245 - Blood Dose Based NTCP Modeling for Severe Radiation Induced Lymphopenia In Lung Cancer Radiotherapy
Presenter(s)
S. Wang1,2, X. Fan1,2, Y. Yin2, and T. Dai2; 1Department of Graduate, Shandong First Medical University, Shandong Academy of Medical Sciences, Jinan, China, 2Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
Purpose/Objective(s): Severe radiation-induced lymphopenia (SRIL) is a poor prognostic factor in lung cancer. This study aimed to develop and validate normal tissue complication probability (NTCP) models for SRIL based on hematologic dose in patients receiving intensity-modulated radiotherapy (IMRT) and intensity-modulated proton therapy (IMPT).
Materials/Methods: We retrospectively analyzed 131 lung cancer patients treated with curative-intent radiotherapy (94 IMRT, 63 IMPT) between 2022 and 2025. Whole-body blood dose-volume histograms (DVHs) were calculated using the HEDOS framework. The Lyman-Kutcher-Burman (LKB) NTCP model was adopted, with parameters optimized via maximum likelihood estimation. Model robustness was assessed using bootstrap resampling with 1000 iterations. Statistical analyses included univariate and multivariate logistic regression to identify SRIL predictors, with Bonferroni correction applied in multivariate analysis. Categorical variables were compared using chi-square or Fisher's exact test, and continuous variables with Mann-Whitney U test. Model performance was evaluated using area under the receiver operating characteristic curve (AUC), Brier score, and stratified 5-fold cross-validation. Calibration was assessed using chi-square goodness-of-fit test and calibration curves.
Results: The incidence of SRIL was 61.7% and 32.4% in the IMRT and IMPT cohorts, respectively. Blood generalized equivalent uniform dose was an independent predictor of SRIL in the IMRT cohort (OR=4.682, p=0.002). The NTCP model demonstrated strong predictive power in both cohorts (IMRT: AUC=0.82; IMPT: AUC=0.80). The volume effect parameter a was 19.85 for IMRT and 2.35 for IMPT. External validation of the IMRT-derived model in the IMPT cohort revealed suboptimal calibration (calibration slope=0.54), indicating systematic overestimation of risk.
Conclusion:
We developed the first modality-specific NTCP models based on whole-blood DVHs for predicting SRIL in lung cancer patients receiving radiotherapy. Our results demonstrated a strong correlation between hematologic dose parameters and lymphocyte depletion, indicating the potential to estimate SRIL risk using blood dose for both IMRT and IMPT. The established models provide valuable tools for individualized risk assessment in clinical practice.