title: Surveying and optimizing the predictors for ependymoma specific survival using SEER data.
abstract: OBJECTIVE
  This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) ependymoma data to identify predictive models and potential disparity in outcome.
  
  
  METHODS
  This study analyzed socio-economic, staging and treatment factors available in the SEER database for ependymoma. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome ('brain and other nervous systems' specific death in yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A random sampling algorithm was used to estimate the modeling errors. Risk of ependymoma death was computed for the predictors for comparison.
  
  
  RESULTS
  A total of 3,500 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 79.8 (82.3) months. Some 46% of the patients were female. The mean (S.D.) age was 34.4 (22.8) years. Age was the most predictive factor of outcome. Unknown grade demonstrated a 15% risk of cause specific death compared to 9% for grades I and II, and 36% for grades III and IV. A 5-tiered grade model (with a ROC area 0.48) was optimized to a 3-tiered model (with ROC area of 0.53). This ROC area tied for the second with that for surgery. African-American patients had 21.5% risk of death compared with 16.6% for the others. Some 72.7% of patient who did not get RT had cerebellar or spinal ependymoma. Patients undergoing surgery had 16.3% risk of death, as compared to 23.7% among those who did not have surgery.
  
  
  CONCLUSIONS
  Grading ependymoma may dramatically improve modeling of data. RT is under used for cerebellum and spinal cord ependymoma and it may be a potential way to improve outcome.
authors.affiliation: FROS Radiation Oncology Cyberknife Center of New York, NY, USA E-mail : cheung.r100@gmail.com.
authors.forename: Min Rex
authors.initials: MR
authors.lastname: Cheung
mesh_terms: D000328:Adult; D004806:Ependymoma / Q000401:mortality*; D005260:Female; D006306:Health Surveys; D006801:Humans; D008297:Male; D060787:Neoplasm Grading; D011237:Predictive Value of Tests; D018426:SEER Program; D013120:Spinal Cord Neoplasms / Q000401:mortality*; D015996:Survival Rate; D055815:Young Adult