Identification of Discrete Prognostic Groups in Ewing Sarcoma.

ABSTRACT: Although multiple prognostic variables have been proposed for Ewing sarcoma (EWS), little work has been done to further categorize these variables into prognostic groups for risk classification.We derived initial prognostic groups from 2,124 patients with EWS in the SEER database. We constructed a multivariable recursive partitioning model of overall survival using the following covariates: age; stage; race/ethnicity; sex; axial primary; pelvic primary; and bone or soft tissue primary. Based on this model, we identified risk groups and estimated 5-year overall survival for each group using Kaplan-Meier methods. We then applied these groups to 1,680 patients enrolled on COG clinical trials.A multivariable model identified five prognostic groups with significantly different overall survival: (i) localized, age <18 years, non-pelvic primary; (ii) localized, age <18, pelvic primary or localized, age ?18, white, non-Hispanic; (iii) localized, age ?18, all races/ethnicities other than white, non-Hispanic; (iv) metastatic, age <18; and (v) metastatic, age ?18. These five groups were applied to the COG dataset and showed significantly different overall and event-free survival based upon this classification system (P?

SUBMITTER: Karski EE 

PROVIDER: S-EPMC5011751 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature