Construction and verification of prognostic nomogram model of osteosarcoma integrating Ki67 and SATB2 expression
JIAO Xiaohang
YANG yong
WU Yanan
LI Jianxiong
ZHANG Yinglong
BI Wenzhi
Abstract：Objective Based on the database of China National Cancer Center,this study constructed and verified a nomogram model of osteosarcoma prognosis integrating clinical features and molecular markers(Ki67,SATB2).Methods The data of 1 817 patients with osteosarcoma from 2013 to 2023 were retrospectively analyzed and randomly divided into training group(1 271 cases)and verification group(546 cases)according to the ratio of 7∶3.The threshold of grouping continuous variables was determined by restricted cubic spline(RCS)curve,and independent prognostic factors were screened by univariate and multivariate Cox regression analysis,and nomogram model was constructed.Model performance is evaluated using the concordance index(C-index),receiver operating characteristic curve(ROC),and calibration curves.Finally,the critical value of risk stratification is determined and Kaplan-Meier survival analysis is carried out.Results The baseline characteristics of the training group and verification group were balanced.Univariate and multivariate Cox regression analysis screened out seven independent prognostic factors such as age,tumor diameter,M stage,surgery,chemotherapy,Ki67 index and SATB2.The nomogram model shows good prediction efficiency in both the training group and the verification group.The C-index of the training group was 0.721(95%CI:0.692～0.749),and that of the verification group was 0.712(95%CI:0.665～0.747).The predicted AUC of 1-year,3-year and 5-year survival rates in the training group were 0.826,0.704 and 0.694 respectively.In the validation group,the predicted AUC of 1-year,3-year and 5-year survival rates were 0.757,0.721 and 0.702 respectively.The calibration curve indicates that the prediction results of the model are highly consistent with the actual observation data.Conclusion The nomogram model shows a good prediction efficiency in the internal verification of the current research cohort,which can help identify high-risk patients and provide reference for clinical prediction.
Keywords：osteosarcomanomogramprognosisoverall survivalcox regression
Publication Date：2025-10-31
Online Publishing Date：2025-11-17(First online date of this platform, not the publication date of the document)
Pages：5( 762-766 )