Development of a predictive model for immune‑related adverse events in patients with cancer

It is crucial to accurately identify patients with cancer at high risk for immune-related adverse events (irAEs) caused by immune checkpoint inhibitors (ICIs). The present retrospective study analyzed the risk factors for irAEs in 992 patients with cancer treated with ICIs at Xi'an International Medical Center Hospital from December 2021 to December 2023. The patients were categorized into one group that experienced irAEs (n=276) and a control group (n=716) based on the occurrence of irAEs. The clinical characteristics of irAEs group (n=276) and control group (n=716) were analyzed to identify the risk factors of irAEs in patients with cancer. Multivariate regression analysis revealed significant differences between the two groups in terms of hypertension, primary cancer, metastasis, targeted drug combination and radiotherapy (P<0.05). A nomogram predictive model for irAEs was developed based on the relevant risk factors. The predictive model for irAEs in patients with cancer yielded an area under the receiver operating characteristic (ROC) curve of 0.672 (95% confidence interval: 0.630-0.714). In the validation set, the Hosmer-Lemeshow goodness-of-fit test demonstrated a favorable fit with a chi-square value of 0.787 and a P-value of 0.978. The developed predictive model can effectively identify high-risk patients with irAEs, facilitate early identification of irAEs, thereby optimizing the management strategies of irAEs, and ultimately improving the quality of life for patients.