Abstract 1172
Background
Rhabdomyosarcoma (RMS) represents a malignant tumor of skeletal muscle origin, accounting for 5-10% of childhood cancers and more than 50% of pediatric soft tissue sarcoma. The head and neck occupied about 35% of the main sites of RMSs and most of these tumors are located in orbit, which contributes to 10% of all sites of RMSs. Due to the rarity of orbital RMS, the published studies of the clinical and pathological factors of orbital RMS could only provide limited information due to the small numbers of cohort or single institution. The aim of the current study was to evaluate the cumulative incidence of cancer-specific and competing risk death for patients with orbital RMS after surgery and build nomograms to predict survival based on a large population-based cohort.
Methods
Patients pathologically diagnosed with orbital RMS between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively collected. Nomograms for estimating overall survival (OS) and cancer-specific survival (CSS) were established based on Cox regression model and Fine and Grey’s model. The precision of the nomograms was evaluated and compared using concordance index (C-index) and the area under receiver operating characteristic (ROC) curve (AUC).
Results
A total of identified 217 patients with orbital RMS were retrospectively collected. The 10-, 20- and 40-year OS rates and cancer-specific mortality were 82.5%, 72.2% and 48.9%, respectively and 14.8%, 21.7% and 21.7%, respectively. The established nomograms were well calibrated and validated, with C-index of 0.901 and 0.944 for OS prediction, 0.923 and 0.904, for CSS prediction in the training and validation cohort, respectively. The values of AUC for 10-, 20-, and 40-year OS and CSS prediction were 0.908, 0.826 and 0.847, and 0.924, 0.863 and 0.863, respectively.
Conclusions
The survival rates were evaluated for patients with orbital RMS and the specialized nomograms were established for OS and CSS prediction for the first time, which showed relatively good performances and could be convenient individualized predictive tools for prognosis.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
This study was supported by the funding of Sun Yat-sen University Grant for Medical Humanities Practice and Teaching (No. 23000-18008023).
Disclosure
All authors have declared no conflicts of interest.
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