Construction And Validation Of A Prognostic Model For Urinary Bladder And Prostate Rhabdomyosarcoma

Background:Rhabdomyosarcoma(RMS)is a malignancy of embryonic mesenchymal cell origin,accounting for about 3%of pediatric solid malignancies.It is the most common soft tissue sarcoma in children and adolescents,accounting for about half of all soft tissue sarcomas.The incidence of rhabdomyosarcoma varies by age,with rhabdomyosarcoma being rare tumors in children and even more rare in adults:soft tissue sarcomas account for<1%of all adult solid tumors malignancies,and rhabdomyosarcomas represent only 3%of all soft tissue sarcomas in adults.The urogenital tract,as the second occurrence site of rhabdomyosarcoma,accounts for about 20%-25%of all cases.Relative to other parts of the urogenital system,Bladder Prostate Rhabdomyosarcoma(BPRMS)has a worse prognosis,the overall 5-year survival rate of rhabdomyosarcoma is about 94%,and the overall 5-year survival rate of BPRMS is about 80%.As a rare tumor,BPRMS has its low incidence,difficult to conduct large-scale epidemiological studies.The natural history of the disease is not clear,and there is no prediction model study for BPRMS at home and abroad.This study was to analyze the relevant clinical data form the Surveillance,Epidemiology,and End Results Program,to find the factor affect the prognosis of BPRMS,and to establish a prognosis model of rhabdomyosarcoma,which assist doctors and patients in better medical decision,and provide more accurate treatment.Methods:The clinical data of the BPRMS patients in SEER database between 1974 and 2019 was collected through SEER*Stat(version 8.4.0).The clinical data as age,sex,tumor site,tumor size,tumor stage,tumor pathology type,and treatment information were included,the possible influencing factors were screened by univariate and multivariate Cox regression analysis.A nomogram prediction model was constructed based on the independent risk factors selected above.The constructed nomogram model was verified internally by using the Bootstrap method,and the C index,receiver operating characteristic curve(ROC)and area under the curve(AUC)were used to evaluate the differentiation of the model,and the calibration was used to evaluate the consistency of the model.Results:Univariate and multivariate regression analysis results showed that age,summary SEER stage,pathological type of tumor and chemotherapy were independent risk factors for prognosis of BPRMS.The clinical prediction model was successfully constructed.The internal verification results showed that the C index was 0.799,and the area under the curve(AUC)for predicting 1-year,3-year and 5-year overall survival rates were 0.833,0.830 and 0.828,indicting the model has good prediction accuracy.The calibration curves for predicting 1-year,3-year and 5-year overall survival rates are close to the reference lines,and the model has good consistency.Conclusion:1.Age,summary SEER stage,pathological type and chemotherapy are independent risk factors for prognosis of BPRMS.2.Based on age,summary SEER stage,pathological type,and chemotherapy,a relatively accurate prognosis nomogram for BPRMS was constructed,which can be used to predict the 1-year,3-year and 5-year overall survival rate of BPRMS individually,providing a reference tool for evaluating the survival of BPRMS.