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Li Y, Wang S, Xiao H, Lu F, Zhang B, Zhou T. Evaluation and validation of the prognostic value of platelet indices in patients with leukemia. Clin Exp Med 2023; 23:1835-1844. [PMID: 36622510 DOI: 10.1007/s10238-022-00985-z] [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: 12/10/2022] [Accepted: 12/29/2022] [Indexed: 01/10/2023]
Abstract
Platelets (PLTs) are believed to play a role in the process by which tumors can accelerate their growth rate, as well as offer the physical and mechanical support necessary to evade the immunological system and metastasis. There is, however, no literature available if PLTs have a role in leukemia. It is significant for PLTs to play a part in hematological malignancies from a therapeutic standpoint and to have the capacity to serve as a prognostic marker in the evolution of leukemia. This is because PLTs play a crucial role in the development of cancer and tumors. In this study, it will be shown that PLT count can be used to predict long-term prognosis after chemotherapy especially in the case of acute myeloid leukemia patients. Furthermore, low PLT-to-lymphocyte ratio and mean PLT volume, as well as high PLT distribution width, are associated with poor prognosis and may represent a novel independent prognostic factor.
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Affiliation(s)
- Yuyan Li
- Department of Experimental Diagnostic, Jilin Kingmed for Clinical Laboratory Co., Ltd., Changchun, 130000, China
| | - Shuangge Wang
- Department of Experimental Diagnostic, Jilin Kingmed for Clinical Laboratory Co., Ltd., Changchun, 130000, China
| | - Han Xiao
- Department of Experimental Diagnostic, Jilin Kingmed for Clinical Laboratory Co., Ltd., Changchun, 130000, China
| | - Fang Lu
- Department of Experimental Diagnostic, Jilin Kingmed for Clinical Laboratory Co., Ltd., Changchun, 130000, China
| | - Bin Zhang
- Department of Experimental Diagnostic, Jilin Kingmed for Clinical Laboratory Co., Ltd., Changchun, 130000, China
| | - Tingting Zhou
- Department of Experimental Diagnostic, Jilin Kingmed for Clinical Laboratory Co., Ltd., Changchun, 130000, China.
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2
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Chronic lymphocytic leukemia treatment algorithm 2022. Blood Cancer J 2022; 12:161. [PMID: 36446777 PMCID: PMC9708674 DOI: 10.1038/s41408-022-00756-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 11/08/2022] [Accepted: 11/10/2022] [Indexed: 12/03/2022] Open
Abstract
The treatment landscape for patients with chronic lymphocytic leukemia (CLL) has changed considerably with the introduction of very effective oral targeted therapies (such as Bruton tyrosine kinase inhibitors and venetoclax) and next-generation anti-CD20 monoclonal antibodies (such as obinutuzumab). These agents lead to improved outcomes in patients with CLL, even among those with high-risk features, such as del17p13 or TP53 mutation and unmutated immunoglobulin heavy chain (IGHV) genes. Selecting the right treatment for the right patient requires consideration of disease characteristics and prior treatment sequence, as well as patient preferences and comorbidities. The CLL-International Prognostic Index (CLL-IPI) remains the best-validated tool in predicting the time to first therapy among previously untreated patients, which guides selection for early intervention efforts. This review summarizes our current approach to the management of CLL, right from the time of diagnosis through relapsed disease.
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3
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Agius R, Parviz M, Niemann CU. Artificial intelligence models in chronic lymphocytic leukemia - recommendations toward state-of-the-art. Leuk Lymphoma 2021; 63:265-278. [PMID: 34612160 DOI: 10.1080/10428194.2021.1973672] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Artificial intelligence (AI), machine learning and predictive modeling are becoming enabling technologies in many day-to-day applications. Translation of these advances to the patient's bedside for AI assisted interventions is not yet the norm. With specific emphasis on CLL, here, we review the progress of prognostic models in hematology and highlight sources of stagnation that may be limiting significant improvements in prognostication in the near future. We discuss issues related to performance, trust, modeling simplicity, and prognostic marker robustness and find that the major limiting factor in progressing toward state-of-the-art prognostication within the hematological community, is not the lack of able AI algorithms but rather, the lack of their adoption. Current models in CLL still deal with the 'average' patient while the use of patient-centric approaches remains absent. Using lessons from research areas where machine learning has become an enabling technology, we derive recommendations and propose methods for achieving state-of-the-art predictions in modeling health data, that can be readily adopted by the CLL modeling community.
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Affiliation(s)
- Rudi Agius
- Department of Hematology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Mehdi Parviz
- Department of Hematology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Carsten Utoft Niemann
- Department of Hematology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
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4
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Smolej L, Vodárek P, Écsiová D, Šimkovič M. Chemoimmunotherapy in the First-Line Treatment of Chronic Lymphocytic Leukaemia: Dead Yet, or Alive and Kicking? Cancers (Basel) 2021; 13:3134. [PMID: 34201565 PMCID: PMC8267736 DOI: 10.3390/cancers13133134] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 06/13/2021] [Accepted: 06/20/2021] [Indexed: 12/23/2022] Open
Abstract
The paradigm of first-line treatment of chronic lymphocytic leukaemia (CLL) is currently undergoing a radical change. On the basis of several randomised phase III trials showing prolongation of progression-free survival, chemoimmunotherapy is being replaced by treatment based on novel, orally available targeted inhibitors such as Bruton tyrosine kinase inhibitors ibrutinib and acalabrutinib or bcl-2 inhibitor venetoclax. However, the use of these agents may be associated with other disadvantages. First, with the exception of one trial in younger/fit patients, no studies have so far demonstrated benefit regarding the ultimate endpoint of overall survival. Second, oral inhibitors are extremely expensive and thus currently unavailable due to the absence of reimbursement in some countries. Third, treatment with ibrutinib and acalabrutinib necessitates long-term administration until progression; this may be associated with accumulation of late side effects, problems with patient compliance, and selection of resistant clones. Therefore, the identification of a subset of patients who could benefit from chemoimmunotherapy would be ideal. Current data suggest that patients with the mutated variable region of the immunoglobulin heavy chain (IGHV) achieve fairly durable remissions, especially when treated with fludarabine, cyclophosphamide, and rituximab (FCR) regimen. This review discusses current options for treatment-naïve patients with CLL.
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Affiliation(s)
- Lukáš Smolej
- 4th Department of Internal Medicine–Hematology, Faculty of Medicine, University Hospital, Charles University, 50005 Hradec Králové, Czech Republic; (P.V.); (D.É.); (M.Š.)
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5
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Pérez-Carretero C, González-Gascón-y-Marín I, Rodríguez-Vicente AE, Quijada-Álamo M, Hernández-Rivas JÁ, Hernández-Sánchez M, Hernández-Rivas JM. The Evolving Landscape of Chronic Lymphocytic Leukemia on Diagnosis, Prognosis and Treatment. Diagnostics (Basel) 2021; 11:diagnostics11050853. [PMID: 34068813 PMCID: PMC8151186 DOI: 10.3390/diagnostics11050853] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 04/25/2021] [Accepted: 05/05/2021] [Indexed: 12/22/2022] Open
Abstract
The knowledge of chronic lymphocytic leukemia (CLL) has progressively deepened during the last forty years. Research activities and clinical studies have been remarkably fruitful in novel findings elucidating multiple aspects of the pathogenesis of the disease, improving CLL diagnosis, prognosis and treatment. Whereas the diagnostic criteria for CLL have not substantially changed over time, prognostication has experienced an expansion with the identification of new biological and genetic biomarkers. Thanks to next-generation sequencing (NGS), an unprecedented number of gene mutations were identified with potential prognostic and predictive value in the 2010s, although significant work on their validation is still required before they can be used in a routine clinical setting. In terms of treatment, there has been an impressive explosion of new approaches based on targeted therapies for CLL patients during the last decade. In this current chemotherapy-free era, BCR and BCL2 inhibitors have changed the management of CLL patients and clearly improved their prognosis and quality of life. In this review, we provide an overview of these novel advances, as well as point out questions that should be further addressed to continue improving the outcomes of patients.
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Affiliation(s)
- Claudia Pérez-Carretero
- Cancer Research Center (IBMCC) CSIC-University of Salamanca, 37007 Salamanca, Spain; (C.P.-C.); (A.E.R.-V.); (M.Q.-Á.)
- Instituto de Investigación Biomédica (IBSAL), 37007 Salamanca, Spain
- Department of Hematology, University Hospital of Salamanca, 37007 Salamanca, Spain
| | | | - Ana E. Rodríguez-Vicente
- Cancer Research Center (IBMCC) CSIC-University of Salamanca, 37007 Salamanca, Spain; (C.P.-C.); (A.E.R.-V.); (M.Q.-Á.)
- Instituto de Investigación Biomédica (IBSAL), 37007 Salamanca, Spain
- Department of Hematology, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - Miguel Quijada-Álamo
- Cancer Research Center (IBMCC) CSIC-University of Salamanca, 37007 Salamanca, Spain; (C.P.-C.); (A.E.R.-V.); (M.Q.-Á.)
- Instituto de Investigación Biomédica (IBSAL), 37007 Salamanca, Spain
- Department of Hematology, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - José-Ángel Hernández-Rivas
- Department of Hematology, Infanta Leonor University Hospital, 28031 Madrid, Spain; (I.G.-G.-y-M.); (J.-Á.H.-R.)
- Department of Medicine, Complutense University, 28040 Madrid, Spain
| | - María Hernández-Sánchez
- Cancer Research Center (IBMCC) CSIC-University of Salamanca, 37007 Salamanca, Spain; (C.P.-C.); (A.E.R.-V.); (M.Q.-Á.)
- Instituto de Investigación Biomédica (IBSAL), 37007 Salamanca, Spain
- Department of Hematology, University Hospital of Salamanca, 37007 Salamanca, Spain
- Correspondence: (M.H.-S.); (J.M.H.-R.); Tel.: +34-923-294-812 (M.H.-S. & J.M.H.-R.)
| | - Jesús María Hernández-Rivas
- Cancer Research Center (IBMCC) CSIC-University of Salamanca, 37007 Salamanca, Spain; (C.P.-C.); (A.E.R.-V.); (M.Q.-Á.)
- Instituto de Investigación Biomédica (IBSAL), 37007 Salamanca, Spain
- Department of Hematology, University Hospital of Salamanca, 37007 Salamanca, Spain
- Department of Medicine, University of Salamanca, 37008 Salamanca, Spain
- Correspondence: (M.H.-S.); (J.M.H.-R.); Tel.: +34-923-294-812 (M.H.-S. & J.M.H.-R.)
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6
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From Biomarkers to Models in the Changing Landscape of Chronic Lymphocytic Leukemia: Evolve or Become Extinct. Cancers (Basel) 2021; 13:cancers13081782. [PMID: 33917885 PMCID: PMC8068228 DOI: 10.3390/cancers13081782] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 03/27/2021] [Accepted: 04/05/2021] [Indexed: 12/23/2022] Open
Abstract
Simple Summary Chronic lymphocytic leukemia (CLL) is characterized by a highly variable clinical course. Thus, predicting the outcome of patients with this disease is a topic of special interest. The rapidly changing treatment landscape of CLL has questioned the value of classical biomarkers and prognostic models. Herein we examine the current state-of-the-art of prognostic and predictive biomarkers in the setting of new oral targeted agents with special focus on the most controversial findings over the last years. We also discuss the available information on the role of “old” and “new” prognostic models in the era of oral small molecules. Abstract Chronic lymphocytic leukemia (CLL) is an extremely heterogeneous disease. With the advent of oral targeted agents (Tas) the treatment of CLL has undergone a revolution, which has been accompanied by an improvement in patient’s survival and quality of life. This paradigm shift also affects the value of prognostic and predictive biomarkers and prognostic models, most of them inherited from the chemoimmunotherapy era but with a different behavior with Tas. This review discusses: (i) the role of the most relevant prognostic and predictive biomarkers in the setting of Tas; and (ii) the validity of classic and new scoring systems in the context of Tas. In addition, a critical point of view about predictive biomarkers with special emphasis on 11q deletion, novel resistance mutations, TP53 abnormalities, IGHV mutational status, complex karyotype and NOTCH1 mutations is stated. We also go over prognostic models in early stage CLL such as IPS-E. Finally, we provide an overview of the applicability of the CLL-IPI for patients treated with Tas, as well as the emergence of new models, generated with data from patients treated with Tas.
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7
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Reid JC, Golubeva D, Boyd AL, Hollands CG, Henly C, Orlando L, Leber A, Hébert J, Morabito F, Cutrona G, Agnelli L, Gentile M, Ferrarini M, Neri A, Leber B, Bhatia M. Human pluripotent stem cells identify molecular targets of trisomy 12 in chronic lymphocytic leukemia patients. Cell Rep 2021; 34:108845. [PMID: 33730576 DOI: 10.1016/j.celrep.2021.108845] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 01/13/2021] [Accepted: 02/17/2021] [Indexed: 10/21/2022] Open
Abstract
Identifying precise targets of individual cancers remains challenging. Chronic lymphocytic leukemia (CLL) represents the most common adult hematologic malignancy, and trisomy 12 (tri12) represents a quarter of CLL patients. We report that tri12 human pluripotent stem cells (hPSCs) allow for the identification of gene networks and targets specific to tri12, which are controlled by comparative normal PSCs. Identified targets are upregulated in tri12 leukemic cells from a cohort of 159 patients with monoclonal B cell lymphocytosis and CLL. tri12 signaling patterns significantly influence progression-free survival. Actionable targets are identified using high-content drug testing and functionally validated in an additional 44 CLL patient samples. Using xenograft models, interleukin-1 receptor-associated kinase 4 (IRAK4) inhibitor is potent and selective against human tri12 CLL versus healthy patient-derived xenografts. Our study uses hPSCs to uncover targets from genetic aberrations and apply them to cancer. These findings provide immediate translational potential as biomarkers and targets for therapeutic intervention.
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Affiliation(s)
- Jennifer C Reid
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Diana Golubeva
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Allison L Boyd
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Cameron G Hollands
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Charisa Henly
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Luca Orlando
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Andrew Leber
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Josée Hébert
- Department of Medicine, Université de Montréal, Montreal, QC, Canada; Division of Hematology-Oncology, Maisonneuve-Rosemont Hospital, Montreal, QC, Canada
| | - Fortunato Morabito
- Department of Onco-Hematology, Biotechnology Research Unit, AO of Cosenza, Cosenza, Italy; Hematology and Bone Marrow Transplant Unit, Augusta Victoria Hospital, Jerusalem, Israel
| | - Giovanna Cutrona
- Molecular Pathology Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Luca Agnelli
- Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy; Department of Onco-Hematology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy; Pathobiology Unit 2, IRCCS National Cancer Institute, Milan, Italy
| | - Massimo Gentile
- Department of Onco-Hematology, Biotechnology Research Unit, AO of Cosenza, Cosenza, Italy
| | - Manlio Ferrarini
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | - Antonino Neri
- Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy; Department of Onco-Hematology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy
| | - Brian Leber
- Department of Medicine, McMaster University, Juravinski Hospital, Hamilton, ON, Canada
| | - Mickie Bhatia
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada.
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8
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Molica S. Chronic lymphocytic leukemia prognostic models in real life: still a long way off. Expert Rev Hematol 2021; 14:137-141. [PMID: 33438478 DOI: 10.1080/17474086.2021.1876558] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Stefano Molica
- Department Hematology-Oncology, Azienda Ospedaliera Pugliese-Ciaccio, Catanzaro, Italy
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9
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Yun X, Zhang Y, Wang X. Recent progress of prognostic biomarkers and risk scoring systems in chronic lymphocytic leukemia. Biomark Res 2020; 8:40. [PMID: 32939265 PMCID: PMC7487566 DOI: 10.1186/s40364-020-00222-3] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 08/26/2020] [Indexed: 12/13/2022] Open
Abstract
Chronic lymphocytic leukemia (CLL) is the most prevalent adult leukemia with high heterogeneity in the western world. Thus, investigators identified a number of prognostic biomarkers and scoring systems to guide treatment decisions and validated them in the context of immunochemotherapy. A better understanding of prognostic biomarkers, including serum markers, flow cytometry outcomes, IGHV mutation status, microRNAs, chromosome aberrations and gene mutations, have contributed to prognosis in CLL. Del17p/ TP53 mutation, NOTCH1 mutation, CD49d, IGHV mutation status, complex karyotypes and microRNAs were reported to be of predictive values to guide clinical decisions. Based on the biomarkers above, classic prognostic models, such as the Rai and Binet staging systems, MDACC nomogram, GCLLSG model and CLL-IPI, were developed to improve risk stratification and tailor treatment intensity. Considering the presence of novel agents, many investigators validated the conventional prognostic biomarkers in the setting of novel agents and only TP53 mutation status/del 17p and CD49d expression were reported to be of prognostic value. Whether other prognostic indicators and models can be used in the context of novel agents, further studies are required.
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Affiliation(s)
- Xiaoya Yun
- Department of Hematology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250021 Shandong China
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No.324, Jingwu Road, Jinan, 250021 Shandong China
- School of Medicine, Shandong University, Jinan, 250012 Shandong China
- Shandong Provincial Engineering Research Center of Lymphoma, Jinan, 250021 Shandong China
- National clinical research center for hematologic diseases, Jinan, 250021 Shandong China
| | - Ya Zhang
- Department of Hematology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250021 Shandong China
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No.324, Jingwu Road, Jinan, 250021 Shandong China
- School of Medicine, Shandong University, Jinan, 250012 Shandong China
- Shandong Provincial Engineering Research Center of Lymphoma, Jinan, 250021 Shandong China
- National clinical research center for hematologic diseases, Jinan, 250021 Shandong China
| | - Xin Wang
- Department of Hematology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250021 Shandong China
- Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No.324, Jingwu Road, Jinan, 250021 Shandong China
- School of Medicine, Shandong University, Jinan, 250012 Shandong China
- Shandong Provincial Engineering Research Center of Lymphoma, Jinan, 250021 Shandong China
- National clinical research center for hematologic diseases, Jinan, 250021 Shandong China
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10
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González-Gascón-y-Marín I, Muñoz-Novas C, Figueroa I, Hernández-Sánchez M, Rodríguez-Vicente AE, Quijada-Álamo M, Pérez-Carretero C, Moreno C, Collado R, Espinet B, Puiggros A, Heras NDL, Bosch F, Hernández JÁ. Prognosis Assessment of Early-Stage Chronic Lymphocytic Leukemia: Are We Ready to Predict Clinical Evolution Without a Crystal Ball? CLINICAL LYMPHOMA MYELOMA & LEUKEMIA 2020; 20:548-555.e4. [DOI: 10.1016/j.clml.2020.03.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Revised: 03/07/2020] [Accepted: 03/12/2020] [Indexed: 12/26/2022]
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Kreuzberger N, Damen JA, Trivella M, Estcourt LJ, Aldin A, Umlauff L, Vazquez-Montes MD, Wolff R, Moons KG, Monsef I, Foroutan F, Kreuzer KA, Skoetz N. Prognostic models for newly-diagnosed chronic lymphocytic leukaemia in adults: a systematic review and meta-analysis. Cochrane Database Syst Rev 2020; 7:CD012022. [PMID: 32735048 PMCID: PMC8078230 DOI: 10.1002/14651858.cd012022.pub2] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
BACKGROUND Chronic lymphocytic leukaemia (CLL) is the most common cancer of the lymphatic system in Western countries. Several clinical and biological factors for CLL have been identified. However, it remains unclear which of the available prognostic models combining those factors can be used in clinical practice to predict long-term outcome in people newly-diagnosed with CLL. OBJECTIVES To identify, describe and appraise all prognostic models developed to predict overall survival (OS), progression-free survival (PFS) or treatment-free survival (TFS) in newly-diagnosed (previously untreated) adults with CLL, and meta-analyse their predictive performances. SEARCH METHODS We searched MEDLINE (from January 1950 to June 2019 via Ovid), Embase (from 1974 to June 2019) and registries of ongoing trials (to 5 March 2020) for development and validation studies of prognostic models for untreated adults with CLL. In addition, we screened the reference lists and citation indices of included studies. SELECTION CRITERIA We included all prognostic models developed for CLL which predict OS, PFS, or TFS, provided they combined prognostic factors known before treatment initiation, and any studies that tested the performance of these models in individuals other than the ones included in model development (i.e. 'external model validation studies'). We included studies of adults with confirmed B-cell CLL who had not received treatment prior to the start of the study. We did not restrict the search based on study design. DATA COLLECTION AND ANALYSIS We developed a data extraction form to collect information based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS). Independent pairs of review authors screened references, extracted data and assessed risk of bias according to the Prediction model Risk Of Bias ASsessment Tool (PROBAST). For models that were externally validated at least three times, we aimed to perform a quantitative meta-analysis of their predictive performance, notably their calibration (proportion of people predicted to experience the outcome who do so) and discrimination (ability to differentiate between people with and without the event) using a random-effects model. When a model categorised individuals into risk categories, we pooled outcome frequencies per risk group (low, intermediate, high and very high). We did not apply GRADE as guidance is not yet available for reviews of prognostic models. MAIN RESULTS From 52 eligible studies, we identified 12 externally validated models: six were developed for OS, one for PFS and five for TFS. In general, reporting of the studies was poor, especially predictive performance measures for calibration and discrimination; but also basic information, such as eligibility criteria and the recruitment period of participants was often missing. We rated almost all studies at high or unclear risk of bias according to PROBAST. Overall, the applicability of the models and their validation studies was low or unclear; the most common reasons were inappropriate handling of missing data and serious reporting deficiencies concerning eligibility criteria, recruitment period, observation time and prediction performance measures. We report the results for three models predicting OS, which had available data from more than three external validation studies: CLL International Prognostic Index (CLL-IPI) This score includes five prognostic factors: age, clinical stage, IgHV mutational status, B2-microglobulin and TP53 status. Calibration: for the low-, intermediate- and high-risk groups, the pooled five-year survival per risk group from validation studies corresponded to the frequencies observed in the model development study. In the very high-risk group, predicted survival from CLL-IPI was lower than observed from external validation studies. Discrimination: the pooled c-statistic of seven external validation studies (3307 participants, 917 events) was 0.72 (95% confidence interval (CI) 0.67 to 0.77). The 95% prediction interval (PI) of this model for the c-statistic, which describes the expected interval for the model's discriminative ability in a new external validation study, ranged from 0.59 to 0.83. Barcelona-Brno score Aimed at simplifying the CLL-IPI, this score includes three prognostic factors: IgHV mutational status, del(17p) and del(11q). Calibration: for the low- and intermediate-risk group, the pooled survival per risk group corresponded to the frequencies observed in the model development study, although the score seems to overestimate survival for the high-risk group. Discrimination: the pooled c-statistic of four external validation studies (1755 participants, 416 events) was 0.64 (95% CI 0.60 to 0.67); 95% PI 0.59 to 0.68. MDACC 2007 index score The authors presented two versions of this model including six prognostic factors to predict OS: age, B2-microglobulin, absolute lymphocyte count, gender, clinical stage and number of nodal groups. Only one validation study was available for the more comprehensive version of the model, a formula with a nomogram, while seven studies (5127 participants, 994 events) validated the simplified version of the model, the index score. Calibration: for the low- and intermediate-risk groups, the pooled survival per risk group corresponded to the frequencies observed in the model development study, although the score seems to overestimate survival for the high-risk group. Discrimination: the pooled c-statistic of the seven external validation studies for the index score was 0.65 (95% CI 0.60 to 0.70); 95% PI 0.51 to 0.77. AUTHORS' CONCLUSIONS Despite the large number of published studies of prognostic models for OS, PFS or TFS for newly-diagnosed, untreated adults with CLL, only a minority of these (N = 12) have been externally validated for their respective primary outcome. Three models have undergone sufficient external validation to enable meta-analysis of the model's ability to predict survival outcomes. Lack of reporting prevented us from summarising calibration as recommended. Of the three models, the CLL-IPI shows the best discrimination, despite overestimation. However, performance of the models may change for individuals with CLL who receive improved treatment options, as the models included in this review were tested mostly on retrospective cohorts receiving a traditional treatment regimen. In conclusion, this review shows a clear need to improve the conducting and reporting of both prognostic model development and external validation studies. For prognostic models to be used as tools in clinical practice, the development of the models (and their subsequent validation studies) should adapt to include the latest therapy options to accurately predict performance. Adaptations should be timely.
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Key Words
- adult
- female
- humans
- male
- age factors
- bias
- biomarkers, tumor
- calibration
- confidence intervals
- discriminant analysis
- disease-free survival
- genes, p53
- genes, p53/genetics
- immunoglobulin heavy chains
- immunoglobulin heavy chains/genetics
- immunoglobulin variable region
- immunoglobulin variable region/genetics
- leukemia, lymphocytic, chronic, b-cell
- leukemia, lymphocytic, chronic, b-cell/mortality
- leukemia, lymphocytic, chronic, b-cell/pathology
- models, theoretical
- neoplasm staging
- prognosis
- progression-free survival
- receptors, antigen, b-cell
- receptors, antigen, b-cell/genetics
- reproducibility of results
- tumor suppressor protein p53
- tumor suppressor protein p53/genetics
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MESH Headings
- Adult
- Age Factors
- Bias
- Biomarkers, Tumor
- Calibration
- Confidence Intervals
- Discriminant Analysis
- Disease-Free Survival
- Female
- Genes, p53/genetics
- Humans
- Immunoglobulin Heavy Chains/genetics
- Immunoglobulin Variable Region/genetics
- Leukemia, Lymphocytic, Chronic, B-Cell/mortality
- Leukemia, Lymphocytic, Chronic, B-Cell/pathology
- Male
- Models, Theoretical
- Neoplasm Staging
- Prognosis
- Progression-Free Survival
- Receptors, Antigen, B-Cell/genetics
- Reproducibility of Results
- Tumor Suppressor Protein p53/genetics
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Affiliation(s)
- Nina Kreuzberger
- Cochrane Haematology, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Johanna Aag Damen
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | | | - Lise J Estcourt
- Haematology/Transfusion Medicine, NHS Blood and Transplant, Oxford, UK
| | - Angela Aldin
- Cochrane Haematology, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Lisa Umlauff
- Cochrane Haematology, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | | | | | - Karel Gm Moons
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Ina Monsef
- Cochrane Haematology, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Farid Foroutan
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Karl-Anton Kreuzer
- Center of Integrated Oncology Cologne-Bonn, Department I of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Nicole Skoetz
- Cochrane Cancer, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
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12
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Morabito F, Gentile M, Monti P, Recchia AG, Menichini P, Skafi M, Atrash M, De Luca G, Bossio S, Al-Janazreh H, Galimberti S, Salah Z, Morabito L, Mujahed A, Hindiyeh M, Dono M, Fais F, Cutrona G, Neri A, Tripepi G, Fronza G, Ferrarini M. TP53 dysfunction in chronic lymphocytic leukemia: clinical relevance in the era of B-cell receptors and BCL-2 inhibitors. Expert Opin Investig Drugs 2020; 29:869-880. [PMID: 32551999 DOI: 10.1080/13543784.2020.1783239] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
INTRODUCTION Patients with TP53 dysfunction, assessed by del(17p) or TP53 mutations, respond poorly to chemo-immunotherapy and fare better with the new therapies (BCR and BCL-2 inhibitors); however, it is unclear whether their response is similar to that of patients without anomalies or whether there is currently an adequate determination of TP53 dysfunction. AREA COVERED A literature search was undertaken on clinical trials and real-world experience data on patients with TP53 dysfunction treated with different protocols. Moreover, data on the TP53 biological function and on the tests currently employed for its assessment were reviewed. EXPERT OPINION Although TP53 dysfunction has less negative influence on the new biological therapies, patients with these alterations, particularly those with biallelic inactivation of TP53, have a worst outcome with these therapies than those without alterations. At present, a determination of TP53, particularly with next generation sequencing (NGS) methodologies, may be sufficient for the identifications of the patients unsuitable for chemo-immunotherapy, although integration with del(17p) would be advisable. For the future, more extensive determinations of the TP53 status, including functional assays, may become part of the current armamentarium for a better patient stratification and treatment with newer protocols.
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Affiliation(s)
- Fortunato Morabito
- Hematology Department and Bone Marrow Transplant Unit, Cancer Care Center, Augusta Victoria Hospital , Jerusalem, Israel.,Biotechnology Research Unit, Aprigliano, AO/ASP , Cosenza, Italy
| | - Massimo Gentile
- Biotechnology Research Unit, Aprigliano, AO/ASP , Cosenza, Italy.,Hematology Unit, Hematology and Oncology Department , Cosenza, Italy
| | - Paola Monti
- Mutagenesis and Cancer Prevention Unit, IRCCS Ospedale Policlinico San Martino , Genoa, Italy
| | | | - Paola Menichini
- Mutagenesis and Cancer Prevention Unit, IRCCS Ospedale Policlinico San Martino , Genoa, Italy
| | - Mamdouh Skafi
- Hematology Department and Bone Marrow Transplant Unit, Cancer Care Center, Augusta Victoria Hospital , Jerusalem, Israel
| | - Moien Atrash
- Hematology Department and Bone Marrow Transplant Unit, Cancer Care Center, Augusta Victoria Hospital , Jerusalem, Israel
| | - Giuseppa De Luca
- Molecular Diagnostic Unit, IRCCS Ospedale Policlinico San Martino , Genoa, Italy
| | - Sabrina Bossio
- Biotechnology Research Unit, Aprigliano, AO/ASP , Cosenza, Italy
| | - Hamdi Al-Janazreh
- Hematology Department and Bone Marrow Transplant Unit, Cancer Care Center, Augusta Victoria Hospital , Jerusalem, Israel
| | | | - Zaidoun Salah
- The Lautenberg Center for General and Tumor Immunology, Department of Immunology and Cancer Research-Institute for Medical Research Israel-Canada, Hebrew University-Hadassah Medical School , Jerusalem, Israel
| | - Lucio Morabito
- Humanitas Clinical and Research Center, IRCCS , Rozzano, Italy
| | - Alham Mujahed
- Laboratory Department, Cancer Care Center, Augusta Victoria Hospital , Jerusalem, Israel
| | - Musa Hindiyeh
- Laboratory Department, Cancer Care Center, Augusta Victoria Hospital , Jerusalem, Israel
| | - Mariella Dono
- Molecular Diagnostic Unit, IRCCS Ospedale Policlinico San Martino , Genoa, Italy
| | - Franco Fais
- Molecular Pathology Unit, IRCCS Ospedale Policlinico San Martino , Genova, Italy.,Department of Experimental Medicine, University of Genoa , Genoa, Italy
| | - Giovanna Cutrona
- Molecular Pathology Unit, IRCCS Ospedale Policlinico San Martino , Genova, Italy
| | - Antonino Neri
- Department of Oncology and Hemato-Oncology, University of Milan , Milan, Italy.,Hematology Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico , Milan, Italy
| | | | - Gilberto Fronza
- Mutagenesis and Cancer Prevention Unit, IRCCS Ospedale Policlinico San Martino , Genoa, Italy
| | - Manlio Ferrarini
- Department of Experimental Medicine, University of Genoa , Genoa, Italy
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13
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Molica S, Giannarelli D. Prognostic models for chronic lymphocytic leukemia (CLL): a systematic review and meta-analysis. Leukemia 2020; 35:615-618. [PMID: 32565543 DOI: 10.1038/s41375-020-0924-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 06/06/2020] [Accepted: 06/09/2020] [Indexed: 01/21/2023]
Affiliation(s)
- Stefano Molica
- Department Hematology-Oncology, Azienda Ospedaliera Pugliese-Ciaccio, Catanzaro, Italy.
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14
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El-Khazragy N, Esmaiel MA, Mohamed MM, Hassan NS. Upregulation of long noncoding RNA Lnc-IRF2-3 and Lnc-ZNF667-AS1 is associated with poor survival in B-chronic lymphocytic leukemia. Int J Lab Hematol 2020; 42:284-291. [PMID: 32083800 DOI: 10.1111/ijlh.13167] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 01/22/2020] [Accepted: 01/27/2020] [Indexed: 01/01/2023]
Abstract
BACKGROUND Lnc-IRF2-3 and Lnc-ZNF667-AS1 were recently studied as a positive biomarker for many tumor cells. However, experimental studies found that they are associated with worse outcomes in B-CLL. METHODS A prospective case study was conducted on 135 B-CLL patients that were compared to thirty healthy controls. The patients were followed up for 40 months and quantitative measurements of Lnc-IRF2-3 and Lnc-ZNF667-AS1 were measured and compared between the two groups as well as high-risk and low low-risk B-CLL. RESULTS Lnc-IRF2-3 and Lnc-ZNF667-AS1 had a high specificity (94% and 85%) and sensitivity (85%, 87%), respectively, to differentiate B-CLL from healthy controls. Furthermore, they showed high expression levels in high-risk CLL groups. For survival analysis, there was a negative correlation between overall survival (OS) and progression-free survival (PFS) and both biomarkers. However, it was not evident in multivariate Cox regression analysis; in patients with Lnc-IRF2-3 expression level, >67 had a significant decrease in OS and PFS. However, there is no significant effect for high expression levels of Lnc-ZNF667-AS1 on OS (P = .16) or PFS (P = .48). CONCLUSION The Lnc-IRF2-3 and Lnc-ZNF667-AS1 are promising prognostic biomarkers in B-CLL.
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Affiliation(s)
- Nashwa El-Khazragy
- Clinical Pathology/Hematology and Biomedical Research Departments, Faculty of Medicine, Ain Shams University, Cairo, Egypt.,Global Research Labs, Cairo, Egypt
| | - Marwa A Esmaiel
- Department of Biochemistry, Faculty of Science, Ain shams University, Cairo, Egypt
| | - Magdy M Mohamed
- Department of Biochemistry, Faculty of Science, Ain shams University, Cairo, Egypt
| | - Nahla S Hassan
- Department of Biochemistry, Faculty of Science, Ain shams University, Cairo, Egypt
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15
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Parikh SA. Chronic lymphocytic leukemia treatment algorithm 2018. Blood Cancer J 2018; 8:93. [PMID: 30283014 PMCID: PMC6170426 DOI: 10.1038/s41408-018-0131-2] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 08/22/2018] [Accepted: 09/17/2018] [Indexed: 11/08/2022] Open
Abstract
The treatment landscape for patients with chronic lymphocytic leukemia (CLL) has changed considerably with the introduction of very effective oral targeted therapies (such as ibrutinib, idelalisib, and venetoclax), and next-generation anti-CD20 monoclonal antibodies (such as obinutuzumab). These agents lead to improved outcomes in CLL, even among patients with high-risk features, such as del17p13 or TP53 mutation and unmutated immunoglobulin heavy chain (IGHV) genes. Each of these treatments is associated with a unique toxicity profile; in the absence of randomized data, the choice of one type of treatment over another depends on the co-morbidities of the patient. Chemoimmunotherapy still plays an important role in the management of previously untreated CLL patients, particularly among young fit patients who have standard risk FISH profile and mutated IGHV genes. Richter's transformation of CLL remains a difficult complication to treat, although therapy with programmed death 1 inhibitors such as pembrolizumab and nivolumab has shown impressive responses in a subset of patients. Our ability to risk stratify CLL patients continues to evolve; the CLL-International Prognostic Index (CLL-IPI) is the best validated tool in predicting time to first therapy among previously untreated patients. This review summarizes the current approach to risk stratification and management of CLL patients.
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MESH Headings
- Algorithms
- Biomarkers, Tumor
- Combined Modality Therapy
- Disease Management
- Disease Progression
- Disease Susceptibility
- Drug Resistance, Neoplasm
- Humans
- Leukemia, Lymphocytic, Chronic, B-Cell/diagnosis
- Leukemia, Lymphocytic, Chronic, B-Cell/etiology
- Leukemia, Lymphocytic, Chronic, B-Cell/mortality
- Leukemia, Lymphocytic, Chronic, B-Cell/therapy
- Practice Guidelines as Topic
- Prognosis
- Recurrence
- Treatment Outcome
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