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Shafei L, Bashir S, Chan EW, Abushanab D, Hamad A, Al-Badriyeh D. Efficacy and safety of selinexor for patients with relapsed and refractory multiple myeloma: A meta-analysis. Curr Probl Cancer 2024; 50:101076. [PMID: 38537395 DOI: 10.1016/j.currproblcancer.2024.101076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 01/25/2024] [Accepted: 02/28/2024] [Indexed: 06/16/2024]
Abstract
PURPOSE Selinexor is a first-in-class, oral selective-inhibitor-of-nuclear-export, granted accelerated approval by FDA (2019) for relapsed and refractory multiple myeloma (RRMM). We sought to quantitatively summarize the selinexor efficacy and safety in RRMM. METHODS We searched PubMed, EMBASE, CENTRAL, clinicaltrial.gov, and google scholar, until May 2023, studies about selinexor use in RRMM. The outcome measures of interest were primarily efficacy outcomes, in addition to safety outcomes. Random-effect model analyses were performed, at statistical significance of P<0.05, using the RevMan software. RESULTS Meta-analyses of eleven included clinical trials yielded a significant 56.21% overall clinical benefit, 46.91% overall response, 4.89% complete response, 23.41% very good partial response, 24.68% partial response, and 28.06% stable disease rates with selinexor. Due to safety reasons, selinexor caused significant increase in discontinuation rate, 16.80%. Subgroup analyses demonstrated higher efficacy with selinexor plus dexamethasone and proteasome inhibitor combinations than with selinexor alone. The multiple myeloma type, high cytogenetic risk, refractory state, and advanced disease state did not affect performance. Risk of selection, performance, and detection biases were unclear in the included trials. CONCLUSION Selinexor led to significant positive responses with an acceptable safety profile in RRMM patients, despite higher rates of safety-related discontinuations. Selinexor-based combinations further enhanced response.
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Affiliation(s)
- Laila Shafei
- College of Pharmacy, QU Health, Qatar University, Doha, Qatar; Pharmacy Department, National Center for Cancer Care & Research, Hamad Medical Corporation, Doha, Qatar
| | - Shaima Bashir
- College of Pharmacy, QU Health, Qatar University, Doha, Qatar
| | - Esther W Chan
- Department of Pharmacology and Pharmacy, LKS, Faculty of Medicine, Centre for Safe Medication Practice and Research, University of Hong Kong, Hong Kong
| | - Dina Abushanab
- Drug Information Department, Hamad Medical Corporation, Doha, Qatar; Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia
| | - Anas Hamad
- College of Pharmacy, QU Health, Qatar University, Doha, Qatar; Pharmacy Department, National Center for Cancer Care & Research, Hamad Medical Corporation, Doha, Qatar
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2
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Gagelmann N, Dima D, Merz M, Hashmi H, Ahmed N, Tovar N, Oliver-Caldés A, Stölzel F, Rathje K, Fischer L, Born P, Schäfer L, Albici AM, Schub N, Kfir-Erenfeld S, Assayag M, Asherie N, Wulf GG, Kharboutli S, Müller F, Shune L, Davis JA, Anwer F, Vucinic V, Platzbecker U, Ayuk F, Kröger N, Khouri J, Gurnari C, McGuirk J, Stepensky P, Abdallah AO, Fernández de Larrea C. Development and Validation of a Prediction Model of Outcome After B-Cell Maturation Antigen-Directed Chimeric Antigen Receptor T-Cell Therapy in Relapsed/Refractory Multiple Myeloma. J Clin Oncol 2024; 42:1665-1675. [PMID: 38358946 PMCID: PMC11095856 DOI: 10.1200/jco.23.02232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 11/21/2023] [Accepted: 01/16/2024] [Indexed: 02/17/2024] Open
Abstract
PURPOSE Although chimeric antigen receptor T therapy (CAR-T) cells are an established therapy for relapsed/refractory multiple myeloma (RRMM), there are no established models predicting outcome to identify patients who may benefit the most from CAR-T. PATIENTS AND METHODS This is an international retrospective observational study including patients with RRMM infused with currently available commercial or academically produced anti-B-cell maturation antigen (BCMA) CAR-T. We describe characteristics and outcomes in Europe (n = 136) and the United States (n = 133). Independent predictors of relapse/progression built a simple prediction model (Myeloma CAR-T Relapse [MyCARe] model) in the training cohort (Europe), which was externally validated (US cohort) and tested within patient- and treatment-specific subgroups. RESULTS The overall response rate was 87% and comparable between both cohorts, and complete responses were seen in 48% (Europe) and 49% (the United States). The median time to relapse was 5 months, and early relapse <5 months from infusion showed poor survival across cohorts, with the 12-month overall survival of 30% (Europe) and 14% (the United States). The presence of extramedullary disease or plasma cell leukemia, lenalidomide-refractoriness, high-risk cytogenetics, and increased ferritin at the time of lymphodepletion were independent predictors of early relapse or progression. Each factor received one point, forming the three-tiered MyCARe model: scores 0-1 (low risk), scores 2-3 (intermediate risk), and a score of 4 (high risk). The MyCARe model was significantly associated with distinct 5-month incidence of relapse/progression (P < .001): 7% for low-risk, 27% for intermediate-risk, and 53% for high-risk groups. The model was validated in the US cohort and maintained prognostic utility for response, survival, and outcomes across subgroups. CONCLUSION Outcomes of patients with RRMM after CAR-T are comparable between Europe and the United States. The MyCARe model may facilitate optimal timing of CAR-T cells in patient-specific subgroups.
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Affiliation(s)
- Nico Gagelmann
- Department of Stem Cell Transplantation, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Danai Dima
- Cleveland Clinic Taussig Cancer Center, Cleveland, OH
- US Myeloma Innovations Research Collaborative (USMIRC), Kansas City, KS
| | - Maximilian Merz
- Department of Hematology, Cellular Therapy, Hemostaseology and Infectiology, University Hospital of Leipzig, Leipzig, Germany
| | - Hamza Hashmi
- US Myeloma Innovations Research Collaborative (USMIRC), Kansas City, KS
- Medical University of South Carolina, Charleston, SC
| | - Nausheen Ahmed
- US Myeloma Innovations Research Collaborative (USMIRC), Kansas City, KS
- The University of Kansas Medical Center, Kansas City, KS
| | - Natalia Tovar
- Hospital Clínic de Barcelona, IDIBAPS, University of Barcelona, Barcelona, Spain
| | - Aina Oliver-Caldés
- Hospital Clínic de Barcelona, IDIBAPS, University of Barcelona, Barcelona, Spain
| | - Friedrich Stölzel
- Division for Stem Cell Transplantation and Cellular Immunotherapy, Department of Medicine II, University Hospital Schleswig-Holstein Kiel, Kiel University, Kiel, Germany
| | - Kristin Rathje
- Department of Stem Cell Transplantation, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Luise Fischer
- Department of Hematology, Cellular Therapy, Hemostaseology and Infectiology, University Hospital of Leipzig, Leipzig, Germany
| | - Patrick Born
- Department of Hematology, Cellular Therapy, Hemostaseology and Infectiology, University Hospital of Leipzig, Leipzig, Germany
| | - Lisa Schäfer
- Department of Hematology and Medical Oncology, Medical Center University of Göttingen, Göttingen, Germany
| | - Anca-Maria Albici
- Division for Stem Cell Transplantation and Cellular Immunotherapy, Department of Medicine II, University Hospital Schleswig-Holstein Kiel, Kiel University, Kiel, Germany
| | - Natalie Schub
- Division for Stem Cell Transplantation and Cellular Immunotherapy, Department of Medicine II, University Hospital Schleswig-Holstein Kiel, Kiel University, Kiel, Germany
| | - Shlomit Kfir-Erenfeld
- Department of Bone Marrow Transplantation and Cancer Immunotherapy, Faculty of Medicine, Hadassah Medical Center, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Miri Assayag
- Department of Bone Marrow Transplantation and Cancer Immunotherapy, Faculty of Medicine, Hadassah Medical Center, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Nathalie Asherie
- Department of Bone Marrow Transplantation and Cancer Immunotherapy, Faculty of Medicine, Hadassah Medical Center, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Gerald Georg Wulf
- Department of Hematology and Medical Oncology, Medical Center University of Göttingen, Göttingen, Germany
| | - Soraya Kharboutli
- Department of Internal Medicine, Haematology and Oncology, University Hospital of Erlangen, Friedrich-Alexander University of Erlangen-Nuremberg (FAU), Erlangen, Germany
| | - Fabian Müller
- Department of Internal Medicine, Haematology and Oncology, University Hospital of Erlangen, Friedrich-Alexander University of Erlangen-Nuremberg (FAU), Erlangen, Germany
| | - Leyla Shune
- US Myeloma Innovations Research Collaborative (USMIRC), Kansas City, KS
- The University of Kansas Medical Center, Kansas City, KS
| | - James A. Davis
- US Myeloma Innovations Research Collaborative (USMIRC), Kansas City, KS
- Medical University of South Carolina, Charleston, SC
| | - Faiz Anwer
- Cleveland Clinic Taussig Cancer Center, Cleveland, OH
- US Myeloma Innovations Research Collaborative (USMIRC), Kansas City, KS
| | - Vladan Vucinic
- Department of Hematology, Cellular Therapy, Hemostaseology and Infectiology, University Hospital of Leipzig, Leipzig, Germany
| | - Uwe Platzbecker
- Department of Hematology, Cellular Therapy, Hemostaseology and Infectiology, University Hospital of Leipzig, Leipzig, Germany
| | - Francis Ayuk
- Department of Stem Cell Transplantation, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Nicolaus Kröger
- Department of Stem Cell Transplantation, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jack Khouri
- Cleveland Clinic Taussig Cancer Center, Cleveland, OH
| | - Carmelo Gurnari
- Cleveland Clinic Taussig Cancer Center, Cleveland, OH
- Department of Biomedicine and Prevention, PhD in Immunology, Molecular Medicine and Applied Biotechnology, University of Rome Tor Vergata, Rome, Italy
| | - Joseph McGuirk
- US Myeloma Innovations Research Collaborative (USMIRC), Kansas City, KS
- The University of Kansas Medical Center, Kansas City, KS
| | - Polina Stepensky
- Department of Bone Marrow Transplantation and Cancer Immunotherapy, Faculty of Medicine, Hadassah Medical Center, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Al-Ola Abdallah
- US Myeloma Innovations Research Collaborative (USMIRC), Kansas City, KS
- The University of Kansas Medical Center, Kansas City, KS
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3
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Ruotsalainen J, Lehmus L, Putkonen M, Lievonen J, Kallio A, Raittinen P, Summanen M, Kosunen M, Korhonen MJ. Recent trends in incidence, survival and treatment of multiple myeloma in Finland - a nationwide cohort study. Ann Hematol 2024; 103:1273-1284. [PMID: 38085293 PMCID: PMC10940444 DOI: 10.1007/s00277-023-05571-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 11/28/2023] [Indexed: 03/16/2024]
Abstract
This study aimed to determine the incidence and prevalence of multiple myeloma (MM) in Finland in 2015-2019, to characterize adult patients newly diagnosed with MM, and to follow-up their overall survival (OS) and treatment patterns until the end of 2020. We sourced the data on inpatient and outpatient diagnoses, outpatient medication use, and date of death from comprehensive, nationwide registers. We identified 2037 incident patients with MM in 2015-2019. On average, the annual crude incidence was 8.8 and the age-standardized incidence (World Standard Population) was 3.3 per 100,000. The crude prevalence at the end of 2019 was 32.7 cases per 100,000 inhabitants ≥ 18 years of age. Median age of the patients at first diagnosis (index date) was 71 years, and 48% were female, the median follow-up being 2.4 years. The median OS was estimated at 4.5 years. The proportion of the patients receiving autologous stem cell transplantation (ASCT) within one year since the index date was 24%, with little variation across study years. Conversely, the proportion of all patients receiving lenalidomide within one year since the index date increased from 27 to 48% overall, and from 39 to 81% among ASCT recipients. The estimated median relapse-free survival after ASCT was 2.9 years. Information on in-hospital MM medication administrations was available for a subset of the study cohort. In this subset, 85.8% of the patients received immunomodulatory drugs and/or proteasome inhibitors within the first year after the index date.
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Affiliation(s)
| | | | - Mervi Putkonen
- Department of Hematology, Turku University Hospital, Turku, Finland
| | - Juha Lievonen
- Department of Hematology, Helsinki University Hospital, Helsinki, Finland
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4
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Goldman-Mazur S, Visram A, Rajkumar SV, Kapoor P, Dispenzieri A, Lacy MQ, Gertz MA, Buadi FK, Hayman SR, Dingli D, Kourelis T, Gonsalves W, Warsame R, Muchtar E, Leung N, Kyle RA, Kumar SK. Predictors and Impact of Timing of Disease Progression Following Primary Therapy in Multiple Myeloma. CLINICAL LYMPHOMA, MYELOMA & LEUKEMIA 2024; 24:e104-e111.e1. [PMID: 38135634 DOI: 10.1016/j.clml.2023.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 11/23/2023] [Indexed: 12/24/2023]
Abstract
In multiple myeloma (MM) significant variation in progression-free survival (PFS) and overall survival (OS) is observed. We examined the outcomes of 1557 MM patients stratified into short (<2 years), medium (between 2 and 5 years) and long (>5 years) PFS. Short PFS occurred in 758 patients (48.7%), medium in 561 patients (36.2%), and long in 238 patients (15.3%). Median post-progression PFS was 9.2 months (95% CI: 8.1-11.0) in the short PFS and 33.1 months (95% CI: 29.0-42.1; P < .001) in the long PFS group. Median post-progression OS was 26.6 months (95% CI: 23.9-29.8) in the short PFS and 87.8 months (95% CI: 71.3- NR; P < .001) in the long PFS. Worse survival in the short PFS was irrespective of high risk (HR) fluorescence in situ hybridization (FISH) features, defined as deletion 17p and/or translocation t(4;14), t(14;16), t(14;20). In a multivariable analysis short PFS was associated with HR FISH, extramedullary plasmacytoma, plasma cell labeling index ≥2% at diagnosis, nonimmunoglobulin G isotype, treatment without autologous stem cell transplantation and achieving less than very good partial remission. In conclusion, the duration of the PFS significantly influences survival, regardless of HR cytogenetic features. Therefore, it should be considered an important parameter for risk stratification in patients experiencing a relapse.
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Affiliation(s)
| | - Alissa Visram
- Division of Hematology, Mayo Clinic Rochester, Rochester, MN; Division of Hematology, Ottawa Hospital Research Institute, Ontario, Canada
| | | | - Prashant Kapoor
- Division of Hematology, Mayo Clinic Rochester, Rochester, MN
| | | | - Martha Q Lacy
- Division of Hematology, Mayo Clinic Rochester, Rochester, MN
| | - Morie A Gertz
- Division of Hematology, Mayo Clinic Rochester, Rochester, MN
| | - Francis K Buadi
- Division of Hematology, Mayo Clinic Rochester, Rochester, MN
| | | | - David Dingli
- Division of Hematology, Mayo Clinic Rochester, Rochester, MN
| | | | | | - Rahma Warsame
- Division of Hematology, Mayo Clinic Rochester, Rochester, MN
| | - Eli Muchtar
- Division of Hematology, Mayo Clinic Rochester, Rochester, MN
| | - Nelson Leung
- Division of Nephrology, Mayo Clinic Rochester, Rochester, MN
| | - Robert A Kyle
- Division of Hematology, Mayo Clinic Rochester, Rochester, MN
| | - Shaji K Kumar
- Division of Hematology, Mayo Clinic Rochester, Rochester, MN.
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5
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Yan W, Xu J, Fan H, Li L, Cui J, Du C, Deng S, Sui W, Xu Y, Hao M, Anderson KC, Zou D, Qiu L, An G. Early relapse within 18 months is a powerful dynamic predictor for prognosis and could revise static risk distribution in multiple myeloma. Cancer 2024; 130:421-432. [PMID: 37846845 DOI: 10.1002/cncr.35056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 08/04/2023] [Accepted: 09/11/2023] [Indexed: 10/18/2023]
Abstract
BACKGROUND The duration of response to treatment is a major prognostic factor, and early relapse (ER) strongly predicts inferior survival in multiple myeloma (MM). However, the definitions of ER in MM vary from study to study and how to dynamically integrate risk distribution is still unsolved. METHODS This study evaluated these ER definitions and further investigated the underlying relationship with static risk distribution in 629 newly diagnosed MM (NDMM) patients from the National Longitudinal Cohort of Hematological Diseases in China (NCT04645199). RESULTS These data indicated that early relapse within 18 months (ER18) after initial treatment was the best time point for identifying early progression and dynamic high-risk in MM. The ER18 population (114 of 587, 19.4%) presented with more aggressive biologic features and the inferior response to treatment compared to a reference cohort (p < .001), with a significantly short median overall survival (OS) of 28.9 months. Multivariate analyses confirmed the most significant prognostic value of ER18 on OS in the context of International Staging System stage, elevated lactate dehydrogenase, thrombocytopenia, cytogenetic abnormalities, and treatment (hazard ratio, 4.467; p < .001). The authors also described the specific transitions from static risk profile to dynamic risk distribution and then constructed a mixed-risk-pattern to identify four novel populations with distinct survival (p < .001). Additionally, the authors proposed a second-state model that predicts dynamic risk changes, enabling a complementary role to the Revised International Staging System model in facilitating individualized systematic treatment. CONCLUSIONS Collectively, this study concludes that ER18 is a simple and dynamic prognostic predictor in MM. In addition to static risk assessment, dynamic risk plays an important role in survival prediction.
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Affiliation(s)
- Wenqiang Yan
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Jingyu Xu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Huishou Fan
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Lingna Li
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Jian Cui
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Chenxing Du
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Shuhui Deng
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Weiwei Sui
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Yan Xu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Mu Hao
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Kenneth C Anderson
- LeBow Institute for Myeloma Therapeutics and Jerome Lipper Center for Multiple Myeloma Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
| | - Dehui Zou
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Lugui Qiu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Gang An
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
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Kleber M, Ntanasis-Stathopoulos I, Terpos E. The Role of t(11;14) in Tailoring Treatment Decisions in Multiple Myeloma. Cancers (Basel) 2023; 15:5829. [PMID: 38136374 PMCID: PMC10742268 DOI: 10.3390/cancers15245829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 12/07/2023] [Accepted: 12/11/2023] [Indexed: 12/24/2023] Open
Abstract
Multiple myeloma (MM) represents a hematological neoplasia with an uncontrolled proliferation of malignant plasma cells and complex cytogenetic abnormalities. t(11;14) has emerged as a crucial genetic aberration and is one of the most common primary translocations in MM. Patients harboring t(11;14) represent a distinctive subgroup with a clinical profile that differs from t(11;14)-negative MM risk categories. One of the key features linked with t(11;14) is the BCL2 dependency, indicating vulnerability to BCL2 inhibition. BCL2 inhibitors, such as venetoclax, demonstrated impressive efficacy alone or in combination with other anti-myeloma drugs in patients with RRMM accompanied by t(11;14) and BCL2 overexpression. Therefore, t(11;14) plays a key role in both risk stratification and informed decision making towards a tailored therapy. In this review, we highlight the biology of t(11;14) in MM cells, summarize the current evolving role of t(11;14) in the era of novel agents and novel targeted therapies, illuminate current efficacy and safety data of BCL2-based treatment options and explore the future prospects of individualized precision medicine for this special subgroup of patients with MM.
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Affiliation(s)
- Martina Kleber
- Department of Internal Medicine, Clinic Hirslanden Zurich, 8032 Zurich, Switzerland;
- Faculty of Medicine, University of Basel, 4031 Basel, Switzerland
| | - Ioannis Ntanasis-Stathopoulos
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece
| | - Evangelos Terpos
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece
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7
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Gay F. A rational approach to functional high-risk myeloma. HEMATOLOGY. AMERICAN SOCIETY OF HEMATOLOGY. EDUCATION PROGRAM 2023; 2023:433-442. [PMID: 38066896 PMCID: PMC10727111 DOI: 10.1182/hematology.2023000443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Multiple myeloma is a clinically and biologically highly heterogeneous disease, as the overall survival can vary from more than a decade in patients with standard risk disease treated with intensive chemotherapy to 2-3 years in patients with high-risk features. The current staging systems, which rely on baseline biological risk factors to stratify patients into groups with differing risks of progression or death, are sometimes suboptimal tools for identifying high-risk patients. This is particularly evident when considering the so-called functional high-risk patients-patients who do not necessarily display baseline high-risk features but typically show a suboptimal response to induction therapy or relapse early after treatment initiation: the survival of these patients is particularly poor even in the context of newer therapies. The prompt identification, as well as a consistent definition, of this subset of patients, as well as their management, currently represents an unmet medical need. In this review we explore the main characteristics of functional high-risk patients, the available known risk factors and scoring systems, and the possible management.
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Affiliation(s)
- Francesca Gay
- Division of Hematology 1, Clinical Trial Unit, AOU Città della Salute e della Scienza, Department of Molecular Biotechnology and Health Science, University of Torino, Torino, Italy
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8
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Fan H, Yan W, Li L, Xu J, Liu J, Xu Y, Sui W, Deng S, Du C, Yi S, Zou D, Qiu L, An G. The prognostic utility of dynamic risk stratification at disease progression in patients with multiple myeloma. Hematology 2023; 28:2182156. [PMID: 36815749 DOI: 10.1080/16078454.2023.2182156] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023] Open
Abstract
OBJECTIVES There may be a shift in risk stratification at progression compared to that at diagnosis in patients with multiple myeloma (MM). We aimed to evaluate whether re-staging and stage migration is of prognostic impact. METHODS Real-world data from the National Longitudinal Cohort of Hematologic Diseases-multiple myeloma were collected; 263 consecutive patients demonstrating disease progression were finally included. Staging at diagnosis and re-staging at progression were performed using the International Staging System (ISS) and Revised International Staging System (RISS). RESULTS Based on ISS re-staging, the median post-progression survival (mPPS) of patients with stage I, II, and III was 44.2, 21.7, and 11.6 months, respectively (P < 0.0001). Based on RISS re-staging, the mPPS of patients with stage I, II, and III was 50.3, 22.2, and 11.4 months, respectively (P < 0.0001). The mPPS in patients with improved, maintained, and deteriorated ISS stage migration from diagnosis was 33.6, 20.9, and 16 months, respectively (P = 0.0051) and that with improved, maintained, and deteriorated RISS stage migration was 48.4, 23.1, and 13.9 months, respectively (P < 0.001). Compared to patients with maintained or improved disease stage, those with deteriorated ISS/RISS migration showed significantly higher incidence of Del(17P) at progression and worse PPS. Multivariate analyses indicated both re-staging and stage migration by ISS/RISS at progression were independent predictors for PPS. CONCLUSIONS We demonstrated that ISS/RISS re-staging showed superior prognostic utility over ISS/RISS staging in predicting PPS. Patients with deteriorated stage migration or maintained advanced stage at progression may need more individualized treatment.
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Affiliation(s)
- Huihsou Fan
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Department of Hematology, The Affiliated Hospital of Qingdao University, Shandong, China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Wenqiang Yan
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Lingna Li
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Jingyu Xu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Jiahui Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Yan Xu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Weiwei Sui
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Shuhui Deng
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Chenxing Du
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Shuhua Yi
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Dehui Zou
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Lugui Qiu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
| | - Gang An
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.,Tianjin Institutes of Health Science, Tianjin, People's Republic of China
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9
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Banerjee R, Cicero KI, Lee SS, Cowan AJ. Definers and drivers of functional high-risk multiple myeloma: insights from genomic, transcriptomic, and immune profiling. Front Oncol 2023; 13:1240966. [PMID: 37849816 PMCID: PMC10577204 DOI: 10.3389/fonc.2023.1240966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 09/18/2023] [Indexed: 10/19/2023] Open
Abstract
Traditional prognostic models for newly diagnosed patients with multiple myeloma (MM), including International Staging System criteria and number of high-risk chromosomal abnormalities, are based on disease characteristics at diagnosis. However, the identification of patients at risk of more rapidly progressive MM is inherently a dynamic assessment. In a subset of patients with MM, adverse disease biology only becomes evident after the failure of first-line therapy. We define this entity as functional high-risk MM (FHRMM), encompassing relapse within 18 months of treatment initiation and/or within 12 months of frontline autologous stem cell transplantation. FHRMM is not adequately captured by traditional prognostic models, and there is a need for better understanding of mechanisms or risk factors for early relapse or progression. In this review, we explore potential definitions of FHRMM before delving into its underlying drivers based on genetic, transcriptomic, and immune cell profiling studies. Emerging data suggest that specific features of both myeloma cells and immune cells can enable the FHRMM phenotype. We conclude our review by discussing ongoing and future studies that seek to identify and intervene upon patients with FHRMM preemptively.
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Affiliation(s)
- Rahul Banerjee
- Division of Hematology and Oncology, Department of Medicine, University of Washington, Seattle, WA, United States
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA, United States
| | - Kara I. Cicero
- Division of Hematology and Oncology, Department of Medicine, University of Washington, Seattle, WA, United States
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA, United States
| | - Sarah S. Lee
- Division of Myeloma, Department of Hematology & Hematopoietic Cell Transplantation, City of Hope, CA, United States
| | - Andrew J. Cowan
- Division of Hematology and Oncology, Department of Medicine, University of Washington, Seattle, WA, United States
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA, United States
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10
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Beksac M, Iacobelli S, Koster L, Cornelissen J, Griskevicius L, Rabin NK, Stoppa AM, Meijer E, Mear JB, Zeerleder S, Mayer J, Fenk R, Fegueux N, Chevallier P, Konirova E, Snowden JA, Engelhardt M, Orchard K, Hulin C, Schaap N, Sossa C, Elmaagacli A, McLornan DP, Hayden PJ, Schönland S, Yakoub-Agha I. An early post-transplant relapse prediction score in multiple myeloma: a large cohort study from the chronic malignancies working party of EBMT. Bone Marrow Transplant 2023; 58:916-923. [PMID: 37160942 DOI: 10.1038/s41409-023-01999-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Revised: 04/17/2023] [Accepted: 04/21/2023] [Indexed: 05/11/2023]
Abstract
Early relapse (ER) following Autologous Hematopoietic Cell Transplantation (AHCT) confers a poor prognosis. We therefore developed a novel scoring system to predict ER. A total of 14,367 AHCT-1 patients were transplanted between 2014 and 2019, and were conditioned with Melphalan 200 mg/m2 (Mel200) (n = 7228; 2014-2017) (training cohort); Mel200 (n = 5616; 2018-2019) or Mel140 (n = 1523; 2018-2019) (validation cohorts). PFS-12 and the Cumulative Incidence of Relapse at 12 months were 84.1% and 14.7% (training Mel200), 87.2% and 11.6% (validation Mel200), and 80.3% and 16.9% (validation Mel140), respectively. The points in the risk score were: 0, 1,2 for ISS stages I, II, and III; Disease status: 0 (CR/VGPR); 1 (PR); 2 (SD/MR); 4 (Relapse/Progression); and 1 for Karnofsky ≤ 70. The distribution of scores: 0 (24%), 1 (33.9%), 2 (29.6 %), 3 (9.5%), and ≥4 (2.7%). The score separated PFS-12, with the lowest risk group (n = 1752) having a PFS-12 of 91.7% and the highest risk group (n = 195) 57.1%. This also applied in cytogenetically high-risk patients. If the pre-score baseline risks are 15% (standard risk) and 25% (high-risk), a score of ≥4 confers calculated risks of 38% and 54%, respectively. This novel EBMT ER score, therefore, allows for the identification of five discrete prognostic groups.
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Affiliation(s)
| | | | - Linda Koster
- European Society for Blood and Marrow Transplantation Leiden Study Unit, Leiden, the Netherlands
| | - Jan Cornelissen
- Erasmus University Medical Center-Daniel Den Hoed, Rotterdam, the Netherlands
| | | | - Neil K Rabin
- University College London Hospitals NHS Foundation Trust, London, UK
| | | | - Ellen Meijer
- VU University Medical Center, Amsterdam, the Netherlands
| | | | | | - Jiri Mayer
- University Hospital Brno, Brno, Czech Republic
| | - Roland Fenk
- University Hospital Duesseldorf, Dusseldorf, Germany
| | | | | | | | | | | | - Kim Orchard
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | | | - Nicolaas Schaap
- Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
| | - Claudia Sossa
- Clinica FOSCAL, Floridablanca, Santander, Colombia
- Universidad Autónoma de Bucaramanga - UNAB, Bucaramanga, Santander, Colombia
| | | | | | - Patrick J Hayden
- Department of Haematology, School of Medicine, Trinity College Dublin, Dublin, Ireland
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11
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Yavorkovsky LL. The role of staging in multiple myeloma. Expert Rev Hematol 2023; 16:933-942. [PMID: 37902242 DOI: 10.1080/17474086.2023.2277876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 10/27/2023] [Indexed: 10/31/2023]
Abstract
INTRODUCTION The importance of cancer staging is determined by how accurately it can predict prognosis, and how useful it is for treatment decisions. Compared to other malignancies, multiple myeloma (MM) staging proved more challenging because of unreliable prognostic factors and wide-ranging life expectancy. As traditional MM staging continues to evolve, it requires reassessment of its prognostic and predictive value. AREAS COVERED The studies that included prognostic and predictive value of MM stages from 1975 through 2023 were selected for this review using PubMed, MEDLINE platforms. The history and evolution of MM staging are revisited, including its role in predicting survival, treatment planning and potential practical implications for the future. The role of MM staging for oncological practice and patient counseling is discussed. EXPERT OPINION The utility of the traditional MM staging remains unsatisfactory because it lacks a strong connection with the disease biology, prognosis or treatment planning. Additionally, it demonstrates a modest value for patient counseling because individual prognosis is subject to under- or overestimation, and the median survival or survival rates are difficult concepts to grasp. Although the role of MM stages may change in the future, the current research upholds the notion that MM staging benefits more medical research and clinical trials than oncological practice.
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Affiliation(s)
- Leonid L Yavorkovsky
- Kaiser Permanente San Jose Medical Center, Oncology Division, 271 International Circle, San Jose, CA, USA
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12
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Geng C, Yang G, Zhou H, Wang H, Li Y, Leng Y, Zhang Z, Jian Y, Chen W. Characteristics and Risk Factors of Ultra-High-Risk Patients with Newly Diagnosed Multiple Myeloma. J Pers Med 2023; 13:jpm13040666. [PMID: 37109052 PMCID: PMC10146518 DOI: 10.3390/jpm13040666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 04/02/2023] [Accepted: 04/12/2023] [Indexed: 04/29/2023] Open
Abstract
OBJECTIVE To investigate the clinical characteristics and risk factors of ultra-high-risk (UHR) patients with newly diagnosed multiple myeloma (MM). METHODS We screened UHR patients with a survival of less than 24 months and we selected patients with a concurrent survival of more than 24 months as a control group. We retrospectively analyzed the clinical characteristics of UHR patients with newly diagnosed MM and screened related risk factors. RESULTS In total we analyzed 477 patients, which included 121 (25.4%) UHR patients and 356 (74.6%) control patients. Median overall survival (OS) and progression-free survival (PFS) of UHR patients was 10.5 months (7.5-13.5 months) and 6.3 months (5.4-7.2 months), respectively. Univariate logistic regression analysis showed that age > 65 years, hemoglobin (HGB) < 100 g/L, lactate dehydrogenase (LDH) > 250 U/L, serum creatinine (SCr) > 2 mg/dL, corrected serum calcium (CsCa) > 2.75 mmol/L, B-type natriuretic peptide (BNP) or N-terminal prohormone BNP (NT-proBNP) > 2 upper limit of normal (ULN), high-risk cytogenetics, Barthel index score, and International Staging System (ISS) stage III were associated with UHR MM. In a multivariate analysis, age > 65 years, LDH > 250 U/L, CsCa > 2.75 mmol/L, BNP or NT-proBNP > 2 ULN, high-risk cytogenetics, and Barthel index score were independent risk factors for UHR MM. Moreover, UHR patients had a worse response rate than control patients. CONCLUSION Our study highlighted the characteristics of UHR MM patients and suggested that the combination of organ insufficiency and highly malignant myeloma cells resulted in poor outcomes of patients with UHR MM.
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Affiliation(s)
- Chuanying Geng
- Department of Hematology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Guangzhong Yang
- Department of Hematology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Huixing Zhou
- Department of Hematology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Huijuan Wang
- Department of Hematology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Yanchen Li
- Department of Hematology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Yun Leng
- Department of Hematology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Zhiyao Zhang
- Department of Hematology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Yuan Jian
- Department of Hematology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Wenming Chen
- Department of Hematology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
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13
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Abstract
Despite recent advances multiple myeloma remains an incurable disease for most of the patients and initial remission will be followed by relapses requiring therapy. For many, there will be several remissions and relapses until resistance develops to all available therapies. With the introduction of several new agents, myeloma treatment has changed drastically and there are new options for the management of relapsed or refractory disease, including new drug classes with distinct mechanisms of action and cellular therapies. However, resistance to major drug classes used in first line remain the most critical factor for the choice of treatment at relapse. Continuous lenalidomide-based therapy is used extensively at first line and resistance to lenalidomide has become the key factor for the choice of salvage therapy. Daratumumab is increasingly used in first line and soon patients that relapse while on daratumumab will become a common challenge. Three-drug regimens are standard approach to manage relapsed disease. Adding drugs with new mechanisms of activity can improves outcomes and overcomes class resistance but, until now, while the biology is important, can offer only limited guidance for the choice of therapy.
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14
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BCMA in Multiple Myeloma-A Promising Key to Therapy. J Clin Med 2021; 10:jcm10184088. [PMID: 34575199 PMCID: PMC8472544 DOI: 10.3390/jcm10184088] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 09/06/2021] [Accepted: 09/07/2021] [Indexed: 12/19/2022] Open
Abstract
Despite the discoveries of numerous agents including next generation proteasome inhibitors, immunomodulatory drugs, and monoclonal antibodies, multiple myeloma (MM) remains an incurable disease. The field of myeloma treatment in refractory or relapsed patients after standard therapy entered a new era due to the B-cell maturation antigen (BMCA) targeted approach. BCMA is a member of the tumor necrosis factor receptor family with high expression in mature B-lymphocytes and plasma cells. Given the understanding of BCMA mechanism of action in MM, BCMA plays a promising role as a therapeutic target. Several clinical trials are underway to evolve the current BCMA targeted treatment concept such as antibody-drug conjugates (ADCs), bispecific T cell engagers (BITEs) and chimeric antigen receptor (CAR) T cell therapy. Current results of representative BCMA trials may close the gap of the unmet clinical need to further improve the outcome of heavily pretreated MM patients with the potency to change the paradigm in newly diagnosed and refractory MM. This comprehensive review will give an update on various BMCA targeted treatment modalities (ADCs, BITEs, CAR T cell therapy) and its existing results on efficacy and safety from preclinical and clinical trials.
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15
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Aberrant Plasma Cell Contamination of Peripheral Blood Stem Cell Autografts, Assessed by Next-Generation Flow Cytometry, Is a Negative Predictor for Deep Response Post Autologous Transplantation in Multiple Myeloma; A Prospective Study in 199 Patients. Cancers (Basel) 2021; 13:cancers13164047. [PMID: 34439201 PMCID: PMC8391595 DOI: 10.3390/cancers13164047] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 07/09/2021] [Accepted: 08/09/2021] [Indexed: 01/10/2023] Open
Abstract
High-dose chemotherapy with autologous stem cell support (ASCT) is the standard of care for eligible newly diagnosed Multiple Myeloma (MM) patients. Stem cell graft contamination by aberrant plasma cells (APCs) has been considered a possible predictive marker of subsequent clinical outcome, but the limited reports to date present unclear conclusions. We prospectively estimated the frequency of graft contamination using highly sensitive next-generation flow cytometry and evaluated its clinical impact in 199 myeloma patients who underwent an ASCT. Contamination (con+) was detected in 79/199 patients at a median level 2 × 10-5. Its presence and levels were correlated with response to induction treatment, with 94%, 71% and 43% achieving CR, VGPR and PR, respectively. Importantly, con+ grafts conferred 2-fold and 2.8-fold higher patient-risk of not achieving or delaying reaching CR (4 vs. 11 months) and MRD negativity (5 vs. 18 months) post ASCT, respectively. Our data also provide evidence of a potentially skewed bone marrow (BM) reconstitution due to unpurged grafts, since con+ derived BM had significantly higher prevalence of memory B cells. These data, together with the absence of significant associations with baseline clinical features, highlight graft contamination as a potential biomarker with independent prognostic value for deeper responses, including MRD negativity. Longer follow-up will reveal if this corresponds to PFS or OS advantage.
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16
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Identification of resistance pathways and therapeutic targets in relapsed multiple myeloma patients through single-cell sequencing. Nat Med 2021; 27:491-503. [PMID: 33619369 DOI: 10.1038/s41591-021-01232-w] [Citation(s) in RCA: 108] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 01/07/2021] [Indexed: 12/19/2022]
Abstract
Multiple myeloma (MM) is a neoplastic plasma-cell disorder characterized by clonal proliferation of malignant plasma cells. Despite extensive research, disease heterogeneity within and between treatment-resistant patients is poorly characterized. In the present study, we conduct a prospective, multicenter, single-arm clinical trial (NCT04065789), combined with longitudinal single-cell RNA-sequencing (scRNA-seq) to study the molecular dynamics of MM resistance mechanisms. Newly diagnosed MM patients (41), who either failed to respond or experienced early relapse after a bortezomib-containing induction regimen, were enrolled to evaluate the safety and efficacy of a daratumumab, carfilzomib, lenalidomide and dexamethasone combination. The primary clinical endpoint was safety and tolerability. Secondary endpoints included overall response rate, progression-free survival and overall survival. Treatment was safe and well tolerated; deep and durable responses were achieved. In prespecified exploratory analyses, comparison of 41 primary refractory and early relapsed patients, with 11 healthy subjects and 15 newly diagnosed MM patients, revealed new MM molecular pathways of resistance, including hypoxia tolerance, protein folding and mitochondria respiration, which generalized to larger clinical cohorts (CoMMpass). We found peptidylprolyl isomerase A (PPIA), a central enzyme in the protein-folding response pathway, as a potential new target for resistant MM. CRISPR-Cas9 deletion of PPIA or inhibition of PPIA with a small molecule inhibitor (ciclosporin) significantly sensitizes MM tumor cells to proteasome inhibitors. Together, our study defines a roadmap for integrating scRNA-seq in clinical trials, identifies a signature of highly resistant MM patients and discovers PPIA as a potent therapeutic target for these tumors.
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17
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Ntanasis-Stathopoulos I, Gavriatopoulou M, Terpos E, Dimopoulos MA. Real-World Treatment of Patients With Relapsed/Refractory Myeloma. CLINICAL LYMPHOMA MYELOMA & LEUKEMIA 2021; 21:379-385. [PMID: 33714682 DOI: 10.1016/j.clml.2021.01.018] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Revised: 01/18/2021] [Accepted: 01/21/2021] [Indexed: 01/18/2023]
Abstract
The continuous advances in the treatment landscape of multiple myeloma has led to the approval of several novel agents and their combinations that significantly improved patient outcomes. Despite their undoubtful effectiveness in the context of clinical trials, their impact on real-world (RW) clinical practice remains debatable. RW data on the role of novel agents and their combinations among patients with relapsed/refractory multiple myeloma have confirmed the efficacy of proteasome inhibitors, immunomodulatory drugs, and monoclonal antibodies. However, the magnitude of the benefit and the safety profile may differ among RW studies and between RW and pivotal clinical trials. Several variables may pertain to these observations and include patient selection, ethnicity, age, comorbidities, disease stage at diagnosis and at relapse, number of prior lines of therapy, disease subtype, presence of renal impairment, extramedullary disease, and cytogenetic abnormalities. All these contribute to a varying degree of disease and patient heterogeneity among the studies that may result in a differential treatment effect. The expertise of each medical center and the treatment setting in terms of availability and drug access are particularly important as well. Interestingly, RW observations may serve as proof of concept for designing novel clinical trials, as is the case with retreatment studies. In conclusion, clinical trial and RW data are complementary, and they should be considered to improve both clinical trial design and clinical practice.
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Affiliation(s)
- Ioannis Ntanasis-Stathopoulos
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Maria Gavriatopoulou
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Evangelos Terpos
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Meletios A Dimopoulos
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.
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18
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Kumar SK, Callander NS, Adekola K, Anderson L, Baljevic M, Campagnaro E, Castillo JJ, Chandler JC, Costello C, Efebera Y, Faiman M, Garfall A, Godby K, Hillengass J, Holmberg L, Htut M, Huff CA, Kang Y, Hultcrantz M, Larson S, Liedtke M, Martin T, Omel J, Shain K, Sborov D, Stockerl-Goldstein K, Weber D, Keller J, Kumar R. Multiple Myeloma, Version 3.2021, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Canc Netw 2020; 18:1685-1717. [PMID: 33285522 DOI: 10.6004/jnccn.2020.0057] [Citation(s) in RCA: 111] [Impact Index Per Article: 27.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Multiple myeloma is a malignant neoplasm of plasma cells that accumulate in bone marrow, leading to bone destruction and marrow failure. This manuscript discusses the management of patients with solitary plasmacytoma, smoldering multiple myeloma, and newly diagnosed multiple myeloma.
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Affiliation(s)
| | | | - Kehinde Adekola
- 3Robert H. Lurie Comprehensive Cancer of Center Northwestern University
| | | | | | | | - Jorge J Castillo
- 7Dana-Farber/Brigham and Women's Cancer Center
- Massachusetts General Hospital Cancer Center
| | - Jason C Chandler
- 8St. Jude Children's Research Hospital/The University of Tennessee Health Science Center
| | | | - Yvonne Efebera
- 10The Ohio State University Comprehensive Cancer Center - James Cancer Hospital and Solove Research Institute
| | - Matthew Faiman
- 11Case Comprehensive Cancer Center/University Hospitals Seidman Cancer Center and Cleveland Clinic Taussig Cancer Institute
| | - Alfred Garfall
- 12Abramson Cancer Center at the University of Pennsylvania
| | | | | | - Leona Holmberg
- 15Fred Hutchinson Cancer Research Center/Seattle Cancer Care Alliance
| | - Myo Htut
- 16City of Hope National Medical Center
| | - Carol Ann Huff
- 17The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins
| | | | | | | | | | - Thomas Martin
- 22UCSF Helen Diller Family Comprehensive Cancer Center
| | | | | | | | | | - Donna Weber
- 27The University of Texas MD Anderson Cancer Center; and
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19
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Beksac M, Savani BN. Prognostic scoring system after transplantation in myeloma: predicting early relapse. Br J Haematol 2020; 191:323-324. [PMID: 32712969 DOI: 10.1111/bjh.16986] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 06/30/2020] [Indexed: 11/30/2022]
Affiliation(s)
- Meral Beksac
- Department of Hematology, Ankara University, Ankara, Turkey
| | - Bipin N Savani
- Division of Hematology and Oncology, Vanderbilt University Medical Center, Nashville, TN, USA
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20
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Terpos E, Ntanasis-Stathopoulos I, Roussou M, Kanellias N, Fotiou D, Migkou M, Eleutherakis-Papaiakovou E, Gavriatopoulou M, Kastritis E, Dimopoulos MA. Long PFS of more than 7 years is achieved in 9% of myeloma patients in the era of conventional chemotherapy and of first-generation novel anti-myeloma agents: a single-center experience over 20-year period. Ann Hematol 2020; 99:1257-1264. [DOI: 10.1007/s00277-020-04060-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2019] [Accepted: 04/27/2020] [Indexed: 12/01/2022]
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