Incidence Trend and Competing Risk Analysis of Patients With Intrahepatic Cholangiocarcinoma: A Population-Based Study

Abstract

Background: Intrahepatic cholangiocarcinoma (ICCA) is a primary liver cancer characterized by rapid progression and poor prognosis. There are few effective tools for evaluating the prognosis of ICCA patients, and the use of liver transplantation (LT) of the treatment for ICCA is still controversial.

Methods: We analyzed ICCA incidence data and clinicopathological data from the Surveillance, Epidemiology, and End Results database. Prognostic predictors were identified by univariate and multivariate Cox regression analyses and then used to establish a nomogram. The prediction performance of the nomogram was evaluated with receiver operating characteristic (ROC) curves, calibration plots and decision curve analysis (DCA) plots. Propensity score matching (PSM) was used to balance the baseline data of patients undergoing LT and other operations, and then, univariate Cox regression analysis was used to evaluate the therapeutic value of LT for ICCA.

Results: The incidence of ICCA increased significantly, from 0.6 per 100,000 in 2,000 to 1.3 per 100,000 in 2018. The median overall survival (OS) of the patients was 13 months, and the 1-, 3-, and 5-year OS rates were 51.40, 22.14, and 13.79%, respectively. Cox regression analysis showed that age under 60 years old, female, tumor size ≤ 50 mm, better differentiation, smaller range of tumor invasion, lack of distant metastasis, regional lymph node surgery and treatment were associated with a better prognosis. The ROC curves, calibration plots, and DCA plots showed that the nomogram had good discrimination and calibration power, as well as clinical utility. After PSM, the univariate Cox regression analysis showed no significant difference in OS between patients treated with LT and patients treated with other operations.

Conclusion: The incidence of ICCA increased significantly. A nomogram with good predictive performance was developed to predict the OS of ICCA patients. LT might be considered as a potential option for some ICCA patients.

Keywords: intrahepatic cholangiocarcinoma; liver transplantation; nomogram; prognosis; risk factor.

FIGURE 1

Flowchart of screening patients with ICCA in the SEER database.

FIGURE 2

Incidence trend of patients with ICCA.

FIGURE 3

Incidence trends of patients with ICCA in different demographic groups. (A) Incidence trends of patients with ICCA between different gender groups. (B) Incidence trends of patients with ICCA between different age groups. (C) Incidence trends of patients with ICCA between different race groups. (D) Incidence trends of patients with ICCA between different origin groups.

FIGURE 4

Survival curve of patients with ICCA.

FIGURE 5

Survival curves of patients with ICCA in different clinicopathological groups in the training dataset. (A) Survival curves of patients with ICCA between different year of diagnosis groups. (B) Survival curves of patients with ICCA between different gender groups. (C) Survival curves of patients with ICCA between different age of diagnosis groups. (D) Survival curves of patients with ICCA between different race groups. (E) Survival curves of patients with ICCA between different tumor size groups. (F) Survival curves of patients with ICCA between different grade groups. (G) Survival curves of patients with ICCA between different AJCC-T groups. (H) Survival curves of patients with ICCA between different AJCC-N groups. (I) Survival curves of patients with ICCA between different AJCC-M groups. (J) Survival curves of patients with ICCA between different AJCC-stage groups. (K) Survival curves of patients with ICCA between different radiotherapy groups. (L) Survival curves of patients with ICCA between different therapy groups.

FIGURE 6

Forest map in the multivariate prognostic analysis.

FIGURE 7

Nomogram for predicting OS of patients with ICCA.

FIGURE 8

ROC curves of the nomogram. (A) ROC curves of the 1-, 3-, and 5- OS in the training dataset. (B) ROC curves of the 1-, 3-, and 5-year OS in the testing dataset.

FIGURE 9

Survival curves of patients with ICCA between different risk score level groups. (A) Survival curves of patients with ICCA between high and low risk score level groups in the training dataset. (B) Survival curves of patients with ICCA between high and low risk score level groups in the testing dataset.

FIGURE 10

Calibration plots of the nomogram. (A) Calibration plots of the 1-, 3-, and 5-year OS in the training dataset. (B) Calibration plots of the 1-, 3-, and 5-year OS in the testing dataset.

FIGURE 11

DCA plots of the nomogram. (A–C) DCA plots of the 1-, 3-, and 5- OS in the training dataset. (D–F) DCA plots of the 1-, 3-, and 5-year OS in the testing dataset.

FIGURE 12

Survival curves between LT and other operations groups.