Prediction of overall survival in resectable intrahepatic cholangiocarcinoma: IS ICC -applied prediction model

Intrahepatic cholangiocarcinoma (ICC) remains a highly heterogeneous disease with poor prognosis. Tumor-infiltrating lymphocytes were predictive in various cancers, but their prognostic value in ICC is less clear. A total of 168 ICC patients who had received liver resection were enrolled and assigned to the derivation cohort. Sixteen immune markers in tumor and peritumor regions were examined by immunohistochemistry. A least absolute shrinkage and selection operator model was used to identify prognostic markers and to establish an immune signature for ICC (IS ). An IS -applied prediction model was built and validated in another independent dataset. Five immune features, including CD3 , CD57 , CD45RA , CD66b and PD-L1 , were identified and integrated into an individualized IS for each patient. Seven prognostic predictors, including total bilirubin, tumor numbers, CEA, CA19-9, GGT, HBsAg and IS , were integrated into the final model. The C-index of the IS -applied prediction model was 0.719 (95% CI, 0.660-0.777) in the derivation cohort and 0.667 (95% CI, 0.581-0.732) in the validation cohort. Compared with the conventional staging systems, the new model presented better homogeneity and a lower Akaike information criteria value in ICC. The IS -applied prediction model may provide a better prediction performance for the overall survival of patients with resectable ICC in clinical practice.