Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis

PURPOSE Radiotherapy can have an impact on the immune system through lymphocyte depletion. In particular, it can influence tumor control. Accurately predicting radiation-induced lymphopenia (RIL) is key to optimizing treatment strategies. We aimed to evaluate mathematical model structures capable of capturing the kinetics of lymphocyte concentrations after irradiation, with attention to the saturation effect observed during fractionated radiotherapy. MATERIALS AND METHODS A meta-analysis of aggregate data from patients with solid tumor treated with specific radiation doses was conducted. We extracted patient and treatment characteristics, lymphocyte counts, including tumor type/location, radiation modality (X-rays v protons), and baseline counts. Various models—including exponential, extended exponential, exponential-quadratic, and saturation models—were tested for their ability to predict lymphocyte kinetics. RESULTS Data from 29 studies covering brain, nasopharyngeal, oropharyngeal, esophageal, non–small cell lung, hepatocarcinoma, cervical, pancreatic, rectal cancers, and soft tissue sarcoma were analyzed. Lymphocyte depletion rates varied, with cervical cancer showing the highest reduction, followed by esophageal, hepatocarcinoma, and others. Lymphocyte recovery post-treatment depended heavily on baseline counts and time since radiotherapy completion. Saturation models best fit most cancer types, but for head and neck/central nervous system cancer without nodal involvement, the exponential-quadratic model performed better, reflecting a unique early lymphocyte increase before RIL. CONCLUSION In conclusion, the choice of lymphocyte depletion model should align with cancer type and location. Standardized prospective studies are needed to refine models and enhance radiotherapy strategies.