Objective:To develop a prognostic model based on adenosine-to-inosine de-amination(A-to-I RNA editing,ATIRE)to improve individualized treatment of breast cancer.Meth-ods:Univariate Cox regression analysis was first used to obtain ATIRE loci associated with overall survival(OS)in the training set,followed by a least absolute shrinkage and selection operator(LASSO)regression algorithm to determine the best prognostic AIRE loci,a multivariate Cox pro-portional risk regression analysis to build a risk model,incorporating AIRE risk scores and clinico-pathological characteristics variables to construct A prognostic nomogram was constructed,calibra-tion curves were plotted and consistency indices were calculated to evaluate the agreement be-tween the predicted probability of the model and the actual,and the clinical benefit value of the model was evaluated by decision curve analysis(DCA).Results:Eighteen prognostic loci were fi-nally identified for constructing prognostic models and generating ATIRE risk scores.Patients with high risk scores had significantly shorter median survival times,and nomogram performed well in predicting the probability of OS in breast cancer.The calibration curves showed excellent agree-ment and the decision curves showed a higher net benefit.Conclusion:To analyze the role of ATIRE events in predicting breast cancer survival,AITRE-based modal prognostic phenotype can help clinicians to make better clinical decisions.
关键词
乳腺癌/A-to-I/RNA编辑/总生存/列线图
Key words
Breast cancer/A-to-I RNA editing/Overall surviva/Nomogram
维普
万方数据