Survival and Analysis of Prognostic Factors for Parosteal Osteosarcoma Patients: A SEER Database Analysis

AuthorHan Qien
AuthorFeng Yaoen
AuthorSuyue Zhuen
AuthorHaiwei Sunen
AuthorDongsheng Zhuen
Issued Date2025-12-31en
AbstractBackground and Objectives: Utilizing the Surveillance, Epidemiology, and End Results (SEER) database, the present study aimed to evaluate the most recent survival rates for parosteal osteosarcoma (POS) and to identify risk factors affecting survival. Additionally, the incidence of POS in recent years was determined. Methods: Data on age, sex, race, SEER stage, surgery, radiation, chemotherapy, and survival were extracted from the SEER database, along with additional predictive variables. Survival curves were generated using Kaplan-Meier estimates, adjusted for various parameters. Predictive nomograms and multivariable Cox regression models were also developed. Results: A total of 127 patients were included. The overall survival rates at 1, 3, and 5 years were 99.21%, 95.23%, and 86.66%, respectively. Survival analysis revealed that patients with distant SEER stage (P < 0.001), no surgery (P = 0.025), and chemotherapy (P = 0.009) had worse outcomes. Multivariate analysis identified surgical treatment as the only independent predictor of a favorable outcome [HR, 0.163; 95% CI, (0.031 - 0.863)]. A nomogram was constructed to predict prognosis, and calibration curves demonstrated good agreement between predicted and actual survival outcomes. Conclusions: Poor overall survival was associated with advanced SEER stage, absence of surgery, and receipt of chemotherapy. The nomogram accurately predicted survival likelihood, showing strong concordance with observed outcomes.en
DOIhttps://doi.org/10.5812/ijpediatr-157542en
URIhttps://brieflands.com/journals/ijp/articles/157542en
KeywordParosteal Osteosarcomaen
KeywordSurveillance, Epidemiology and End Resultsen
KeywordSurvivalen
PublisherBrieflandsen
TitleSurvival and Analysis of Prognostic Factors for Parosteal Osteosarcoma Patients: A SEER Database Analysisen
TypeResearch Articleen

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