What question did this study set out to answer?

To identify predictors of severe immune-related adverse events in patients undergoing ICI therapy for advanced NSCLC.

April 6, 2026Open Access

Predictors of severe immune-related adverse events during first-line immune checkpoint inhibitor therapy for advanced non-small cell lung cancer

Key Points

To identify predictors of severe immune-related adverse events in patients undergoing ICI therapy for advanced NSCLC.
Conducted a population-based retrospective study using SEER-Medicare data from 2010–2019.
Included adults aged ≥ 66 years initiating first-line therapy with nivolumab, pembrolizumab, or atezolizumab.
Defined severe irAEs requiring systemic immunosuppressants and ICI treatment modifications.
Applied Fine-Gray competing risks models for analysis with evaluation of model performance.
14.2% of 2,729 patients experienced severe irAEs, mostly within the first 3 months of treatment.
Higher risk associated with pre-existing autoimmune disease (HR = 1.25) and chemoimmunotherapy (HR = 2.35).
Lower risk linked to Black patients (HR = 0.56) and those treated with atezolizumab or nivolumab compared to pembrolizumab.
The prediction model showed good discrimination with an AUC of 0.85.

Abstract

Immune checkpoint inhibitors (ICIs) have transformed treatment for advanced non-small cell lung cancer (NSCLC) treatment but can trigger immune-related adverse events (irAEs). Evidence on clinically meaningful irAEs in first-line ICI settings is limited. Using the SEER-Medicare data (2010–2019), we conducted a population-based retrospective study of adults aged ≥ 66 years with advanced NSCLC initiating first-line nivolumab, pembrolizumab, or atezolizumab. Severe irAEs were defined as immune-related events requiring systemic immunosuppressants and resulting in ICI delay or discontinuation occurring after treatment initiation. Fine-Gray competing risks models were used to identify predictors of irAE, and model performance was evaluated using bootstrap and ten-fold cross-validation. Among 2,729 patients, 14.2% developed severe irAEs (median onset = 1.4 months; IQR = 0.5–4); mostly within 3 months. Common organ systems affected were pulmonary (14.2%), hematologic (14.0%), gastrointestinal (13.4%), and musculoskeletal (13.3%). Higher risk of severe irAEs was associated with pre-existing autoimmune disease (HR = 1.25, 95% CI = 1.17–1.32), chemoimmunotherapy (HR = 2.35, 95% CI = 1.39–3.96), and longer diagnosis-to-treatment interval (HR = 1.50, 95% CI = 1.31–1.60). Lower risks occurred among Black patients (HR = 0.56, 95%CI = 0.34–0.92), those with baseline metastasis (HR = 0.84, 95% CI = 0.75–0.93), opioid use (HR = 0.68, 95% CI = 0.54–0.87), and with atezolizumab (HR = 0.75, 95% CI = 0.65–0.86) or nivolumab (HR = 0.91, 95% CI = 0.87–0.96) vs. pembrolizumab. The prediction model demonstrated good discrimination and calibration (bootstrap-corrected AUC = 0.85; Brier score = 0.14), supporting risk-stratified monitoring in patients receiving ICIs.

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