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

Abstract

ObjectivesTo establish a nomogram based on preoperative laboratory study variables using least absolute shrinkage and selection operator (LASSO) regression for differentiating combined hepatocellular cholangiocarcinoma (cHCC) from intrahepatic cholangiocarcinoma (iCCA).MethodsWe performed a retrospective analysis of iCCA and cHCC patients who underwent liver resection. Blood signatures were established using LASSO regression, and then, the clinical risk factors based on the multivariate logistic regression and blood signatures were combined to establish a nomogram for a 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, and the results were validated using a 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.ResultsA total of 587 patients who underwent curative liver resection for iCCA or cHCC between January 2008 and December 2017 at West China Hospital were enrolled in this study. The cHCC score was based on the personalized levels of the seven laboratory study variables. On multivariate logistic analysis, the independent factors for distinguishing cHCC were age, sex, biliary duct stones, and portal hypertension, all of which were incorporated into the nomogram combined with the 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 optimal agreement between the nomogram prediction and actual observation in the training and validation sets. The decision curves indicated significant clinical usefulness.ConclusionThe nomogram showed good accuracy for the differential diagnosis between iCCA and cHCC preoperatively, and therapeutic decisions would improve if it was applied in clinical practice.

Morbidity, Prognostic Factors, and Competing Risk Nomogram for Combined Hepatocellular-Cholangiocarcinoma

“…As another important part of the AJCC staging system, LNM was identified in 85 (11.5%) patients in this study, similar to previous studies (8.6%–21.4%) [ 1 , 12 , 14 , 23 , 37 – 42 ]. The incidence of LNM in CHC patients was higher than that of HCC patients (3.1%–4.9%) [ 43 – 45 ] but lower than that of ICC patients (22.6%–45.2%) [ 46 – 49 ].…”

“…e American Joint Committee on Cancer (AJCC) classifies CHC and ICC under the same category in the 8 th edition staging system. However, some studies have pointed out the sufficient differences in clinical features and outcomes between CHC and ICC, indicating that CHC should be considered as a separate entity for a unique staging system [11][12][13][14]. During the follow-up period, various events, socalled competing risks, may either hinder the observation or modify the occurrence chance of events of interest, including accidents and comorbidities.…”

Promising role of liver transplantation in patients with combined hepatocellular-cholangiocarcinoma: a propensity score matching analysis

“…In addition, the current American Joint Committee on Cancer (AJCC) staging system (8 th edition) classifies CHC and ICC into the same category. However, many studies have pointed out sufficient differences between the 2 cancers, indicating that CHC should be considered a separate entity to be evaluated independently (14,(24)(25)(26)(27). Therefore, several researchers have refocused on the therapeutic value of LT in CHC patients and obtained some contradictory results (18,19,(28)(29)(30)(31)(32).…”

Prediction of Survival and Analysis of Prognostic Factors for Patients With Combined Hepatocellular Carcinoma and Cholangiocarcinoma: A Population-Based Study

“…However, many studies have shown that several independent risk factors, including age (23), race (5,9), alpha-fetoprotein (AFP) status (23), cirrhosis (4), and treatment strategies (1,5,9,(24)(25)(26), affect the survival and prognosis of patients with CHC. At present, some singlecenter studies have constructed many nomogram prediction models for CHC (22,(27)(28)(29)(30). Furthermore, studies have recently used the Surveillance, Epidemiology, and End Results (SEER) database to describe incidence trends and clinical outcomes of patients with CHC (1, 5); however, there was a lack of a nomogram to predict long-term survival.…”