AUTHOR=Wang Tao , Wang Wanxiang , Zhang Jinfu , Yang Xianwei , Shen Shu , Wang Wentao 

TITLE=Development and Validation of a Nomogram for Differentiating Combined Hepatocellular Cholangiocarcinoma From Intrahepatic Cholangiocarcinoma

JOURNAL=Frontiers in Oncology

VOLUME=Volume 10 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2020.598433

DOI=10.3389/fonc.2020.598433

ISSN=2234-943X

ABSTRACT=Objectives: To establish nomogram based on preoperative blood variables using the least absolute shrinkage and selection operator (LASSO) regression for differentiating combined hepatocellular cholangiocarcinoma (cHCC) from intrahepatic cholangiocarcinoma (iCCA).
Methods: We performed a retrospective analysis of iCCA and cHCC patients who underwent liver resection. Blood signatures were established using the LASSO regression, and then, we combined the clinical risk factors based on the multivariate logistic regression and blood signature to establish the nomogram for differential preoperative diagnosis between iCCA and cHCC. The differential accuracy ability of the nomogram was determined by Harrell’s index (C-index) and decision curve analysis, the results were validated using the validation set. Furthermore, patients were categorized into two groups according to the optimal cut-off values of the nomogram-based scores, and their survival differences were assessed using Kaplan-Meier curves. 
Results: A total of 587 patients who underwent curative liver resection for iCCA or cHCC between January 2006 and December 2017 at West China Hospital were enrolled in this study. The cHCC-score is based on their personalized levels of the seven blood variables. On multivariate logistic analysis, independent factors for distinguishing cHCC were age, sex, biliary duct stones, portal hypertension which were all selected into the nomogram combined with cHCC-score. The nomogram had a good discriminating capability with a C-index of 0.796 (95% CI, 0.752-0.840). The calibration plot for distinguishing cHCC from iCCA showed an optimal agreement between the nomogram prediction and actual observation in the training and validation set. The decision curves indicate significant clinical usefulness.