The immune related adverse events(irAE)caused by tumor immune checkpoint inhibitors(ICI)have attracted increasing attention of clinical experts.Immune-mediated liver injury caused by ICIs(ILICI)is not uncommon in clinical practice,but specific diagnostic method of ILICI is lacking.Biopsy of liver tissue can help improve the diagnosis and management of ILICI.In the treatment of ILICI,the immediate use of corticosteroid therapy is not necessarily.A balance between efficacy,toxicity,and specific treatment need to be achieved,and further refined through multidisciplinary team(MDT)cooperation.Appropriate dosaging and identification of novel predictive targets should be considered in order to reduce the incidence and severity of ILICI in the future.Meanwhile,further basic research is required to elucidate the potential pathophysiological mechanisms and risk factors of ILICI.With the refinement of evidence in clinical evidence-based medicine and deepening of basic research,the diagnosis and treatment level of ILICI will also be further improved.

Objective To investigate the independent risk factors for acute severe cholangitis and related protective factors, and to construct a risk prediction scoring model for acute severe cholangitis. Methods A retrospective analysis was performed for the clinical data of 381 patients with acute cholangitis who were admitted to Department of Hepatobiliary Surgery, The 940th Hospital of Joint Logistics Support Force of Chinese People's Liberation Army, from January 2016 to July 2021, among whom there were 273 patients with non-severe cholangitis and 108 patients with severe cholangitis. Univariate and multivariate logistic regression analyses were used to screen out the independent risk factors for acute severe cholangitis and related protective factors, and then a logistic regression model was established. The receiver operating characteristic (ROC) curve was used to evaluate the discriminatory ability of the model, the calibration curve was used to evaluate the prediction accuracy of the model, and decision curve analysis (DCA) was used to evaluate the clinical value of the model. Moreover, the enhanced Bootstrap method was used to perform internal validation of the model and evaluate the performance of the model in internal validation. The model was visualized by the construction of Web calculator, nomogram, and scoring system. The two-independent-samples t test was used for comparison of normally distributed continuous data between groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups; the chi-square test was used for comparison of categorical data between groups. Results The univariate and multivariate logistic regression analyses showed that total bilirubin (TBil) (odds ratio [ OR ]=1.014, 95% confidence interval [ CI ]: 1.009-1.020, P < 0.001), percentage of neutrophils ( OR =1.128, 95% CI : 1.088-1.175, P < 0.001), and age ( OR =1.053, 95% CI : 1.027-1.082, P < 0.001) were independent risk factors, and albumin (Alb) ( OR =0.871, 95% CI : 0.817-0.924, P < 0.001) was a protective factor. The above independent risk factors and protective factor were included in the logistic regression analysis for model fitting, and the predictive model obtained had an area under the ROC curve (AUC) of 0.925 (95% CI : 0.897-0.952), with a specificity of 0.817 and a sensitivity of 0.935 at the optimal cut-off value of 0.245. The calibration curve showed that the predicted probability of the model was approximately equal to the actual probability, with a Brier value of 0.098, and the decision curve analysis showed that the model had a higher net income within the threshold probability interval of 0.1-0.9. Internal validation showed an AUC internal validation of 0.915 and a Brier value internal verification of 0.106. Conclusion TBil, percentage of neutrophils, and age are independent risk factors for acute severe cholangitis, while Alb is a protective factor. The established risk prediction scoring model has good discriminatory ability, calibration, and clinical value and can identify patients with acute severe cholangitis at an early stage, which provides a reference for subsequent diagnosis and treatment.