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Negrete-Rodríguez P, Gallardo-Pérez MM, Lira-Lara O, Melgar-de-la-Paz M, Hamilton-Avilés LE, Ocaña-Ramm G, Robles-Nasta M, Sánchez-Bonilla D, Olivares-Gazca JC, Mateos MV, Ruiz-Delgado GJ, Ruiz-Argüelles GJ. Prevalence and Consequences of a Delayed Diagnosis in Multiple Myeloma: A Single Institution Experience. CLINICAL LYMPHOMA, MYELOMA & LEUKEMIA 2024; 24:478-483. [PMID: 38555259 DOI: 10.1016/j.clml.2024.03.004] [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: 12/06/2023] [Revised: 02/19/2024] [Accepted: 03/06/2024] [Indexed: 04/02/2024]
Abstract
BACKGROUND Multiple myeloma (MM) is a disease with unspecific initial symptoms which may lead into a delay in the diagnosis, seemingly increasing the risk of complications and in turn reducing the overall survival (OS). OBJECTIVE To analyze the consequences of a delayed diagnosis of MM in both the OS and the progression-free survival (PFS) of the patients in a single center in México. METHODS The study included patients with MM who were diagnosed at Clínica Ruiz, Puebla, México, between 1983 and 2022. According to the time elapsed between the onset of symptoms to the establishment of the definite diagnosis of MM, 4 groups were constructed: 1) Less than 3 months, 2) 3-6 months, 3) 6-12 months, and 4) More than 12 months. RESULTS About 136 patients had a complete clinical record and at least a 3-month follow up period. A delay in the diagnosis of MM (more than 3 months from the onset of symptoms) was recorded in 92/136 persons (68%). The median follow-up for the whole group was 24.7 months, median OS was 131.4 months, whereas median PFS was 85.4 months. There was a significant trend for being in earlier stages of the disease and being diagnosed within 3 months from the onset of symptoms (P = .049). Both OS and PFS were similar in the patients diagnosed before or after 3 months from the symptoms onset (P = .772). The 6-12 months group was the group with the better median both OS (197.4 months) and DFS (197.4) from the diagnosis. The median OS for the other groups were similar among them. CONCLUSION A delay in the diagnosis of MM is very frequent in México (68% of cases); despite the fact that there was a significant trend for being in earlier stages of the disease and being diagnosed within 3 months from the onset of symptoms, we did not find a relationship between a delay on the diagnosis of the disease and a higher risk of complications and/or poor prognosis. Possible explanations to these findings are discussed.
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Affiliation(s)
- Paola Negrete-Rodríguez
- Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, México; Facultad de Medicina, Universidad de las Américas Puebla, Puebla, México
| | - Moisés Manuel Gallardo-Pérez
- Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, México; Facultad de Medicina, Universidad Popular Autónoma del Estado de Puebla, Puebla, México
| | - Olivia Lira-Lara
- Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, México; Facultad de Medicina, Universidad Veracruzana, Veracruz, México
| | - Miranda Melgar-de-la-Paz
- Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, México; Facultad de Medicina, Universidad Anáhuac Puebla, Puebla, México
| | - Luis Enrique Hamilton-Avilés
- Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, México; Facultad de Medicina, Universidad Popular Autónoma del Estado de Puebla, Puebla, México
| | - Guillermo Ocaña-Ramm
- Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, México; Facultad de Medicina, Universidad Popular Autónoma del Estado de Puebla, Puebla, México
| | - Max Robles-Nasta
- Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, México; Facultad de Medicina, Universidad Popular Autónoma del Estado de Puebla, Puebla, México
| | - Daniela Sánchez-Bonilla
- Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, México; Facultad de Medicina, Universidad Popular Autónoma del Estado de Puebla, Puebla, México
| | - Juan Carlos Olivares-Gazca
- Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, México; Facultad de Medicina, Universidad Popular Autónoma del Estado de Puebla, Puebla, México
| | - María-Victoria Mateos
- Department of Hematology, University Hospital of Salamanca (CAUSA/IBSAL) and Center for Biomedical Research in Network of Cancer (CIBERONC), Salamanca, Spain
| | - Guillermo J Ruiz-Delgado
- Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, México; Facultad de Medicina, Universidad Popular Autónoma del Estado de Puebla, Puebla, México
| | - Guillermo J Ruiz-Argüelles
- Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, México; Facultad de Medicina, Universidad Popular Autónoma del Estado de Puebla, Puebla, México.
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Malard F, Neri P, Bahlis NJ, Terpos E, Moukalled N, Hungria VTM, Manier S, Mohty M. Multiple myeloma. Nat Rev Dis Primers 2024; 10:45. [PMID: 38937492 DOI: 10.1038/s41572-024-00529-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/16/2024] [Indexed: 06/29/2024]
Abstract
Multiple myeloma (MM) is a haematological lymphoid malignancy involving tumoural plasma cells and is usually characterized by the presence of a monoclonal immunoglobulin protein. MM is the second most common haematological malignancy, with an increasing global incidence. It remains incurable because most patients relapse or become refractory to treatments. MM is a genetically complex disease with high heterogeneity that develops as a multistep process, involving acquisition of genetic alterations in the tumour cells and changes in the bone marrow microenvironment. Symptomatic MM is diagnosed using the International Myeloma Working Group criteria as a bone marrow infiltration of ≥10% clonal plasma cells, and the presence of at least one myeloma-defining event, either standard CRAB features (hypercalcaemia, renal failure, anaemia and/or lytic bone lesions) or biomarkers of imminent organ damage. Younger and fit patients are considered eligible for transplant. They receive an induction, followed by consolidation with high-dose melphalan and autologous haematopoietic cell transplantation, and maintenance therapy. In older adults (ineligible for transplant), the combination of daratumumab, lenalidomide and dexamethasone is the preferred option. If relapse occurs and requires further therapy, the choice of therapy will be based on previous treatment and response and now includes immunotherapies, such as bi-specific monoclonal antibodies and chimeric antigen receptor T cell therapy.
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Affiliation(s)
- Florent Malard
- Sorbonne Université, Centre de Recherche Saint-Antoine INSERM UMRs938, Service d'Hématologie Clinique et de Thérapie Cellulaire, Hôpital Saint Antoine, AP-HP, Paris, France.
| | - Paola Neri
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Canada
| | - Nizar J Bahlis
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Canada
| | - Evangelos Terpos
- Department of Clinical Therapeutics, Alexandra General Hospital, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Nour Moukalled
- Bone Marrow Transplantation Program, Department of Internal Medicine, American University of Beirut Medical Center, Beirut, Lebanon
| | | | - Salomon Manier
- Department of Hematology, Lille University Hospital and INSERM UMR-S1277 and CNRS UMR9020, Lille, France
| | - Mohamad Mohty
- Sorbonne Université, Centre de Recherche Saint-Antoine INSERM UMRs938, Service d'Hématologie Clinique et de Thérapie Cellulaire, Hôpital Saint Antoine, AP-HP, Paris, France.
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Geng J, Zhao J, Fan R, Zhu Z, Zhang Y, Zhu Y, Yang Y, Xu L, Lin X, Hu K, Rudan I, Song P, Li X, Wu X. Global, regional, and national burden and quality of care of multiple myeloma, 1990-2019. J Glob Health 2024; 14:04033. [PMID: 38299781 PMCID: PMC10832550 DOI: 10.7189/jogh.14.04033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024] Open
Abstract
Background Multiple myeloma (MM) is the second most common haematologic malignancy, presenting a great disease burden on the general population; however, the quality of care of MM is overlooked. We therefore assessed gains and disparity in quality of care worldwide from 1990 to 2019 based on a novel summary indicator - the quality of care index (QCI) - and examined its potential for improvement. Methods Using the Global Burden of Disease 2019 data set, we calculated the QCI of MM for 195 countries and territories. We used the principal component analysis to extract the first principal component of ratios with the combinations of mortality to incidence, prevalence to incidence, disability-adjusted life years to prevalence, and years of life lost to years lived with disability as QCI. We also conducted a series of descriptive and comparative analyses of QCI disparities with age, gender, period, geographies, and sociodemographic development, and compared the QCI among countries with similar socio-demographic index (SDI) through frontier analysis. Results The age-standardised rates of MM were 1.92 (95% uncertainty interval (UI) = 1.68, 2.12) in incidence and 1.42 (95% UI = 1.24, 1.52) in deaths per 100 000 population in 2019, and were predicted to increase in the future. The global age-standardised QCI increased from 51.31 in 1990 to 64.28 in 2019. In 2019, New Zealand had the highest QCI at 99.29 and the Central African Republic had the lowest QCI at 10.74. The gender disparity of QCI was reduced over the years, with the largest being observed in the sub-Saharan region. Regarding age, QCI maintained a decreasing trend in patients aged >60 in SDI quintiles. Generally, QCI improved with the SDI increase. Results of frontier analysis suggested that there is a potential to improve the quality of care across all levels of development spectrum. Conclusions Quality of care of MM improved during the past three decades, yet disparities in MM care remain across different countries, age groups, and genders. It is crucial to establish local objectives aimed at enhancing MM care and closing the gap in health care inequality.
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Affiliation(s)
- Jiawei Geng
- Department of Big Data in Health Science School of Public Health, Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Centre for Global Health, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianhui Zhao
- Department of Big Data in Health Science School of Public Health, Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Rong Fan
- Department of Big Data in Health Science School of Public Health, Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zecheng Zhu
- Department of Big Data in Health Science School of Public Health, Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuchen Zhang
- Department of Big Data in Health Science School of Public Health, Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yingshuang Zhu
- Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yichi Yang
- Department of Biostatistics, Graduate School of Medicine, Hokkaido University, Sapporo, Japan
- Department of Social Medicine, Graduate School of Medicine, Hirosaki University, Hirosaki, Japan
| | - Liying Xu
- Department of Big Data in Health Science School of Public Health, Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiangjie Lin
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Hematologic Malignancies, Diagnosis and Treatment, Hangzhou, Zhejiang, China
| | - Kejia Hu
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Igor Rudan
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Peige Song
- School of Public Health and Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xue Li
- Department of Big Data in Health Science School of Public Health, Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Xifeng Wu
- Department of Big Data in Health Science School of Public Health, Centre of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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