival than patients with MGRS-NA (HR = 0.41, 95%CI: 0.25-0.69; p = 0.0007). Both hematologic and renal responses were associated with longer survival. Achievement of ≥VGPR was generally predictive of a renal response (OR = 8.03 95%CI: 4.04-115.96; p < 0.0001), one-fourth of patients with ≥VGPR were renal nonresponders. In MGRS-A, factors associated with poor prognosis included elevated levels of creatinine, beta-2-microglobulin, and hemodialysis at diagnosis. In MGRS-NA, only age >65 years was associated with increased risk of death. Treatments provided similar hematologic response rates in both types of MGRS. Autologous stem cell transplantation led to better response than other treatments. This multicenter and international effort is currently the largest report on MGRS.

• MeSH
• Transplantation, Autologous adverse effects   MeSH
• Adult MeSH
• Humans MeSH
• Monoclonal Gammopathy of Undetermined Significance * complications   diagnosis   therapy   MeSH
• Kidney Diseases * etiology   pathology   therapy   MeSH
• Paraproteinemias * diagnosis   MeSH
• Precancerous Conditions * MeSH
• Prognosis MeSH
• Retrospective Studies MeSH
• Aged MeSH
• Hematopoietic Stem Cell Transplantation * adverse effects   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Aged MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH
• Research Support, Non-U.S. Gov't MeSH

Large-scale immune monitoring is becoming routinely used in clinical trials to identify determinants of treatment responsiveness, particularly to immunotherapies. Flow cytometry remains one of the most versatile and high throughput approaches for single-cell analysis; however, manual interpretation of multidimensional data poses a challenge when attempting to capture full cellular diversity and provide reproducible results. We present FlowCT, a semi-automated workspace empowered to analyze large data sets. It includes pre-processing, normalization, multiple dimensionality reduction techniques, automated clustering, and predictive modeling tools. As a proof of concept, we used FlowCT to compare the T-cell compartment in bone marrow (BM) with peripheral blood (PB) from patients with smoldering multiple myeloma (SMM), identify minimally invasive immune biomarkers of progression from smoldering to active MM, define prognostic T-cell subsets in the BM of patients with active MM after treatment intensification, and assess the longitudinal effect of maintenance therapy in BM T cells. A total of 354 samples were analyzed and immune signatures predictive of malignant transformation were identified in 150 patients with SMM (hazard ratio [HR], 1.7; P < .001). We also determined progression-free survival (HR, 4.09; P < .0001) and overall survival (HR, 3.12; P = .047) in 100 patients with active MM. New data also emerged about stem cell memory T cells, the concordance between immune profiles in BM and PB, and the immunomodulatory effect of maintenance therapy. FlowCT is a new open-source computational approach that can be readily implemented by research laboratories to perform quality control, analyze high-dimensional data, unveil cellular diversity, and objectively identify biomarkers in large immune monitoring studies. These trials were registered at www.clinicaltrials.gov as #NCT01916252 and #NCT02406144.

• MeSH
• Biomarkers MeSH
• Smoldering Multiple Myeloma * MeSH
• Immunophenotyping MeSH
• Bone Marrow MeSH
• Humans MeSH
• Flow Cytometry methods   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Biomarkers MeSH

Multiple myeloma (MM) is a hematological malignancy caused by the clonal expansion of plasma cells. The incidence of MM worldwide is increasing with greater than 140 000 people being diagnosed with MM per year. Whereas 5-year survival after a diagnosis of MM has improved from 28% in 1975 to 56% in 2012, the disease remains essentially incurable. In this review, we summarize our current understanding of MM including its epidemiology, genetics and biology. We will also provide an overview of MM management that has led to improvements in survival, including recent changes to diagnosis and therapies. Areas of unmet need include the management of patients with high-risk MM, those with reduced performance status and those refractory to standard therapies. Ongoing research into the biology and early detection of MM as well as the development of novel therapies, such as immunotherapies, has the potential to influence MM practice in the future.

• Keywords
• clinical presentation, plasma cell disease, risks factors, survival, treatment,
• MeSH
• Cyclin D1 genetics   MeSH
• Exosome Multienzyme Ribonuclease Complex genetics   MeSH
• Genetic Predisposition to Disease MeSH
• Histone Demethylases genetics   MeSH
• Immunotherapy methods   MeSH
• Humans MeSH
• Survival Rate MeSH
• Multiple Myeloma diagnosis   epidemiology   genetics   therapy   MeSH
• Mutation MeSH
• Biomarkers, Tumor genetics   MeSH
• Plasma Cells immunology   pathology   MeSH
• Repressor Proteins genetics   MeSH
• Risk Factors MeSH
• Transcriptional Elongation Factors genetics   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Names of Substances
• CCND1 protein, human MeSH Browser
• CDCA7L protein, human MeSH Browser
• Cyclin D1 MeSH
• DIS3 protein, human MeSH Browser
• ELL2 protein, human MeSH Browser
• Exosome Multienzyme Ribonuclease Complex MeSH
• Histone Demethylases MeSH
• KDM1A protein, human MeSH Browser
• Biomarkers, Tumor MeSH
• Repressor Proteins MeSH
• Transcriptional Elongation Factors MeSH

According to the updated International Myeloma Working Group criteria, smoldering multiple myeloma (SMM) is an asymptomatic plasma cell disorder characterized by an M-component >3 g/dL, bone marrow plasma cell infiltration >10% and <60%, and absence of any myeloma-defining event. Active multiple myeloma is preceded by SMM, with a median time to progression of approximately 5 years. Cases of SMM range from the extremes of "monoclonal gammopathy of undetermined significance-like", in which patients never progress during their lifetimes, to "early multiple myeloma", in which transformation into symptomatic disease, based on genomic evolution, may be rapid and devastating. Such a "split personality" makes the prognosis and management of individual patients challenging, particularly with regard to the identification and possible early treatment of high-risk SMM. Outside of clinical trials, the conventional approach to SMM generally remains close observation until progression to active multiple myeloma. However, two prospective, randomized trials have recently demonstrated a significant clinical benefit in terms of time to progression, and of overall survival in one of the two studies, for some patients with higher-risk SMM treated with lenalidomide ± dexamethasone, raising the question of whether such an approach should be considered a new standard of care. In this paper, experts from the European Myeloma Network describe current biological and clinical knowledge on SMM, focusing on novel insights into its molecular pathogenesis, new prognostic scoring systems proposed to identify SMM patients at higher risk of early transformation, and updated results of completed or ongoing clinical trials. Finally, some practical recommendations for the real-life management of these patients, based on Delphi consensus methodology, are provided.

• MeSH
• Smoldering Multiple Myeloma * diagnosis   therapy   MeSH
• Humans MeSH
• Multiple Myeloma * drug therapy   therapy   MeSH
• Monoclonal Gammopathy of Undetermined Significance * diagnosis   therapy   MeSH
• Disease Progression MeSH
• Prospective Studies MeSH
• Risk Factors MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Review MeSH