TY - JOUR
T1 - SOHO State of the Art Updates and Next Questions | Infections in Chronic Lymphocytic Leukemia Patients
T2 - Risks and Management
AU - Gargiulo, Ernesto
AU - Ribeiro, Eduardo Flavio Oliveira
AU - Niemann, Carsten U
N1 - Disclosure
This work was supported by grants from Luxembourg National Research Fund (FNR; PRIDE15/10675146/CANBIO and C20/BM/14592342) and the Danish National Research Foundation (DNRF; DNRF126) to EG. CN received funding from the Danish Cancer Society and the EU funded ERA PERMED program for this work.
CUN received research funding and/or consultancy fees outside this work from Abbvie, AstraZeneca, Octapharma, Janssen, CSL Behring, Beigene, Genmab, Eli Lilly and Takeda. All the other authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest
Copyright © 2023 Elsevier Inc. All rights reserved.
PY - 2023/5
Y1 - 2023/5
N2 - Although chronic lymphocytic leukemia (CLL) is a malignancy characterized by accumulation of tumor cells in the blood, bone marrow, lymph nodes and secondary lymphoid tissues, the hallmark of the disease and the major cause of death for patients with CLL is actually immune dysfunction and associated infections. Despite improvement in treatment based on combination chemoimmunotherapy and targeted treatment with BTK and BCL-2 inhibitors leading to longer overall survival for patients with CLL, the mortality due to infections have not improved over the last 4 decades. Thus, infections are now the main cause of death for patients with CLL, posing threats to the patient whether during the premalignant state of monoclonal B lymphocytosis (MBL), during the watch & wait phase for treatment naïve patients, or upon treatment in terms of chemoimmunotherapy or targeted treatment. To test whether the natural history of immune dysfunction and infections in CLL can be changed, we have developed the machine learning based algorithm CLL-TIM.org to identify these patients. The CLL-TIM algorithm is currently being used for selection of patients for the clinical trial PreVent-ACaLL (NCT03868722), testing whether short-term treatment with the BTK inhibitor acalabrutinib and the BCL-2 inhibitor venetoclax can improve immune function and decrease the risk of infections for this high-risk patient population. We here review the background for and management of infectious risks in CLL.
AB - Although chronic lymphocytic leukemia (CLL) is a malignancy characterized by accumulation of tumor cells in the blood, bone marrow, lymph nodes and secondary lymphoid tissues, the hallmark of the disease and the major cause of death for patients with CLL is actually immune dysfunction and associated infections. Despite improvement in treatment based on combination chemoimmunotherapy and targeted treatment with BTK and BCL-2 inhibitors leading to longer overall survival for patients with CLL, the mortality due to infections have not improved over the last 4 decades. Thus, infections are now the main cause of death for patients with CLL, posing threats to the patient whether during the premalignant state of monoclonal B lymphocytosis (MBL), during the watch & wait phase for treatment naïve patients, or upon treatment in terms of chemoimmunotherapy or targeted treatment. To test whether the natural history of immune dysfunction and infections in CLL can be changed, we have developed the machine learning based algorithm CLL-TIM.org to identify these patients. The CLL-TIM algorithm is currently being used for selection of patients for the clinical trial PreVent-ACaLL (NCT03868722), testing whether short-term treatment with the BTK inhibitor acalabrutinib and the BCL-2 inhibitor venetoclax can improve immune function and decrease the risk of infections for this high-risk patient population. We here review the background for and management of infectious risks in CLL.
UR - https://pubmed.ncbi.nlm.nih.gov/36868914
U2 - 10.1016/j.clml.2023.02.001
DO - 10.1016/j.clml.2023.02.001
M3 - Review article
C2 - 36868914
SN - 2152-2650
VL - 23
SP - 322
EP - 332
JO - Clinical Lymphoma, Myeloma and Leukemia
JF - Clinical Lymphoma, Myeloma and Leukemia
IS - 5
ER -