A web-based nomogram model for predicting the overall survival of hepatocellular carcinoma patients with external beam radiation therapy: A population study based on SEER database and a Chinese cohort.

Background: External beam radiation therapy (EBRT) for hepatocellular carcinoma (HCC) is rarely used in clinical practice. This study aims to develop and validate a prognostic nomogram model to predict overall survival (OS) in HCC patients treated with EBRT. Method: We extracted eligible data of HCC patients between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Those patients were randomly divided into a training cohort (n=1004) and an internal validation cohort (n=429), and an external validation cohort composed of a Chinese cohort (n=95). A nomogram was established based on the independent prognostic variables identified from univariate and multivariate Cox regression analyses. The effective performance of the nomogram was evaluated using the concordance index (C-index), receiver operating characteristic curve (ROC), and calibration curves. The clinical practicability was evaluated using decision curve analysis (DCA). Results: T stage, N stage, M stage, AFP, tumor size, surgery, and chemotherapy were independent prognostic risk factors that were all included in the nomogram to predict OS in HCC patients with EBRT. In the training cohort, internal validation cohort, and external validation cohort, the C-index of the prediction model was 0.728 (95% confidence interval (CI): 0.716-0.740), 0.725 (95% CI:0.701-0.750), and 0.696 (95% CI:0.629-0.763), respectively. The 6-, 12-,18- and 24- month areas under the curves (AUC) of ROC in the training cohort were 0.835 、0.823 、0.810, and 0.801, respectively; and 0.821 、0.809 、0.813 and 0.804 in the internal validation cohort, respectively; and 0.749 、0.754 、0.791 and 0.798 in the external validation cohort, respectively. The calibration curves indicated that the predicted value of the prediction model performed well. The DCA curves showed better clinical practicability. In addition, based on the nomogram, we established a web-based nomogram to predict the OS of these patients visually. Conclusion: Based on the SEER database and an independent external cohort from China, we established and validated a nomogram to predict OS in HCC patients treated with EBRT. In addition, for the first time, a web-based nomogram model can help clinicians judge the prognoses of these patients and make better clinical decisions.