A prognostic nomogram model of osteosarcoma based on SEER database
Objective To construct a nomogram model to predict overall survival(OS)of patients with osteosarcoma.Methods Osteosarcoma patients diagnosed between 2010 and 2015 were collected from the National Cancer Institute's Surveillance,Epidemiology,and End Results(SEER)database,and were randomly divided into training and validation sets in a 7:3 ratio for model construction and validation.In the training set,univariate and multifactor Cox regression analyses were used to screen variables that affected patient prognosis,and then the nomogram prediction model was constructed using these variables.The efficiency of the nomogram was verified using the C-index,receiver operating characteristic curve(ROC curve),and calibration curve in the training set and validation set.Results A total of 872 patients were included in the study.Univariate and multivariate Cox regression analyses showed that age,sex,tumor site,pathological grade,T stage,M stage and surgery were independent factors influencing the prognosis of patients with osteosarcoma(P<0.05).A nomogram was built based on these variables.The C index and the areas under ROC curve of the training set and validation set showed that the nomogram model in this study had strong predictive ability.In addition,the calibration curves of the training and validation sets showed a high correlation between the predicted and observed results.Conclusions This study identifies clinical variables associated with osteosarcoma survival and then establishes a nomogram to predict 1-,3-,and 5-year overall survival in patients with osteosarcoma.The model could help clinicians develop treatment and follow-up strategies for more effective treatment of osteosarcoma.
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