From real-world pharmacovigilance data to clinical practice: a geriatric-specific predictive model for immune-related...

Immune checkpoint inhibitors frequently cause severe immune-related adverse events (irAEs) in elderly lung cancer patients due to age-related immune decline. This study conducted a pharmacovigilance analysis of the FDA Adverse Event Reporting System (FAERS) to investigate the safety profile in this vulnerable population and explore influencing factors of irAEs based on retrospective real-world data.

We obtained adverse event reports for elderly lung cancer patients (≥ 65 years) treated with FDA-approved immune checkpoint inhibitors from the FAERS database, covering the period from the third quarter of 2014 to the third quarter of 2025. The reporting odds ratio was used to identify significant adverse event signals. A retrospective single-center cohort of 250 patients was used to develop a random forest model for predicting grade ≥ 2 irAEs.

Analysis of 19,681 reports revealed a higher reporting proportion of fatal outcomes in elderly patients (ROR = 1.09, 95% CI: 1.04-1.14, p < 0.001). In the development cohort (median age 71), 36.8% developed grade ≥ 2 irAEs. The model incorporating Geriatric-8, platelet-to-lymphocyte ratio, and body mass index showed moderate discriminative performance (AUC = 0.740; 95% CI: 0.705-0.775) and good calibration (Brier score = 0.18). SHAP analysis revealed that lower Geriatric-8 scores and higher platelet-to-lymphocyte ratio increased irAE risk, with body mass index showing a U-shaped association.

Elderly lung cancer patients face a higher reporting proportion of severe and fatal adverse events during immune checkpoint inhibitor treatment, based on FAERS data. Geriatric-8, platelet-to-lymphocyte ratio, and body mass index were identified as potential clinical predictors for irAEs in this population, offering a practical tool for risk assessment and management pending external validation.