Development and evaluation of a clinical and ultrasound features-based nomogram for the preoperative diagnosis of intrahepatic cholangiocarcinoma
10.3760/cma.j.cn113884-20231205-00155
- VernacularTitle:基于临床和超声特征的术前诊断肝内胆管癌列线图的构建与评估
- Author:
Chunrui LIU
1
;
Haiyan XUE
;
Han LIU
;
Peng WAN
;
Jing YAO
;
Wentao KONG
;
Zhengyang ZHOU
Author Information
1. 南京大学医学院附属鼓楼医院超声医学科，南京 210008
- Keywords:
Cholangiocarcinoma;
Carcinoma, hepatocellular;
Nomograms;
Ultrasound
- From:
Chinese Journal of Hepatobiliary Surgery
2024;30(5):354-359
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish and evaluate a clinical and ultrasound parameters-based nomogram for the preoperative differentiating diagnosis of intrahepatic cholangiocarcinoma (ICC).Methods:A total of 723 patients undergoing hepatectomy in Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from January 2016 to August 2022 were retrospectively screened. A total of 399 patients with hepatocellular carcinoma (HCC, 198 cases) or ICC (201 cases) were enrolled in this study, including 284 males and 115 females, aged (60.5±10.5) years. Through random sampling using computer-generated random numbers, patients were divided into training ( n=279) and validation groups ( n=120) in a ratio of 7∶3. Univariate and multivariate logistic regression were performed to identify factors differentiating ICC, and a nomogram was established using R software based on independent risk factors for ICC. The accuracy of the nomogram was evaluated by receiver operating characteristic curve and calibration curves. Decision curve analysis was performed to assess the net benefit of the model. Results:Multivariate logistic regression analysis showed that irregular shape, cholangiectasis, female, cirrhosis, carbohydrate antigen 242 >10 U/ml, carbohydrate antigen 125 >30 U/ml and alpha-fetoprotein >10 μg/L were independent differentiating factors for ICC (all P<0.05). A nomogram was constructed based on those factors. The nomogram showed a better discrimination between ICC and HCC. The area under the curve of the training group and the validation group were 0.966 and 0.956, respectively. The calibration curve showed that the prediction effect of the model is in good agreement with the actual situation. Decision curve analysis showed that the nomogram was more effective than diagnosing all patients as either HCC or ICC, which yielded a net benefit at the most reasonable threshold probabilities. Conclusion:The nomogram for the preoperative diagnosis of ICC based on clinical and ultrasound features showed a good diagnostic performance.
