AUTHOR=Gao Bing , Wang Meng-die , Li Yanan , Huang Fei 

TITLE=Risk stratification system and web-based nomogram constructed for predicting the overall survival of primary osteosarcoma patients after surgical resection

JOURNAL=Frontiers in Public Health

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.949500

DOI=10.3389/fpubh.2022.949500

ISSN=2296-2565

ABSTRACT=Background: Previous prediction models of osteosarcoma have not focused on survival in patients undergoing surgery, nor have they distinguished and compared prognostic differences between radical and local resection. This study aimed to establish and validate the first reliable prognostic nomogram to accurately predict overall survival (OS) after surgical resection in patients with osteosarcoma. On this basis, we constructed a risk stratification system and a web-based nomogram.
Methods: We enrolled 1451 patients with primary osteosarcoma who underwent surgery between 2004 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database. We divided them into internal and external cohorts according to different state registries. In patients with primary osteosarcoma, Kaplan-Meier (KM) survival analysis, univariate and multivariate cox proportional hazards regression analyses were utilized to identify independent prognostic factors after surgical resection and construct a novel nomogram for the 1-, 3-, and 5-year OS. Then in both internal and external cohorts, the nomogram's predictive performance and clinical utility were evaluated by the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
Result: Age, sex, primary site, histological type, grade, disease stage, and tumor size were identified as independent prognostic factors for the nomogram. The C-index and area under the curve (AUC) demonstrated that this nomogram was significantly more accurate than the AJCC staging system in predicting the OS. Additionally, the calibration curve revealed that the actual survival rate for OS was in close agreement with the predicted survival rate from the nomogram. DCA demonstrated that this nomogram was significantly superior to the AJCC staging system, with more net clinical benefit. We then established a risk stratification system and a web-based nomogram to facilitate clinical therapeutic options.
Conclusion: In conclusion, radical surgery had the best survival prognosis and was the first choice for patients with osteosarcoma. We have established and validated a novel nomogram that could objectively predict the overall survival of patients with primary osteosarcoma after surgical resection. Furthermore, a risk stratification system and a web-based nomogram could be applied in clinical practice to assist in therapeutic decision-making.