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Published on: September 12, 2019
Risk Factors and Biomarkers for Immune Checkpoint Inhibitor-mediated Hepatotoxicity: Emerging Insights and Future
Zaoqin Yu1, Yanjiao Xu1, Wei Li1
1Department of Pharmacy, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Immune checkpoint inhibitors (ICIs) improve cancer treatment but can cause liver damage. Identifying risk factors and biomarkers for immune-mediated hepatotoxicity (IMH) is crucial for patient safety.
Area of Science:
- Oncology
- Immunology
- Hepatology
Background:
- Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy.
- Increased ICI use has led to a rise in immune-related adverse events, including immune-mediated hepatotoxicity (IMH).
- IMH poses significant risks, necessitating early detection and management strategies.
Purpose of the Study:
- To review current knowledge on risk factors for IMH in patients receiving ICI therapy.
- To explore potential predictive biomarkers for IMH.
- To highlight the need for further research in early IMH identification and management.
Main Methods:
- Literature review of risk factors and predictive biomarkers for IMH.
- Categorization of risk factors into patient-associated, tumor-associated, and agent-associated.
- Summary of potential biomarkers including blood cells, serum proteins, autoantibodies, cytokines, gene profiles, and gut microbiome.
Main Results:
- Patient factors (sex, age, BMI, ethnicity, liver disease), tumor factors (cancer type, prior ICI), and agent factors (dual ICI, concurrent therapies) are associated with higher IMH risk.
- Various biomarkers show promise but lack consistent predictive value.
- No definitive biomarker is currently established for routine clinical use.
Conclusions:
- Early identification and individualized management of IMH are critical for patients on ICI therapy.
- Further large-scale prospective studies are required to validate predictive biomarkers.
- Integrating validated biomarkers into clinical practice will enhance IMH prediction and patient care.
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