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

A machine learning predictive model for recurrence of resected distal cholangiocarcinoma: Development and validation of predictive model using artificial intelligence

INTRODUCTION

Distal Cholangiocarcinoma (dCCA) represents a challenge in hepatobiliary oncology, that requires nuanced post-resection prognostic modeling. Conventional staging criteria may oversimplify dCCA complexities, prompting the exploration of novel prognostic factors and methodologies, including machine learning algorithms. This study aims to develop a machine learning predictive model for recurrence after resected dCCA.

MATERIAL AND METHODS

This retrospective multicentric observational study included patients with dCCA from 13 international centers who underwent curative pancreaticoduodenectomy (PD). A LASSO-regularized Cox regression model was used to feature selection, examine the path of the coefficient and create a model to predict recurrence. Internal and external validation and model performance were assessed using the C-index score. Additionally, a web application was developed to enhance the clinical use of the algorithm.

RESULTS

Among 654 patients, LNR (Lymph Node Ratio) 15, neural invasion, N stage, surgical radicality, and differentiation grade emerged as significant predictors of disease-free survival (DFS). The model showed the best discrimination capacity with a C-index value of 0.8 (CI 95 %, 0.77%-0.86 %) and highlighted LNR15 as the most influential factor. Internal and external validations showed the model's robustness and discriminative ability with an Area Under the Curve of 92.4 % (95 % CI, 88.2%-94.4 %) and 91.5 % (95 % CI, 88.4%-93.5 %), respectively. The predictive model is available at https://imim.shinyapps.io/LassoCholangioca/.

CONCLUSIONS

This study pioneers the integration of machine learning into prognostic modeling for dCCA, yielding a robust predictive model for DFS following PD. The tool can provide information to both patients and healthcare providers, enhancing tailored treatments and follow-up.

Development and validation of a clinical prediction model for the risk of distal metastasis in intrahepatic cholangiocarcinoma: a real-world study

BACKGROUND

Cholangiocarcinoma (CCA) is a highly malignant and easily metastatic bile duct tumor with poor prognosis. We aimed at studying the associated risk factors affecting distal metastasis of CCA and using nomogram to guide clinicians in predicting distal metastasis of CCA.

METHODS

Based on inclusion and exclusion criteria, 345 patients with CCA were selected from the Fifth Medical Center of Chinese PLA General Hospital and were divided into distal metastases (N = 21) and non-distal metastases (N = 324). LASSO regression models were used to screen for relevant parameters and to compare basic clinical information between the two groups of patients. Risk factors for distal metastasis were identified based on the results of univariate and multivariate logistic regression analyses. The nomogram was established based on the results of multivariate logistic regression, and we drawn the corresponding correlation heat map. The predictive accuracy of the nomogram was evaluated by receiver operating characteristic (ROC) curves and calibration plots. The utility of the model in clinical applications was illustrated by applying decision curve analysis (DCA), and overall survival(OS) analysis was performed using the method of Kaplan-meier.

RESULTS

This study identified 4 independent risk factors for distal metastasis of CCA, including CA199, cholesterol, hypertension and margin invasion, and developed the nomogram based on this. The result of validation showed that the model had significant accuracy for diagnosis with the area under ROC (AUC) of 0.882 (95% CI: 0.843-0.914). Calibration plots and DCA showed that the model had high clinical utility.

CONCLUSIONS

This study established and validated a model of nomogram for predicting distal metastasis in patients with CCA. Based on this, it could guide clinicians to make better decisions and provide more accurate prognosis and treatment for patients with CCA.

MRI-Based Radiomics Nomogram for Preoperatively Differentiating Intrahepatic Mass-Forming Cholangiocarcinoma From Resectable Colorectal Liver Metastases

RATIONALE AND OBJECTIVES

To establish a radiomics nomogram based on multiparameter magnetic resonance (MR) images for preoperatively differentiating intrahepatic mass-forming cholangiocarcinoma (IMCC) from colorectal cancer liver metastasis (CRLM).

MATERIALS AND METHODS

A total of 133 patients in training cohort (64 IMCC and 69 CRLM), 57 patients in internal validation cohort (29 IMCC and 28 CRLM), and 51 patients (23 IMCC and 28 CRLM) in external validation cohort were included. Radiomics features were extracted from the multiparameter MR images and selected by the least absolute shrinkage and selection operator algorithm to establish the radiomics model. Clinical variables and magnetic resonance imaging (MRI) findings were selected by univariate and multivariate analyses to construct a clinical model. The radiomics nomogram was combined with radiomics model and clinical model.

RESULTS

Six features were selected to construct the radiomics model. The radiomics signature showed better discrimination than the clinical model in the training cohort (Area Under the Curve (AUC), 0.92; 95% confidence interval (CI), 0.87-0.96 vs. AUC, 0.74; 95% CI, 0.66-0.83) and the external validation cohort (AUC, 0.90; 95% CI, 0.82-0.98 vs. AUC, 0.81; 95% CI, 0.69-0.93). The radiomics nomogram showed the best discrimination performance with favorable calibration in the training cohort (AUC, 0.94; 95% CI, 0.90-0.97) and the external validation cohort (AUC, 0.92; 95% CI, 0.84-1.00).

CONCLUSION

The radiomics nomogram combining radiomics signatures based on multiparameter MRI with clinical factors (serum carcinoembryonic antigen level and tumor diameter) may provide a reliable and noninvasive tool to discriminate IMCC from CRLM, which could help guide treatment strategies and prognosis preoperatively prediction.

Perioperative and oncologic outcomes of laparoscopic versus open liver resection for combined hepatocellular-cholangiocarcinoma: a propensity score matching analysis

BACKGROUND

Laparoscopic liver resection (LLR) has now been established as a safe and minimally invasive technique that is deemed feasible for treating hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). However, the role of LLR in treating combined hepatocellular-cholangiocarcinoma (cHCC-CC) patients has been rarely reported. This study aimed to assess the efficacy of LLR when compared with open liver resection (OLR) procedure for patients with cHCC-CC.

METHODS

A total of 229 cHCC-CC patients who underwent hepatic resection (34 LLR and 195 OLR patients) from January 2014 to December 2018 in Zhongshan Hospital, Fudan University were enrolled and underwent a 1:2 propensity score matching (PSM) analysis between the LLR and OLR groups to compare perioperative and oncologic outcomes. Overall survival (OS) and recurrence-free survival (RFS) parameters were assessed by the log-rank test and the sensitivity analysis.

RESULTS

A total of 34 LLR and 68 OLR patients were included after PSM analysis. The LLR group displayed a shorter postoperative hospital stay (6.61 vs. 8.26 days; p value < 0.001) when compared with the OLR group. No significant differences were observed in the postoperative complications' incidence or a negative surgical margin rate between the two groups (p value = 0.409 and p value = 1.000, respectively). The aspartate aminotransferase (AST), alanine aminotransferase (ALT), and inflammatory indicators in the LLR group were significantly lower than those in the OLR group on the first and third postoperative days. Additionally, OS and RFS were comparable in both the LLR and OLR groups (p value = 0.700 and p value = 0.780, respectively), and similar results were obtained by conducting a sensitivity analysis.

CONCLUSION

LLR can impart less liver function damage, better inflammatory response attenuation contributing to a faster recovery, and parallel oncologic outcomes when compared with OLR. Therefore, LLR can be recommended as a safe and effective therapeutic modality for treating selected cHCC-CC patients, especially for those with small tumors in favorable location.

Lymph Node Ratio Nomogram-Based Prognostic Model for Resected Distal Cholangiocarcinoma

BACKGROUND

Several variables have been described as prognostic factors for resected distal cholangiocarcinoma (dCC), including lymph node metastases (N status) and lymph node ratio (LNR). The present study aimed to evaluate the prognostic value of LNR on survival and to establish a novel prognostic nomogram to predict the cancer-specific recurrence-free survival (RFS) of dCC.

STUDY DESIGN

Between December 2006 and September 2020, 415 consecutive patients who underwent pancreaticoduodenectomy (PD) for dCC in 10 centers were identified. Multivariate Cox analysis was used to identify all independent risk factors among several prognostic factors. A nomogram was then developed and assessed by integrating the independent prognostic factors into the model, and the concordance index (C-index) was used to evaluate its performance.

RESULTS

According to Cox regression multivariate analysis, a nomogram based on independent prognostic factor for RFS was performed including LNR 15 (hazard ratio [HR] 2.442, 95% CI 1.348-4.425, p = 0.003), perineural invasion (HR 3.100, 95% CI 1.183-8.122, p = 0.025), differentiation grade (HR 2.100, 95% CI 1.172-4.143, p = 0.021), and radicality of PD (HR 2.276, 95% CI 1.223-4.234, p = 0.009). The C-index of the nomogram, tailored based on the previous significant factors, was 0.8.

CONCLUSIONS

LNR15 yields a high prognostic efficiency for RFS. The nomogram based on LNR can provide an accurate prognosis assessment for patients with resected dCC.

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

Background

Combined hepatocellular-cholangiocarcinoma (CHC) is a rare but vital heterogeneous histological subtype of primary liver cancer (PLC) with no standardized treatment strategy. This study aimed to preliminarily investigate the role of liver transplantation (LT) in CHC and develop a novel risk scoring model (RSM) to evaluate the benefits of transplantation.

Methods

The study cohort was taken from the Surveillance, Epidemiology, and End Results database. The annual percent change (APC) in incidence or ratio was calculated utilizing the Joinpoint regression. Propensity score matching (PSM) was introduced to reduce the selection bias between groups. A novel RSM was developed based on the independent prognostic factors identified by the Cox regression model. The predictive performance of the RSM was compared with the Milan Criteria and the University of California, San Francisco (UCSF) Criteria, respectively.

Results

A total of 223 CHC patients were enrolled, and 60 (26.9%) of them received LT. The incidence-based mortality did not decrease between 2004 and 2015 (APC =1.7%, P=0.195). Although LT was considered an independent protective predictor for CHC, it showed a declining ratio from 33.3% in 2004 to 15.4% in 2015 (APC =-8.9%, P=0.012). The LT recipients had better outcomes than others who underwent hepatectomy or local destruction (P<0.05). Compared with other subtypes of PLC, the post-transplantation prognoses of CHC patients were similar to those with hepatocellular carcinoma (P>0.05) but significantly better than those with intrahepatic cholangiocarcinoma (ICC) (P<0.05). Based on the RSM (vascular invasion: 1 point; tumor size >2 cm: 1 point; multiple tumors: 2 points), patients were stratified into two prognostic subgroups: the low-risk (scoring ≤2) and the high-risk (scoring >2 or extrahepatic metastasis) groups. Patients in the low-risk group were more likely to benefit from LT. The predictive performance of the RSM outperformed the Milan and UCSF Criteria in both the training and validation sets.

Conclusions

Therapeutic strategies for CHC should be further improved. Patients with CHC should also be considered potential LT candidates. The novel RSM could be helpful to stratify patients and assist clinical decision-making.

Preoperative Differentiation of Combined Hepatocellular-Cholangiocarcinoma From Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma: A Nomogram Based on Ultrasonographic Features and Clinical Indicators

OBJECTIVE

To establish a predictive nomogram to distinguish combined hepatocellular-cholangiocarcinoma (CHC) from hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) based on preoperative clinical and ultrasound findings.

METHODS

A total of 261 patients with pathologically confirmed primary liver cancers (PLCs) were enrolled in this retrospective study, comprising 87 CHCs, 87 HCCs, and 87 ICCs matched by propensity score matching. Patients were randomly assigned to a training cohort and a validation one at the ratio of 7:3. A nomogram integrating ultrasound imaging characteristics and clinical features was established based on the independent risk factors selected by least absolute shrinkage and selection operator (LASSO) regression. The performance of the nomogram was evaluated in the training and validation cohorts in terms of discrimination, calibration, and clinical usefulness.

RESULTS

The nomogram, consisting of ultrasound imaging features (shape and margin on B-mode ultrasound, enhanced pattern on contrast-enhanced ultrasound) and clinical information [elevated alpha fetoprotein (AFP) level and serum protein electrophoresis (SPE) α1 level], showed promising performance in differentiating CHC from HCC and ICC, with the concordance index (C-index) of 0.8275 and 0.8530 in the training cohort and the validation cohort, respectively. Hosmer-Lemeshow test and the calibration curves suggested good consistency between predictions and observations. High clinical practicability was confirmed by the decision curve analysis.

CONCLUSIONS

The nomogram based on clinical and ultrasound imaging characteristics showed good performance in the discrimination of CHC from other subtypes of PLC and would be valuable in clinical decision-making.

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

Background

Combined hepatocellular-cholangiocarcinoma (CHC) is a rare and heterogeneous histological subtype of primary liver cancer, which is still poorly understood. This study aimed to describe the epidemiological and clinical features, investigate the prognostic indicators, and develop a competing risk nomogram for CHC.

Methods

The study cohort was taken from the Surveillance, Epidemiology, and End Results database. The annual percent change (APC) in incidence was calculated using the joinpoint regression. The nomogram was developed based on multivariate competing risk survival analyses and validated by calibration curves. Akaike information criterion, Bayesian information criterion, Harrell's C-index, and area under the receiver operating characteristic curves were obtained to compare prognostic performance. Decision curve analysis was introduced to examine the clinical value of the models.

Results

The overall incidence of CHC was 0.062 per 100,000 individuals in 2004 and 0.081 per 100,000 individuals in 2018, with an APC of 1.0% (P > 0.05). CHC displayed intermediate clinicopathological features of hepatocellular carcinoma and intrahepatic cholangiocarcinoma. Race, tumor size, vascular invasion, extrahepatic invasion, distant metastasis, grade, surgery, and Metavir stage were confirmed as the independent predictors of cancer-specific survival. The constructed nomogram was well calibrated, which showed better discrimination power and higher net benefits than the current American Joint Committee on Cancer staging system. Patients with liver transplantation had better survival than those with hepatectomy, especially patients within the Milan Criteria (P=0.022 and P=0.015). There was no survival difference between liver transplantation and hepatectomy in patients beyond the Milan Criteria (P=0.340).

Conclusion

The morbidity of CHC remained stable between 2004 and 2018. The constructed nomogram could predict the prognosis with good performance, which was meaningful to individual treatment strategies optimization. CHC patients should also be considered as potential liver transplantation recipients, especially those within the Milan Criteria, but the finding still needs more evidence to be further confirmed.

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

Background

Combined hepatocellular carcinoma and cholangiocarcinoma (CHC) is an uncommon subtype of primary liver cancer. Because of limited epidemiological data, prognostic risk factors and therapeutic strategies for patients with CHC tend to be individualized. This study aimed to identify independent prognostic factors and develop a nomogram-based model for predicting the overall survival (OS) of patients with CHC.

Methods

We recruited eligible individuals from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015 and randomly divided them into the training or verification cohort. Univariate and multivariate analyses were performed to identify independent variables associated with OS. Based on multivariate analysis, the nomogram was established, and its prediction performance was evaluated using the consistency index (C-index) and calibration curve.

Results

In total, 271 patients with CHC were included in our study. The median OS was 14 months, and the 1-, 3-, and 5-year OS rates were 52.3%, 27.1%, and 23.3%, respectively. In the training cohort, multivariate analysis showed that the pathological grade (hazard ratio [HR], 1.26; 95% confidence interval [CI]: 0.96–1.66), TNM stage (HR, 1.21; 95% CI: 1.02 - 1.44), and surgery (HR, 0.26; 95% CI: 0.17 - 0.40) were independent indicators of OS. The nomogram-based model related C-indexes were 0.76 (95% CI: 0.72 - 0.81) and 0.72 (95% CI: 0.66 - 0.79) in the training and validation cohorts, respectively. The calibration of the nomogram showed good consistency of 1-, 3-, and 5-year OS rates between the actual observed survival and predicted survival in both cohorts. The TNM stage (HR, 1.23; 95% CI: 1.01 - 1.49), and M stage (HR, 1.87; 95% CI: 1.14 3.05) were risk factors in the surgical treatment group. Surgical resection and liver transplantation could significantly prolong the survival, with no statistical difference observed.

Conclusions

The pathological grade, TNM stage, and surgery were independent prognostic factors for patients with CHC. We developed a nomogram model, in the form of a static nomogram or an online calculator, for predicting the OS of patients with CHC, with a good predictive performance.