Pre-treatment inflammatory markers can identify the risk of immune-related toxicity in non-small cell lung cancer patients receiving immune checkpoint inhibitor therapy.

OBJECTIVE: This work intended to explore how peripheral blood inflammatory markers at baseline predict the occurrence of immune-related adverse events (irAEs) in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs). METHODS: This retrospective study included 285 patients with stage III-IV NSCLC who received ICI therapy at our hospital from January 2020 to December 2023. Based on the presence of irAEs, patients were assigned to an irAEs group (91 patients) or a non-irAEs group (194 patients). Baseline clinical data and peripheral blood inflammatory markers (including CRP, TNF-α, IL-2, IL-4, IL-6, NLR, MLR, PLR, and SII) were collected within one week before treatment initiation. LASSO regression was applied for variable selection, followed by multivariate logistic regression to identify independent predictors of irAEs. A nomogram prediction model was constructed and its discrimination, calibration, and clinical utility were assessed using AUC, calibration curves, and decision curve analysis, with internal validation via bootstrap resampling. RESULTS: 91 patients (31.93%) developed irAEs, with the most common being pneumonia (21 cases). OS and PFS did not significantly differ between the irAEs and non-irAEs groups, according to survival analysis (P>0.05). CRP, IL-4, NLR, IL-2, and TNF-α were found to be independent predictors of irAEs (P < 0.05) using multivariate logistic regression. The AUC of the nomogram was 0.896 (95% CI: 0.859-0.934). The bootstrap-corrected AUC was 0.891 (95% CI: 0.851-0.930). The decision curve showed a net benefit greater than 0 across the entire threshold range of 0.00-0.08. CONCLUSION: The nomogram model, based on pre-treatment peripheral blood inflammatory markers (CRP, IL-4, NLR, IL-2, and TNF-α), demonstrated good discriminatory and calibration capabilities in the validation cohort. However, this model should be regarded as an exploratory tool designed to generate hypotheses for identifying patients at risk of developing immune-related adverse events. External validation is required before any clinical application.