Model to predict the survival benefit of radiation for patients with rhabdomyosarcoma after surgery: a population-based study.

The aim of this study was to build a model to predict the survival benefit of radiotherapy for resected rhabdomyo-sarcoma at the individual level, to help clinicians and their patients make more informed decisions about adjuvant radiotherapy. Patients with resection of rhabdomyosarcoma between 1990 and 2010 were derived from the Surveillance, Epidemiology and End Results database. A multivariate Cox proportional hazard model was built to model cause-specific survival. We used inverse-probability weighting with propensity scores to minimize selection bias in the observation study. The Akaike information criterion technique was used to reduce variables in the model. Nomograms were created with the reduced model after model selection. The study cohort comprised 1578 patients. The 5-year cause-specific survival rate was 64.3% (95% confidence interval (CI) 61.7-66.9%) and the 10-year cause-specific survival rate was 61.4% (95% CI, 58.7-64.2%) for the entire cohort. Five-year cause-specific survival rates were 62.3% (95% CI, 58.6-66.2%) and 66.1% (95% CI, 62.6-69.8%) for patients with surgery alone and adjuvant radiotherapy, respectively (P<0.01). Age, size, histological type, tumor stage, positive regional nodes and adjuvant radiotherapy were retained in the reduced model. Model performance was good, with a c-index of 0.78 (95% CI, 0.76-0.80). This clinical predictive tool can quantify the benefit of adjuvant radiotherapy after resection of rhabdomyosarcoma, and provide patients and clinicians with assistance in treatment selection.