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. 2024 Jan 2;24(1):1.
doi: 10.1186/s12876-023-03084-9.

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

Caixia Fang  1 , Chan Xu  2 , Xiaodong Jia  3 , Xiaoping Li  4 , Chengliang Yin  5 , Xiaojuan Xing  6 , Wenle Li  7 , Zhenyun Wang  8
Affiliations

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

Caixia Fang et al. BMC Gastroenterol. .

Abstract

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.

Keywords: Cholangiocarcinoma; Distal metastasis; Nomogram; Prediction model; Risk factor.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The LASSO regression used for parameter screening. A Each curve represents a variable. B 10-fold cross-validation to adjust parameter selection in the LASSO model
Fig. 2
Fig. 2
The correlation heat map of the parameters
Fig. 3
Fig. 3
A The nomogram for the risk of distal metastasis in patients with CCA. B ROC of the nomogram. C The calibration plots of the model
Fig. 4
Fig. 4
A The Kaplan-Meier overall survival (OS) analysis of patients with distal metastases or not. B The DCA plots of nomogram for the risk of distal metastasis in patients with CCA. The red curve shows the number of people classified as positive of each threshold probability, and the green one shows the number of true positives
See this image and copyright information in PMC

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