Evaluating the toxicity profile of combination immune checkpoint inhibitors: a disproportionality analysis of real-world adverse events from the FDA Adverse Event Reporting System for tremelimumab, durvalumab, ipilimumab, and nivolumab.

Background: As one of the therapeutic modalities for treating tumors, immune checkpoint inhibitors (ICIs) have gained widespread application in clinical practice, including non-small cell lung cancer, melanoma, head and neck squamous cell carcinoma, hepatocellular carcinoma, and other types of cancers. However, the safety profile of combining ICIs remains inadequately understood, which poses limitations on the clinical utilization of this novel class of medications. To investigate the toxicity spectrum associated with combination immunotherapy, we conducted an extensive data mining and analysis of the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. Methods: By mining adverse event (AE) reports from the FAERS database covering the period from the first quarter of 2011 through the second quarter of 2024, baseline data were analyzed using Cramer's V coefficient and p-value. Subsequently, two methods, the reporting odds ratio (ROR) and the Bayesian confidence propagation neural network, were employed to detect AE signals for single immune checkpoint inhibitors (sICIs) and dual immunotherapy group (tremelimumab plus durvalumab and ipilimumab plus nivolumab, DIG). Results: A total of 55,052 patients and 118,001 AEs were selected. The DIG exhibited a higher incidence of AE signals across 14 distinct system organ class level. Moreover, DIG exhibited higher positive signal intensity compared to sICIs in the following preferred terms: myocarditis [ROR 2.221, 95% confidence interval lower limit of information component (IC Conclusions: Our findings indicate that the AEs associated with dual ICI predominantly originate from immune-related AEs, including myotoxicity, endocrine toxicity, and hepatotoxicity. Notably, cytokine release syndrome, a rarely reported AE with a strongly positive signal, warrants particular attention in clinical decision-making.