Optimal, Interpretable, and Personalized Immune Checkpoint Inhibitor Duration in Non‐Small Cell Lung Cancer: A Multicenter Real‐World Study
Siqi Wang, Jianhua Liu, Qiang Nie, Ruichuan Shi, Nan Xu, Qianqian He, Guanchao Ye, Jingyi Liu, Qiuyang Hou, Kexue Deng, Lu Wang, Taixue An, Anyi An, Xiujuan Qu, Jiangdian SongABSTRACT
The optimal treatment duration of immune checkpoint inhibitors (ICIs) in non‐small cell lung cancer (NSCLC) remains undefined. We conducted a multicenter retrospective cohort study of 1054 patients with NSCLC treated with ICIs across six hospitals in China and one in the United States. Using a training cohort of 372 patients, we constructed a counterfactual random forest reward‐estimation matrix incorporating age, tumor diameter, and derived neutrophil‐to‐lymphocyte ratio, and an Optimal Policy Survival Tree (OPST) was developed to characterize phenotype‐specific associations between baseline clinical features, treatment duration patterns (short‐, intermediate‐, and long‐course), and survival outcomes. Two external cohorts ( n = 324 and n = 358) were used for validation. The OPST reproducibly defined seven patient subgroups across datasets. Subgroups 4 and 6 (37.8%) showed more favorable overall survival (OS) associations with short‐course therapy (median OS 28.6 and 24.5 months), whereas Subgroups 3 and 5 (41.5%) showed more favorable associations with long‐course therapy (median OS 27.0 and 22.0 months; all p < 0.001). The OPST framework identified a subset of patients (18.1%) potentially associated with limited incremental survival benefit from prolonged treatment exposure. This transparent and interpretable framework based on routine clinical data may help inform future prospective evaluation of individualized ICI duration strategies, with the potential to support individualized treatment planning while reducing unnecessary treatment exposure.