Diagnostic and prognostic nomograms for newly diagnosed intrahepatic cholangiocarcinoma with brain metastasis: A population-based analysis

Abstract

Brain metastasis (BM) is one of the rare metastatic sites of intrahepatic cholangiocarcinoma (ICC). ICC with BM can seriously affect the quality of life of patients and lead to a poor prognosis. The aim of this study was to establish two nomograms to estimate the risk of BM in ICC patients and the prognosis of ICC patients with BM. Data on 19,166 individuals diagnosed with ICC were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database. Independent risk factors and prognostic factors were identified by the logistic and the Cox regression, respectively. Next, two nomograms were developed, and their discrimination was estimated by concordance index (C-index) and calibration plots, while the clinical benefits of the prognostic nomogram were evaluated using the receiver operating characteristic (ROC) curves, the decision curve analysis (DCA), and the Kaplan–Meier analyses. The independent risk factors for BM were T stage, N stage, surgery, alpha-fetoprotein (AFP) level, and tumor size. T stage, surgery, radiotherapy, and bone metastasis were prognostic factors for overall survival (OS). For the prognostic nomogram, the C-index was 0.759 (95% confidence interval (CI) = 0.745–0.773) and 0.764 (95% CI = 0.747–0.781) in the training and the validation cohort, respectively. The calibration curves revealed a robust agreement between predictions and actual observations probability. The area under curves (AUCs) for the 3-, 6-, and 9-month OS were 0.721, 0.727, and 0.790 in the training cohort and 0.702, 0.777, and 0.853 in the validation cohort, respectively. The DCA curves yielded remarkable positive net benefits over a wide range of threshold probabilities. The Kaplan–Meier analysis illustrated that the nomogram could significantly distinguish the population with different survival risks. We successfully established the two nomograms for predicting the incidence of BM and the prognosis of ICC patients with BM, which may assist clinicians in choosing more effective treatment strategies.