Development of a Predictive Model for Classifying Immune Checkpoint Inhibitor-Induced Liver Injury Types.

Furthermore, the type of ICI regimen (anti‐CTLA‐4 regimen) (OR, 0.40; 95% CI, 0.13–1.22; p = 0.108) was also identified as an independent factor using a stepwise selection method based on the Akaike information criterion, though it did not reach statistical significance (Table 3 ). 3.4 Establishment of Predictive Regression Equations in the Training Set Based on the regression coefficients, the following equation was derived to represent the probability transformation in the logistic regression model for predicting the likelihood of mixed or cholestatic ICI‐LI (P): P = 1 / { 1 + e ( − 5.02 + 1.20 × sex F : 0 , M : 1 − 0.87 × albumin g / dL − 0.03 × ALT U / L − 0.9 × ( drug [ non − anti − CTLA − 4 related regimen : 0 anti − CTLA − 4 related regimen : 1 ] ) ) } The ROC curve analysis yielded an AUROC of 0.73 (95% CI, 0.63–0.82) (Figure 2 ).

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