Appropriateness of using granulocyte colony-stimulating factor (G-CSF) for primary prophylaxis of febrile neutropenia in solid tumors

Immune Dysfunction and Infection - Interaction between CLL and Treatment: A Reflection on Current Treatment Paradigms and Unmet Needs

BACKGROUND

Chronic lymphocytic leukemia (CLL) is a hematological malignancy characterized by immune dysfunction, which significantly contributes to increased morbidity and mortality due to infections.

SUMMARY

Advancement in therapeutic strategies based on combination chemoimmunotherapy and targeted treatment have increased life expectancy for patients affected by CLL. However, mortality and morbidity due to infection showed no improvement over the last decades. Although therapy options are highly efficient in targeting leukemic cells, several studies highlighted the interactions of different treatments with the tumor microenvironment immune components, significantly impacting their clinical efficacy and fostering increased risk of infections.

KEY MESSAGES

Given the profound immune dysfunction caused by CLL itself, treatment can thus represent a double-edged sword. Thus, it is essential to increase our understanding and awareness on how conventional therapies affect the disease-microenvironment-infection axis to ensure the best personalized strategy for each patient. This requires careful consideration of the advantages and disadvantages of efficient treatments, whether chemoimmunotherapy or targeted combinations, leading to risk of infectious complications. To this regard, our machine learning-based algorithm CLL Treatment-Infection Model, currently implemented into the local electronic health record system for Eastern Denmark, aims at early identification of patients at high risk of serious infections (PreVent-ACaLL; NCT03868722). We here review strategies for management of immune dysfunction and infections in CLL.

SOHO State of the Art Updates and Next Questions | Infections in Chronic Lymphocytic Leukemia Patients: Risks and Management

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.

Febrile neutropenia prophylaxis, G-CSF physician preferences: discrete-choice experiment

OBJECTIVES

Febrile neutropenia (FN) commonly occurs during cancer chemotherapy. Prophylaxis with granulocyte colony-stimulating factors (G-CSFs) is known to reduce the severity and incidence of FN and infections in patients with cancer. Despite the proven efficacy, G-CSFs are not always prescribed as recommended. We performed a discrete-choice experiment (DCE) to determine what factors drive the physician preference for FN prophylaxis in patients with cancer undergoing chemotherapy.

METHODS

Attributes for the DCE were selected based on literature search and on expert focus group discussions and comprised pain at the injection site, presence of bone pain, associated fever/influenza syndrome, efficacy of prophylaxis, biosimilar availability, number of injections per chemotherapy cycle and cost. Oncologists, in a national database, were solicited to participate in an online DCE. The study collected the responses to the choice scenarios, the oncologist characteristics and their usual prescriptions of G-CSFs in the context of breast, lungs and gastrointestinal cancers.

RESULTS

Overall, the responses from 205 physicians were analysed. The physicians were mainly male (61%), with ≤20 years of experience (76%) and working only in public hospitals (73%). The physicians prescribe G-CSF primary prophylaxis for 32% of patients: filgrastim in 46% and pegfilgrastim in 54%. The choice of G-CSF for primary and secondary prophylaxis was driven by cost and number of injections. Biosimilars were well accepted.

CONCLUSION

Cost and convenience of G-CSF drive the physician decision to prescribe or not G-CSF for primary and secondary FN prophylaxes. It is important that these results be incorporated in the optimisation of G-CSF prescription in the clinical setting.

A Risk-Prediction Nomogram for Neutropenia or Febrile Neutropenia after Etoposide-Based Chemotherapy in Cancer Patients: A Retrospective Cohort Study

INTRODUCTION

This study was conducted to develop and validate a nomogram for predicting the risk of neutropenia or febrile neutropenia (FN) in tumor patients in the first cycle of etoposide-based chemotherapy.

METHODS

This retrospective cohort study used an information system to monitor patients with non-Hodgkin's lymphoma or solid tumors receiving an etoposide regimen in the first chemotherapy cycle in our hospital from 2009 to 2020. Binary logistic regression analysis was used to identify the influencing factors of patients with neutropenia or FN. Those factors were then used to develop a nomogram.

RESULTS

A total of 1,554 patients were divided into the development group (n = 1,072) and validation group (n = 482). Variables used to predict neutropenia or FN were Karnofsky performance status (odds ratio [OR] = 0.85, 95% confidence interval [CI] = 0.81-0.89, p < 0.01), metastatic sites ≥3 (OR = 6.33, 95% CI = 2.66-15.11, p < 0.01), comorbidity of heart disease (OR = 4.88, 95% CI = 1.74-13.67, p < 0.01), recent surgery (OR = 7.96, 95% CI = 1.96-32.36, p < 0.01), administration of alkylating agents (OR = 4.50, 95% CI = 1.10-18.48, p < 0.01), total bilirubin ≥25 μmol/L (OR = 11.42, 95% CI = 4.00-32.61, p < 0.01), and lymphocyte count <0.7 × 109/L (OR = 4.22, 95% CI = 2.00-9.75, p < 0.01).

CONCLUSION

This model can aid the early identification and screening of the potential risk of neutropenia or FN in the first cycle of treatment for patients using etoposide-based chemotherapy.