Predicting the occurrence of liver injury induced by immune checkpoint inhibitors in hepatocellular carcinoma patients: a retrospective analysis

预测免疫检查点抑制剂在肝细胞癌患者中诱发肝损伤的发生:一项回顾性分析

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Abstract

PURPOSE: Immune checkpoint inhibitors (ICIs) have been widely used in the systemic treatment of hepatocellular carcinoma (HCC). Immune-mediated liver injury caused by ICIs (ILICI) often leads to anti-tumor therapy suspension or interruption and adversely affects prognosis. Therefore, this study retrospectively analyzed its characteristics, searched for its risk factors and attempted to establish a predictive model. METHODS: A total of 207 inpatients with HCC who received ICIs treatment were retrospectively analyzed. They were divided into ILICI group (n = 52) and Non-ILICI group (n = 155) according to whether ILICI occurred or not, and the clinical characteristics of ILICI were analyzed. The risk factors were screened by logistic regression analysis between these two groups, and then a predictive model for ILICI occurrence was established. RESULTS: Overall, ILICI mostly occurred on 4 to 12 weeks after ICIs treatment was initiated with an incidence 25.1%. The clinical types of liver injury were cholestasis (65.4%), heapatocellular (11.5%) and mixed (23.1%) respectively. The severity of ILICI mostly was mild with 40 cases (76.9%). Diabetes (odds ratio [OR] 3.026, 95% confidence interval [CI] 1.057–8.661, P = 0.039), cirrhosis (OR 6.758, 95% CI 1.433–31.882, P = 0.016) and multiple (3 or more) nodules of HCC (OR 3.097, 95% CI 1.532–6.261, P = 0.002) were risk factors for the occurrence of ILICI through multivariate analysis. A model was established to predict ILICI occurrence with the area under the receiver operating characteristic curve 0.701, sensitivity 0.712, specificity 0.632, positive predictive value 0.720 and negative predictive value 0.630. CONCLUSIONS: ILICI in HCC patients is not rare, especially in those with diabetes, liver cirrhosis or multi-nodular liver tumors. Although most cases are mild, it should not be overlooked. The model we established to predict ILICI occurrence has certain value and is helpful for clinicians to make clinical decisions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-025-14540-y.

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