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.
Keywords: Antibiotics; CLL; Immune Dysfunction; Immunoglobulins; Preemptive Treatment.
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