Causal AI-based clinical and radiomic analysis for optimizing patient selection in combined immunotherapy and SABR in early-stage NSCLC: a secondary analysis of the phase II I-SABR trial

作者：Maliazurina B. Saad, Eman Showkatian, Vivek Verma, Qasem Al-Tashi, Muhammad Aminu, Xinyan Xu, M. Qayati Mohamed, Morteza Salehjahromi, Sheeba J. Sujit, Yuliya Kitsel, Steven H. Lin, Zhongxing Liao, Saumil Gandhi, David C. Qian, David A. Jaffray, Caroline Chung, Natalie I. Vokes, Jianjun Zhang, J. Jack Lee, John V. Heymach, Jia Wu, Joe Y. Chang · 发表于：Journal for ImmunoTherapy of Cancer · 年份：2025 · DOI：10.1136/jitc-2025-013074 · 被引用次数：4 · 研究领域：Radiomics and Machine Learning in Medical Imaging、Lung Cancer Diagnosis and Treatment、Cancer Immunotherapy and Biomarkers

BACKGROUND: The recent phase II randomized stereotactic ablative radiotherapy with and without immunotherapy (I-SABR) trial has shown improved event-free survival (EFS) when adding immunotherapy to stereotactic ablative radiotherapy (SABR) for early-stage inoperable non-small cell lung cancer (NSCLC). However, optimizing patient selection thereof is critical, because not every patient benefits from immunotherapy. Leveraging the powerful use of artificial intelligence, this secondary analysis of the I-SABR trial developed a modeling system (named "I-SABR-SELECT") based on clinical and radiomic factors to address which patients should receive additional immunotherapy. METHODS: The discovery/validation cohorts were from the I-SABR trial, with external validation from the single-arm STARS trial. Individual treatment effect scores, estimating the benefit of adding immunotherapy, were derived from radiomic and clinical predictors using counterfactual reasoning. Dimensionality reduction was applied to mitigate overfitting and enhance model robustness. We also evaluated the average treatment effect between subgroups of patients who were treated following versus against the model's recommendation. RESULTS: The model recommended that 49% (69/141) patients enrolled in the I-SABR trial switch treatments (65% (49/75) in the SABR arm and 30% (20/66) in the I-SABR arm). Patients treated by the model's recommendation had higher EFS, with HRs of 0.06 (in the I-SABR arm, p<0.001) and 0.26 (in ...