Two simple-to-use web-based nomograms to predict overall survival and cancer-specific survival in patients with extremity fibrosarcoma - Li, Yubo; Yang, Jianing; Zhao, Long; Chen, Bin; An, Yongsheng (Frontiers in Oncology, 2023)
Background: Fibrosarcoma is a rare sarcoma of the soft tissue in adults, occurring most commonly in the extremities. This study aimed to construct two web-based nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in patients with EF(EF), and validate it with multi-center data from Asian/Chinese population.. Method: Patients with EF in Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015 were included in this study and were randomly divided into a training cohort and a verification cohort. Nomogram was developed based on the independent prognostic factors determined by univariate and multivariate Cox proportional hazard regression analysis. The predictive accuracy of nomogram was validated with the Harrells concordance index (C-index), receiver operating curve and calibration curve. Decision curve analysis (DCA) was utilized to compare the clinical usefulness between novel model and existing staging system. Result: A total of 931 patients finally were obtained in our study. Multivariate Cox analysis determined five independent prognostic factors for OS and CSS, including age, , M stage, tumor size, grade and surgery. nomogram and corresponding web-based calculator were developed to predict OS (https://orthosurgery.shinyapps.io/osnomogram/) and CSS (https://orthosurgery.shinyapps.io/cssnomogram/) probability at 24-, 36- and 48-months. The C-index of nomogram was 0.784 in the training cohort and 0.825 in the verification cohort for OS, and 0.798 in the training cohort and 0.813 in the verification cohort for CSS, respectively, indicating excellent predictive performance. The calibration curves showed excellent agreement between the prediction by nomogram and actual outcomes. Additionally, the results of DCA showed the newly proposed nomogram was significantly better than the conventional staging system with more clinical net benefits. The Kaplan-Meier survival curves showed patients assigned into the low-risk group had more satisfactory survival outcome than the high-risk group. Conclusion: In this study, we constructed two nomograms and web-based survival calculators including five independent prognostic factors for survival prediction of patients with EF, which could help clinicians make personalized clinical decision.