AUTHOR=Song Jiazhao , Di Yupeng , Kang Xiaoli , Ren Gang , Wang Yingjie TITLE=Development and validation of a nomogram to predict cancer-specific survival with unresected cholangiocarcinoma undergoing external radiotherapy JOURNAL=Frontiers in Public Health VOLUME=Volume 11 - 2023 YEAR=2023 URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2023.1012069 DOI=10.3389/fpubh.2023.1012069 ISSN=2296-2565 ABSTRACT=Objective To analyze the prognostic factors of patients with cholangiocarcinoma (CCA) who were unresected and received radiotherapy to establish a nomogram model for the prediction of patient cancer-specific survival (CSS). Methods Suitable patient cases were selected from the Surveillance, Epidemiology, and End Results (SEER) database, survival rates were calculated using the Kaplan-Meier method, prognostic factors were analyzed by Lasso, Cox regression, and nomogram was developed based on independent prognostic factors to predict 6 months and 12 months CSS. The consistency index (C-index), calibration curve, and decision curve analysis (DCA) were tested for the predictive efficacy of the model, respectively. Results The primary site, tumor size, T-stage, M-stage, and chemotherapy (P < 0.05) were identified as independent risk factors after Cox and Lasso regression analysis. Patients in training cohort had a 6 months CSS rates was 68.6% ± 2.6%, a 12-month CSS rates was 49.0% ± 2.8%. The median CSS time of 12.00 months (95% CI: 10.17-13.83 months). The C-index was 0.664 ± 0.039 for the training cohort and 0.645 ± 0.042 for the validation cohort. The nomogram predicted CSS and demonstrated satisfactory and consistent predictive performance in 6 months (73.4% vs. 64.9%) and 12 months (72.2% vs. 64.9%), respectively. The external validation calibration plot is shown AUC for 6- and 12-month compared with AJCC stage was (71.2% vs. 63.0%) and (65.9% vs. 59.8%). Meanwhile, the calibration plot of the nomogram for the probability of CSS at 6 months and 12 months indicates that the actual and nomogram predict that the CSS remains largely consistent. DCA showed that using a nomogram to predict CSS results in better clinical decisions compared to the AJCC staging system. Conclusion A nomogram model based on clinical prognostic characteristics can be used to provide CSS prediction reference for patients with CCA who have not undergone surgery but have received radiotherapy.