Prognostic Nomograms and Risk Stratification for Rhabdomyosarcoma Across Anatomic Sites

Purpose Rhabdomyosarcoma (RMS) is a rare soft tissue sarcoma that predominantly affects children and adolescents. Current prognostic models are limited by their focus on single anatomic sites or small patient cohorts. This study aims to develop and validate two prognostic nomograms incorporating clinical, pathological, and treatment-related factors to predict overall survival (OS) and cancer-specific survival (CSS) in RMS patients across different anatomic locations. Methods Data from patients diagnosed with primary RMS between 2010 and 2018 were extracted. Prognostic nomograms were constructed based on independent risk factors, with model performance assessed via the concordance index (C-index), calibration curves, and decision curve analysis (DCA). Risk stratification was performed based on nomogram-derived scores. Results The study included 4,335 patients, randomly divided into training (n = 3,034) and validation (n = 1,301) cohorts. The median age was 19 years, with 53.9% male predominance. Common primary sites were the head/neck (29.3%), extremities (24.4%), and genitourinary tract (20.5%). Alveolar (32.8%) and embryonal (23.9%) subtypes were most frequent. Key independent prognostic factors included age, tumor size, histologic subtype, T stage, nodal status, metastasis, and treatment modalities (all P  < 0.05). The OS nomogram achieved C-indices of 0.759 (training) and 0.785 (validation), while the CSS nomogram reached 0.790 and 0.774, outperforming conventional staging systems. Calibration curves and DCA confirmed strong predictive accuracy and clinical utility. Risk stratification effectively differentiated low-, intermediate-, and high-risk groups ( P  < 0.001), with consistent validation results. Conclusion These comprehensive nomograms offer individualized OS and CSS predictions for RMS patients, serving as valuable tools for prognostic evaluation.