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Modeling frameworks for radiation induced lymphopenia: A critical review
Laura Cella1, Serena Monti1, Roberto Pacelli2
1Institute of Biostructures and Bioimaging, National Research Council, Naples, Italy.
Summary
Radiation-induced lymphopenia (RIL), a common side effect of radiation therapy (RT), negatively impacts cancer treatment outcomes and immune function. This review critically analyzes RIL modeling approaches to improve prediction and support immunity-sparing RT strategies.
Area of Science:
- Oncology
- Radiation Oncology
- Immunology
Background:
- Radiation-induced lymphopenia (RIL) is a frequent side effect of radiation therapy (RT).
- RIL can negatively affect therapeutic outcomes and patient survival.
- Preserving immune function is crucial, especially with the rise of cancer immunotherapy.
Purpose of the Study:
- To critically review existing literature on RIL modeling.
- To summarize recent approaches for predicting RIL after RT.
- To identify strategies for immunity-sparing RT.
Main Methods:
- Literature review of RIL modeling studies from the last five years.
- Critical analysis of different RIL definitions and modeling frameworks.
- Illustration of proposed approaches through their applications.
Main Results:
- Diverse RIL modeling frameworks exist, often based on varying definitions.
- Conflicting results reported regarding RIL's impact on patient survival.
- Recent research focuses on improving RIL prediction and developing immunity-sparing RT.
Conclusions:
- Harmonizing diverse RIL modeling methods is necessary.
- A critical analysis of current approaches is the first step toward effective RIL management.
- Developing strategies for immunity-sparing RT is essential for optimizing cancer treatment.
