Background: This study used the receiver operating characteristic curve (ROC) to analyze Surveillance,Epidemiology and End Results (SEER) bronchioaveolar carcinoma data to identify predictive models and potentialdisparity in outcomes. Materials and
Methods: Socio-economic, staging and treatment factors were assessed. Forthe risk modeling, each factor was fitted by a Generalized Linear Model to predict cause specific survival. Thearea under the ROC was computed. Similar strata were combined to construct the most parsimonious models.A random sampling algorithm was used to estimate modeling errors. Risk of cause specific death was computedfor the predictors for comparison.
Results: There were 7,309 patients included in this study. The mean followup time (S.D.) was 24.2 (20) months. Female patients outnumbered male ones 3:2. The mean (S.D.) age was 70.1(10.6) years. Stage was the most predictive factor of outcome (ROC area of 0.76). After optimization, severalstrata were fused, with a comparable ROC area of 0.75. There was a 4% additional risk of death associatedwith lower county family income, African American race, rural residency and lower than 25% county collegegraduate. Radiotherapy had not been used in 2/3 of patients with stage III disease.
Conclusions: There aresocio-economic disparities in cause specific survival. Under-use of radiotherapy may have contributed to pooroutcome. Improving education, access and rates of radiotherapy use may improve outcome.