Development and validation of a novel nomogram for predicting outcomes in advanced lung cancer patients treated beyond progression with immune checkpoint inhibitors

Background Standardized management of lung cancer (LC) progressing post-immunotherapy remains challenging, with debated clinical benefits of treatment beyond progression (TBP). We evaluated the efficacy of continued immune checkpoint inhibitors (ICIs) and developed a pharmacologically guided nomogram to optimize TBP decision-making. Methods This retrospective analysis of 153 LC patients undergoing post-progression ICIs continuation identified significant predictors via the least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis. A nomogram predicting overall survival (OS) and progression-free survival (PFS) was constructed and validated using time-dependent receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Results Treatment regimen, Eastern Cooperative Oncology Group (ECOG) performance status, efficacy evaluation, lymph node metastasis, and liver metastasis independently predicted OS, while liver metastasis and efficacy evaluation influenced PFS. The nomogram demonstrated robust discrimination (OS C-index=0.700; PFS C-index=0.599) with area under the curve (AUC) values of 0.786/0.777/0.705 (OS) and 0.621/0.638/0.630 (PFS) at 6/12/24 months. DCA confirmed the clinical utility of the OS nomogram. Patients were stratified into high- and low-risk groups based on optimal cutoff values, and risk stratification revealed significant survival differences (p<0.01). Conclusion This validated nomogram provides a clinically actionable tool to identify patients benefiting from sustained ICIs exposure, enabling pharmacologically informed TBP strategies while minimizing futile drug exposure. Future prospective multicenter studies should validate utility across diverse pharmacogenomic populations.