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A nomogram incorporating six easily obtained parameters to discriminate intrahepatic cholangiocarcinoma and hepatocellular carcinoma.

ABSTRACT: Intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are the most prevalent histologic types of primary liver cancer (PLC). Although ICC and HCC share similar risk factors and clinical manifestations, ICC usually bears poorer prognosis than HCC. Confidently discriminating ICC and HCC before surgery is beneficial to both treatment and prognosis. Given the lack of effective differential diagnosis biomarkers and methods, construction of models based on available clinicopathological characteristics is in need. Nomograms present a simple and efficient way to make a discrimination. A total of 2894 patients who underwent surgery for PLC were collected. Of these, 1614 patients formed the training cohort for nomogram construction, and thereafter, 1280 patients formed the validation cohort to confirm the model's performance. Histopathologically confirmed ICC was diagnosed in 401 (24.8%) and 296 (23.1%) patients in these two cohorts, respectively. A nomogram integrating six easily obtained variables (Gender, Hepatitis B surface antigen, Aspartate aminotransferase, Alpha-fetoprotein, Carcinoembryonic antigen, Carbohydrate antigen 19-9) is proposed in accordance with Akaike's Information Criterion (AIC). A score of 15 was determined as the cut-off value, and the corresponding discrimination efficacy was sufficient. Additionally, patients who scored higher than 15 suffered poorer prognosis than those with lower scores, regardless of the subtype of PLC. A nomogram for clinical discrimination of ICC and HCC has been established, where a higher score indicates ICC and poor prognosis. Further application of this nomogram in multicenter investigations may confirm the practicality of this tool for future clinical use.

SUBMITTER: Wang M

PROVIDER: S-EPMC5852370 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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A nomogram incorporating six easily obtained parameters to discriminate intrahepatic cholangiocarcinoma and hepatocellular carcinoma.

Wang Mengmeng M Gao Yuzhen Y Feng Huijuan H Warner Elisa E An Mingrui M Jia Jian'an J Chen Shipeng S Fang Meng M Ji Jun J Gu Xing X Gao Chunfang C

Cancer medicine 20180223 3

Intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are the most prevalent histologic types of primary liver cancer (PLC). Although ICC and HCC share similar risk factors and clinical manifestations, ICC usually bears poorer prognosis than HCC. Confidently discriminating ICC and HCC before surgery is beneficial to both treatment and prognosis. Given the lack of effective differential diagnosis biomarkers and methods, construction of models based on available clinicopathologi ...[more]

PMID: 29473340

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Project description: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.

Project description:Introduction: The emerging field of "radiomics" has considerable potential in disease diagnosis, pathologic grading, prognosis evaluation, and prediction of treatment response. We aimed to develop a novel radiomics nomogram based on radiomics features and clinical characteristics that could preoperatively predict early recurrence (ER) of intrahepatic cholangiocarcinoma (ICC) after partial hepatectomy. Methods: A predictive model was developed from a training cohort comprising 139 ICC patients diagnosed between January 2010 and June 2014. Radiomics features were extracted from arterial-phase image of contrast-enhanced magnetic resonance imaging. Feature selection and construction of a "radiomics signature" were through Spearman's rank correlation and least absolute shrinkage and selection operator (LASSO) logistic regression. Combined with clinical characteristics, a radiomics nomogram was developed with multivariable logistic regression. Performance of the nomogram was evaluated with regard to discrimination, calibration, and clinical utility. An independent validation cohort involving 70 patients recruited from July 2014 to March 2016 was used to evaluate the utility of the nomogram developed. Results: The radiomics signature, consisting of nine features, differed significantly between ER patients and non-ER patients in training and validation cohorts. The area under the curve (AUC) of the radiomics signature in training and validation cohorts was 0.82 (confidence interval [CI], 0.74-0.88) and 0.77 (95% CI, 0.65-0.86), respectively. The AUC of the radiomics nomogram combining the radiomics signature and clinical stage in the two cohorts was 0.90 (95%CI, 0.83-0.94) and 0.86 (95% CI, 0.76-0.93), respectively. Decision curve analysis confirmed the clinical usefulness of the radiomics nomogram. Conclusion: The non-invasive radiomics nomogram developed using the radiomics signature and clinical stage could be used to predict ER of ICC after partial hepatectomy.

Project description:BackgroundCombined 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.MethodsThe 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.ResultsThe 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).ConclusionThe 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.

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A nomogram incorporating six easily obtained parameters to discriminate intrahepatic cholangiocarcinoma and hepatocellular carcinoma.

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A nomogram incorporating six easily obtained parameters to discriminate intrahepatic cholangiocarcinoma and hepatocellular carcinoma.

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