CT-based radiomics predicts CD38 expression: indirectly reflects clinical prognosis in epithelial ovarian cancer

Abstract

Background Cluster of differentiation 38 (CD38) has been found to be highly expressed in various solid tumors, and its expression level may be associated with patient prognosis and survival. The study aimed to explore the prognostic value of CD38 expression for patients with epithelial ovarian cancer (EOC) and to construct two computed tomography (CT)-based radiomics models for CD38 expression prediction. Methods A total of 333 cases of EOC were enrolled from The Cancer Genome Atlas (TCGA) database for CD38 related bioinformatics and survival analysis. 56 intersection cases from TCGA and The Cancer Imaging Archive (TCIA) databases were selected for radiomics feature extraction and model construction. Logistic regression (LR) and support vector machine (SVM) models were constructed and internally validated using 5-fold cross-validation to assess the performance of the models for CD38 expression levels. Results High expression of CD38 was an independent protective factor (HR = 0.540) for overall survival (OS) in EOC patients. 5 radiomics features based on CT images were selected to build models for CD38 expression prediction. In the training set and internal validation set, for the receiver operating characteristic (ROC) Curve, the LR model reached area under the curve (AUC) of 0.739 and 0.732, while the SVM model achieved AUC values of 0.741 and 0.700, respectively. For the precision-recall (PR) Curve, the LR model and SVM model demonstrated AUC of 0.760 and 0.721. The calibration curves and decision curve analysis (DCA) provided evidence supporting the fitness and net benefit of the models. Conclusions High expression of CD38 can improve OS in EOC patients. CT-based radiomics models can be a new predictive tool for CD38 expression, offering possibilities for individualized survival assessment for patients with EOC.