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Arguello-Tomas M, Mozas P, Albiol N, López-Esteban M, Sierra J, Nomdedéu J, Martinez-Laperche C, Moga E, Piñeyroa JA, Delgado J, Osorio S, Moreno C. Risk scores predicting disease progression in early-stage CLL: Comparative analysis and usefulness of IGHV subset #2 to improve their accuracy. Cancer 2024. [PMID: 39264834 DOI: 10.1002/cncr.35552] [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: 06/07/2024] [Revised: 07/29/2024] [Accepted: 08/19/2024] [Indexed: 09/14/2024]
Abstract
BACKGROUND Overall, the prognosis of patients with chronic lymphocytic leukemia (CLL) in the early phase of the disease (Rai 0, Binet A) is favorable; some patients never require therapy. However, some patients require intervention shortly after diagnosis. In the past decade, several risk scores (RS) have been developed to predict disease progression, yet some patients are misclassified. On the other hand, IGHV subset 2 (IGHV2) predicts poor outcomes. METHODS A retrospective and multicentric study was conducted to compare the accuracy of five different RS (IPS-E, CR0, AIPS-E, CLL-IPI, and Barcelona-Brno) to predict disease progression in 781 stage A previously untreated patients with CLL. As an exploratory analysis, it was further investigated whether the inclusion of the IGHV2 as a poor prognostic parameter improved the accuracy of RS. RESULTS All the scores identified a similar group of patients with CLL in early stage with low-, intermediate-, and high-risk progression. Discrimination was high and similar in all RS (c-index = 0.74-0.79, area under the curve = 0.7-0.75), as well as calibration (p = .98) and parsimony, although CLL-IPI showed the best results (Akaike information criterion = 441). A total of 34.4% of patients were categorized within the same RS and concordance was at least moderate between RS. CONCLUSION Moreover, the results suggest that IGHV2 may improve the accuracy of RS.
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Affiliation(s)
- Miguel Arguello-Tomas
- Hospital de la Santa Creu I Sant Pau, Barcelona, Spain
- Facultat Medicina Universitat Autònoma Barcelona, Barcelona, Spain
- Institut de Recerca Sant Pau, Barcelona, Spain
- Institut Josep Carreras, Barcelona, Spain
| | - Pablo Mozas
- Hospital Clínic Barcelona, Barcelona, Spain
- Institut Investigaciones Biomédicas August Pi i Sunyer, Barcelona, Spain
| | - Nil Albiol
- Hospital Clínic Barcelona, Barcelona, Spain
- Institut Investigaciones Biomédicas August Pi i Sunyer, Barcelona, Spain
| | | | - Jorge Sierra
- Hospital de la Santa Creu I Sant Pau, Barcelona, Spain
- Facultat Medicina Universitat Autònoma Barcelona, Barcelona, Spain
- Institut de Recerca Sant Pau, Barcelona, Spain
- Institut Josep Carreras, Barcelona, Spain
| | - Josep Nomdedéu
- Hospital de la Santa Creu I Sant Pau, Barcelona, Spain
- Facultat Medicina Universitat Autònoma Barcelona, Barcelona, Spain
- Institut de Recerca Sant Pau, Barcelona, Spain
| | - Carolina Martinez-Laperche
- Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Gregorio Marañón, Madrid, Spain
| | - Esther Moga
- Hospital de la Santa Creu I Sant Pau, Barcelona, Spain
- Facultat Medicina Universitat Autònoma Barcelona, Barcelona, Spain
- Institut de Recerca Sant Pau, Barcelona, Spain
| | - Juan A Piñeyroa
- Hospital Clínic Barcelona, Barcelona, Spain
- Institut Investigaciones Biomédicas August Pi i Sunyer, Barcelona, Spain
| | - Julio Delgado
- Hospital Clínic Barcelona, Barcelona, Spain
- Institut Investigaciones Biomédicas August Pi i Sunyer, Barcelona, Spain
- Universitat de Barcelona, Barcelona, Spain
| | - Santiago Osorio
- Hospital General Universitario Gregorio Marañón, Madrid, Spain
- Instituto de Investigación Gregorio Marañón, Madrid, Spain
| | - Carol Moreno
- Hospital de la Santa Creu I Sant Pau, Barcelona, Spain
- Facultat Medicina Universitat Autònoma Barcelona, Barcelona, Spain
- Institut de Recerca Sant Pau, Barcelona, Spain
- Institut Josep Carreras, Barcelona, Spain
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González-Gascón-y-Marín I, Ballesteros-Andrés M, Martínez-Flores S, Rodríguez-Vicente AE, Pérez-Carretero C, Quijada-Álamo M, Rodríguez-Sánchez A, Hernández-Rivas JÁ. The Five "Ws" of Frailty Assessment and Chronic Lymphocytic Leukemia: Who, What, Where, Why, and When. Cancers (Basel) 2023; 15:4391. [PMID: 37686667 PMCID: PMC10486487 DOI: 10.3390/cancers15174391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 08/28/2023] [Accepted: 08/30/2023] [Indexed: 09/10/2023] Open
Abstract
Chronic lymphocytic leukemia (CLL) is a disease of the elderly, but chronological age does not accurately discriminate frailty status at the inter-individual level. Frailty describes a person's overall resilience. Since CLL is a stressful situation, it is relevant to assess the patient´s degree of frailty, especially before starting antineoplastic treatment. We are in the era of targeted therapies, which have helped to control the disease more effectively and avoid the toxicity of chemo (immuno) therapy. However, these drugs are not free of side effects and other aspects arise that should not be neglected, such as interactions, previous comorbidities, or adherence to treatment, since most of these medications are taken continuously. The challenge we face is to balance the risk of toxicity and efficacy in a personalized way and without forgetting that the most frequent cause of death in CLL is related to the disease. For this purpose, comprehensive geriatric assessment (GA) provides us with the opportunity to evaluate multiple domains that may affect tolerance to treatment and that could be improved with appropriate interventions. In this review, we will analyze the state of the art of GA in CLL through the five Ws.
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Affiliation(s)
| | | | - Sara Martínez-Flores
- Department of Geriatric Medicine, University Hospital Infanta Leonor, 28031 Madrid, Spain
| | - Ana-E Rodríguez-Vicente
- IBSAL, IBMCC, CSIC, Cancer Research Center, University of Salamanca, 37007 Salamanca, Spain
- Department of Hematology, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - Claudia Pérez-Carretero
- IBSAL, IBMCC, CSIC, Cancer Research Center, University of Salamanca, 37007 Salamanca, Spain
- Department of Hematology, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - Miguel Quijada-Álamo
- IBSAL, IBMCC, CSIC, Cancer Research Center, University of Salamanca, 37007 Salamanca, Spain
- Department of Hematology, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - Alberto Rodríguez-Sánchez
- IBSAL, IBMCC, CSIC, Cancer Research Center, University of Salamanca, 37007 Salamanca, Spain
- Department of Hematology, University Hospital of Salamanca, 37007 Salamanca, Spain
| | - José-Ángel Hernández-Rivas
- Department of Hematology, University Hospital Infanta Leonor, 28031 Madrid, Spain
- Department of Medicine, Complutense University, 28040 Madrid, Spain
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Huang HY, Wang Y, Herold T, Gale RP, Wang JZ, Li L, Lin HX, Liang Y. A survival prediction model and nomogram based on immune-related gene expression in chronic lymphocytic leukemia cells. Front Med (Lausanne) 2022; 9:1026812. [PMID: 36600891 PMCID: PMC9806429 DOI: 10.3389/fmed.2022.1026812] [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: 09/05/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Introduction There are many different chronic lymphoblastic leukemia (CLL) survival prediction models and scores. But none provide information on expression of immune-related genes in the CLL cells. Methods We interrogated data from the Gene Expression Omnibus database (GEO, GSE22762; Number = 151; training) and International Cancer Genome Consortium database (ICGC, CLLE-ES; Number = 491; validation) to develop an immune risk score (IRS) using Least absolute shrinkage and selection operator (LASSO) Cox regression analyses based on expression of immune-related genes in CLL cells. The accuracy of the predicted nomogram we developed using the IRS, Binet stage, and del(17p) cytogenetic data was subsequently assessed using calibration curves. Results A survival model based on expression of 5 immune-related genes was constructed. Areas under the curve (AUC) for 1-year survivals were 0.90 (95% confidence interval, 0.78, 0.99) and 0.75 (0.54, 0.87) in the training and validation datasets, respectively. 5-year survivals of low- and high-risk subjects were 89% (83, 95%) vs. 6% (0, 17%; p < 0.001) and 98% (95, 100%) vs. 92% (88, 96%; p < 0.001) in two datasets. The IRS was an independent survival predictor of both datasets. A calibration curve showed good performance of the nomogram. In vitro, the high expression of CDKN2A and SREBF2 in the bone marrow of patients with CLL was verified by immunohistochemistry analysis (IHC), which were associated with poor prognosis and may play an important role in the complex bone marrow immune environment. Conclusion The IRS is an accurate independent survival predictor with a high C-statistic. A combined nomogram had good survival prediction accuracy in calibration curves. These data demonstrate the potential impact of immune related genes on survival in CLL.
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Affiliation(s)
- Han-ying Huang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China,Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China,Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yun Wang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China,Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Tobias Herold
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Robert Peter Gale
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China,Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China,Haematology Research Centre, Department of Immunology and Inflammation, Imperial College London, London, United Kingdom
| | - Jing-zi Wang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China,Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Liang Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China,Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Huan-xin Lin
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China,Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China,Huan-xin Lin,
| | - Yang Liang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China,Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China,*Correspondence: Yang Liang,
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The CLL comorbidity index in a population-based cohort: a tool for clinical care and research. Blood Adv 2022; 6:2701-2706. [PMID: 35008098 PMCID: PMC9043948 DOI: 10.1182/bloodadvances.2021005716] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 12/16/2021] [Indexed: 11/20/2022] Open
Abstract
The CLL comorbidity index demonstrates prognostic significance in a large patient cohort, justifying its use in clinical care and research. The CLL comorbidity index associates with time to first treatment, event-free survival, and overall survival in treatment-naive patients with CLL.
The chronic lymphocytic leukemia comorbidity index (CLL-CI) is an efficient, CLL-specific tool derived from the Cumulative Illness Rating Scale. The CLL-CI is based on the assessment of the organ systems found to be most strongly associated with event-free survival (EFS) in CLL: vascular, upper gastrointestinal, and endocrine, at the time of initiation of CLL therapy. The CLL-CI categorizes patients into low, intermediate, and high risk groups. In the present study, we have employed the CLL-CI in a population-based cohort comprising 4975 patients with CLL. We demonstrate that CLL-CI retains prognostic significance in this large cohort and is associated with overall survival (OS) and EFS from time of first therapy. Furthermore, CLL-CI associates with OS, EFS, and time to first treatment from diagnosis independently of the CLL International Prognostic Index. These findings support the use of the CLL-CI both in research and in clinical practice.
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Molica S, Seymour JF, Polliack A. A perspective on prognostic models in chronic lymphocytic leukemia in the era of targeted agents. Hematol Oncol 2021; 39:595-604. [PMID: 34596261 DOI: 10.1002/hon.2929] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 09/18/2021] [Accepted: 09/20/2021] [Indexed: 12/23/2022]
Abstract
Despite the increase in the number of prognostic models currently available for evaluating patients with chronic lymphocytic leukemia (CLL), their current application and utilization in clinical practice in the era of targeted agents is unclear. A critical reappraisal of recently developed prognostic models is presented in this review. The underlying CLL's genetic instability and changes in the host's health and comorbidities can all contribute to the acquisition of additional risk factors for adverse outcomes during the course of the disease. Therefore, available risk models solely based on pretreatment variables only partially predict patients' clinical outcome. A dynamic prognostic model that takes into account changes in the risk profile over time could indeed be useful in routine clinical practice. The next generation of risk assessment models should incorporate post-treatment and response biomarkers such as minimal residual disease. Finally, recent advances in the field of machine learning present novel opportunities to generate models capable of providing an individualized estimation of clinical outcomes in CLL. However, in the era of improved prognostic models, it is important to remember that these indices should supplement but not replace clinical expertise and medical decision-making.
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Affiliation(s)
- Stefano Molica
- Department Hematology-Oncology, Azienda Ospedaliera Pugliese-Ciaccio, Catanzaro, Italy
| | - John F Seymour
- Department of Haematology, Peter MacCallum Cancer Centre, Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia
| | - Aaron Polliack
- Department of Hematology, Hadassah - Hebrew University Medical Center, Jerusalem, Israel
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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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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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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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