Development and Validation of a Prognostic Model to Predict the Prognosis of Patients With Retroperitoneal Liposarcoma: A Large International Population-Based Cohort Study - Li, Yiding; Wu, Guiling; Zhang, Yujie; Yang, Wanli; Wang, Xiaoqian; Duan, Lili; Niu, Liaoran; Chen, Junfeng; Zhou, Wei; Liu, Jinqiang; Zhong, Helun; Fan, Daiming; et al. (Frontiers in Oncology, 2022)
Background: Retroperitoneal liposarcomas (RPLs), sarcoma of mesenchymal origin, are the most common soft tissue sarcomas (STS) of the retroperitoneum. Given the rarity of RPLs, the prognostic values of clinicopathological features in the patients remain unclear. The nomogram can provide a visual interface to aid in calculating the predicted probability that a patient will achieve a particular clinical endpoint and communication with patients. Methods: We included a total of 1392 RPLs patients diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. The overall survival (OS) and cancer-specific survival (CSS) curves were drawn using the Kaplan–Meier method and assessed using the log-rank test. Univariable/multivariable Cox analysis were performed to select the prognostic factors for survival time. We constructed a predictive nomogram based on the results of the multivariate analyses. Further, we verified the prognostic value of the nomogram using an external validation set from our hospital database. Results: Through the Kaplan–Meier method univariate and multivariate cox analysis, it is found that age, histological grade, classification, SEER stage, surgery constitute significant risk factors for OS, and age, classification, SEER stage, AJCC stage, surgery, and tumor size constitute risk factors for CSS. The constructed prognostic nomogram demonstrated good calibration and discrimination performance in the training and validation dataset. Conclusion: Age, histological grade, classification, SEER stage, surgery constitute significant risk factors for OS of patients with RPLs, and age, classification, SEER stage, AJCC stage, surgery, and tumor size constitute risk factors for CSS. We constructed and externally validated an unprecedented nomogram for predicting the OS and CSS in patients with RPLs. The nomogram can be used as a potential, objective, and supplementary tool for clinicians to predict the prognosis of RPLs patients around the world.