Based On The AJCC Staging System To Establish A Clinical Prediction Model Of Extremity Osteosarcoma

Objective: Based on the traditional American Joint Committee on Cancer(AJCC)staging system,we combined patient-related clinical variables to establish a more novel clinical prognostic model for postoperative patients.It also provides a reference for clinical medical workers to more accurately and efficiently predict the postoperative tumor-specific survival(CSS)of patients with osteosarcoma of the extremity.Methods : We used R scripts to extract clinical information from all patients with osteosarcoma of the extremity from the US SEER(Surveillance,Epidemiology,and End Results)database,and initially excluded patients with missing information,and then developed exclusion criteria to determine the final number of candidates.Patient variables were coded using SPSS,categorical variables were processed for continuous variables,then univariate COX regression analysis was performed on the patient variables,and variables with univariate analysis significance were included in the multivariate COX regression model.Finally,the meaningful variables of the multivariate COX regression model are used as the benchmark variables,and the Akaike information criterion(AIC)is calculated according to the remaining variables of interest.The model with the smallest AIC is selected for the Nomogram visualization,and the C-index is adopted.Initial evaluation of the model,in addition,in order to assess the stability of the model,we also randomly selected a third of the patients for internal validation.Finally,we evaluated the sensitivity and specificity of the fitted model Nomogram using the most commonly used receiver operating characteristic curve(ROC).Results: Univariate COX regression analysis suggested that race,T_stage,N_stage,and M_stage were the prognostic factors affecting postoperative osteosarcoma patients,but the location,gender,and age of diagnosis were not statistically significant.Multivariate COX regression analysis showed that non-whites(HR=4.155,95% CI,2.999-5.755;P<0.001)and M1_stage(HR=2.614,95% CI,2.002-3.414;P<0.001)were independent risk factors for postoperative prognosis in patients with osteosarcoma of the extremity.In the T_stage,compared with T1,T2(HR=0.584,95% CI,0.413-0.827;P=0.002)was an independent protective factor affecting the prognosis of patients with osteosarcoma of the extremity,while T3 was not statistically significant.Although the multivariate COX regression results did not show that the diagnostic age and N_stage were independent prognostic factors,the AIC model assessment showed that when T,N,M,and race and diagnostic age were combined,the minimum AIC value of 32.15 was obtained.The model is the most stable,at this time the C-index is 0.733;95% CI(0.703-0.763),and the area under the ROC curve AUC is 0.745;the same internally validated model correction curve also shows the stability of the model.Conclusion: The postoperative survival Nomogram model of extremity osteosarcoma patients based on the AJCC staging system combined with patient characteristic variables showed good stability in multi-method verification,suggested that this model can provide potential value for clinicians to evaluate the survival of patients after operation.